Profit Accumulator Relative Strength IndexHi Everyone
Thought I'd share this nice and simple RSI indicator with you which uses short and long length crossover to determine potential long and short trades. This indicator also has multiple timeframe functionality.
Please use this with other indicators or price action etc to confirm long and short trades.
Personally I like to see the crossover on the longer timeframe and close out on a lower timeframe (i.e. spot the entry on the 1hr charts and close my position based on the 15min)
If anyone would like alerts putting on here for crossover then just let me know.
Cheers
Mike
Tìm kiếm tập lệnh với "profit"
Profit Accumulator Support and ResistanceHi Everyone
Thought I'd share this support and resistance script.
This has two settings on it which are resolution (timeframe) and the number of bars back to look. The default setting is 1 Week and 2 bars which is the one I like using the most.
The highest high and lowest low are indicated by the thicker red lines on the chart.
Enjoy using this.
Cheers
Mike
Profit Accumulator Heat MapHi Everyone
Happy to share this heat map packed full of indicators to make those trading decisions. There are a whole host of indicators including:
Inverse Fischer Transform
Moving Average Slope
EMA50 Crossover
Schaff Trend Cycle
MACD
RSI
Stochastic RSI
Moving Average Cross Over
Quantitative Qualitative Estimation
On Balance Volume
All of the indicators are customisable in the settings so you can adjust them to how you want.
I often find that the combination of MACD and QQE provide good early entry and exit signals.
Any comments or improvements then please feel free to get in touch.
Cheers
Mike
Big thanks go to @everget, @JustUncleL and @LazyBear for the use of their codes.
Profit Accumulator VolatilityHi Everyone
I thought I'd share my new volatility trend indicator for anyone to use.
The indicator tracks the volatility in the market and plots this accordingly. Any plot above the zero line is a bullish signal and anything below the zero line is a bearish signal.
Long and Short Entry points are indicated at the 10 and -10 values respectively. A value of over 40 , or under -40 indicates a strong trend.
Possible entry and exit points are also highlighted on the chart.
I've added alerts onto this indicator highlighting possible entry and exit points as well as when strong trends are developing and when they are over.
This is intended to be used with your own indicators and/or analysis of the market and should be used carefully.
I personally like to use this indicator for entry on the one hour chart and then drop down to the 15 minute chart to confirm my entry and to use that timeframe for my exit.
Please feel free to forward any improvements that you'd like to make.
Cheers
Mike
Profit Accumulator On Balance VolumeOn Balance Volume Indicator
This is a support indicator to the Main Indicator which has also been published.
This indicator is from the basis of user Everget and a friend of mine on another site. This indicator has used a smoothing function in an attempt to provide more robust signals.
In this indicator the user is looking for:
Long trade: Upward sloping signal line and OBV greater than the signal line (shaded green).
Short trade: Downward sloping signal line and OBV less than the signal line (shaded red).
A horizontal signal line is a sign that the market is moving horizontally and trades should be placed very carefully. This indicator should definitely be used with the others in the suite to provide confluence when making a trade.
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Profit Accumulator Heat MapHeat Map Indicator
This is a support indicator to the Main Indicator which has also been published.
This is a list of a number of indicators which cover trend, momentum and volatility. The key is very simple for this indicator, green is a long trade, red is a short trade and grey is an indicator which may be transitioning. The indicators uses are: MACD, PSAR, Bollinger Bands, RSI, Momentum and Chandelier Exit. All of the settings are customisable within the indicator and the user can best fit these around their charts. The simplicity of the heat map is that the more of one colour there is, the more likely it is that a trade can be placed.
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Profit Accumulator Moving Average SlopeMoving Average Slope Indicator
This is a support indicator to the Main Indicator which has also been published.
This indicator makes use of custom and adjustable moving averages. There are two options for this centred oscillator:
Average of Three Moving Averages on Current Time Frame
Average of Three Moving Average Time Frames for One Length (i.e. if I'm using a 1hr time frame I would take the average of 30min, 1hr and 4hr moving averages with a 12 length).
When the trend line crosses above zero it is an indication for a long trade and when the trend line crosses below zero it is an indication for a short trade.
Whilst an actual alert function is not set for the indicator, the TradingView alert function can be used to trigger a message when the trendline crosses above or below zero.
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Profit Accumulator Momentum Trend IndicatorMomentum Trend Indicator
This is a support indicator to the Main Indicator which has also been published.
This indicator uses a modified stochastic trendline and a smoothed momentum line (which combines stochastic, RSI and moving average). This is a centred oscillator from -100 to 100 which makes it easier to track. The stochastic line is the quicker moving line which potentially acts as the first trigger. If the momentum line then begins to follow, then it is an indication that a trade should be made.
Long Trades: The Stochastic line is above 25 and the momentum line is greater than -25.
Short Trade: The Stochastic line is below -25 and the momentum line is less than 25.
Whilst an actual alert function is not set for the indicator, the TradingView alert function can be used to trigger a message when either the stochastic line or momentum line crosses -25/25 (the key levels).
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Profit Accumulator %BB%Bollinger Band Width
This is a support indicator to the Main Indicator which has also been published.
This indicator uses the close of a candle and compares where it is in relation to the upper and lower levels of a Bollinger Band. This is a centred oscillator where anything below the zero line is indicating a short signal and anything above zero is indicating a long signal. The crossing of the zero line is an important point for this indicator.
Whilst an actual alert function is not set for the indicator, the TradingView alert function can be used to trigger a message when the line crosses zero (up or down).
I've been using this successfully on the one hour FX charts, but seems to work equally as well on higher or lower time frames (not less than 15min).
The other indicators which are part of the suite are shown on the website which is highlighted in my signature at the bottom of the page. Purchase of the main indicator gives access to the full suite of eight indicators. I use the other indicators to confirm the direction of the trade and to determine if I want to trade or not. I use it along with the 2min, 15min and 4hr timeframes to identify the best entry window and how long I'm likely to be in the trade.
Support can be provided via private message or in the comments below.
The links are provided below for access to the indicator.
Profit target areaUpdate.
- you can specify count of bars used to detect reversal pattern
- you can specify count of bars used to determine lowest or highest price to place support or resistance
- area between lines is filled by green - ascending, red - descending trend
To trade:
- open position using stop command on S/R
- close position using limit command on retracement line
- close position when background colour indicates trend change
(erratum: last balloon on right should say "buy limit")
Anurag Institutional Swing Trader Pro [Robust]nstitutional Swing Flow is a comprehensive, multi-timeframe system designed for swing traders who want to align with "Smart Money" rather than fight against it.
Unlike standard indicators that rely solely on price crossovers, this script analyzes the underlying order flow—tracking stealth accumulation, volume anomalies, and institutional footprints—to generate high-probability swing setups.
Key Features (The "Smart Money" Logic)
1. Institutional Footprints
Stealth Accumulation/Distribution: Detects when price is held in a tight range despite high volume (a classic sign of institutions building a position).
Smart Money Divergence: Identifies when price makes a lower low but Money Flow (OBV/Accumulation-Distribution) makes a higher high.
Fair Value Gaps (FVG): Automatically plots Bullish and Bearish imbalance zones where price is likely to retrace before continuing the trend.
2. Safety First (Risk Management)
Real Earnings Detection: Automatically checks upcoming earnings dates. If an earnings report is within 5 days (adjustable), the script blocks new signals to prevent gambling on binary events.
Visual Exits: Plots dynamic Stop Loss and Take Profit levels on the chart the moment a trade is taken, along with "SL Hit" or "TP Hit" markers for visual backtesting.
3. The "Confluence Score" Dashboard A sophisticated dashboard in the top-right corner rates every setup on a scale of 0 to 100 based on:
Multi-Timeframe Trend: Is the Weekly, Daily, and 4H trend aligned?
Relative Strength: Is the asset outperforming the SPY benchmark?
Volatility: Is the asset in a "Squeeze" (Bollinger Band compression)?
Momentum: RSI, MACD, and CMF confirmation.
Only setups with a score > 65 (adjustable) trigger a BUY or SELL signal.
How to Use
Timeframe: Optimized for 4-Hour (4H) and Daily (D) charts. (Avoid using on <15m charts due to multi-timeframe calculations).
The Signal: Wait for a large "CALL" or "PUT" label.
The Confirmation: Check the Dashboard. Ideally, look for a "Squeeze: YES" combined with a high Institutional Buy Score.
The Exit: Follow the Red (Stop Loss) and Green (Take Profit) lines plotted automatically.
Disclaimer
This tool is for educational purposes only. Swing trading involves risk. Always confirm signals with your own analysis and risk management rules.
Body Close Continuity & failure Backtesting @MaxMaseratiThis indicator, is a highly advanced institutional-grade tool designed to track the "lifespan" of a trend based on Body Close (BC) sequences.
Unlike basic indicators that just show direction, this script analyzes the structural integrity of a trend by monitoring how many candles continue the move before a "Touch" (retest) or a "Break" (failure) occurs.
The Continuity & Failure Stats indicator tracks sequences of Bullish Body Closes (BuBC) and Bearish Body Closes (BeBC). It measures three critical phases: Building (pure momentum), Touching (price retesting the low/high of the sequence), and Resumption (price continuing the trend after a retest). It provides a statistical distribution of how long these "buildings" typically last before failing, allowing traders to know exactly when a trend is overextended.
This comprehensive analysis blends the statistical breakdown of the Continuity & Failure Stats indicator to provide a deep understanding of the structural momentum for the S&P 500 E-mini (ES1!) on a 4-hour timeframe.
1. Extensive Table Breakdown
A. Building Distribution (Left Table): The Fatigue Gauge
This table acts as a histogram of momentum, tracking the "Building Count"—the number of consecutive candles closing in a trend without price returning to its origin.
Count Column: Represents the streak length (e.g., 1, 2, or 3 candles).
Touch Column: Shows how many times a streak was interrupted by a retest ("touch") but remained structurally intact.
Break Column: Counts total structural failures where price closed beyond the sequence's anchor.
Data Insight: For BuBC, 92 sequences reached Count 1, but only 28 remained by Count 4. This reveals a steep momentum decay after the 3rd candle, establishing a "Statistical Wall" where only 2 sequences in history reached a count of 9.
B. MMM Summary Stats (Top Right): The Mathematical DNA
This table provides the "Expected Value" and behavior of a trend over the lookback period.
Avg Building (2.39 for BuBC): On average, a bullish move lasts ~2.4 candles of pure momentum before a retest or reversal occurs.
Avg Touches (0.8): This low number indicates "clean" trends that rarely wobble back to retest levels multiple times before reaching a conclusion.
Avg R Cycles (0.55): This suggests that once a bullish trend is interrupted, it only successfully resumes its momentum about half the time.
Max R Count (1): Typically, once a trend is "touched," it only manages one more push before failing.
C. Multi-Timeframe (MTF) Quick Stats (Bottom Right): Trend Weight
This compares the 4H chart against other layers of the market to identify "global" alignment.
Sample Comparison: There are 3,594 tracked BuBC sequences on the 4H compared to only 142 on the Weekly chart.
Fractal Law: The Avg Building (2.4) is consistent across several timeframes, implying that the "Rule of Three" (momentum fading after 3 candles) is a fractal characteristic of this asset.
2. Table Comparison: Synthesizing the Data
To trade effectively, you must compare Distribution (timing) against Summary Stats (averages):
Continuity vs. Failure: The Summary Stats show an average building of 2.39. When checking the Distribution table at Count 2, the "Break" count (58) is already high relative to the "Total". This confirms that the risk of failure increases exponentially the moment you exceed the average.
Momentum vs. Mean Reversion: Distribution tells you when a trend is "tired". If the 4H is at a "Building Count 4" (statistically overextended) while the Weekly chart is at "Building Count 1" (fresh momentum), you may choose to prioritize the higher timeframe's strength despite the local overextension.
3. Strategic Summary & Application
This indicator proves that market momentum follows a predictable "Building" cycle rather than an infinite streak.
The "Rule of Three" for ES1! 4H:
The Entry Zone (Momentum Start): The most profitable entries occur at Building Count 1. Statistically, you have a high probability of reaching a count of 2 or 3.
The Exit Zone (Momentum Limit): Take profits or tighten stops at Count 3. The data shows the sample size drops by nearly 50% between Count 3 and Count 4.
The "Touch" Rule (Retest Reliability): If price returns to the sequence low (a "Touch"), do not expect a massive continuation. The Max R Count of 1 tells us that resumptions are usually short-lived.
Danger Zone: Entering at Building Count 4 or higher is statistically dangerous, as the "Break" probability significantly outweighs the "Touch" or continuation probability.
Long Short Trading System With TableSmart Trading System Pro is an advanced TradingView indicator designed for precision and clarity.
It combines Order Blocks, Liquidity Zones, EMA trend alignment, MACD, RSI, Volume, and ATR-based risk management to generate high-quality LONG / SHORT signals.
🔹 Clear trade direction
🔹 Smart entry, stop-loss & multi-level take-profit
🔹 Automatic risk/reward & leverage calculation
🔹 Clean visual dashboard for fast decision-making
Built for traders who value structure, confirmation, and risk control.
Best suited for crypto, forex, and indices on all timeframes.
Disclaimer:
This indicator is for educational and informational purposes only and does not constitute financial advice.
Trading involves risk, and past performance does not guarantee future results.
You are solely responsible for your trading decisions and outcomes.
SMC SNI LAP ULTRA This indicator is a multi-tool market-structure and confluence signal assistant designed for EDUCATIONAL PURPOSES ONLY. It combines Smart Money Concepts (SMC) and classic technical confirmations to help visualize context, zones, and potential trade ideas.
What it shows
• Market Structure: Swing/Internal pivots, BOS / CHoCH / MSS labels and structure lines
• Liquidity Concepts: EQH/EQL style areas and liquidity sweep detection (when enabled)
• Zones & Areas of Interest: Supply/Demand, Order Blocks (OB), Fair Value Gaps (FVG) and key levels (depending on settings)
• Confirmation Tools: Pin bar / engulfing patterns, RSI-based filters and optional divergence
• Confluence Scoring (AI-like): A rule-based scoring system that weights multiple conditions (trend alignment, momentum strength, volume spike, sweep, zone location, RR quality, etc.)
• Risk Visualization: Optional Entry / TP / SL guide lines based on selected TP/SL modes and RR settings
• Alerts: Optional alerts that can be used for notifications or webhook integrations (signals only)
About “AI” / Scoring
The “AI” features in this script are NOT machine learning and do NOT predict the future. They are rule-based calculations that assign a score from multiple factors and track simple win/loss statistics based on user-defined TP/SL logic. Results depend on market conditions and your settings.
Important Disclaimer
This indicator does NOT provide financial advice and does NOT guarantee profits. Trading involves risk and you can lose money. Any signals, scores, or projections are informational and for research/testing only. Always do your own analysis, manage risk properly, and consider using a demo account for evaluation.
Recommended Use
Use it as a context tool:
1) Identify structure (BOS/CHoCH) and trend bias
2) Mark zones (OB/FVG/Supply-Demand)
3) Wait for confirmation (candle patterns, RSI/divergence, volume, etc.)
4) Use the scoring as a filter—not as a guarantee
If you need automated execution, connect alerts to your own external system at your own responsibility. This script itself is an indicator (not an auto-trading system).
