Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction
The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts.
Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern.
The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it.
🔵 Identifying the QM Pattern
🟣 Bullish QM
In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement.
🟣 Bearish QM
The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes.
🔵 How to Use
The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases.
🟣 Bullish Quasimodo
A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low.
This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy.
🟣 Bearish Quasimodo
A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped.
Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps.
🔵 Setting
Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5.
Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter.
Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter.
Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point.
Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980.
Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15.
🔵 Results
The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image.
⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences.
Default Properties of Backtests :
OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year :
BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year :
CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year :
NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year :
OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year :
PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
Phân tích Sóng
RastaRasta — Educational Strategy (Pine v5)
Momentum · Smoothing · Trend Study
Overview
The Rasta Strategy is a visual and educational framework designed to help traders study momentum transitions using the interaction between a fast-reacting EMA line and a slower smoothed reference line.
It is not a signal generator or profit system; it’s a learning tool for understanding how smoothing, crossovers, and filters interact under different market conditions.
The script displays:
A primary EMA line (the fast reactive wave).
A Smoothed line (using your chosen smoothing method).
Optional fog zones between them for quick visual context.
Optional DNA rungs connecting both lines to illustrate volatility compression and expansion.
Optional EMA 8 / EMA 21 trend filter to observe higher-time-frame alignment.
Core Idea
The Rasta model focuses on wave interaction. When the fast EMA crosses above the smoothed line, it reflects a shift in short-term momentum relative to background trend pressure. Cross-unders suggest weakening or reversal.
Rather than treating this as a trading “signal,” use it to observe structure, study trend alignment, and test how smoothing type affects reaction speed.
Smoothing Types Explained
The script lets you experiment with multiple smoothing techniques:
Type Description Use Case
SMA (Simple Moving Average) Arithmetic mean of the last n values. Smooth and steady, but slower. Trend-following studies; filters noise on higher time frames.
EMA (Exponential Moving Average) Weights recent data more. Responds faster to new price action. Momentum or reactive strategies; quick shifts and reversals.
RMA (Relative Moving Average) Used internally by RSI; smooths exponentially but slower than EMA. Momentum confirmation; balanced response.
WMA (Weighted Moving Average) Linear weights emphasizing the most recent data strongly. Intraday scalping; crisp but potentially noisy.
None Disables smoothing; uses the EMA line alone. Raw comparison baseline.
Each smoothing method changes how early or late the strategy reacts:
Faster smoothing (EMA/WMA) = more responsive, good for scalping.
Slower smoothing (SMA/RMA) = more stable, good for trend following.
Modes of Study
🔹 Scalper Mode
Use short EMA lengths (e.g., 3–5) and fast smoothing (EMA or WMA).
Focus on 1 min – 15 min charts.
Watch how quick crossovers appear near local tops/bottoms.
Fog and rung compression reveal volatility contraction before bursts.
Goal: study short-term rhythm and liquidity pulses.
🔹 Momentum Mode
Use moderate EMA (5–9) and RMA smoothing.
Ideal for 1 H–4 H charts.
Observe how the fog color aligns with trend shifts.
EMA 8 / 21 filter can act as macro bias; “Enter” labels will appear only in its direction when enabled.
Goal: study sustained motion between pullbacks and acceleration waves.
🔹 Trend-Follower Mode
Use longer EMA (13–21) with SMA smoothing.
Great for daily/weekly charts.
Focus on periods where fog stays unbroken for long stretches — these illustrate clear trend dominance.
Watch rung spacing: tight clusters often precede consolidations; wide rungs signal expanding volatility.
Goal: visualize slow-motion trend transitions and filter whipsaw conditions.
Components
EMA Line (Red): Fast-reacting short-term direction.
Smoothed Line (Yellow): Reference trend baseline.
Fog Zone: Green when EMA > Smoothed (up-momentum), red when below.
DNA Rungs: Thin connectors showing volatility structure.
EMA 8 / 21 Filter (optional):
When enabled, the strategy will only allow Enter events if EMA 8 > EMA 21.
Use this to study higher-trend gating effects.
Educational Applications
Momentum Visualization: Observe how the fast EMA “breathes” around the smoothed baseline.
Trend Transitions: Compare different smoothing types to see how early or late reversals are detected.
Noise Filtering: Experiment with fog opacity and smoothing lengths to understand trade-off between responsiveness and stability.
Risk Concept Simulation: Includes a simple fixed stop-loss parameter (default 13%) for educational demonstrations of position management in the Strategy Tester.
How to Use
Add to Chart → “Strategy.”
Works on any timeframe and instrument.
Adjust Parameters:
Length: base EMA speed.
Smoothing Type: choose SMA, EMA, RMA, or WMA.
Smoothing Length: controls delay and smoothness.
EMA 8 / 21 Filter: toggles trend gating.
Fog & Rungs: visual study options only.
Study Behavior:
Use Strategy Tester → List of Trades for entry/exit context.
Observe how different smoothing types affect early vs. late “Enter” points.
Compare trend periods vs. ranging periods to evaluate efficiency.
Combine with External Tools:
Overlay RSI, MACD, or Volume for deeper correlation analysis.
Use replay mode to visualize crossovers in live sequence.
Interpreting the Labels
Enter: Marks where fast EMA crosses above the smoothed line (or when filter flips positive).
Exit: Marks where fast EMA crosses back below.
These are purely analytical markers — they do not represent trade advice.
Educational Value
The Rasta framework helps learners explore:
Reaction time differences between moving-average algorithms.
Impact of smoothing on signal clarity.
Interaction of local and global trends.
Visualization of volatility contraction (tight DNA rungs) and expansion (wide fog zones).
It’s a sandbox for studying price structure, not a promise of profit.
Disclaimer
This script is provided for educational and research purposes only.
It does not constitute financial advice, trading signals, or performance guarantees. Past market behavior does not predict future outcomes.