Session Opening Bar RangeSession Opening Bar Range (OBR) - Advanced Opening Range Indicator with Statistical Analysis
Overview
The Session First Bar Range (FBR) indicator is a comprehensive tool that captures and projects key levels based on the first bar of a user-defined trading session. Unlike traditional daily opening range indicators, this script allows traders to focus on specific session windows (New York RTH, London, Asia, etc.) and analyze price behavior relative to the initial momentum established in that session's opening bar.
What makes this indicator unique is its combination of three distinct projection methodologies: statistical analysis based on historical range data, Fibonacci extensions, and fixed-point rotation levels commonly used by institutional traders. To our knowledge, this is the only opening range indicator that incorporates statistical standard deviation levels calculated from historical first bar ranges, making it both a technical and probabilistic tool.
Core Concept
The opening range concept is based on the principle that the initial price action of a trading session often sets the tone for the remainder of that session.
Professional traders have long observed that:
The first bar's high and low act as key reference points
Price often respects or breaks these levels with significance
Expansion beyond the opening range tends to occur in measurable increments
This indicator takes these observations and enhances them with:
Historical probability analysis - "Based on the last 60 sessions, price typically extends X standard deviations beyond the opening range"
Proportional projections - Fibonacci-based extensions showing where measured moves typically target
Fixed-point rotations - Institutional rotation levels (e.g., 65 points for NQ, 15 points for ES)
How It Works
Session Detection & First Bar Capture
The indicator uses Pine Script's time() function with timezone support to precisely detect when a trading session begins. When the first bar of the selected timeframe occurs within the session window, the script captures:
High (H): The high of the first bar
Low (L): The low of the first bar
Mid (M): The midpoint (hl2) of the first bar
Critical Detail: These levels are fixed from the first bar only - they do not update as the session progresses. This differs from many "opening range" indicators that use a time period (e.g., first 30 minutes). Here, you select the bar timeframe (default 5-minute), and only that single first bar's range is captured.
Statistical Level Calculation
The indicator maintains a rolling array of the last N session's first bar ranges (default: 60 sessions). For each new session, it calculates:
Average Range: Mean of historical first bar ranges
Standard Deviation: Volatility of those ranges
Projection Levels: High/Low ± (Average Range + Std Dev × Multiplier)
This provides probability-based levels. For example, a +2σ level suggests: "Historically, price extending this far beyond the opening range is a 2-standard-deviation event (approximately 95th percentile)."
Fibonacci Extensions
Using the first bar range as the base unit (100%), the indicator projects Fibonacci levels:
100% extension: One full range above the high / below the low
1.618x extension: (Default) Golden ratio projection
2.618x, 3.618x extensions: Additional Fibonacci levels
Calculation: Range = H - L, then Target = H + (Range × Multiplier) for upside projections.
OR Rotation Levels
These are fixed-point increments from the first bar's high and low. Unlike percentage-based methods, rotations use absolute point values:
NQ traders often use 65-point increments
ES traders often use 15-point increments
Gold/bonds use different values
The indicator draws 5 levels above the high (R+1 through R+5) and 5 below the low (R-1 through R-5), each separated by your specified point increment.
Features:
Session Options
Pre-configured Sessions:
New York RTH (9:30am - 4:00pm)
New York Futures (8:00am - 5:00pm)
London (2:00am - 8:00am)
Asia (7:00pm - 2:00am)
Midnight to 5pm
ZB/Gold/Silver OR (8:20am - 4:00pm)
CL OR (9:00am - 4:00pm)
Custom Session: Define your own start/end times in HHMM format
Timezone Support: All sessions respect the selected timezone (default: America/New_York)
Customizable Timeframe
Select any timeframe for the first bar (1min, 5min, 15min, etc.)
Default: 5-minute bars
Important: This is the timeframe for the first bar capture, independent of your chart's timeframe
Display Options
Historical Ranges: Show/hide past session ranges (with configurable limit to manage performance)
Line Styles: Choose between Solid, Dashed, or Dotted for range lines and midline
Label Position: Left or Right side of range
Show Prices: Optionally display actual price values on labels
Custom Colors: Fully customizable colors for all components
Statistical Levels
Lookback Period: Number of historical sessions to analyze (default: 60)
Two Multiplier Levels: Default 1σ and 2σ, fully adjustable
Separate styling: Different line styles (dashed vs dotted) for each sigma level
Optional Labels: Show/hide sigma notation labels
Fibonacci Extensions
Four Extension Levels: 100%, 1.618x, 2.618x, 3.618x (all customizable)
Bidirectional: Projections both above and below the opening range
Optional Labels: Toggle percentage/multiplier labels
OR Rotation Levels
Configurable Increment: Set the point value for your instrument
Five Levels Each Direction: R±1 through R±5
Dynamic Labels: Show both rotation number and point value (e.g., "R+1 (65)")
Three Line Styles: Solid, Dashed, or Dotted
How to Use
Setup
Add the indicator to your chart
Select your trading session from the dropdown
Set the timeframe for first bar capture (typically 5-15 minutes)
Configure which projection methods you want to see (Statistical, Fibonacci, and/or Rotations)
For Day Traders
Scenario: Trading NQ during New York RTH
Session: Select "New York RTH (9:30am - 4:00pm)"
Timeframe: 5-minute (captures 9:30-9:35 bar)
Enable: OR Rotations with 65-point increments
Strategy:
Watch for acceptance/rejection at rotation levels
Use R+1/R-1 as initial profit targets
R+2/R-2 as extended targets
Statistical levels show when price is in "outlier" territory
and rotation levels
Performance Notes
The indicator limits objects to stay within TradingView's constraints (500 max)
If you enable all features, reduce "Maximum Historical Ranges" to prevent slowdown
Typical configuration: 10-20 historical ranges with all features enabled works well
Settings Guide
Session Settings
Session: Choose from pre-configured sessions or "Custom"
Custom Session Start/End: HHMM format (e.g., "0930" for 9:30am)
Timezone: Critical for accurate session detection
Opening Bar Format
Timeframe: The bar size for capturing the first bar's range
Show Midline: Toggle the mid-point line
Show Historical Ranges: Display previous sessions (recommended: leave ON)
Maximum Historical Ranges: Limit history to manage performance (1-500)
Range Style / MidLine Style: Solid, Dashed, or Dotted
Position: Label placement (Left or Right)
Show Prices: Include actual price values on labels
Statistical Levels
Lookback Periods: How many historical first bar ranges to analyze (default: 60)
Std Dev Multiplier 1/2: The sigma levels to project (default: 1.0 and 2.0)
All visual settings (colors, line width, label size)
Fibonacci Extensions
Show Fib Extensions: Enable/disable Fibonacci projections
Measured Move Extensions 1-4: The multipliers (default: 1.618, 2.618, 3.618, 4.618)
Visual customization options
OR Rotations
Rotation Increment: The point value for your instrument
NQ: 65 points
ES: 15 points
Adjust for other instruments based on their typical rotation behavior
Show Rotation Labels: Display level numbers and point values
Visual customization options
Use Cases
Gap Trading: When price gaps away from previous day's close, the first bar range shows the initial gap acceptance/rejection zone
Breakout Confirmation: Price breaking and holding above the first bar high with volume suggests trend day potential. Rotation levels provide measured targets.
Reversal Identification: Price reaching +2σ statistical level = rare event, potential exhaustion
Range Bound Days: Price oscillating between first bar high/low suggests range-bound session; trade reversals at extremes
Institutional Level Awareness: OR Rotations at 65 points (NQ) align with levels professional traders watch
Technical Notes
The indicator uses request.security() with lookahead=barmerge.lookahead_on to ensure the first bar levels are captured correctly
All drawing objects (lines, labels, fills) are managed in arrays with automatic cleanup to prevent memory issues
The statistical calculations use array.avg() and array.stdev() for accurate probability estimates
Rotation levels use individual line variables (like Fibonacci) rather than loops for reliability
Summary
This indicator is original in its combination of three distinct methodologies for projecting levels from a session's opening range:
Statistical Analysis - No other opening range indicator (to our knowledge) calculates standard deviation projections from historical first bar ranges
Time-Based Session Flexibility - Most OR indicators use only daily or fixed time periods; this allows any custom session window
Multiple Projection Methods - Traders can use statistical, Fibonacci, AND rotation levels together or separately
BTC - Institutional Cost Corridor (Overlay)BTC - Institutional Cost Corridor | RM
Strategic Context
The approval of Spot Bitcoin ETFs on January 11, 2024, signaled the beginning of the "Institutional Era." Since then, price discovery has shifted from being purely retail-driven to being heavily influenced by massive, off-chain equity flows.
The Institutional Cost Corridor is an approach for a quantitative tool designed to solve the problem of "Institutional Blindness" by mapping the aggregate cost basis of Wall Street's entry. It allows for the identification of structural "gravity zones" where institutional capital is most likely to move from a state of profit into a state of defense.
The Methodology: Data Selection & Weighting
To ensure the output is statistically significant, the data engine focuses exclusively on the "Big 3" liquidity providers: BlackRock (IBIT), Fidelity (FBTC), and Bitwise (BITB). These three funds represent over 80% of total Spot ETF liquidity. A weighted ratio is applied (prioritizing BlackRock) to reflect the reality that a dollar flowing into IBIT has a significantly higher impact on market structure than a dollar in smaller, fragmented funds. This ensures the indicator follows the actual mass of institutional capital.
Recalculating the Shadow: Nominal Price & AUM
A common point of confusion is that Bitcoin ETFs have a completely different nominal price than Bitcoin itself (e.g., an IBIT share may trade at $50 while BTC is at $100,000). To solve this, the script does not look at the dollar price of the shares. Instead, it uses Assets Under Management (AUM) and Relative Performance Mapping . By calculating the percentage growth of the funds' underlying value since inception and projecting that growth onto the Bitcoin price axis, the script "re-scales" the institutional entry levels. This allows us to see exactly where Wall Street is "underwater" on a standard Bitcoin chart.
The Mathematical Foundations: Genesis vs. Anchored
The indicator utilizes two distinct mathematical approaches to triangulate the "Truth" of institutional positioning. These are not arbitrary assumptions, but forward-mapped models verified against professional financial benchmarks.
1. Conservative Floor (Genesis Mode)
• The Logic: This model uses a Cumulative Inflow VWAP . It treats every dollar that has entered the ETFs since Day 1 as part of a single, massive ledger.
• Scientific Justification: This approach maps to the "Fortress Zone" of early, high-conviction capital. Historical AUM performance data suggests that the largest influx of structural capital occurred during the launch phase of 2024. This logic identifies the Ultimate Floor —the level where the entire ETF cohort would flip to a net loss. In late 2025 research (e.g., Glassnode "True Market Mean"), this model consistently aligns with the deepest structural support of the bull cycle.
2. Wall Street Entry (Anchored Mode)
• The Logic: This model utilize a Relative Performance Anchor . It synchronizes the Bitcoin price on Launch Day with the growth performance of the ETF fund shares.
• Scientific Justification: This approach identifies the "Active Participant Basis." It reflects the entry price for the capital that fueled the most recent expansion cycles. It maps directly to the "Active Investors' Realized Price" cited by institutional research firms, identifying the immediate psychological "pain threshold" for the current market majority.
3. Institutional Mean (Hybrid Mode)
• The Logic: A 50/50 mathematical blend of the Conservative Floor and the Wall Street Entry .
• Justification: This is the "Equilibrium Zone." It serves as a neutral baseline by balancing early-stage "Genesis" conviction with late-cycle volatility. It represents the median cost basis of all current institutional holders.
4. The Shadow Corridor (Full Range)
• The Logic: Visualizes the entire spread between the Conservative Floor and the Wall Street Entry.
• Justification: The "Structural Support Cloud." Instead of a single price, it defines a regime . As long as Bitcoin remains above this cloud, the institutional trend remains in an "Expansion Phase." A re-entry into this corridor suggests a transition from a trending market into a value-accumulation phase.
Tactical Playbook: Scenario Logic
The Shadow Corridor (Full Range) visualizes the area between these two models, creating an "Institutional War Zone."
• Active Support Test: When price tests the Wall Street Entry (upper boundary), it indicates the active institutional majority is at breakeven. Expect significant defensive buying (bids) as funds protect their yearly performance reports.
• Deep Value Regime: Trading inside the Corridor is defined as a "Value Regime." This is where institutional accumulation historically absorbs retail capitulation.
• The Premium Trap: When the distance between price and the Corridor exceeds 35-40%, the market is "speculatively overextended," signaling a high probability of mean-reversion.
• Macro Breakdown: A Weekly (1W) candle closing below the Conservative Floor (lower boundary) signals a structural trend shift, indicating the majority of ETF-era capital is officially in a drawdown.
Operational Recommendation Best viewed on the Daily (1D) timeframe for macro structural analysis, providing the most reliable signal for institutional defense zones.
Tags: bitcoin, btc, etf, blackrock, ibit, institutional, cost-basis, vwap, macro, cycle, realized-price, Rob Maths
Sigma Levels😎 How to Use Sigma Levels (Gold & Crude Only)
Sigma Levels are not magic buttons.
If you click Buy or Sell the moment price touches a line…
Congratulations — you’ve just donated liquidity to the market.
⚠️ Works ONLY for Gold (XAUUSD) and Crude Oil (WTI / USOIL / CL)
🧠 The Right Way (Sigma Way)
These levels are waiting zones, not entry alarms.
When price reaches a Sigma Level:
Sit on your hands
Watch the candles
Wait for price to speak first
Only consider an entry AFTER you see proper confirmation, such as:
Hammer or Inverted Hammer saying “nope, not going further”
Bullish or Bearish Engulfing that actually engulfs (not politely taps)
Morning Star / Evening Star waking the market up
Strong rejection wicks screaming “wrong direction”
❌ What NOT to Do
No blind entries
No guessing
No “it feels like it will reverse”
No revenge trades because the last one hurt your feelings
✅ Sigma Rule
Levels tell you where to look
Candles tell you when to act
No pattern = no trade
Patience = profit potential
Trade calm. Trade disciplined.
Let Sigma Levels do the waiting — not your stop-loss.
AMD Phases + Dashboard📊 AMD (Accumulation–Manipulation–Distribution) Indicator – How It Works
This indicator is a rule-based market phase classifier inspired by Wyckoff / Smart Money Concepts.
It does not predict the future, but instead interprets current market behavior using price range, volume, and volatility to identify where we are in the market cycle.
🔁 The AMD Market Cycle (Big Picture)
Markets tend to repeat this cycle:
Accumulation → Smart money buys quietly
Manipulation → Liquidity grab / false breakout
Distribution → Smart money sells to the public
Expansion / Decline → Strong directional move
Your script focuses on detecting phases 1–3, which occur before large moves.
🧠 What Data the Script Uses
The script analyzes three core variables:
1️⃣ Price Range (Structure)
Highest high vs lowest low over a lookback window
Tight range = consolidation
Expanding range = distribution or breakout
2️⃣ Volume Behavior
Low volume = lack of interest (accumulation)
Sudden volume spike = manipulation or distribution
3️⃣ Volatility Expansion
Small candles → compression
Large impulsive candles → transition or distribution
🟥 Phase 1 — Accumulation (Red Bubble, White Text)
What it means
Smart money is building positions
Price moves sideways
Public interest is low
Volume is below average
Volatility is compressed
How the script detects it
Narrow price range
Volume below its moving average
No strong trend direction
How traders use it
Look for long setups
Mark support and resistance
Prepare for a future breakout
Do NOT chase trades here
🟧 Phase 2 — Manipulation (Dark Orange Bubble, White Text)
What it means
Liquidity grab
False breakout above or below the range
Designed to trigger stop-losses
Often very emotional price action
How the script detects it
Sudden range expansion
Volume spike relative to recent average
Break outside the accumulation range
Candle closes back inside or shows rejection
How traders use it
Avoid entering breakouts immediately
Look for reversal confirmation
This is often the best risk-to-reward phase
🟦 Phase 3 — Distribution (Dark Blue Bubble, White Text)
What it means
Smart money is exiting positions
Public traders are buying late
Volatility increases
Trend starts to weaken or reverse
How the script detects it
Larger candles
Sustained high volume
Expanding range
Signs of exhaustion
How traders use it
Take profits on longs
Look for short setups
Watch for trend reversals
Stops should be tighter
🧭 Dashboard & On-Chart Bubbles
🔹 Dashboard
Shows the current detected phase
Updates in real time
Helps with context, not entries
🔹 Locked Bubbles
Labels are anchored to the candle
Each bubble appears only when a phase is active
Color-coded for instant recognition
Phase Color Text
Accumulation Red White
Manipulation Dark Orange White
Distribution Dark Blue White
⚠️ Important Notes
This is a context tool, not a signal generator
Best used with:
Support & resistance
Liquidity levels
Market structure (HH / HL / LH / LL)
Works best on:
15m – 4H
Crypto, Forex, Indices
🧩 How to Trade With It (Simple Framework)
Identify phase
Wait for confirmation
Enter on structure
Manage risk tightly
Exit when phase changes
🧠 Final Thought
Think of this indicator as:
“A market story teller, not a fortune teller.”
It helps you understand who is in control — buyers or sellers — and when NOT to trade, which is just as important.
WARNING , TRADE AT YOUR OWN RISK, THIS INFORMATION IS TO HELP , THE INFORMATION PROVIDED BY THE INDICATOR IS SPECULATIVE
Backtesting & Trading Engine [PineCoders]The PineCoders Backtesting and Trading Engine is a sophisticated framework with hybrid code that can run as a study to generate alerts for automated or discretionary trading while simultaneously providing backtest results. It can also easily be converted to a TradingView strategy in order to run TV backtesting. The Engine comes with many built-in strats for entries, filters, stops and exits, but you can also add you own.
If, like any self-respecting strategy modeler should, you spend a reasonable amount of time constantly researching new strategies and tinkering, our hope is that the Engine will become your inseparable go-to tool to test the validity of your creations, as once your tests are conclusive, you will be able to run this code as a study to generate the alerts required to put it in real-world use, whether for discretionary trading or to interface with an execution bot/app. You may also find the backtesting results the Engine produces in study mode enough for your needs and spend most of your time there, only occasionally converting to strategy mode in order to backtest using TV backtesting.
As you will quickly grasp when you bring up this script’s Settings, this is a complex tool. While you will be able to see results very quickly by just putting it on a chart and using its built-in strategies, in order to reap the full benefits of the PineCoders Engine, you will need to invest the time required to understand the subtleties involved in putting all its potential into play.
Disclaimer: use the Engine at your own risk.
Before we delve in more detail, here’s a bird’s eye view of the Engine’s features:
More than 40 built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
By combining your own strats to the built-in strats supplied with the Engine, and then tuning the numerous options and parameters in the Inputs dialog box, you will be able to play what-if scenarios from an infinite number of permutations.
USE CASES
You have written an indicator that provides an entry strat but it’s missing other components like a filter and a stop strategy. You add a plot in your indicator that respects the Engine’s External Signal Protocol, connect it to the Engine by simply selecting your indicator’s plot name in the Engine’s Settings/Inputs and then run tests on different combinations of entry stops, in-trade stops and profit taking strats to find out which one produces the best results with your entry strat.
You are building a complex strategy that you will want to run as an indicator generating alerts to be sent to a third-party execution bot. You insert your code in the Engine’s modules and leverage its trade management code to quickly move your strategy into production.
You have many different filters and want to explore results using them separately or in combination. Integrate the filter code in the Engine and run through different permutations or hook up your filtering through the external input and control your filter combos from your indicator.
You are tweaking the parameters of your entry, filter or stop strat. You integrate it in the Engine and evaluate its performance using the Engine’s statistics.
You always wondered what results a random entry strat would yield on your markets. You use the Engine’s built-in random entry strat and test it using different combinations of filters, stop and exit strats.
You want to evaluate the impact of fees and slippage on your strategy. You use the Engine’s inputs to play with different values and get immediate feedback in the detailed numbers provided in the Data Window.
You just want to inspect the individual trades your strategy generates. You include it in the Engine and then inspect trades visually on your charts, looking at the numbers in the Data Window as you move your cursor around.
You have never written a production-grade strategy and you want to learn how. Inspect the code in the Engine; you will find essential components typical of what is being used in actual trading systems.
You have run your system for a while and have compiled actual slippage information and your broker/exchange has updated his fees schedule. You enter the information in the Engine and run it on your markets to see the impact this has on your results.
FEATURES
Before going into the detail of the Inputs and the Data Window numbers, here’s a more detailed overview of the Engine’s features.
Built-in strats
The engine comes with more than 40 pre-coded strategies for the following standard system components:
Entries,
Filters,
Entry stops,
2 stage in-trade stops with kick-in rules,
Pyramiding rules,
Hard exits.
While some of the filter and stop strats provided may be useful in production-quality systems, you will not devise crazy profit-generating systems using only the entry strats supplied; that part is still up to you, as will be finding the elusive combination of components that makes winning systems. The Engine will, however, provide you with a solid foundation where all the trade management nitty-gritty is handled for you. By binding your custom strats to the Engine, you will be able to build reliable systems of the best quality currently allowed on the TV platform.
On-chart trade information
As you move over the bars in a trade, you will see trade numbers in the Data Window change at each bar. The engine calculates the P&L at every bar, including slippage and fees that would be incurred were the trade exited at that bar’s close. If the trade includes pyramided entries, those will be taken into account as well, although for those, final fees and slippage are only calculated at the trade’s exit.
You can also see on-chart markers for the entry level, stop positions, in-trade special events and entries/exits (you will want to disable these when using the Engine in strategy mode to see TV backtesting results).
Customization
You can couple your own strats to the Engine in two ways:
1. By inserting your own code in the Engine’s different modules. The modular design should enable you to do so with minimal effort by following the instructions in the code.
2. By linking an external indicator to the engine. After making the proper selections in the engine’s Settings and providing values respecting the engine’s protocol, your external indicator can, when the Engine is used in Indicator mode only:
Tell the engine when to enter long or short trades, but let the engine’s in-trade stop and exit strats manage the exits,
Signal both entries and exits,
Provide an entry stop along with your entry signal,
Filter other entry signals generated by any of the engine’s entry strats.
Conversion from strategy to study
TradingView strategies are required to backtest using the TradingView backtesting feature, but if you want to generate alerts with your script, whether for automated trading or just to trigger alerts that you will use in discretionary trading, your code has to run as a study since, for the time being, strategies can’t generate alerts. From hereon we will use indicator as a synonym for study.
Unless you want to maintain two code bases, you will need hybrid code that easily flips between strategy and indicator modes, and your code will need to restrict its use of strategy() calls and their arguments if it’s going to be able to run both as an indicator and a strategy using the same trade logic. That’s one of the benefits of using this Engine. Once you will have entered your own strats in the Engine, it will be a matter of commenting/uncommenting only four lines of code to flip between indicator and strategy modes in a matter of seconds.
Additionally, even when running in Indicator mode, the Engine will still provide you with precious numbers on your individual trades and global results, some of which are not available with normal TradingView backtesting.
Post-Exit Analysis for alternate outcomes (PEA)
While typical backtesting shows results of trade outcomes, PEA focuses on what could have happened after the exit. The intention is to help traders get an idea of the opportunity/risk in the bars following the trade in order to evaluate if their exit strategies are too aggressive or conservative.
After a trade is exited, the Engine’s PEA module continues analyzing outcomes for a user-defined quantity of bars. It identifies the maximum opportunity and risk available in that space, and calculates the drawdown required to reach the highest opportunity level post-exit, while recording the number of bars to that point.
Typically, if you can’t find opportunity greater than 1X past your trade using a few different reasonable lengths of PEA, your strategy is doing pretty good at capturing opportunity. Remember that 100% of opportunity is never capturable. If, however, PEA was finding post-trade maximum opportunity of 3 or 4X with average drawdowns of 0.3 to those areas, this could be a clue revealing your system is exiting trades prematurely. To analyze PEA numbers, you can uncomment complete sets of plots in the Plot module to reveal detailed global and individual PEA numbers.
Statistics
The Engine provides stats on your trades that TV backtesting does not provide, such as:
Average Profitability Per Trade (APPT), aka statistical expectancy, a crucial value.
APPT per bar,
Average stop size,
Traded volume .
It also shows you on a trade-by-trade basis, on-going individual trade results and data.
In-trade events
In-trade events can plot reminders and trigger alerts when they occur. The built-in events are:
Price approaching stop,
Possible tops/bottoms,
Large stop movement (for discretionary trading where stop is moved manually),
Large price movements.
Slippage and Fees
Even when running in indicator mode, the Engine allows for slippage and fees to be included in the logic and test results.
Alerts
The alert creation mechanism allows you to configure alerts on any combination of the normal or pyramided entries, exits and in-trade events.
Backtesting results
A few words on the numbers calculated in the Engine. Priority is given to numbers not shown in TV backtesting, as you can readily convert the script to a strategy if you need them.
We have chosen to focus on numbers expressing results relative to X (the trade’s risk) rather than in absolute currency numbers or in other more conventional but less useful ways. For example, most of the individual trade results are not shown in percentages, as this unit of measure is often less meaningful than those expressed in units of risk (X). A trade that closes with a +25% result, for example, is a poor outcome if it was entered with a -50% stop. Expressed in X, this trade’s P&L becomes 0.5, which provides much better insight into the trade’s outcome. A trade that closes with a P&L of +2X has earned twice the risk incurred upon entry, which would represent a pre-trade risk:reward ratio of 2.
The way to go about it when you think in X’s and that you adopt the sound risk management policy to risk a fixed percentage of your account on each trade is to equate a currency value to a unit of X. E.g. your account is 10K USD and you decide you will risk a maximum of 1% of it on each trade. That means your unit of X for each trade is worth 100 USD. If your APPT is 2X, this means every time you risk 100 USD in a trade, you can expect to make, on average, 200 USD.
By presenting results this way, we hope that the Engine’s statistics will appeal to those cognisant of sound risk management strategies, while gently leading traders who aren’t, towards them.
We trade to turn in tangible profits of course, so at some point currency must come into play. Accordingly, some values such as equity, P&L, slippage and fees are expressed in currency.
Many of the usual numbers shown in TV backtests are nonetheless available, but they have been commented out in the Engine’s Plot module.
Position sizing and risk management
All good system designers understand that optimal risk management is at the very heart of all winning strategies. The risk in a trade is defined by the fraction of current equity represented by the amplitude of the stop, so in order to manage risk optimally on each trade, position size should adjust to the stop’s amplitude. Systems that enter trades with a fixed stop amplitude can get away with calculating position size as a fixed percentage of current equity. In the context of a test run where equity varies, what represents a fixed amount of risk translates into different currency values.
Dynamically adjusting position size throughout a system’s life is optimal in many ways. First, as position sizing will vary with current equity, it reproduces a behavioral pattern common to experienced traders, who will dial down risk when confronted to poor performance and increase it when performance improves. Second, limiting risk confers more predictability to statistical test results. Third, position sizing isn’t just about managing risk, it’s also about maximizing opportunity. By using the maximum leverage (no reference to trading on margin here) into the trade that your risk management strategy allows, a dynamic position size allows you to capture maximal opportunity.
To calculate position sizes using the fixed risk method, we use the following formula: Position = Account * MaxRisk% / Stop% [, which calculates a position size taking into account the trade’s entry stop so that if the trade is stopped out, 100 USD will be lost. For someone who manages risk this way, common instructions to invest a certain percentage of your account in a position are simply worthless, as they do not take into account the risk incurred in the trade.
The Engine lets you select either the fixed risk or fixed percentage of equity position sizing methods. The closest thing to dynamic position sizing that can currently be done with alerts is to use a bot that allows syntax to specify position size as a percentage of equity which, while being dynamic in the sense that it will adapt to current equity when the trade is entered, does not allow us to modulate position size using the stop’s amplitude. Changes to alerts are on the way which should solve this problem.
In order for you to simulate performance with the constraint of fixed position sizing, the Engine also offers a third, less preferable option, where position size is defined as a fixed percentage of initial capital so that it is constant throughout the test and will thus represent a varying proportion of current equity.
Let’s recap. The three position sizing methods the Engine offers are:
1. By specifying the maximum percentage of risk to incur on your remaining equity, so the Engine will dynamically adjust position size for each trade so that, combining the stop’s amplitude with position size will yield a fixed percentage of risk incurred on current equity,
2. By specifying a fixed percentage of remaining equity. Note that unless your system has a fixed stop at entry, this method will not provide maximal risk control, as risk will vary with the amplitude of the stop for every trade. This method, as the first, does however have the advantage of automatically adjusting position size to equity. It is the Engine’s default method because it has an equivalent in TV backtesting, so when flipping between indicator and strategy mode, test results will more or less correspond.
3. By specifying a fixed percentage of the Initial Capital. While this is the least preferable method, it nonetheless reflects the reality confronted by most system designers on TradingView today. In this case, risk varies both because the fixed position size in initial capital currency represents a varying percentage of remaining equity, and because the trade’s stop amplitude may vary, adding another variability vector to risk.
Note that the Engine cannot display equity results for strategies entering trades for a fixed amount of shares/contracts at a variable price.
SETTINGS/INPUTS
Because the initial text first published with a script cannot be edited later and because there are just too many options, the Engine’s Inputs will not be covered in minute detail, as they will most certainly evolve. We will go over them with broad strokes; you should be able to figure the rest out. If you have questions, just ask them here or in the PineCoders Telegram group.
Display
The display header’s checkbox does nothing.
For the moment, only one exit strategy uses a take profit level, so only that one will show information when checking “Show Take Profit Level”.
Entries
You can activate two simultaneous entry strats, each selected from the same set of strats contained in the Engine. If you select two and they fire simultaneously, the main strat’s signal will be used.
The random strat in each list uses a different seed, so you will get different results from each.
The “Filter transitions” and “Filter states” strats delegate signal generation to the selected filter(s). “Filter transitions” signals will only fire when the filter transitions into bull/bear state, so after a trade is stopped out, the next entry may take some time to trigger if the filter’s state does not change quickly. When you choose “Filter states”, then a new trade will be entered immediately after an exit in the direction the filter allows.