Users are encouraged to experiment responsibly, record observations, and develop their own understanding of price behavior.
Author: Michael Culpepper (mikeyc747)
License: Educational / Open for study and modification with credit.
Philosophy:
“Learning the rhythm of the market is more valuable than chasing its profits.” — Rasta
Sigma Trinity ModelAbstract
Sigma Trinity Model is an educational framework that studies how three layers of market behavior interact within the same trend: (1) structural momentum (Rasta), (2) internal strength (RSI), and (3) continuation/compounding structure (Pyramid). The model deliberately combines bar-close momentum logic with intrabar, wick-aware strength checks to help users see how reversals form, confirm, and extend. It is not a signal service or automation tool; it is a transparent learning instrument for chart study and backtesting.
Why this is not “just a mashup”
Many scripts merge indicators without explaining the purpose. Sigma Trinity is a coordinated, three-engine study designed for a specific learning goal:
Rasta (structure): defines when momentum actually flips using a dual-line EMA vs smoothed EMA. It gives the entry/exit framework on bar close for clean historical study.
RSI (energy): measures internal strength with wick-aware triggers. It uses RSI of LOW (for bottom touches/reclaims) and RSI of HIGH (for top touches/exhaustion) so users can see intrabar strength/weakness that the close can hide.
Pyramid (progression): demonstrates how continuation behaves once momentum and strength align. It shows the logic of adds (compounding) as a didactic layer, also on bar close to keep historical alignment consistent.
These three roles are complementary, not redundant: structure → strength → progression.
Architecture Overview
Execution model
Rasta & Pyramid: bar close only by default (historically stable, easy to audit).
RSI: per tick (realtime) with bar-close backup by default, using RSI of LOW for entries and RSI of HIGH for exits. This makes the module sensitive to intra-bar wicks while still giving a close-based safety net for backtests.
Stops (optional in strategy builds): wick-accurate: trail arms/ratchets on HIGH; stop hit checks with LOW (or Close if selected) with a small undershoot buffer to avoid micro-noise hits.
Visual model
Dual lines (EMA vs smoothed EMA) for Rasta + color fog to see direction and compression/expansion.
Rungs (small vertical lines) drawn between the two Rasta lines to visualize wave spacing and rhythm.
Clean labels for Entry/Exit/Pyramid Add/RSI events. Everything is state-locked to avoid spamming.
Module 1 — Rasta (Structural Momentum Layer)
Goal: Identify structural momentum reversals and maintain a consistent, replayable backbone for study.
Method:
Compute an EMA of a chosen price source (default Close), and a smoothed version (SMA/EMA/RMA/WMA/None selectable).
Flip points occur when the EMA line crosses the smoothed line.
Optional EMA 8/21 trend filter can gate entries (long-bias when EMA8 > EMA21). A small “adaptive on flip” option lets an entry fire when the filter itself flips to ON and the EMA is already above the smoothed line—useful for trend resumption.
Why bar close only?
Bar-close Rasta gives a stable, auditable timeline for the structure of the trend. It teaches users to separate “structure” (close-resolved) from “energy” (intrabar, via RSI).
Visuals:
Fog between the lines (green/red) to show regime.
Rungs between lines to show spread (compression vs expansion).
Optional plotting of EMA8/EMA21 so users can see the gating effect.
Module 2 — RSI (Internal Strength / Energy Layer)
Goal: Reveal the intrabar strength/weakness that often precedes or confirms structural flips.
Method:
Standard RSI with adjustable length and signal smoothing for the panel view.
Logic uses wick-aware sources:
Entry trigger: RSI of LOW (same RSI length) touching or below a lower band (default 15). Think of it as intraband reactivation from the bottom, using the candle’s deepest excursion.
Exit trigger: RSI of HIGH touching or above an upper band (default 85). Think of it as exhaustion at the top, using the candle’s highest excursion.
Realtime + Close Backup: fires intrabar on tick, but if the realtime event was missed, the close backup will note it at bar end.
Cooldown control: optional bars-between-signals to avoid rapid re-triggers on choppy sequences.
Why wick-aware RSI?
A close-only RSI can miss the true micro-extremes that cause reversals. Using LOW/HIGH for triggers captures the behavior that traders actually react to during the bar, while the bar-close backup preserves historical reproducibility.
Module 3 — Pyramid (Continuation / Compounding Layer)
Goal: Teach how continuation behaves once a trend is underway, and how adds can be structured.
Method:
Same dual-line logic as Rasta (EMA vs smoothed EMA), but only fires when already in a position (or after prior entry conditions).
Supports the same EMA 8/21 filter and optional adaptive-on-flip behavior.
Bar close only to maintain historical cohesion.
What it teaches:
Adds tend to cluster when momentum persists.
Students can experiment with add spacing and compare “one-shot entries” vs “laddered adds” during strong regimes.
How the Pieces Work Together
Rasta establishes the structural frame (when the wave flip is real enough to record at close).
RSI validates or challenges that structure by tracking intrabar energy at the extremes (low/high touches).
Pyramid shows what sustained continuation looks like once (1) and (2) align.
This produces a layered view: Structure → Energy → Progression. Users can see when all three line up (strongest phases) and when they diverge (riskier phases or transitions).
How to Use It (Step-by-Step)
Quick Start
Apply script to any symbol/timeframe.
In Strategy/Indicator Properties:
Enable On every tick (recommended).
If available, enable Using bar magnifier and choose a lower resolution (e.g., 1m) to simulate intrabar fills more realistically.
Keep On bar close unchecked if you want to observe realtime logic in live charts (strategies still place orders on close by platform design).
Default behavior: Rasta & Pyramid = bar close; RSI = per tick with close backup.
Reading the Chart
Watch for Rasta Entry/Exit labels: they define clean structural turns on close.