If you select “External Indicator”, your indicator will need to generate a +2/-2 (or a positive/negative stop value) to enter a long/short position, providing the selected filters allow for it. If you wish to use the Engine’s capacity to also derive the entry stop level from your indicator’s signal, then you must explicitly choose this option in the Entry Stops section.
Filters
You can activate as many filters as you wish; they are additive. The “Maximum stop allowed on entry” is an important component of proper risk management. If your system has an average 3% stop size and you need to trade using fixed position sizes because of alert/execution bot limitations, you must use this filter because if your system was to enter a trade with a 15% stop, that trade would incur 5 times the normal risk, and its result would account for an abnormally high proportion in your system’s performance.
Remember that any filter can also be used as an entry signal, either when it changes states, or whenever no trade is active and the filter is in a bull or bear mode.
Entry Stops
An entry stop must be selected in the Engine, as it requires a stop level before the in-trade stop is calculated. Until the selected in-trade stop strat generates a stop that comes closer to price than the entry stop (or respects another one of the in-trade stops kick in strats), the entry stop level is used.
It is here that you must select “External Indicator” if your indicator supplies a +price/-price value to be used as the entry stop. A +price is expected for a long entry and a -price value will enter a short with a stop at price. Note that the price is the absolute price, not an offset to the current price level.
In-Trade Stops
The Engine comes with many built-in in-trade stop strats. Note that some of them share the “Length” and “Multiple” field, so when you swap between them, be sure that the length and multiple in use correspond to what you want for that stop strat. Suggested defaults appear with the name of each strat in the dropdown.
In addition to the strat you wish to use, you must also determine when it kicks in to replace the initial entry’s stop, which is determined using different strats. For strats where you can define a positive or negative multiple of X, percentage or fixed value for a kick-in strat, a positive value is above the trade’s entry fill and a negative one below. A value of zero represents breakeven.
Pyramiding
What you specify in this section are the rules that allow pyramiding to happen. By themselves, these rules will not generate pyramiding entries. For those to happen, entry signals must be issued by one of the active entry strats, and conform to the pyramiding rules which act as a filter for them. The “Filter must allow entry” selection must be chosen if you want the usual system’s filters to act as additional filtering criteria for your pyramided entries.
Hard Exits
You can choose from a variety of hard exit strats. Hard exits are exit strategies which signal trade exits on specific events, as opposed to price breaching a stop level in In-Trade Stops strategies. They are self-explanatory. The last one labelled When Take Profit Level (multiple of X) is reached is the only one that uses a level, but contrary to stops, it is above price and while it is relative because it is expressed as a multiple of X, it does not move during the trade. This is the level called Take Profit that is show when the “Show Take Profit Level” checkbox is checked in the Display section.
While stops focus on managing risk, hard exit strategies try to put the emphasis on capturing opportunity.
Slippage
You can define it as a percentage or a fixed value, with different settings for entries and exits. The entry and exit markers on the chart show the impact of slippage on the entry price (the fill).
Fees
Fees, whether expressed as a percentage of position size in and out of the trade or as a fixed value per in and out, are in the same units of currency as the capital defined in the Position Sizing section. Fees being deducted from your Capital, they do not have an impact on the chart marker positions.
In-Trade Events
These events will only trigger during trades. They can be helpful to act as reminders for traders using the Engine as assistance to discretionary trading.
Post-Exit Analysis
It is normally on. Some of its results will show in the Global Numbers section of the Data Window. Only a few of the statistics generated are shown; many more are available, but commented out in the Plot module.
Date Range Filtering
Note that you don’t have to change the dates to enable/diable filtering. When you are done with a specific date range, just uncheck “Date Range Filtering” to disable date filtering.
Alert Triggers
Each selection corresponds to one condition. Conditions can be combined into a single alert as you please. Just be sure you have selected the ones you want to trigger the alert before you create the alert. For example, if you trade in both directions and you want a single alert to trigger on both types of exits, you must select both “Long Exit” and “Short Exit” before creating your alert.
Once the alert is triggered, these settings no longer have relevance as they have been saved with the alert.
When viewing charts where an alert has just triggered, if your alert triggers on more than one condition, you will need the appropriate markers active on your chart to figure out which condition triggered the alert, since plotting of markers is independent of alert management.
Position sizing
You have 3 options to determine position size:
1. Proportional to Stop -> Variable, with a cap on size.
2. Percentage of equity -> Variable.
3. Percentage of Initial Capital -> Fixed.
External Indicator
This is where you connect your indicator’s plot that will generate the signals the Engine will act upon. Remember this only works in Indicator mode.
DATA WINDOW INFORMATION
The top part of the window contains global numbers while the individual trade information appears in the bottom part. The different types of units used to express values are:
curr: denotes the currency used in the Position Sizing section of Inputs for the Initial Capital value.
quote: denotes quote currency, i.e. the value the instrument is expressed in, or the right side of the market pair (USD in EURUSD ).
X: the stop’s amplitude, itself expressed in quote currency, which we use to express a trade’s P&L, so that a trade with P&L=2X has made twice the stop’s amplitude in profit. This is sometimes referred to as R, since it represents one unit of risk. It is also the unit of measure used in the APPT, which denotes expected reward per unit of risk.
X%: is also the stop’s amplitude, but expressed as a percentage of the Entry Fill.
The numbers appearing in the Data Window are all prefixed:
“ALL:” the number is the average for all first entries and pyramided entries.
”1ST:” the number is for first entries only.
”PYR:” the number is for pyramided entries only.
”PEA:” the number is for Post-Exit Analyses
Global Numbers
Numbers in this section represent the results of all trades up to the cursor on the chart.
Average Profitability Per Trade (X): This value is the most important gauge of your strat’s worthiness. It represents the returns that can be expected from your strat for each unit of risk incurred. E.g.: your APPT is 2.0, thus for every unit of currency you invest in a trade, you can on average expect to obtain 2 after the trade. APPT is also referred to as “statistical expectancy”. If it is negative, your strategy is losing, even if your win rate is very good (it means your winning trades aren’t winning enough, or your losing trades lose too much, or both). Its counterpart in currency is also shown, as is the APPT/bar, which can be a useful gauge in deciding between rivalling systems.
Profit Factor: Gross of winning trades/Gross of losing trades. Strategy is profitable when >1. Not as useful as the APPT because it doesn’t take into account the win rate and the average win/loss per trade. It is calculated from the total winning/losing results of this particular backtest and has less predictive value than the APPT. A good profit factor together with a poor APPT means you just found a chart where your system outperformed. Relying too much on the profit factor is a bit like a poker player who would think going all in with two’s against aces is optimal because he just won a hand that way.
Win Rate: Percentage of winning trades out of all trades. Taken alone, it doesn’t have much to do with strategy profitability. You can have a win rate of 99% but if that one trade in 100 ruins you because of poor risk management, 99% doesn’t look so good anymore. This number speaks more of the system’s profile than its worthiness. Still, it can be useful to gauge if the system fits your personality. It can also be useful to traders intending to sell their systems, as low win rate systems are more difficult to sell and require more handholding of worried customers.
Equity (curr): This the sum of initial capital and the P&L of your system’s trades, including fees and slippage.
Return on Capital is the equivalent of TV’s Net Profit figure, i.e. the variation on your initial capital.
Maximum drawdown is the maximal drawdown from the highest equity point until the drop . There is also a close to close (meaning it doesn’t take into account in-trade variations) maximum drawdown value commented out in the code.
The next values are self-explanatory, until:
PYR: Avg Profitability Per Entry (X): this is the APPT for all pyramided entries.
PEA: Avg Max Opp . Available (X): the average maximal opportunity found in the Post-Exit Analyses.
PEA: Avg Drawdown to Max Opp . (X): this represents the maximum drawdown (incurred from the close at the beginning of the PEA analysis) required to reach the maximal opportunity point.
Trade Information
Numbers in this section concern only the current trade under the cursor. Most of them are self-explanatory. Use the description’s prefix to determine what the values applies to.
PYR: Avg Profitability Per Entry (X): While this value includes the impact of all current pyramided entries (and only those) and updates when you move your cursor around, P&L only reflects fees at the trade’s last bar.
PEA: Max Opp . Available (X): It’s the most profitable close reached post-trade, measured from the trade’s Exit Fill, expressed in the X value of the trade the PEA follows.
PEA: Drawdown to Max Opp . (X): This is the maximum drawdown from the trade’s Exit Fill that needs to be sustained in order to reach the maximum opportunity point, also expressed in X. Note that PEA numbers do not include slippage and fees.
EXTERNAL SIGNAL PROTOCOL
Only one external indicator can be connected to a script; in order to leverage its use to the fullest, the engine provides options to use it as either an entry signal, an entry/exit signal or a filter. When used as an entry signal, you can also use the signal to provide the entry’s stop. Here’s how this works:
For filter state: supply +1 for bull (long entries allowed), -1 for bear (short entries allowed).
For entry signals: supply +2 for long, -2 for short.
For exit signals: supply +3 for exit from long, -3 for exit from short.
To send an entry stop level with an entry signal: Send positive stop level for long entry (e.g. 103.33 to enter a long with a stop at 103.33), negative stop level for short entry (e.g. -103.33 to enter a short with a stop at 103.33). If you use this feature, your indicator will have to check for exact stop levels of 1.0, 2.0 or 3.0 and their negative counterparts, and fudge them with a tick in order to avoid confusion with other signals in the protocol.
Remember that mere generation of the values by your indicator will have no effect until you explicitly allow their use in the appropriate sections of the Engine’s Settings/Inputs.
An example of a script issuing a signal for the Engine is published by PineCoders.
RECOMMENDATIONS TO ASPIRING SYSTEM DESIGNERS
Stick to higher timeframes. On progressively lower timeframes, margins decrease and fees and slippage take a proportionally larger portion of profits, to the point where they can very easily turn a profitable strategy into a losing one. Additionally, your margin for error shrinks as the equilibrium of your system’s profitability becomes more fragile with the tight numbers involved in the shorter time frames. Avoid <1H time frames.
Know and calculate fees and slippage. To avoid market shock, backtest using conservative fees and slippage parameters. Systems rarely show unexpectedly good returns when they are confronted to the markets, so put all chances on your side by being outrageously conservative—or a the very least, realistic. Test results that do not include fees and slippage are worthless. Slippage is there for a reason, and that’s because our interventions in the market change the market. It is easier to find alpha in illiquid markets such as cryptos because not many large players participate in them. If your backtesting results are based on moving large positions and you don’t also add the inevitable slippage that will occur when you enter/exit thin markets, your backtesting will produce unrealistic results. Even if you do include large slippage in your settings, the Engine can only do so much as it will not let slippage push fills past the high or low of the entry bar, but the gap may be much larger in illiquid markets.
Never test and optimize your system on the same dataset , as that is the perfect recipe for overfitting or data dredging, which is trying to find one precise set of rules/parameters that works only on one dataset. These setups are the most fragile and often get destroyed when they meet the real world.
Try to find datasets yielding more than 100 trades. Less than that and results are not as reliable.
Consider all backtesting results with suspicion. If you never entertained sceptic tendencies, now is the time to begin. If your backtest results look really good, assume they are flawed, either because of your methodology, the data you’re using or the software doing the testing. Always assume the worse and learn proper backtesting techniques such as monte carlo simulations and walk forward analysis to avoid the traps and biases that unchecked greed will set for you. If you are not familiar with concepts such as survivor bias, lookahead bias and confirmation bias, learn about them.
Stick to simple bars or candles when designing systems. Other types of bars often do not yield reliable results, whether by design (Heikin Ashi) or because of the way they are implemented on TV (Renko bars).
Know that you don’t know and use that knowledge to learn more about systems and how to properly test them, about your biases, and about yourself.
Manage risk first , then capture opportunity.
Respect the inherent uncertainty of the future. Cleanse yourself of the sad arrogance and unchecked greed common to newcomers to trading. Strive for rationality. Respect the fact that while backtest results may look promising, there is no guarantee they will repeat in the future (there is actually a high probability they won’t!), because the future is fundamentally unknowable. If you develop a system that looks promising, don’t oversell it to others whose greed may lead them to entertain unreasonable expectations.
Have a plan. Understand what king of trading system you are trying to build. Have a clear picture or where entries, exits and other important levels will be in the sort of trade you are trying to create with your system. This stated direction will help you discard more efficiently many of the inevitably useless ideas that will pop up during system design.
Be wary of complexity. Experienced systems engineers understand how rapidly complexity builds when you assemble components together—however simple each one may be. The more complex your system, the more difficult it will be to manage.
Play! . Allow yourself time to play around when you design your systems. While much comes about from working with a purpose, great ideas sometimes come out of just trying things with no set goal, when you are stuck and don’t know how to move ahead. Have fun!
@LucF
NOTES
While the engine’s code can supply multiple consecutive entries of longs or shorts in order to scale positions (pyramid), all exits currently assume the execution bot will exit the totality of the position. No partial exits are currently possible with the Engine.
Because the Engine is literally crippled by the limitations on the number of plots a script can output on TV; it can only show a fraction of all the information it calculates in the Data Window. You will find in the Plot Module vast amounts of commented out lines that you can activate if you also disable an equivalent number of other plots. This may be useful to explore certain characteristics of your system in more detail.
When backtesting using the TV backtesting feature, you will need to provide the strategy parameters you wish to use through either Settings/Properties or by changing the default values in the code’s header. These values are defined in variables and used not only in the strategy() statement, but also as defaults in the Engine’s relevant Inputs.
If you want to test using pyramiding, then both the strategy’s Setting/Properties and the Engine’s Settings/Inputs need to allow pyramiding.
If you find any bugs in the Engine, please let us know.
THANKS
To @glaz for allowing the use of his unpublished MA Squize in the filters.
To @everget for his Chandelier stop code, which is also used as a filter in the Engine.
To @RicardoSantos for his pseudo-random generator, and because it’s from him that I first read in the Pine chat about the idea of using an external indicator as input into another. In the PineCoders group, @theheirophant then mentioned the idea of using it as a buy/sell signal and @simpelyfe showed a piece of code implementing the idea. That’s the tortuous story behind the use of the external indicator in the Engine.
To @admin for the Volatility stop’s original code and for the donchian function lifted from Ichimoku .
To @BobHoward21 for the v3 version of Volatility Stop .
To @scarf and @midtownsk8rguy for the color tuning.
To many other scripters who provided encouragement and suggestions for improvement during the long process of writing and testing this piece of code.
To J. Welles Wilder Jr. for ATR, used extensively throughout the Engine.
To TradingView for graciously making an account available to PineCoders.
And finally, to all fellow PineCoders for the constant intellectual stimulation; it is a privilege to share ideas with you all. The Engine is for all TradingView PineCoders, of course—but especially for you.
Look first. Then leap.
Great Expectations [LucF]Great Expectations helps traders answer the question: What is possible? It is a powerful question, yet exploration of the unknown always entails risk. A more complete set of questions better suited to traders could be:
What opportunity exists from any given point on a chart?
What portion of this opportunity can be realistically captured?
What risk will be incurred in trying to do so, and how long will it take?
Great Expectations is the result of an exploration of these questions. It is a trade simulator that generates visual and quantitative information to help strategy modelers visually identify and analyse areas of optimal expectation on charts, whether they are designing automated or discretionary strategies.