Watch RSI Entry (LOW touch at/below lower band) and RSI Exit (HIGH touch at/above upper band) to gauge internal energy extremes.
Pyramid Add labels reveal continuation phases once a move is already in progress.
Tuning
Rasta smoothing: choose SMA/EMA/RMA/WMA or None. Higher smoothing → later but cleaner flips; lower smoothing → earlier but choppier.
RSI bands: a common educational setting is 15/85 for strong extremes; 20/80 is a bit looser.
Cooldown: increase if you see too many RSI re-fires in chop.
EMA 8/21 filter: toggle ON to study “trend-gated” entries, OFF to study raw momentum flips.
Backtesting Notes (for Strategy Builds)
Stops (optional): trail is armed when price advances by a trigger (default D–F₀), ratchets only upward from HIGH, and hits from LOW (or Close if chosen) with a tiny undershoot buffer to avoid micro-wicks.
Order sequencing per bar (mirrors the script’s code comments):
Trail ratchet via HIGH
Intrabar stop hit via LOW/CLOSE → immediate close
If still in position at bar close: process exits (Rasta/RSI)
If still in position at bar close: process Pyramid Add
If flat at bar close: process entries (Rasta/RSI)
Platform reality: strategies place orders at bar close in historical testing; the intrabar logic improves realism for stops and event marking but final order timestamps are still close-resolved.
Inputs Reference (common)
Modules: enable/disable RSI and Pyramid learning layers.
Rasta: EMA length, smoothing type/length, EMA8/21 filter & adaptive flip, fog opacity, rungs on/off & limit.
RSI: RSI length, signal MA length (panel), Entry band (LOW), Exit band (HIGH), cooldown bars, labels.
Pyramid: EMA length, smoothing, EMA8/21 filter & adaptive adds.
Execution: toggle Bar Close Only for Rasta/Pyramid; toggle Realtime + Close Backup for RSI.
Stops (strategy): Fixed Stop % (first), Fixed Stop % (add), Trail Distance %, Trigger rule (auto D–F₀ or custom), undershoot buffer %, and hit source (LOW/CLOSE).
What to Study With It
Convergence: how often RSI-LOW entry touches precede the next Rasta flip.
Divergence: cases where RSI screams exhaustion (HIGH >= upper band) but Rasta hasn’t flipped yet—often transition zones.
Continuation: how Pyramid adds cluster in strong moves; how spacing changes with smoothing/filter choices.
Regime changes: use EMA8/21 filter toggles to see what happens at macro turns vs chop.
Limitations & Scope
This is a learning tool, not a trade copier. It does not provide financial advice or automated execution.
Intrabar results depend on data granularity; bar magnifier (when available) can help simulate lower-resolution ticks, but true tick-by-tick fills are a platform-level feature and not guaranteed across all symbols.
Suggested Publication Settings (Strategy)
Initial capital: 100
Order size: 100 USD (cash)
Pyramiding: 10
Commission: 0.25%
Slippage: 3 ticks
Recalculate: ✓ On every tick
Fill orders: ✓ Using bar magnifier (choose 1m or similar); leave On bar close unchecked for live viewing.
Educational License
Released under the Michael Culpepper Gratitude License (2025).
Use and modify freely for education and research with attribution. No resale. No promises of profitability. Purpose is understanding, not signals.
BUY LOW, BUY MORE, SELL HIGH -BUFFET STRATEGY LITE__________________________________________________________________________
Buy Low, Buy More, Sell High With Buffett Meter (LITE – JTMarketAI)
__________________________________________________________________________
Category: Quantitative Momentum & Liquidity Flow
Author: JTMarketAI
Architecture: Non-Repainting
This strategy accumulates into validated pullbacks during fear cycles, scales intelligently as price declines into liquidity support, and exits when momentum weakens after meaningful run-ups. It uses synthetic higher-timeframe OHLC data (non-repainting), liquidity imbalance confirmation, adaptive KAMA trend logic, RSI validation, and a live Buffett macro valuation gauge.
This is a patient, conviction-based accumulation engine designed for equities.
It is not a scalp bot.
__________________________________________________________________________
Core Features
__________________________________________________________________________
Non-repainting (confirmed bars only)
Synthetic HTF OHLC (no lookahead)
Dynamic trailing exit preserves ~80–87% of peak profit
Bull vs Bear liquidity dominance and flow imbalance
Rolling lowest-low tracking (LLL)
NY-session alignment (default)
Buffett Macro Meter integration
Technical Highlights
Flow-confidence derived from volume-order pressure
Adaptive KAMA smoothing for lower-lag confirmation
Daily > Weekly > Monthly synthetic aggregation
LLL progression display for trend exhaustion
Fully profiler-optimized
Supports averaging down when pyramiding enabled
__________________________________________________________________________
Why It Does Not Repaint
__________________________________________________________________________
All state updates occur only on confirmed bars
Synthetic HTFs built without lookahead
Persistent arrays freeze historical values
Trailing highs updated only after confirmation
No forward-reference to future bars
__________________________________________________________________________
Lite Edition Notes
__________________________________________________________________________
Manual trading focused
Buffett Meter enabled
Up to 20 trades per session
Visual dashboard included
No alerts, automation, or webhooks (PRO unlocks IBKR + TradersPost)
__________________________________________________________________________
Limitations
__________________________________________________________________________
Best on intraday equities (1m–4h)
Designed for US stocks only
High-resource if full visuals enabled
Avoid penny stocks and extremely low-volume tickers
Does not guard against after-hours gaps or major news moves
__________________________________________________________________________
Warnings
__________________________________________________________________________
Contrarian scaling requires discipline and patience
Expect longer-duration trades, not rapid scalps
Use on quality tickers unlikely to permanently collapse
Confirm price behavior outside cash session
Test manually before automating anything
Not suitable for every market environment or asset
Notes on Philosophy
This strategy attempts to accumulate when markets overshoot lower, and distribute after recovery momentum fades. It reflects a patient, value-driven approach built on the principle of buying fear and reducing exposure into strength.
__________________________________________________________________________
Disclaimer
__________________________________________________________________________
For research and educational use only. Not financial advice. Past performance does not guarantee future results. Test thoroughly and use appropriate risk management.
__________________________________________________________________________
Hashtags
__________________________________________________________________________
#buffett #quantstrategy #valuemomentum #accumulation #contrarian #nonrepaint #equitystrategy #swingtrading #liquidityanalysis #synthetichtf #tradingviewstrategy
BUY LOW, BUY MORE, SELL HIGH - MARKET FLOW STRATEGY LITE
TV Description - Buffett Meter Lite
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Buy Low, Buy More, Sell High With Buffett Meter (Lite v1283 – JTM)
Category: Quantitative Momentum & Liquidity Flow
Author: JTM
Architecture: Non-Repainting
This strategy accumulates into validated pullbacks during fear cycles, scales intelligently as price declines into liquidity support, and exits when momentum weakens after meaningful run-ups. It uses synthetic higher-timeframe OHLC data (non-repainting), liquidity imbalance confirmation, adaptive KAMA trend logic, RSI validation, and a live Buffett macro valuation gauge.
This is a patient, conviction-based accumulation engine designed for equities.
It is not a scalp bot.
Core Features
Non-repainting (confirmed bars only)
Synthetic HTF OHLC (no lookahead)
Dynamic trailing exit preserves ~80–87% of peak profit
Bull vs Bear liquidity dominance and flow imbalance
Rolling lowest-low tracking (LLL)
NY-session alignment (default)
Buffett Macro Meter integration
Technical Highlights
Flow-confidence derived from volume-order pressure
Adaptive KAMA smoothing for lower-lag confirmation
Daily > Weekly > Monthly synthetic aggregation
LLL progression display for trend exhaustion
Fully profiler-optimized
Supports averaging down when pyramiding enabled
Why It Does Not Repaint
All state updates occur only on confirmed bars
Synthetic HTFs built without lookahead
Persistent arrays freeze historical values
Trailing highs updated only after confirmation
No forward-reference to future bars
Lite Edition Notes
Manual trading focused
Buffett Meter enabled
Limit of 20 trades per session
Buffet Meter dashboard included
No alerts, automation, or webhooks (PRO unlocks IBKR + TradersPost)
Limitations
Best on intraday equities (1m–4h)
Designed for US stocks only
High-resource if full visuals enabled
Avoid penny stocks and extremely low-volume tickers
Does not guard against after-hours gaps or major news moves
Warnings
Contrarian scaling requires discipline and patience
Expect longer-duration trades, not rapid scalps
Use on quality tickers unlikely to permanently collapse
Confirm price behavior outside cash session
Test manually before automating anything
Not suitable for every market environment or asset
Notes on Philosophy
This strategy attempts to accumulate when markets overshoot lower, and distribute after recovery momentum fades. It reflects a patient, value-driven approach built on the principle of buying fear and reducing exposure into strength.
This is edge-based, not “trade every wiggle” logic
“Be fearful when others are greedy, and greedy when others are fearful.” — Buffett
“The stock market transfers money from the impatient to the patient.” — Buffett
Disclaimer
For research and educational use only. Not financial advice. Past performance does not guarantee future results. Test thoroughly and use appropriate risk management.
Hashtags
#buffett #quantstrategy #valuemomentum #accumulation #contrarian #nonrepaint #equitystrategy #swingtrading #liquidityanalysis #synthetichtf #tradingviewstrategy
STRATEGY Fibonacci Levels with High/Low Criteria - AYNET
Here is an explanation of the Fibonacci Levels Strategy with High/Low Criteria script:
Overview
This strategy combines Fibonacci retracement levels with high/low criteria to generate buy and sell signals based on price crossing specific thresholds. It utilizes higher timeframe (HTF) candlesticks and user-defined lookback periods for high/low levels.
Key Features
Higher Timeframe Integration:
The script calculates the open, high, low, and close values of the higher timeframe (HTF) candlestick.
Users can choose to calculate levels based on the current or the last HTF candle.
Fibonacci Levels:
Fibonacci retracement levels are dynamically calculated based on the HTF candlestick's range (high - low).
Users can customize the levels (0.000, 0.236, 0.382, 0.500, 0.618, 0.786, 1.000).
High/Low Lookback Criteria:
The script evaluates the highest high and lowest low over user-defined lookback periods.
These levels are plotted on the chart for visual reference.
Trade Signals:
Long Signal: Triggered when the close price crosses above both:
The lowest price criteria (lookback period).
The Fibonacci level 3 (default: 0.5).
Short Signal: Triggered when the close price crosses below both:
The highest price criteria (lookback period).
The Fibonacci level 3 (default: 0.5).
Visualization:
Plots Fibonacci levels and high/low criteria on the chart for easy interpretation.
Inputs
Higher Timeframe:
Users can select the timeframe (default: Daily) for the HTF candlestick.
Option to calculate based on the current or last HTF candle.
Lookback Periods:
lowestLookback: Number of bars for the lowest low calculation (default: 20).
highestLookback: Number of bars for the highest high calculation (default: 10).
Fibonacci Levels:
Fully customizable Fibonacci levels ranging from 0.000 to 1.000.
Visualization
Fibonacci Levels:
Plots six customizable Fibonacci levels with distinct colors and transparency.
High/Low Criteria:
Plots the highest and lowest levels based on the lookback periods as reference lines.
Trading Logic
Long Condition:
Price must close above:
The lowest price criteria (lowcriteria).
The Fibonacci level 3 (50% retracement).
Short Condition:
Price must close below:
The highest price criteria (highcriteria).
The Fibonacci level 3 (50% retracement).