WARNING: Great Expectations is NOT an indicator that helps determine the current state of a market. It works by looking at points in the past from which the future is already known. It uses one definition of repainting extensively (i.e. it goes back in the past to print information that could not have been know at the time). Repainting understood that way is in fact almost all the indicator does! —albeit for what I hope is a noble cause. The indicator is of no use whatsoever in analyzing markets in real-time. If you do not understand what it does, please stay away!
This is an indicator—not a strategy that uses TradingView’s backtesting engine. It works by simulating trades, not unlike a backtest, but with the crucial difference that it assumes a trade (either long or short) is entered on all bars in the historic sample. It walks forward from each bar and determines possible outcomes, gathering individual trade statistics that in turn generate precious global statistics from all outcomes tested on the chart.
Great Expectations provides numbers summarizing trade results on all simulations run from the chart. Those numbers cannot be compared to backtest-produced numbers since all non-filtered bars are examined, even if an entry was taken on the bar immediately preceding the current one, which never happens in a backtest. This peculiarity does NOT invalidate Great Expectations calculations; it just entails that results be considered under a different light. Provided they are evaluated within the indicator’s context, they can be useful—sometimes even more than backtesting results, e.g. in evaluating the impact of parameter-fitting or variations in entry, exit or filtering strats.
Traders and strategy modelers are creatures of hope often suffering from blurred vision; my hope is that Great Expectations will help them appraise the validity of their setup and strat intuitions in a realistic fashion, preventing confirmation bias from obstructing perspective—and great expectations from turning into financial great deceptions.
USE CASES
You’ve identified what looks like a promising setup on other indicators. You load Great Expectations on the chart and evaluate if its high-expectation areas match locations where your setup’s conditions occur. Unless today is your lucky day, chances are the indicator will help you realize your setup is not as promising as you had hoped.
You want to get a rough estimate of the optimal trade duration for a chart and you don’t mind using the entry and exit strategies provided with the indicator. You use the trade length readouts of the indicator.
You’re experimenting with a new stop strategy and want to know how long it will keep you in trades, on average. You integrate your stop strategy in the indicator’s code and look at the average trade length it produces and the TST ratio to evaluate its performance.
You have put together your own entry and exit criteria and are looking for a filter that will help you improve backtesting results. You visually ascertain the suitability of your filter by looking at its results on the charts with great Expectations, to see if your filter is choosing its areas correctly.
You have a strategy that shows backtested trades on your chart. Great Expectations can help you evaluate how well your strategy is benefitting from high-opportunity areas while avoiding poor expectation spots.
You want more complete statistics on your set of strategies than what backtesting will provide. You use Great Expectations, knowing that it tests all bars in the sample that correspond to your criteria, as opposed to backtesting results which are limited to a subset of all possible entries.
You want to fool your friends into thinking you’ve designed the holy grail of indicators, something that identifies optimal opportunities on any chart; you show them the P&L cloud.
FEATURES
For one trade
At any given point on the chart, assuming a trade is entered there, Great Expectations shows you information specific to that trade simulation both on the chart and in the Data Window.
The chart can display:
the P & L Cloud which shows whether the trade ended profitably or not, and by how much,
the Opportunity & Risk Cloud which the maximum opportunity and risk the simulation encountered. When superimposed over the P & L cloud, you will see what I call the managed opportunity and risk, i.e the portion of maximum opportunity that was captured and the portion of the maximum risk that was incurred,
the target and if it was reached,
a background that uses a gradient to show different levels of trade length, P&L or how frequently the target was reached during simulation.
The Data Window displays more than 40 values on individual trades and global results. For any given trade you will know:
Entry/Exit levels, including slippage impact,
It’s outcome and duration,
P/L achieved,
The fraction of the maximum opportunity/risk managed by the trade.
For all trades
After going through all the possible trades on the chart, the indicator will provide you with a rare view of all outcomes expressed with the P&L cloud, which allows us to instantly see the most/least profitable areas of a chart using trade data as support, while also showing its relationship with the opportunity/risk encountered during the simulation. The difference between the two clouds is the managed opportunity and risk.
The Data Window will present you with numbers which we will go through later. Some of them are: average stop size, P/L, win rate, % opportunity managed, trade lengths for different types of trade outcomes and the TST (Target:Stop Travel) ratio.
Let’s see Great Expectations in action… and remember to open your Data Window!
INPUTS
Trade direction : You must first choose if you wish to look at long or short trades. Because of the way the indicator works and the amount of visual information on the chart, it is only practical to look at one type of trades at a time. The default is Longs.
Maximum trade Length (MaxL) : This is the maximum walk forward distance the simulator will go in analyzing outcomes from any given point in the past. It also determines the size of the dead zone among the chart’s last bars. A red background line identifies the beginning of the dead zone for which not enough bars have elapsed to analyze outcomes for the maximum trade length defined. If an ATR-based entry stop is used, that length is added to the wait time before beginning simulations, so that the first entry starts with a clean ATR value. On a sample of around 16000 bars, my tests show that the indicator runs into server errors at lengths of around 290, i.e. having completed ~4,6M simulation loop iterations. That is way too high a length anyways; 100 will usually be amply enough to ring out all the possibilities out of a simulation, and on shorter time frames, 30 can be enough. While making it unduly small will prevent simulations of expressing the market’s potential, the less you use, the faster the indicator will run. The default is 40.
Unrealized P&L base at End of Trade (EOT) : When a simulation ends and the trade is still open, we calculate unrealized P&L from an exit order executed from either the last in-trade stop on the previous bar, or the close of the last bar. You can readily see the impact of this selection on the chart, with the P&L cloud. The default is on the close.
Display : The check box besides the title does nothing.
Show target : Shows a green line displaying the trade’s target expressed as a multiple of X, i.e. the amplitude of the entry stop. I call this value “X” and use it as a unit to express profit and loss on a trade (some call it “R”). The line is highlighted for trades where the close reached the target during the trade, whether the trade ended in profit or loss. This is also where you specify the multiple of X you wish to use in calculating targets. The multiple is used even if targets are not displayed.
Show P&L Cloud : The cloud allows traders to see right away the profitable areas of the chart. The only line printed with the cloud is the “end of trade line” (EOT). The EOT line is the only way one can see the level where a trade ended on the chart (in the Data Window you can see it as the “Exit Fill” value). The EOT level for the trade determines if the trade ended in a profit or a loss. Its value represents one of the following:
- fill from order executed at close of bar where stop is breached during trade (which produces “Realized P/L”),
- simulation of a fill pseudo-fill at the user-defined EOT level (last close or stop level) if the trade runs its course through MaxL bars without getting stopped (producing Unrealized P/L).
The EOT line and the cloud fill print in green when the trade’s outcome is profitable and in red when it is not. If the trade was closed after breaching the stop, the line appears brighter.
Show Opportunity&Risk Cloud : Displays the maximum opportunity/risk that was present during the trade, i.e. the maximum and minimum prices reached.
Background Color Scheme : Allows you to choose between 3 different color schemes for the background gradients, to accommodate different types of chart background/candles. Select “None” if you don’t want a background.
Background source : Determines what value will be used to generate the different intensities of the gradient. You can choose trade length (brighter is shorter), Trade P&L (brighter is higher) or the number of times the target was reached during simulation (brighter is higher). The default is Trade Length.
Entry strat : The check box besides the title does nothing. The default strat is All bars, meaning a trade will be simulated from all bars not excluded by the filters where a MaxL bars future exists. For fun, I’ve included a pseudo-random entry strat (an indirect way of changing the seed is to vary the starting date of the simulation).
Show Filter State : Displays areas where the combination of filters you have selected are allowing entries. Filtering occurs as per your selection(s), whether the state is displayed or not. The effect of multiple selections is additive. The filters are:
1. Bar direction: Longs will only be entered if close>open and vice versa.
2. Rising Volume: Applies to both long and shorts.
3. Rising/falling MA of the length you choose over the number of bars you choose.
4. Custom indicator: You can feed your own filtering signal through this from another indicator. It must produce a signal of 1 to allow long entries and 0 to allow shorts.
Show Entry Stops :
1. Multiple of user-defined length ATR.
2. Fixed percentage.
3. Fixed value.
All entry stops are calculated using the entry fill price as a reference. The fill price is calculated from the current bar’s open, to which slippage is added if configured. This simulates the case where the strategy issued the entry signal on the previous bar for it to be executed at the next bar’s open.
The entry stop remains active until the in-trade stop becomes the more aggressive of the two stops. From then on, the entry stop will be ignored, unless a bar close breaches the in-trade stop, in which case the stop will be reset with a new entry stop and the process repeats.
Show In-trade stops : Displays in bright red the selected in-trade stop (be sure to read the note in this section about them).
1. ATR multiple: added/subtracted from the average of the two previous bars minimum/maximum of open/close.
2. A trailing stop with a deviation expressed as a multiple of entry stop (X).
3. A fixed percentage trailing stop.
Trailing stops deviations are measured from the highest/lowest high/low reached during the trade.
Note: There is a twist with the in-trade stops. It’s that for any given bar, its in-trade stop can hold multiple values, as each successive pass of the advancing simulation loops goes over it from a different entry points. What is printed is the stop from the loop that ended on that bar, which may have nothing to do with other instances of the trade’s in-trade stop for the same bar when visited from other starting points in previous simulations. There is just no practical way to print all stop values that were used for any given bar. While the printed entry stops are the actual ones used on each bar, the in-trade stops shown are merely the last instance used among many.
Include Slippage : if checked, slippage will be added/subtracted from order price to yield the fill price. Slippage is in percentage. If you choose to include slippage in the simulations, remember to adjust it by considering the liquidity of the markets and the time frame you’ll be analyzing.
Include Fees : if checked, fees will be subtracted/added to both realized an unrealized trade profits/losses. Fees are in percentage. The default fees work well for crypto markets but will need adjusting for others—especially in Forex. Remember to modify them accordingly as they can have a major impact on results. Both fees and slippage are included to remind us of their importance, even if the global numbers produced by the indicator are not representative of a real trading scenario composed of sequential trades.
Date Range filtering : the usual. Just note that the checkbox has to be selected for date filtering to activate.
DATA WINDOW
Most of the information produced by this indicator is made available in the Data Window, which you bring up by using the icon below the Watchlist and Alerts buttons at the right of the TV UI. Here’s what’s there.
Some of the information presented in the Data Window is standard trade data; other values are not so standard; e. g. the notions of managed opportunity and risk and Target:Stop Travel ratio. The interplay between all the values provided by Great Expectations is inherently complex, even for a static set of entry/filter/exit strats. During the constant updating which the habitual process of progressive refinement in building strategies that is the lot of strategy modelers entails, another level of complexity is no doubt added to the analysis of this indicator’s values. While I don’t want to sound like Wolfram presenting A New Kind of Science , I do believe that if you are a serious strategy modeler and spend the time required to get used to using all the information this indicator makes available, you may find it useful.
Trade Information
Entry Order : This is the open of the bar where simulation starts. We suppose that an entry signal was generated at the previous bar.
Entry Fill (including slip.) : The actual entry price, including slippage. This is the base price from which other values will be calculated.
Exit Order : When a stop is breached, an exit order is executed from the close of the bar that breached the stop. While there is no “In-trade stop” value included in the Data Window (other than the End of trade Stop previously discussed), this “Exit Order” value is how we can know the level where the trade was stopped during the simulation. The “Trade Length” value will then show the bar where the stop was breached.
Exit Fill (including slip.) : When the exit order is simulated, slippage is added to the order level to create the fill.
Chart: Target : This is the target calculated at the beginning of the simulation. This value also appear on the chart in teal. It is controlled by the multiple of X defined under the “Show Target” checkbox in the Inputs.
Chart: Entry Stop : This value also appears on the chart (the red dots under points where a trade was simulated). Its value is controlled by the Entry Strat chosen in the Inputs.
X (% Fill, including Fees) and X (currency) : This is the stop’s amplitude (Entry Fill – Entry Stop) + Fees. It represents the risk incurred upon entry and will be used to express P&L. We will show R expressed in both a percentage of the Entry Fill level (this value), and currency (the next value). This value represents the risk in the risk:reward ratio and is considered to be a unit of 1 so that RR can be expressed as a single value (i.e. “2” actually meaning “1:2”).
Trade Length : If trade was stopped, it’s the number of bars elapsed until then. The trade is then considered “Closed”. If the trade ends without being stopped (there is no profit-taking strat implemented, so the stop is the only exit strat), then the trade is “Open”, the length is MaxL and it will show in orange. Otherwise the value will print in green/red to reflect if the trade is winning/losing.
P&L (X) : The P&L of the trade, expressed as a multiple of X, which takes into account fees paid at entry and exit. Given our default target setting at 2 units of “X”, a trade that closes at its target will have produced a P&L of +2.0, i.e. twice the value of X (not counting fees paid at exit ). A trade that gets stopped late 50% further that the entry stop’s level will produce a P&L of -1.5X.
P&L (currency, including Fees) : same value as above, but expressed in currency.
Target first reached at bar : If price closed above the target during the trade (even if it occurs after the trade was stopped), this will show when. This value will be used in calculating our TST ratio.
Times Stop/Target reached in sim. : Includes all occurrences during the complete simulation loop.
Opportunity (X) : The highest/lowest price reached during a simulation, i.e. the maximum opportunity encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk (X) : The lowest/highest price reached during a simulation, i.e. the maximum risk encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk:Opportunity : The greater this ratio, the greater Opportunity is, compared to Risk.
Managed Opportunity (%) : The portion of Opportunity that was captured by the highest/low stop position, even if it occurred after a previous stop closed the trade.
Managed Risk (%) : The portion of risk that was protected by the lowest/highest stop position, even if it occurred after a previous stop closed the trade. When this value is greater than 100%, it means the trade’s stop is protecting more than the maximum risk, which is frequent. You will, however, never see close to those values for the Managed Opportunity value, since the stop would have to be higher than the Maximum opportunity. It is much easier to alleviate the risk than it is to lock in profits.
Managed Risk:Opportunity : The ratio of the two preceding values.
Managed Opp. vs. Risk : The Managed Opportunity minus the Managed Risk. When it is negative, which is most often is, it means your strat is protecting a greater portion of the risk than it captures opportunity.
Global Numbers
Win Rate(%) : Percentage of winning trades over all entries. Open trades are considered winning if their last stop/close (as per user selection) locks in profits.
Avg X%, Avg X (currency) : Averages of previously described values:.
Avg Profitability/Trade (APPT) : This measures expectation using: Average Profitability Per Trade = (Probability of Win × Average Win) − (Probability of Loss × Average Loss) . It quantifies the average expectation/trade, which RR alone can’t do, as the probabilities of each outcome (win/lose) must also be used to calculate expectancy. The APPT combine the RR with the win rate to yield the true expectancy of a strategy. In my usual way of expressing risk with X, APPT is the equivalent of the average P&L per trade expressed in X. An APPT of -1.5 means that we lose on average 1.5X/trade.
Equity (X), Equity (currency) : The cumulative result of all trade outcomes, expressed as a multiple of X. Multiplied by the Average X in currency, this yields the Equity in currency.