Use Case
Trend Reversal Strategy:
Combines Fibonacci retracement with recent high/low criteria to identify potential reversal or breakout points.
Custom Timeframe Analysis:
Incorporates higher timeframe data for multi-timeframe trading strategies.
Custom Buy BID StrategyThis Pine Script strategy is designed to identify and capitalize on upward trends in the market using the Average True Range (ATR) as a core component of the analysis. The script provides the following features:
Customizable ATR Calculation: Users can switch between different methods of ATR calculation (traditional or simple moving average).
Adjustable Parameters: The strategy allows for adjustable ATR periods, ATR multipliers, and custom time windows for executing trades.
Buy Signal Alerts: The strategy generates buy signals when the market shifts from a downtrend to an uptrend, based on ATR and price action.
Profit and Stop-Loss Management: Built-in take profit and stop-loss conditions are calculated as a percentage of the entry price, allowing for automatic position management.
Visual Enhancements: The script highlights the uptrend with green lines and optionally colors bars to help visualize market direction.
Flexible Timeframe: Users can configure a specific date range to activate the strategy, offering more control over when trades are executed.
This strategy is ideal for traders looking to automate their buy entries and manage risk with a straightforward trend-following approach. By utilizing customizable settings, it adapts to various market conditions and timeframes.
DCA, Support and Resistance with RSI and Trend FilterThis script is based on
script from Kieranj with added pyramiding and DCA
The buy condition (buyCondition) is triggered when the RSI crosses above the oversold threshold (ta.crossover(rsi, oversoldThreshold)), the trend filter confirms an uptrend (isUptrend is true), and the close price is greater than or equal to the support level (close >= supportLevel).
The partial sell condition (sellCondition) is triggered when the RSI crosses below the overbought threshold (ta.crossunder(rsi, overboughtThreshold)) and profit goal is reached, the trend filter confirms a downtrend (isUptrend is false), and the close price is less than or equal to the resistance level (close <= resistanceLevel).
Full sell will be triggered if trend is broken and profit goal is reached
With this implementation, the signals will only be generated in the direction of the trend on the 4-hour timeframe. The trend is considered up when the 50-period SMA is below the 200-period SMA (ta.sma(trendFilterSource, 50) < ta.sma(trendFilterSource, 200)).
Pyramiding should be activated, values like 100, so every DCA step should be around 1%
i have best results on 5 min charts
Fibonacci-Only StrategyFibonacci-Only Strategy
This script is a custom trading strategy designed for traders who leverage Fibonacci retracement levels to identify potential trade entries and exits. The strategy is versatile, allowing users to trade across multiple timeframes, with built-in options for dynamic stop loss, trailing stops, and take profit levels.
Key Features:
Custom Fibonacci Levels:
This strategy calculates three specific Fibonacci retracement levels: 19%, 82.56%, and the reverse 19% level. These levels are used to identify potential areas of support and resistance where price reversals or breaks might occur.
The Fibonacci levels are calculated based on the highest and lowest prices within a 100-bar period, making them dynamic and responsive to recent market conditions.
Dynamic Entry Conditions:
Touch Entry: The script enters long or short positions when the price touches specific Fibonacci levels and confirms the move with a bullish (for long) or bearish (for short) candle.
Break Entry (Optional): If the "Use Break Strategy" option is enabled, the script can also enter positions when the price breaks through Fibonacci levels, providing more aggressive entry opportunities.
Stop Loss Management:
The script offers flexible stop loss settings. Users can choose between a fixed percentage stop loss or an ATR-based stop loss, which adjusts based on market volatility.
The ATR (Average True Range) stop loss is multiplied by a user-defined factor, allowing for tailored risk management based on market conditions.
Trailing Stop Mechanism:
The script includes an optional trailing stop feature, which adjusts the stop loss level as the market moves in favor of the trade. This helps lock in profits while allowing the trade to run if the trend continues.
The trailing stop is calculated as a percentage of the difference between the entry price and the current market price.
Multiple Take Profit Levels:
The strategy calculates seven take profit levels, each at incremental percentages above (for long trades) or below (for short trades) the entry price. This allows for gradual profit-taking as the market moves in the trade's favor.
Each take profit level can be customized in terms of the percentage of the position to be closed, providing precise control over exit strategies.
Strategy Backtesting and Results:
Realistic Backtesting:
The script has been backtested with realistic account sizes, commission rates, and slippage settings to ensure that the results are applicable to actual trading scenarios.
The backtesting covers various timeframes and markets to ensure the strategy's robustness across different trading environments.
Default Settings:
The script is published with default settings that have been optimized for general use. These settings include a 15-minute timeframe, a 1.0% stop loss, a 2.0 ATR multiplier for stop loss, and a 1.5% trailing stop.
Users can adjust these settings to better fit their specific trading style or the market they are trading.
How It Works:
Long Entry Conditions:
The strategy enters a long position when the price touches the 19% Fibonacci level (from high to low) or the reverse 19% level (from low to high) and confirms the move with a bullish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a long position when the price breaks below the 19% Fibonacci level and then moves back up, confirming the break with a bullish candle.
Short Entry Conditions:
The strategy enters a short position when the price touches the 82.56% Fibonacci level and confirms the move with a bearish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a short position when the price breaks above the 82.56% Fibonacci level and then moves back down, confirming the break with a bearish candle.
Stop Loss and Take Profit Logic:
The stop loss for each trade is calculated based on the selected method (fixed percentage or ATR-based). The strategy then manages the trade by either trailing the stop or taking profit at predefined levels.
The take profit levels are set at increments of 0.5% above or below the entry price, depending on whether the position is long or short. The script gradually exits the trade as these levels are hit, securing profits while minimizing risk.
Usage:
For Fibonacci Traders:
This script is ideal for traders who rely on Fibonacci retracement levels to find potential trade entries and exits. The script automates the process, allowing traders to focus on market analysis and decision-making.
For Trend and Swing Traders:
The strategy's flexibility in handling both touch and break entries makes it suitable for trend-following and swing trading strategies. The multiple take profit levels allow traders to capture profits in trending markets while managing risk.
Important Notes:
Originality: This script uniquely combines Fibonacci retracement levels with dynamic stop loss management and multiple take profit levels. It is not just a combination of existing indicators but a thoughtful integration designed to enhance trading performance.
Disclaimer: Trading involves risk, and it is crucial to test this script in a demo account or through backtesting before applying it to live trading. Users should ensure that the settings align with their individual risk tolerance and trading strategy.
Hurst Future Lines of Demarcation StrategyJ. M. Hurst introduced a concept in technical analysis known as the Future Line of Demarcation (FLD), which serves as a forward-looking tool by incorporating a simple yet profound line into future projections on a financial chart. Specifically, the FLD is constructed by offsetting the price half a cycle ahead into the future on the time axis, relative to the Hurst Cycle of interest. For instance, in the context of a 40 Day Cycle, the FLD would be represented by shifting the current price data 20 days forward on the chart, offering an idea of future price movement anticipations.
The utility of FLDs extends into three critical areas of insight, which form the backbone of the FLD Trading Strategy:
A price crossing the FLD signifies the confirmation of either a peak or trough formation, indicating pivotal moments in price action.
Such crossings also help determine precise price targets for the upcoming peak or trough, aligned with the cycle of examination.
Additionally, the occurrence of a peak in the FLD itself signals a probable zone where the price might experience a trough, helping to anticipate of future price movements.
These insights by Hurst in his "Cycles Trading Course" during the 1970s, are instrumental for traders aiming to determine entry and exit points, and to forecast potential price movements within the market.
To use the FLD Trading Strategy, for example when focusing on the 40 Day Cycle, a trader should primarily concentrate on the interplay between three Hurst Cycles:
The 20 Day FLD (Signal) - Half the length of the Trade Cycle
The 40 Day FLD (Trade) - The Cycle you want to trade
The 80 Day FLD (Trend) - Twice the length of the Trade Cycle
Traders can gauge trend or consolidation by watching for two critical patterns:
Cascading patterns, characterized by several FLDs running parallel with a consistent separation, typically emerge during pronounced market trends, indicating strong directional momentum.
Consolidation patterns, on the other hand, occur when multiple FLDs intersect and navigate within the same price bandwidth, often reversing direction to traverse this range multiple times. This tangled scenario results in the formation of Pause Zones, areas where price momentum is likely to temporarily stall or where the emergence of a significant trend might be delayed.
This simple FLD indicator provides 3 FLDs with optional source input and smoothing, A-through-H FLD interaction background, adjustable “Close the Trade” triggers, and a simple strategy for backtesting it all.
The A-through-H FLD interactions are a framework designed to classify the different types of price movements as they intersect with or diverge from the Future Line of Demarcation (FLD). Each interaction (designated A through H by color) represents a specific phase or characteristic within the cycle, and understanding these can help traders anticipate future price movements and make informed decisions.
The adjustable “Close the Trade” triggers are for setting the crossover/under that determines the trade exits. The options include: Price, Signal FLD, Trade FLD, or Trend FLD. For example, a trader may want to exit trades only when price finally crosses the Trade FLD line.
Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help:
🏆 @TerryPascoe
🏅 @Hpotter
👏 @parisboy
Elliott's Quadratic Momentum - Strategy [presentTrading]█ Introduction and How It Is Different
The "Elliott's Quadratic Momentum - Strategy" is a unique and innovative approach in the realm of technical trading. This strategy is a fusion of multiple SuperTrend indicators combined with an Elliott Wave-like pattern analysis, offering a comprehensive and dynamic trading tool. It stands apart from conventional strategies by incorporating multiple layers of trend analysis, thereby providing a more robust and nuanced view of market movements.
*Although the script doesn't explicitly analyze Elliott Wave patterns, it employs a wave-like approach by considering multiple SuperTrend indicators. Elliott Wave theory is based on the premise that markets move in predictable wave patterns. While this script doesn't identify specific Elliott Wave structures like impulsive and corrective waves, the sequential checking of trend conditions across multiple SuperTrend indicators mimics a wave-like progression.
BTC 8hr Long/Short Performance
Local Detail
█ Strategy, How It Works: Detailed Explanation
The core of this strategy lies in its multi-tiered approach:
1. Multiple SuperTrend Indicators:
The strategy employs four different SuperTrend indicators, each with unique ATR lengths and multipliers. These indicators offer various perspectives on market trends, ranging from short to long-term views.
By analyzing the convergence of these indicators, the strategy can pinpoint robust entry signals for both long and short positions.
2. Elliott Wave-like Pattern Recognition:
While not directly applying Elliott Wave theory, the strategy takes inspiration from its pattern recognition approach. It looks for alignments in market movements that resemble the characteristic waves of Elliott's theory.
This pattern recognition aids in confirming the signals provided by the SuperTrend indicators, adding an extra layer of validation to the trading signals.
3. Comprehensive Market Analysis:
By combining multiple indicators and pattern analysis, the strategy offers a holistic view of the market. This allows for capturing potential trend reversals and significant market moves early.
█ Trade Direction
The strategy is designed with flexibility in mind, allowing traders to select their preferred trading direction – Long, Short, or Both. This adaptability is key for traders looking to tailor their approach to different market conditions or personal trading styles. The strategy automatically adjusts its logic based on the chosen direction, ensuring that traders are always aligned with their strategic objectives.
█ Usage
To utilize the "Elliott's Quadratic Momentum - Strategy" effectively:
Traders should first determine their trading direction and adjust the SuperTrend settings according to their market analysis and risk appetite.
The strategy is versatile and can be applied across various time frames and asset classes, making it suitable for a wide range of trading scenarios.