Risk:Opportunity, Managed Risk:Opportunity, Managed Opp. vs. Risk : The global values of the ones previously described.
Avg Trade Length (TL) : One of the most important values derived by going through all the simulations. Again, it is composed of either the length of stopped trades, or MaxL when the trade isn’t stopped (open). This value can help systems modelers shape the characteristics of the components they use to build their strategies.
Avg Closed Win TL and Avg Closed Lose TL : The average lengths of winning/losing trades that were stopped.
Target reached? Avg bars to Stop and Target reached? Avg bars to Target : For the trades where the target was reached at some point in the simulation, the number of bars to the first point where the stop was breached and where the target was reached, respectively. These two values are used to calculate the next value.
TST (Target:Stop Travel Ratio) : This tracks the ratio between the two preceding values (Bars to first stop/Bars to first target), but only for trades where the target was reached somewhere in the loop. A ratio of 2 means targets are reached twice as fast as stops.
The next values of this section are counts or percentages and are self-explanatory.
Chart Plots
Contains chart plots of values already describes.
NOTES
Optimization/Overfitting: There is a fine line between optimizing and overfitting. Tools like this indicator can lead unsuspecting modelers down a path of overfitting that often turns strategies into over-specialized beasts that do not perform elegantly when confronted to the real-world. Proven testing strategies like walk forward analysis will go a long way in helping modelers alleviate this risk.
Input tuning: Because the results generated by the indicator will vary with the parameters used in the active entry, filtering and exit strats, it’s important to realize that although it may be fun at first, just slapping the default settings on a chart and time frame will not yield optimal nor reliable results. While using ATR as often as possible (as I do in this indicator) is a good way to make strat parametrization adaptable, it is not a foolproof solution.
There is no data for the last MaxL bars of the chart, since not enough trade future has elapsed to run a simulation from MaxL bars back.
Modifying the code: I have tried to structure the code modularly, even if that entails a larger code base, so that you can adapt it to your needs. I’ve included a few token components in each of the placeholders designed for entry strategies, filters, entry stops and in-trade stops. This will hopefully make it easier to add your own. In the same spirit, I have also commented liberally.
You will find in the code many instances of standard trade management tasks that can be lifted to code TV strategies where, as I do in mine, you manage everything yourself and don’t rely on built-in Pine strategy functions to act on your trades.
Enjoy!
THANKS
To @scarf who showed me how plotchar() could be used to plot values without ruining scale.
To @glaz for the suggestion to include a Chandelier stop strat; I will.
To @simpelyfe for the idea of using an indicator input for the filters (if some day TV lets us use more than one, it will be useful in other modules of the indicator).
To @RicardoSantos for the random generator used in the random entry strat.
To all scripters publishing open source on TradingView; their code is the best way to learn.
To my trading buddies Irving and Bruno; who showed me way back how pro traders get it done.
Hellenic EMA Matrix - PremiumHellenic EMA Matrix - Alpha Omega Premium
Complete User Guide
Table of Contents
Introduction
Indicator Philosophy
Mathematical Constants
EMA Types
Settings
Trading Signals
Visualization
Usage Strategies
FAQ
Introduction
Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market.
Key Features:
6 EMA types based on mathematical constants
Premium visualization with Neon Glow and Gradient Clouds
Automatic Fast/Mid/Slow EMA sorting
STRONG signals for powerful trends
Pulsing Ribbon Bar for instant trend assessment
Works on all timeframes (M1 - MN)
Indicator Philosophy
Why Mathematical Constants?
Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature:
Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions
Pi (3.14159) - Pi: circles, waves, cycles
e (2.71828) - Natural logarithm base: exponential growth, radioactive decay
Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles.
Mathematical Constants
Phi (Phi) - Golden Ratio
Phi = 1.618033988749895
Properties:
Phi² = Phi + 1 = 2.618
Phi³ = 4.236
Phi⁴ = 6.854
Application: Ideal for trending movements and Fibonacci corrections
Pi (Pi) - Pi Number
Pi = 3.141592653589793
Properties:
2Pi = 6.283 (full circle)
3Pi = 9.425
4Pi = 12.566
Application: Excellent for cyclical markets and wave structures
e (Euler) - Euler's Number
e = 2.718281828459045
Properties:
e² = 7.389
e³ = 20.085
e⁴ = 54.598
Application: Suitable for exponential movements and volatile markets
EMA Types
1. Phi (Phi) - Golden Ratio EMA
Description: EMA based on the golden ratio
Period Formula:
Period = Phi^n × Base Multiplier
Parameters:
Phi Power Level (1-8): Power of Phi
Phi¹ = 1.618 → ~16 period (with Base=10)
Phi² = 2.618 → ~26 period
Phi³ = 4.236 → ~42 period (recommended)
Phi⁴ = 6.854 → ~69 period
Recommendations:
Phi² or Phi³ for day trading
Phi⁴ or Phi⁵ for swing trading
Works excellently as Fast EMA
2. Pi (Pi) - Circular EMA
Description: EMA based on Pi for cyclical movements
Period Formula:
Period = Pi × Multiple × Base Multiplier
Parameters:
Pi Multiple (1-10): Pi multiplier
1Pi = 3.14 → ~31 period (with Base=10)
2Pi = 6.28 → ~63 period (recommended)
3Pi = 9.42 → ~94 period
Recommendations:
2Pi ideal as Mid or Slow EMA
Excellently identifies cycles and waves
Use on volatile markets (crypto, forex)
3. e (Euler) - Natural EMA
Description: EMA based on natural logarithm
Period Formula:
Period = e^n × Base Multiplier
Parameters:
e Power Level (1-6): Power of e
e¹ = 2.718 → ~27 period (with Base=10)
e² = 7.389 → ~74 period (recommended)
e³ = 20.085 → ~201 period
Recommendations:
e² works excellently as Slow EMA
Ideal for stocks and indices
Filters noise well on lower timeframes
4. Delta (Delta) - Adaptive EMA
Description: Adaptive EMA that changes period based on volatility
Period Formula:
Period = Base Period × (1 + (Volatility - 1) × Factor)
Parameters:
Delta Base Period (5-200): Base period (default 20)
Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0)
How it works:
During low volatility → period decreases → EMA reacts faster
During high volatility → period increases → EMA smooths noise
Recommendations:
Works excellently on news and sharp movements
Use as Fast EMA for quick adaptation
Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks
5. Sigma (Sigma) - Composite EMA
Description: Composite EMA combining multiple active EMAs
Composition Methods:
Weighted Average (default):
Sigma = (Phi + Pi + e + Delta) / 4
Simple average of all active EMAs
Geometric Mean:
Sigma = fourth_root(Phi × Pi × e × Delta)
Geometric mean (more conservative)
Harmonic Mean:
Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta)
Harmonic mean (more weight to smaller values)
Recommendations:
Enable for additional confirmation
Use as Mid EMA
Weighted Average - most universal method
6. Lambda (Lambda) - Wave EMA
Description: Wave EMA with sinusoidal period modulation
Period Formula:
Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency))
Parameters:
Lambda Base Period (10-200): Base period
Lambda Wave Amplitude (0.1-2.0): Wave amplitude
Lambda Wave Frequency (10-200): Wave frequency in bars
How it works:
Period pulsates sinusoidally
Creates wave effect following market cycles
Recommendations:
Experimental EMA for advanced users
Works well on cyclical markets
Frequency = 50 for day trading, 100+ for swing
Settings
Matrix Core Settings
Base Multiplier (1-100)
Multiplies all EMA periods
Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7)
Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74)
Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148)
Recommendations by timeframe:
M1-M5: Base = 5-10
M15-H1: Base = 10-15 (recommended)
H4-D1: Base = 15-25
W1-MN: Base = 25-50
Matrix Source
Data source selection for EMA calculation:
close - closing price (standard)
open - opening price
high - high
low - low
hl2 - (high + low) / 2
hlc3 - (high + low + close) / 3
ohlc4 - (open + high + low + close) / 4
When to change:
hlc3 or ohlc4 for smoother signals
high for aggressive longs
low for aggressive shorts
Manual EMA Selection
Critically important setting! Determines which EMAs are used for signal generation.
Use Manual Fast/Slow/Mid Selection
Enabled (default): You select EMAs manually
Disabled: Automatic selection by periods
Fast EMA
Fast EMA - reacts first to price changes
Recommendations:
Phi Golden (recommended) - universal choice
Delta Adaptive - for volatile markets
Must be fastest (smallest period)
Slow EMA
Slow EMA - determines main trend
Recommendations:
Pi Circular (recommended) - excellent trend filter
e Natural - for smoother trend
Must be slowest (largest period)
Mid EMA
Mid EMA - additional signal filter
Recommendations:
e Natural (recommended) - excellent middle level
Pi Circular - alternative
None - for more frequent signals (only 2 EMAs)
IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods:
Fast = EMA with smallest period
Mid = EMA with middle period
Slow = EMA with largest period
Therefore, you can select any combination - the indicator will arrange them correctly!
Premium Visualization
Neon Glow
Enable Neon Glow for EMAs - adds glowing effect around EMA lines
Glow Strength:
Light - subtle glow
Medium (recommended) - optimal balance
Strong - bright glow (may be too bright)
Effect: 2 glow layers around each EMA for 3D effect
Gradient Clouds
Enable Gradient Clouds - fills space between EMAs with gradient
Parameters:
Cloud Transparency (85-98): Cloud transparency
95-97 (recommended)
Higher = more transparent
Dynamic Cloud Intensity - automatically changes transparency based on EMA distance
Cloud Colors:
Phi-Pi Cloud:
Blue - when Pi above Phi (bullish)
Gold - when Phi above Pi (bearish)
Pi-e Cloud:
Green - when e above Pi (bullish)
Blue - when Pi above e (bearish)
2 layers for volumetric effect
Pulsing Ribbon Bar
Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart
Parameters:
Ribbon Position: Top / Bottom (recommended)
Pulse Speed: Slow / Medium (recommended) / Fast
Symbols and colors:
Green filled square - STRONG BULLISH
Pink filled square - STRONG BEARISH
Blue hollow square - Bullish (regular)
Red hollow square - Bearish (regular)
Purple rectangle - Neutral
Effect: Pulsation with sinusoid for living market feel
Signal Bar Highlights
Enable Signal Bar Highlights - highlights bars with signals
Parameters:
Highlight Transparency (88-96): Highlight transparency
Highlight Style:
Light Fill (recommended) - bar background fill
Thin Line - bar outline only
Highlights:
Golden Cross - green
Death Cross - pink
STRONG BUY - green
STRONG SELL - pink
Show Greek Labels
Shows Greek alphabet letters on last bar:
Phi - Phi EMA (gold)
Pi - Pi EMA (blue)
e - Euler EMA (green)
Delta - Delta EMA (purple)
Sigma - Sigma EMA (pink)
When to use: For education or presentations
Show Old Background
Old background style (not recommended):
Green background - STRONG BULLISH
Pink background - STRONG BEARISH
Blue background - Bullish
Red background - Bearish
Not recommended - use new Gradient Clouds and Pulsing Bar
Info Table
Show Info Table - table with indicator information
Parameters:
Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right
Size: Tiny / Small (recommended) / Normal / Large
Table contents:
EMA list - periods and current values of all active EMAs
Effects - active visual effects
TREND - current trend state:
STRONG UP - strong bullish
STRONG DOWN - strong bearish
Bullish - regular bullish
Bearish - regular bearish
Neutral - neutral
Momentum % - percentage deviation of price from Fast EMA
Setup - current Fast/Slow/Mid configuration
Trading Signals
Show Golden/Death Cross
Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal)
Symbols:
Yellow dot "GC" below - Golden Cross
Dark red dot "DC" above - Death Cross
Show STRONG Signals
STRONG BUY and STRONG SELL - the most powerful indicator signals
Conditions for STRONG BULLISH:
EMA Alignment: Fast > Mid > Slow (all EMAs aligned)
Trend: Fast > Slow (clear uptrend)
Distance: EMAs separated by minimum 0.15%
Price Position: Price above Fast EMA
Fast Slope: Fast EMA rising
Slow Slope: Slow EMA rising
Mid Trending: Mid EMA also rising (if enabled)
Conditions for STRONG BEARISH:
Same but in reverse
Visual display:
Green label "STRONG BUY" below bar
Pink label "STRONG SELL" above bar
Difference from Golden/Death Cross:
Golden/Death Cross = crossing moment (1 bar)
STRONG signal = sustained trend (lasts several bars)
IMPORTANT: After fixes, STRONG signals now:
Work on all timeframes (M1 to MN)
Don't break on small retracements
Work with any Fast/Mid/Slow combination
Automatically adapt thanks to EMA sorting
Show Stop Loss/Take Profit
Automatic SL/TP level calculation on STRONG signal
Parameters:
Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss
1.5 (recommended) - standard
1.0 - tight stop
2.0-3.0 - wide stop
Take Profit R:R (1.0-5.0): Risk/reward ratio
2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR)
1.5 - conservative
3.0-5.0 - aggressive
Formulas:
LONG:
Stop Loss = Entry - (ATR × Stop Loss ATR)
Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R)
SHORT:
Stop Loss = Entry + (ATR × Stop Loss ATR)
Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R)
Visualization:
Red X - Stop Loss
Green X - Take Profit
Levels remain active while STRONG signal persists
Trading Signals
Signal Types
1. Golden Cross
Description: Fast EMA crosses Slow EMA from below
Signal: Beginning of bullish trend
How to trade:
ENTRY: On bar close with Golden Cross
STOP: Below local low or below Slow EMA
TARGET: Next resistance level or 2:1 R:R
Strengths:
Simple and clear
Works well on trending markets
Clear entry point
Weaknesses:
Lags (signal after movement starts)
Many false signals in ranging markets
May be late on fast moves
Optimal timeframes: H1, H4, D1
2. Death Cross
Description: Fast EMA crosses Slow EMA from above
Signal: Beginning of bearish trend
How to trade:
ENTRY: On bar close with Death Cross
STOP: Above local high or above Slow EMA
TARGET: Next support level or 2:1 R:R
Application: Mirror of Golden Cross
3. STRONG BUY
Description: All EMAs aligned + trend + all EMAs rising
Signal: Powerful bullish trend
How to trade:
ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA
STOP: Below Fast EMA or automatic SL (if enabled)
TARGET: Automatic TP (if enabled) or by levels
TRAILING: Follow Fast EMA
Entry strategies:
Aggressive: Enter immediately on signal
Conservative: Wait for pullback to Fast EMA, then enter on bounce
Pyramiding: Add positions on pullbacks to Mid EMA
Position management:
Hold while STRONG signal active
Exit on STRONG SELL or Death Cross appearance
Move stop behind Fast EMA
Strengths:
Most reliable indicator signal
Doesn't break on pullbacks
Catches large moves
Works on all timeframes
Weaknesses:
Appears less frequently than other signals
Requires confirmation (multiple conditions)
Optimal timeframes: All (M5 - D1)