It's particularly effective in trending markets, where the alignment of multiple SuperTrend indicators can provide strong trade signals.
█ Default Settings
Trading Direction: Configurable (Long, Short, Both)
SuperTrend Settings:
SuperTrend 1: ATR Length 7, Multiplier 4.0
SuperTrend 2: ATR Length 14, Multiplier 3.618
SuperTrend 3: ATR Length 21, Multiplier 3.5
SuperTrend 4: ATR Length 28, Multiplier 3.382
Additional Settings: Gradient effect for trend visualization, customizable color schemes for upward and downward trends.
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
SuperTrend Multi Time Frame Long and Short Trading Strategy
Hello All
This is non-repainting Supertrend Multi Time Frame script, I got so many request on Supertrend with Multi Time Frame. This is for all of them ..I am making it open for all so you can change its coding according to your need.
How the Basic Indicator works
SuperTrend is one of the most common ATR based trailing stop indicators.
In this version you can change the ATR calculation method from the settings. Default method is RMA.
The indicator is easy to use and gives an accurate reading about an ongoing trend. It is constructed with two parameters, namely period and multiplier. The default values used while constructing a Supertrend indicator are 10 for average true range or trading period and three for its multiplier.
The average true range (ATR) plays an important role in 'Supertrend' as the indicator uses ATR to calculate its value. The ATR indicator signals the degree of price volatility .
The buy and sell signals are generated when the indicator starts plotting either on top of the closing price or below the closing price. A buy signal is generated when the ‘Supertrend’ closes above the price and a sell signal is generated when it closes below the closing price.
It also suggests that the trend is shifting from descending mode to ascending mode. Contrary to this, when a ‘Supertrend’ closes above the price, it generates a sell signal as the colour of the indicator changes into red.
A ‘Supertrend’ indicator can be used on spot, futures, options or forex, or even crypto markets and also on daily, weekly and hourly charts as well, but generally, it fails in a sideways-moving market.
How the Strategy works
This is developed based on SuperTrend.
Use two time frame for confirm all entry signals.
Two time frame SuperTrend works as Trailing stop for both long and short positions.
More securely execute orders, because it is wait until confine two time frames(example : daily and 30min)
Each time frame developed as customisable for user to any timeframe.
User can choose trading position side from Long, Short, and Both.
Custom Stop Loss level, user can enter Stop Loss percentage based on timeframe using.
Multiple Take Profit levels with customisable TP price percentage and position size.
Back-testing with custom time frame.
This strategy is develop for specially for automation purpose.
The strategy includes:
Entry for Long and Short.
Take Profit.
Stop Loss.
Trailing Stop Loss.
Position Size.
Exit Signal.
Risk Management Feature.
Backtesting.
Trading Alerts.
Use the strategy with alerts
This strategy is alert-ready. All you have to do is:
Go on a pair you would like to trade
Create an alert
Select the strategy as a Trigger
Wait for new orders to be sent to you
This is develop for specially for automating trading on any exchange, if you need to get that automating service for this strategy or any Tradingview strategy or indicator please contact me I am have 8 year experience on that field.
I hope you enjoy it!
Thanks,
Ranga
Davin's 10/200MA Pullback on SPY Strategy v2.0Strategy:
Using 10 and 200 Simple moving averages, we capitalize on price pullbacks on a general uptrend to scalp 1 - 5% rebounds. 200 MA is used as a general indicator for bullish sentiment, 10 MA is used to identify pullbacks in the short term for buy entries.
An optional bonus: market crash of 20% from 52 days high is regarded as a buy the dip signal.
An optional bonus: can choose to exit on MA crossovers using 200 MA as reference MA (etc. Hard stop on 50 cross 200)
Recommended Ticker: SPY 1D (I have so far tested on SPY and other big indexes only, other stocks appear to be too volatile to use the same short period SMA parameters effectively) + AAPL 4H
How it works:
Buy condition is when:
- Price closes above 200 SMA
- Price closes below 10 SMA
- Price dumps at least 20% (additional bonus contrarian buy the dip option)
Entry is on the next opening market day the day after the buy condition candle was fulfilled.
Sell Condition is when:
- Prices closes below 10 SMA
- Hard stop at 15% drawdown from entry price (adjustable parameter)
- Hard stop at medium term and long term MA crossovers (adjustable parameters)
So far this strategy has been pretty effective for me, feel free to try it out and let me know in the comments how you found :)
Feel free to suggest new strategy ideas for discussion and indicator building
Ichimoku Cloud and Bollinger Bands (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
This strategy combines the Ichimoku Cloud with Bollinger Bands to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
The closing price is greater than the upper standard deviation of the Bollinger Bands
Short Position:
Tenkan-Sen is below the Kijun-Sen
Chikou-Span is below the close of 26 bars ago
Close is below the Kumo Cloud
The upper standard deviation of the Bollinger Band is greater than the closing price
The script is backtested from 1 January 2022 and provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
This script also works well on BTC 30m/1h, ETH 2h, MATIC 2h/30m, AVAX 1h/2h, SOL 45m timeframes
J2S Backtest: Steven Primo`s Big Trend StrategyIs it possible to benefit from big trend moves? In this study I present you a strategy that aims to capture big trend moves.
Created by trader Steven Primo, The Big Trend strategy is advocates and shared through his YouTube channel without restrictions.
Note:
This is not an investment recommendation. The purpose of this study is only to share knowledge with the community on TradingView.
What is the purpose of the strategy?
The strategy focuses on capturing the movement of trends, providing an entry signal for both LONG and SHORT positions.
To which time-frame of a chart is it applicable to?
According to the author, it is applicable to any chart in different markets.
What about risk management?
The author does not establish a risk management model for strategy. This is left to the definition of each trader.
How are the trends identified in this strategy?
A 20-periods Bollinger Bands with 0.382 deviation should be plotted on the chart. Prices above the upper band indicate an uptrend, on the other hand, prices below the lower band indicate an downtrend. Finally, prices between the two bands indicate sideways trend.
How to identify a signal for LONG entry?
The signal is given after five consecutive closes above the upper Bollinger band. After that, you must enter the trade after the first trade occurs above the high of the signal bar.
How to identify a signal for SHORT entry?
The signal is given after five consecutive closes below the lower Bollinger band. After that, you must enter the trade after the first trade occurs below the low of the signal bar.
Tips and tricks
In my backtest, I tried to prove the strategy from a position trading perspective, so I proposed use fixed stop-loss and take-profits. The stop-loss is defined as being low of the first bar that generated the movement until the signal bar. The value range from the stop-loss to the signal bar is used in determining the profit target. Given any trade, position closing will be triggered when the bar trading limit is reached.
Backtest features
Backtest parameters are fully customizable, for instance: number of bars inside a trend indicating trend maturity for entry, bar limit for trading entry (after a buy or sell signals). Also, the user chooses to validate only LONG or SHORT entries, or both. It is also possible to determine the specific time period for running the backtests.
Final message
In my tests, I noticed excellent results for other crypto pairs, for example: ETH/USDT, BNB/USDT, FIL/USDT, GALA/USDT and ILV/USDT. Of course, no one strategy works perfectly for every asset, crypto, and bond out there. That's why we should explore each trading model and carry out our backtests. Please, feel free to provide me with any improvement suggestions for the backtest script. Bear in mind, feel free to use the ideas in my script in your studies.
Cipher B divergencies for Crypto (Finandy support)Hello Traders!
In times of high volatility, it is important to follow a market-neutral strategy to protect your hard-earned assets. The simple script employs common buy/sell and/or divergencies signals from the VuManChu Cipher B indicator with fixed stop losses and takes profits. The signals are filtered by a local trend of a coin of interest and the global trend of Bitcoin. These trends-filtered signals demonstrated better performance on most of the back- and forward- tests for USDT cryptocurrency futures. The strategy is based on my real experience, it's a diamond I want to share with you.
In terms of visualization if the background is red and the price is below the yellow line then only a short position can be opened. Conversely, if the price is above the yellow line AND the background is green only a long position can be opened.
Inputs from VuManChu you can find on the top. Frankly, I do not know how they can help you to improve the performance of the strategy. My inputs of the script you can find in "Trend Settings" and "TP/SL Settings" at the bottom.
The checkbox "Only divergencies" lets to broadcast only more reliable buy/sell signals for a cost of rare deals.
The checkbox "Cancel all positions if price crosses local sma?" makes additional trailing stop loss. Usually, this function increases the win rate by "smoothing" the risk/reward ratio, as a usual stop loss does.
You can tune SL/TP based on backtesting.
To connect the script to Finandy just edit "name" and "secret" to connect your webhook (see the bottom of the script).
The rule of thumb for the strategy is "only divergencies" - ON, high reward/risk (TP/SL) ratio, 5 min timeframe on chart help with performance.
Finally, I am looking forward to feedback from you. If you have some cool features for my script in your mind, do not hesitate to leave them in the comments.
Good luck!
BTC WaveTrend R:R=1:1.5In this strategy, I used Wavetrend indicator (Lazy Bear).
It is very simple and easy to understanding: Long when Wavetrend1 crossover Wavetrend2 and they are less than a limit value (not buy when price overbought). Stoploss at lowest 3 bar previous. R:R = 1:1,5.
About other shortterm strategies for crypto market, you can view my published strategies.
Intraday Grid trading exampleHello everyone,
This was a grid trading example for intraday trading.
Please be advised that every commodity have diferent kind of reaction and rate of change between periods therefore the percentages need to be adjusted acording to the commodities change %.
In order to specify the adjustment rate we add the Zig Zag in the script.
For Example ;
Last 3 days zigzag high points are %25 , %13 and %8 , the average %is about %9 therefore you have to put the adjustment ratios something like;
Z%1 = %3
Z%2 = %6
Z%3 = %9
Feel free to use the script with caution( it was not a investment advice), this was only a example of grid trading strategy on our trading platform.
Regards.
Easy System 420In this strategy, 15 indicators are used, each giving its results as a numerical value, which then is added or subtracted from the total points, gathered from all 15 indicators.
Many thanks to RafaelZioni for his great work making the EasySys1 script which i modified to create this script.
Onchart is drawn some of the indicators, but not all, a info panel is drawn showing the value each indicator has calculated. The info panel can be turned on or off.
Many of the indicator settings can be changed by user, and this is recommended, to tune the strategy to users chosen pair/timeframe.
Therefore any pair or timeframe can be used, the strategy tester results showing possible results, remember to set commission to match your broker. example chart settings here have common crypto exchange commission value: 0.25%
indicator list : SAR + STT + ZigZag + ROC + DMI + CCI + Weis + SMA + AO + MOM + Hist + BB + Ichimoku + HMA
BEST Trend Direction Helper (Strategy Edition)Hello traders
A follower asked me to convert my Trend Direction Helper into a strategy
So blessed this indicator reached the 1400+ likes milestone - I can't believe how many people are trading with it
I based the setup as follow:
- Entries on those green/red labels
- exit whenever a Simple Moving Averages cross in the opposite direction happen
- possibility to filter only Longs/Shorts or both
Also...
The strategy includes the Zig Zag/Pivots high/low and other options from the indicator version. I only added a quick strategy component with a hard exit concept based on SMA cross
All the best fam and... HAPPY NEW YEAR !!!!!!!!!!!
Dave
Elliott strategyIt uses Elliott teory to shift two moving averages 8 positions (based on 5-3 fractal), and the crossing is close to reversions. And it keeps an eye on RSI level to be sure it is on hot level to sell/buy