4. STRONG SELL
Description: All EMAs aligned down + downtrend + all EMAs falling
Signal: Powerful bearish trend
How to trade: Mirror of STRONG BUY
Visual Signals
Pulsing Ribbon Bar
Quick market assessment at a glance:
Symbol Color State
Filled square Green STRONG BULLISH
Filled square Pink STRONG BEARISH
Hollow square Blue Bullish
Hollow square Red Bearish
Rectangle Purple Neutral
Pulsation: Sinusoidal, creates living effect
Signal Bar Highlights
Bars with signals are highlighted:
Green highlight: STRONG BUY or Golden Cross
Pink highlight: STRONG SELL or Death Cross
Gradient Clouds
Colored space between EMAs shows trend strength:
Wide clouds - strong trend
Narrow clouds - weak trend or consolidation
Color change - trend change
Info Table
Quick reference in corner:
TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN)
Momentum %: Movement strength
Effects: Active visual effects
Setup: Fast/Slow/Mid configuration
Usage Strategies
Strategy 1: "Golden Trailing"
Idea: Follow STRONG signals using Fast EMA as trailing stop
Settings:
Fast: Phi Golden (Phi³)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
Wait for STRONG BUY
Enter on bar close or on pullback to Fast EMA
Stop below Fast EMA
Management:
Hold position while STRONG signal active
Move stop behind Fast EMA daily
Exit on STRONG SELL or Death Cross
Take Profit:
Partially close at +2R
Trail remainder until exit signal
For whom: Swing traders, trend followers
Pros:
Catches large moves
Simple rules
Emotionally comfortable
Cons:
Requires patience
Possible extended drawdowns on pullbacks
Strategy 2: "Scalping Bounces"
Idea: Scalp bounces from Fast EMA during STRONG trend
Settings:
Fast: Delta Adaptive (Base 15, Sensitivity 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base Multiplier: 5
Timeframe: M5, M15
Entry rules:
STRONG signal must be active
Wait for price pullback to Fast EMA
Enter on bounce (candle closes above/below Fast EMA)
Stop behind local extreme (15-20 pips)
Take Profit:
+1.5R or to Mid EMA
Or to next level
For whom: Active day traders
Pros:
Many signals
Clear entry point
Quick profits
Cons:
Requires constant monitoring
Not all bounces work
Requires discipline for frequent trading
Strategy 3: "Triple Filter"
Idea: Enter only when all 3 EMAs and price perfectly aligned
Settings:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi)
Base Multiplier: 15
Timeframe: H4, D1
Entry rules (LONG):
STRONG BUY active
Price above all three EMAs
Fast > Mid > Slow (all aligned)
All EMAs rising (slope up)
Gradient Clouds wide and bright
Entry:
On bar close meeting all conditions
Or on next pullback to Fast EMA
Stop:
Below Mid EMA or -1.5 ATR
Take Profit:
First target: +3R
Second target: next major level
Trailing: Mid EMA
For whom: Conservative swing traders, investors
Pros:
Very reliable signals
Minimum false entries
Large profit potential
Cons:
Rare signals (2-5 per month)
Requires patience
Strategy 4: "Adaptive Scalper"
Idea: Use only Delta Adaptive EMA for quick volatility reaction
Settings:
Fast: Delta Adaptive (Base 10, Sensitivity 3.0)
Mid: None
Slow: Delta Adaptive (Base 30, Sensitivity 2.0)
Base Multiplier: 3
Timeframe: M1, M5
Feature: Two different Delta EMAs with different settings
Entry rules:
Golden Cross between two Delta EMAs
Both Delta EMAs must be rising/falling
Enter on next bar
Stop:
10-15 pips or below Slow Delta EMA
Take Profit:
+1R to +2R
Or Death Cross
For whom: Scalpers on cryptocurrencies and forex
Pros:
Instant volatility adaptation
Many signals on volatile markets
Quick results
Cons:
Much noise on calm markets
Requires fast execution
High commissions may eat profits
Strategy 5: "Cyclical Trader"
Idea: Use Pi and Lambda for trading cyclical markets
Settings:
Fast: Pi Circular (1Pi)
Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50)
Slow: Pi Circular (3Pi)
Base Multiplier: 10
Timeframe: H1, H4
Entry rules:
STRONG signal active
Lambda Wave EMA synchronized with trend
Enter on bounce from Lambda Wave
For whom: Traders of cyclical assets (some altcoins, commodities)
Pros:
Catches cyclical movements
Lambda Wave provides additional entry points
Cons:
More complex to configure
Not for all markets
Lambda Wave may give false signals
Strategy 6: "Multi-Timeframe Confirmation"
Idea: Use multiple timeframes for confirmation
Scheme:
Higher TF (D1): Determine trend direction (STRONG signal)
Middle TF (H4): Wait for STRONG signal in same direction
Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA)
Settings for all TFs:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base Multiplier: 10
Rules:
All 3 TFs must show one trend
Entry on lower TF
Stop by lower TF
Target by higher TF
For whom: Serious traders and investors
Pros:
Maximum reliability
Large profit targets
Minimum false signals
Cons:
Rare setups
Requires analysis of multiple charts
Experience needed
Practical Tips
DOs
Use STRONG signals as primary - they're most reliable
Let signals develop - don't exit on first pullback
Use trailing stop - follow Fast EMA
Combine with levels - S/R, Fibonacci, volumes
Test on demo before real
Adjust Base Multiplier for your timeframe
Enable visual effects - they help see the picture
Use Info Table - quick situation assessment
Watch Pulsing Bar - instant state indicator
Trust auto-sorting of Fast/Mid/Slow
DON'Ts
Don't trade against STRONG signal - trend is your friend
Don't ignore Mid EMA - it adds reliability
Don't use too small Base Multiplier on higher TFs
Don't enter on Golden Cross in range - check for trend
Don't change settings during open position
Don't forget risk management - 1-2% per trade
Don't trade all signals in row - choose best ones
Don't use indicator in isolation - combine with Price Action
Don't set too tight stops - let trade breathe
Don't over-optimize - simplicity = reliability
Optimal Settings by Asset
US Stocks (SPY, AAPL, TSLA)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 10-15
Timeframe: H4, D1
Features:
Use on daily for swing
STRONG signals very reliable
Works well on trending stocks
Forex (EUR/USD, GBP/USD)
Recommendation:
Fast: Delta Adaptive (Base 15, Sens 2.0)
Mid: Phi Golden (Phi²)
Slow: Pi Circular (2Pi)
Base: 8-12
Timeframe: M15, H1, H4
Features:
Delta Adaptive works excellently on news
Many signals on M15-H1
Consider spreads
Cryptocurrencies (BTC, ETH, altcoins)
Recommendation:
Fast: Delta Adaptive (Base 10, Sens 3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M5, M15, H1
Features:
High volatility - adaptation needed
STRONG signals can last days
Be careful with scalping on M1-M5
Commodities (Gold, Oil)
Recommendation:
Fast: Pi Circular (1Pi)
Mid: Phi Golden (Phi³)
Slow: Pi Circular (3Pi)
Base: 12-18
Timeframe: H4, D1
Features:
Pi works excellently on cyclical commodities
Gold responds especially well to Phi
Oil volatile - use wide stops
Indices (S&P500, Nasdaq, DAX)
Recommendation:
Fast: Phi Golden (Phi³)
Mid: e Natural (e²)
Slow: Pi Circular (2Pi)
Base: 15-20
Timeframe: H4, D1, W1
Features:
Very trending instruments
STRONG signals last weeks
Good for position trading
Alerts
The indicator supports 6 alert types:
1. Golden Cross
Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!"
When: Fast EMA crosses Slow EMA from below
2. Death Cross
Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!"
When: Fast EMA crosses Slow EMA from above
3. STRONG BULLISH
Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!"
When: All conditions for STRONG BUY met (first bar)
4. STRONG BEARISH
Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!"
When: All conditions for STRONG SELL met (first bar)
5. Bullish Ribbon
Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend"
When: EMAs aligned bullish + price above Fast EMA (less strict condition)
6. Bearish Ribbon
Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend"
When: EMAs aligned bearish + price below Fast EMA (less strict condition)
How to Set Up Alerts:
Open indicator on chart
Click on three dots next to indicator name
Select "Create Alert"
In "Condition" field select needed alert:
Golden Cross
Death Cross
STRONG BULLISH
STRONG BEARISH
Bullish Ribbon
Bearish Ribbon
Configure notification method:
Pop-up in browser
Email
SMS (in Premium accounts)
Push notifications in mobile app
Webhook (for automation)
Select frequency:
Once Per Bar Close (recommended) - once on bar close
Once Per Bar - during bar formation
Only Once - only first time
Click "Create"
Tip: Create separate alerts for different timeframes and instruments
FAQ
1. Why don't STRONG signals appear?
Possible reasons:
Incorrect Fast/Mid/Slow order
Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods
Base Multiplier too large
Solution: Reduce Base to 5-10 on lower timeframes
Market in range
Solution: STRONG signals appear only in trends - this is normal
Too strict EMA settings
Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10
Mid EMA too close to Fast or Slow
Solution: Select Mid EMA with period between Fast and Slow
2. How often should STRONG signals appear?
Normal frequency:
M1-M5: 5-15 signals per day (very active markets)
M15-H1: 2-8 signals per day
H4: 3-10 signals per week
D1: 2-5 signals per month
W1: 2-6 signals per year
If too many signals - market very volatile or Base too small
If too few signals - market in range or Base too large
4. What are the best settings for beginners?
Universal "out of the box" settings:
Matrix Core:
Base Multiplier: 10
Source: close
Phi Golden: Enabled, Power = 3
Pi Circular: Enabled, Multiple = 2
e Natural: Enabled, Power = 2
Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0
Manual Selection:
Fast: Phi Golden
Mid: e Natural
Slow: Pi Circular
Visualization:
Gradient Clouds: ON
Neon Glow: ON (Medium)
Pulsing Bar: ON (Medium)
Signal Highlights: ON (Light Fill)
Table: ON (Top Right, Small)
Signals:
Golden/Death Cross: ON
STRONG Signals: ON
Stop Loss: OFF (while learning)
Timeframe for learning: H1 or H4
5. Can I use only one EMA?
No, minimum 2 EMAs (Fast and Slow) for signal generation.
Mid EMA is optional:
With Mid EMA = more reliable but rarer signals
Without Mid EMA = more signals but less strict filtering
Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment
6. Does the indicator work on cryptocurrencies?
Yes, works excellently! Especially good on:
Bitcoin (BTC)
Ethereum (ETH)
Major altcoins (SOL, BNB, XRP)
Recommended settings for crypto:
Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0)
Mid: Pi Circular (2Pi)
Slow: e Natural (e²)
Base: 5-10
Timeframe: M15, H1, H4
Crypto market features:
High volatility → use Delta Adaptive
24/7 trading → set alerts
Sharp movements → wide stops
7. Can I trade only with this indicator?
Technically yes, but NOT recommended.
Best approach - combine with:
Price Action - support/resistance levels, candle patterns
Volume - movement strength confirmation
Fibonacci - retracement and extension levels
RSI/MACD - divergences and overbought/oversold
Fundamental analysis - news, company reports
Hellenic Matrix:
Excellently determines trend and its strength
Provides clear entry/exit points
Doesn't consider fundamentals
Doesn't see major levels
8. Why do Gradient Clouds change color?
Color depends on EMA order:
Phi-Pi Cloud:
Blue - Pi EMA above Phi EMA (bullish alignment)
Gold - Phi EMA above Pi EMA (bearish alignment)
Pi-e Cloud:
Green - e EMA above Pi EMA (bullish alignment)
Blue - Pi EMA above e EMA (bearish alignment)
Color change = EMA order change = possible trend change
9. What is Momentum % in the table?
Momentum % = percentage deviation of price from Fast EMA
Formula:
Momentum = ((Close - Fast EMA) / Fast EMA) × 100
Interpretation:
+0.5% to +2% - normal bullish momentum
+2% to +5% - strong bullish momentum
+5% and above - overheating (correction possible)
-0.5% to -2% - normal bearish momentum
-2% to -5% - strong bearish momentum
-5% and below - oversold (bounce possible)
Usage:
Monitor momentum during STRONG signals
Large momentum = don't enter (wait for pullback)
Small momentum = good entry point
10. How to configure for scalping?
Settings for scalping (M1-M5):
Base Multiplier: 3-5
Source: close or hlc3 (smoother)
Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0)
Mid: None (for more signals)
Slow: Phi Golden (Phi²) or Pi Circular (1Pi)
Visualization:
- Gradient Clouds: ON (helps see strength)
- Neon Glow: OFF (doesn't clutter chart)
- Pulsing Bar: ON (quick assessment)
- Signal Highlights: ON
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0)
Scalping rules:
Trade only STRONG signals
Enter on bounce from Fast EMA
Tight stops (10-20 pips)
Quick take profit (+1R to +2R)
Don't hold through news
11. How to configure for long-term investing?
Settings for investing (D1-W1):
Base Multiplier: 20-30
Source: close
Fast: Phi Golden (Phi³ or Phi⁴)
Mid: e Natural (e²)
Slow: Pi Circular (3Pi or 4Pi)
Visualization:
- Gradient Clouds: ON
- Neon Glow: ON (Medium)
- Everything else - to taste
Signals:
- Golden/Death Cross: ON
- STRONG Signals: ON
- Stop Loss: OFF (use percentage stop)
Investing rules:
Enter only on STRONG signals
Hold while STRONG active (weeks/months)
Stop below Slow EMA or -10%
Take profit: by company targets or +50-100%
Ignore short-term pullbacks
12. What if indicator slows down chart?
Indicator is optimized, but if it slows:
Disable unnecessary visual effects:
Neon Glow: OFF (saves 8 plots)
Gradient Clouds: ON but low quality
Lambda Wave EMA: OFF (if not using)
Reduce number of active EMAs:
Sigma Composite: OFF
Lambda Wave: OFF
Leave only Phi, Pi, e, Delta
Simplify settings:
Pulsing Bar: OFF
Greek Labels: OFF
Info Table: smaller size
13. Can I use on different timeframes simultaneously?
Yes! Multi-timeframe analysis is very powerful:
Classic scheme:
Higher TF (D1, W1) - determine global trend
Wait for STRONG signal
This is our trading direction
Middle TF (H4, H1) - look for confirmation
STRONG signal in same direction
Precise entry zone
Lower TF (M15, M5) - entry point
Golden Cross or bounce from Fast EMA
Precise stop loss
Example:
W1: STRONG BUY active (global uptrend)
H4: STRONG BUY appeared (confirmation)
M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY
Advantages:
Maximum reliability
Clear timeframe hierarchy
Large targets
14. How does indicator work on news?
Delta Adaptive EMA adapts excellently to news:
Before news:
Low volatility → Delta EMA becomes fast → pulls to price
During news:
Sharp volatility spike → Delta EMA slows → filters noise
After news:
Volatility normalizes → Delta EMA returns to normal
Recommendations:
Don't trade at news release moment (spreads widen)
Wait for STRONG signal after news (2-5 bars)
Use Delta Adaptive as Fast EMA for quick reaction
Widen stops by 50-100% during important news
Advanced Techniques
Technique 1: "Divergences with EMA"
Idea: Look for discrepancies between price and Fast EMA
Bullish divergence:
Price makes lower low
Fast EMA makes higher low
= Possible reversal up
Bearish divergence:
Price makes higher high
Fast EMA makes lower high
= Possible reversal down
How to trade:
Find divergence
Wait for STRONG signal in divergence direction
Enter on confirmation
Technique 2: "EMA Tunnel"
Idea: Use space between Fast and Slow EMA as "tunnel"
Rules:
Wide tunnel - strong trend, hold position
Narrow tunnel - weak trend or consolidation, caution
Tunnel narrowing - trend weakening, prepare to exit
Tunnel widening - trend strengthening, can add
Visually: Gradient Clouds show this automatically!
Trading:
Enter on STRONG signal (tunnel starts widening)
Hold while tunnel wide
Exit when tunnel starts narrowing
Technique 3: "Wave Analysis with Lambda"
Idea: Lambda Wave EMA creates sinusoid matching market cycles
Setup:
Lambda Base Period: 30
Lambda Wave Amplitude: 0.5
Lambda Wave Frequency: 50 (adjusted to asset cycle)
How to find correct Frequency:
Look at historical cycles (distance between local highs)
Average distance = your Frequency
Example: if highs every 40-60 bars, set Frequency = 50
Trading:
Enter when Lambda Wave at bottom of sinusoid (growth potential)
Exit when Lambda Wave at top (fall potential)
Combine with STRONG signals
Technique 4: "Cluster Analysis"
Idea: When all EMAs gather in narrow cluster = powerful breakout soon
Cluster signs:
All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other
Gradient Clouds almost invisible
Price jumping around all EMAs
Trading:
Identify cluster (all EMAs close)
Determine breakout direction (where more volume, higher TFs direction)
Wait for breakout and STRONG signal
Enter on confirmation
Target = cluster size × 3-5
This is very powerful technique for big moves!
Technique 5: "Sigma as Dynamic Level"
Idea: Sigma Composite EMA = average of all EMAs = magnetic level
Usage:
Enable Sigma Composite (Weighted Average)
Sigma works as dynamic support/resistance
Price often returns to Sigma before trend continuation
Trading:
In trend: Enter on bounces from Sigma
In range: Fade moves from Sigma (trade return to Sigma)
On breakout: Sigma becomes support/resistance
Risk Management
Basic Rules
1. Position Size
Conservative: 1% of capital per trade
Moderate: 2% of capital per trade (recommended)
Aggressive: 3-5% (only for experienced)
Calculation formula:
Lot Size = (Capital × Risk%) / (Stop in pips × Pip value)
2. Risk/Reward Ratio
Minimum: 1:1.5
Standard: 1:2 (recommended)
Optimal: 1:3
Aggressive: 1:5+
3. Maximum Drawdown
Daily: -3% to -5%
Weekly: -7% to -10%
Monthly: -15% to -20%
Upon reaching limit → STOP trading until end of period
Position Management Strategies
1. Fixed Stop
Method:
Stop below/above Fast EMA or local extreme
DON'T move stop against position
Can move to breakeven
For whom: Beginners, conservative traders
2. Trailing by Fast EMA
Method:
Each day (or bar) move stop to Fast EMA level
Position closes when price breaks Fast EMA
Advantages:
Stay in trend as long as possible
Automatically exit on reversal
For whom: Trend followers, swing traders
3. Partial Exit
Method:
50% of position close at +2R
50% hold with trailing by Mid EMA or Slow EMA
Advantages:
Lock profit
Leave position for big move
Psychologically comfortable
For whom: Universal method (recommended)
4. Pyramiding
Method:
First entry on STRONG signal (50% of planned position)
Add 25% on pullback to Fast EMA
Add another 25% on pullback to Mid EMA
Overall stop below Slow EMA
Advantages:
Average entry price
Reduce risk
Increase profit in strong trends
Caution:
Works only in trends
In range leads to losses
For whom: Experienced traders
Trading Psychology
Correct Mindset
1. Indicator is a tool, not holy grail
Indicator shows probability, not guarantee
There will be losing trades - this is normal
Important is series statistics, not one trade
2. Trust the system
If STRONG signal appeared - enter
Don't search for "perfect" moment
Follow trading plan
3. Patience
STRONG signals don't appear every day
Better miss signal than enter against trend
Quality over quantity
4. Discipline
Always set stop loss
Don't move stop against position
Don't increase risk after losses
Beginner Mistakes
1. "I know better than indicator"
Indicator says STRONG BUY, but you think "too high, will wait for pullback"
Result: miss profitable move
Solution: Trust signals or don't use indicator
2. "Will reverse now for sure"
Trading against STRONG trend
Result: stops, stops, stops
Solution: Trend is your friend, trade with trend
3. "Will hold a bit more"
Don't exit when STRONG signal disappears
Greed eats profit
Solution: If signal gone - exit!
4. "I'll recover"
After losses double risk
Result: huge losses
Solution: Fixed % risk ALWAYS
5. "I don't like this signal"
Skip signals because of "feeling"
Result: inconsistency, no statistics
Solution: Trade ALL signals or clearly define filters
Trading Journal
What to Record
For each trade:
1. Entry/exit date and time
2. Instrument and timeframe
3. Signal type
Golden Cross
STRONG BUY
STRONG SELL
Death Cross
4. Indicator settings
Fast/Mid/Slow EMA
Base Multiplier
Other parameters
5. Chart screenshot
Entry moment
Exit moment
6. Trade parameters
Position size
Stop loss
Take Profit
R:R
7. Result
Profit/Loss in $
Profit/Loss in %
Profit/Loss in R
8. Notes
What was right
What was wrong
Emotions during trade
Lessons
Journal Analysis
Analyze weekly:
1. Win Rate
Win Rate = (Profitable trades / All trades) × 100%
Good: 50-60%
Excellent: 60-70%
Exceptional: 70%+
2. Average R
Average R = Sum of all R / Number of trades
Good: +0.5R
Excellent: +1.0R
Exceptional: +1.5R+
3. Profit Factor
Profit Factor = Total profit / Total losses
Good: 1.5+
Excellent: 2.0+
Exceptional: 3.0+
4. Maximum Drawdown
Track consecutive losses
If more than 5 in row - stop, check system
5. Best/Worst Trades
What was common in best trades? (do more)
What was common in worst trades? (avoid)
Pre-Trade Checklist
Technical Analysis
STRONG signal active (BUY or SELL)
All EMAs properly aligned (Fast > Mid > Slow or reverse)
Price on correct side of Fast EMA
Gradient Clouds confirm trend
Pulsing Bar shows STRONG state
Momentum % in normal range (not overheated)
No close strong levels against direction
Higher timeframe doesn't contradict
Risk Management
Position size calculated (1-2% risk)
Stop loss set
Take profit calculated (minimum 1:2)
R:R satisfactory
Daily/weekly risk limit not exceeded
No other open correlated positions
Fundamental Analysis
No important news in coming hours
Market session appropriate (liquidity)
No contradicting fundamentals
Understand why asset is moving
Psychology
Calm and thinking clearly
No emotions from previous trades
Ready to accept loss at stop
Following trading plan
Not revenging market for past losses
If at least one point is NO - think twice before entering!
Learning Roadmap
Week 1: Familiarization
Goals:
Install and configure indicator
Study all EMA types
Understand visualization
Tasks:
Add indicator to chart
Test all Fast/Mid/Slow settings
Play with Base Multiplier on different timeframes
Observe Gradient Clouds and Pulsing Bar
Study Info Table
Result: Comfort with indicator interface
Week 2: Signals
Goals:
Learn to recognize all signal types
Understand difference between Golden Cross and STRONG
Tasks:
Find 10 Golden Cross examples in history
Find 10 STRONG BUY examples in history
Compare their results (which worked better)
Set up alerts
Get 5 real alerts
Result: Understanding signals
Week 3: Demo Trading
Goals:
Start trading signals on demo account
Gather statistics
Tasks:
Open demo account
Trade ONLY STRONG signals
Keep journal (minimum 20 trades)
Don't change indicator settings
Strictly follow stop losses
Result: 20+ documented trades
Week 4: Analysis
Goals:
Analyze demo trading results
Optimize approach
Tasks:
Calculate win rate and average R
Find patterns in profitable trades
Find patterns in losing trades
Adjust approach (not indicator!)
Write trading plan
Result: Trading plan on 1 page
Month 2: Improvement
Goals:
Deepen understanding
Add additional techniques
Tasks:
Study multi-timeframe analysis
Test combinations with Price Action
Try advanced techniques (divergences, tunnels)
Continue demo trading (minimum 50 trades)
Achieve stable profitability on demo
Result: Win rate 55%+ and Profit Factor 1.5+
Month 3: Real Trading
Goals:
Transition to real account
Maintain discipline
Tasks:
Open small real account
Trade minimum lots
Strictly follow trading plan
DON'T increase risk
Focus on process, not profit
Result: Psychological comfort on real
Month 4+: Scaling
Goals:
Increase account
Become consistently profitable
Tasks:
With 60%+ win rate can increase risk to 2%
Upon doubling account can add capital
Continue keeping journal
Periodically review and improve strategy
Share experience with community
Result: Stable profitability month after month
Additional Resources
Recommended Reading
Technical Analysis:
"Technical Analysis of Financial Markets" - John Murphy
"Trading in the Zone" - Mark Douglas (psychology)
"Market Wizards" - Jack Schwager (trader interviews)
EMA and Moving Averages:
"Moving Averages 101" - Steve Burns
Articles on Investopedia about EMA
Risk Management:
"The Mathematics of Money Management" - Ralph Vince
"Trade Your Way to Financial Freedom" - Van K. Tharp
Trading Journals:
Edgewonk (paid, very powerful)
Tradervue (free version + premium)
Excel/Google Sheets (free)
Screeners:
TradingView Stock Screener
Finviz (stocks)
CoinMarketCap (crypto)
Conclusion
Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines:
Mathematical elegance - Phi, Pi, e instead of arbitrary numbers
Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar
Reliable signals - STRONG BUY/SELL work on all timeframes
Flexibility - 6 EMA types, adaptation to any trading style
Automation - auto-sorting EMAs, SL/TP calculation, alerts
Key Success Principles:
Simplicity - start with basic settings (Phi/Pi/e, Base=10)
Discipline - follow STRONG signals strictly
Patience - wait for quality setups
Risk Management - 1-2% per trade, ALWAYS
Journal - document every trade
Learning - constantly improve skills
Remember:
Indicator shows probability, not guarantee
Important is series statistics, not one trade
Psychology more important than technique
Quality more important than quantity
Process more important than result
Acknowledgments
Thank you for using Hellenic EMA Matrix - Alpha Omega Premium!
The indicator was created with love for mathematics, markets, and beautiful visualization.
Wishing you profitable trading!
Guide Version: 1.0
Date: 2025
Compatibility: Pine Script v6, TradingView
"In the simplicity of mathematical constants lies the complexity of market movements"
Buffett Quality Score [Consumer Discretionary]Evaluating Consumer Discretionary Companies with the Buffett Quality Score
The consumer discretionary sector, characterized by its sensitivity to economic cycles and consumer spending patterns, demands a robust framework for financial evaluation. The Buffett Quality Score offers a comprehensive assessment of financial health and performance specifically tailored to this dynamic industry. This scoring system combines critical financial ratios uniquely relevant to consumer discretionary companies, providing investors and analysts with a reliable tool for evaluation.
Selected Financial Metrics and Criteria
1. Altman Z-Score > 2.0
Relevance: The Altman Z-Score assesses bankruptcy risk, combining profitability, leverage, liquidity, solvency, and activity ratios. For consumer discretionary companies, which often face volatile market conditions, a score above 2.0 indicates financial stability and the ability to withstand economic downturns. This metric is particularly important in this sector due to the high variability in consumer spending.
2. Piotroski F-Score > 6.0
Relevance: The Piotroski F-Score evaluates fundamental strength based on profitability, leverage, liquidity, and operating efficiency. In the consumer discretionary sector, where rapid changes in consumer preferences can impact performance, a score above 6.0 highlights strong fundamental performance and resilience. This score is crucial for identifying companies with robust financial foundations in a highly competitive environment.
3. Asset Turnover > 1.0
Relevance: Asset Turnover measures the efficiency of asset use in generating sales. For consumer discretionary companies, a ratio above 1.0 signifies effective utilization of assets to drive revenue growth. Given the sector's reliance on high sales volumes and rapid inventory turnover, this metric is key to assessing operational efficiency.
4. Current Ratio > 1.5
Relevance: The Current Ratio assesses liquidity by comparing current assets to current liabilities. A ratio above 1.5 ensures that consumer discretionary companies can meet short-term obligations. This liquidity is essential for maintaining operational stability and flexibility to adapt to market changes, especially during economic fluctuations.
5. Debt to Equity Ratio < 1.0
Relevance: A lower Debt to Equity Ratio indicates prudent financial management and reduced reliance on debt. This is particularly important for consumer discretionary companies, which need to maintain financial flexibility to invest in new trends and innovations without overleveraging. Lower debt levels also reduce risk during economic downturns.
6. EBITDA Margin > 15.0%
Relevance: The EBITDA Margin measures operating profitability. A margin above 15.0% indicates efficient operations and the ability to generate sufficient earnings before interest, taxes, depreciation, and amortization. This is crucial for sustaining profitability in a competitive and fluctuating market, ensuring the company can reinvest in growth and innovation.
7. EPS One-Year Growth > 5.0%
Relevance: EPS growth reflects the company’s ability to increase earnings per share over the past year. For consumer discretionary companies, growth exceeding 5.0% signals positive earnings momentum, which is vital for investor confidence and the ability to fund future growth initiatives. This metric highlights companies that are successfully increasing profitability.
8. Gross Margin > 25.0%
Relevance: Gross Margin represents the profitability of sales after production costs. A margin exceeding 25.0% indicates strong pricing power and effective cost management, crucial for maintaining profitability while adapting to changing consumer demands. High gross margins are indicative of a company’s ability to control costs and price products competitively.
9. Net Margin > 10.0%
Relevance: Net Margin measures overall profitability after all expenses. A margin above 10.0% highlights the company’s ability to maintain strong profit levels, ensuring financial health and stability. This is essential for sustaining operations and investing in new opportunities, reflecting the company's efficiency in converting revenue into actual profit.
10.Return on Equity (ROE) > 15.0%
Relevance: ROE indicates how effectively a company uses equity to generate profits. An ROE above 15.0% signifies strong shareholder value creation. This metric is key for evaluating long-term performance in the consumer discretionary sector, where investor returns are closely tied to the company’s ability to innovate and grow. High ROE demonstrates effective management and profitable use of equity capital.
Interpreting the Buffett Quality Score
0-4 Points: Indicates potential weaknesses across multiple financial areas, warranting further investigation and risk assessment.
5 Points: Suggests average performance based on sector-specific criteria, indicating a need for cautious optimism.
6-10 Points: Signifies strong financial health and quality, meeting or exceeding most performance thresholds, making the company a potentially attractive investment.
Conclusion
The Buffett Quality Score provides a structured approach to evaluating financial health and performance. By focusing on these essential financial metrics, stakeholders can make informed decisions, identifying companies that are well-positioned to thrive in the competitive and economically sensitive consumer discretionary sector.
Disclaimer: The Buffett Quality Score serves as a tool for financial evaluation and analysis. It is not a substitute for professional financial advice or investment recommendations. Investors should conduct thorough research and seek personalized guidance based on individual circumstances.
