Chaikin MF% (CMFP) w. Alerts, Bells & Whistles [LucF]This is Chaikin’s Money Flow indicator on a 0-100 scale with buy/sell signals, alerts and other bells & whistles.
It includes:
- a fast EMA (16 periods by default),
- a slow MA (64 periods by default),
- histograms,
- 3 different sorts of crosses,
- big swings identification,
- buy/sell signals on CMFP crossing back from outside user-defined levels,
- buy/sell signals on the slow MA pivots above/below user-defined levels,
- alerts on big swings and buy/sells.
This indicator started with @LazyBear code (VAPI) at:
@cI8DH then changed the scale to 0-100, which I find very useful:
I then added the rest.
The chart above shows both clean and busy versions of the indicator.
Note that the default length is 10 rather than the commonly used 20. I use CMFP in conjunction with VFI and like the fact that it is faster than VFI. The default inputs show the way I normally use this indicator, with the slow MA shown in histogram mode. I find it gives good context to the signal line. Crosses between the two are often useful.
The buy/sell signals aren’t the main attraction of this indicator, and nothing to write home about. Like the big swing markers, I think it’s more realistic to view them as pointers to potentially interesting areas on charts. Their nature makes them more suited to identifying reversals. They certainly aren’t reliable enough to turn this study into a strategy and I normally don’t use them. The levels pre-defined for the buy/sell signals on CMFP are most useful on short intervals. The buy/sell signals on the slow MA pivots work on a more complete range of intervals. Optimization for your specific instruments and intervals will improve their reliability.
As usual when defining alerts, be sure you already have defined proper inputs and that you are on the intended interval, as they will be used when triggering alerts.
Tìm kiếm tập lệnh với "美元指数跌破100大关"
3 of SlowStochastics
스토캐스틱 3개를 한번에 볼수 있습니다. 천장과 바닥은 각 100의 위치마다 존재합니다
You can see three slow stochastics at once. The ceiling and floor are located at each 100 (0 - 100 - 200- 300)
Percentage Price Oscillator (PPO)The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price.
Calculations
PPO: {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals as the MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price > 20K) can be compared against the PPO levels of IBM (price < 200) because the PPO “levels” the playing field. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for the MACD.
Limitations
Despite its advantages, the PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Source: Stockcharts
Multiple Moving AveragesThis is really simple. But useful for me as I don't have a paid account. No-pro users can only use 3 indicators at once and because I rely heavily on simple moving averages it can be a real pain.
This one indicator features:
20 MA
50 MA
100 MA
200 MA
which I find are the most useful overall. The 20 and 50 over all time frame but in particular < 1 day, the 100 and 200 at > 4 hr time frames. In general I don't use the 100 MA that much. The daily 200 MA is a critical support for many assets like stocks and cryptos. I'm by no means a pro and if you are learning I recommend becoming familiar with moving averages right at the beginning.
If you want to deactivate some of the lines, you can do it via the indicator's settings icon.
Exponential Moving Average (Set of 3) [Krypt] + 13/34 EMAsI took Krypt's script and essentially added on to it.
the 20/50/100/200 EMAs should be used together as support and resistance as normal.
Wait for price to break 200 EMA
Wait for 50 EMA to cross 200 EMA
Wait for pullback to 50 EMA to open position
20 and 100 EMAs are for extra information about moving support and resistance
and 13/34 EMAs should be used in conjunction
When 13 EMA crosses 34 EMA, open position
When price gets far from 13/34, close position (because price will attempt to revert back to mean)
This is better for scalping and swing trades than the 20/50/100/200 setup.
Twitter: @AzorAhai06
Ichimoku Cloud Score v1.0This script calculates a simple Ichimoku Score based on the signals documented here , with a few additions. Each of the score components can be individually weighted via the script inputs . The output is a plot of the normalized Ichimoku score, in the range of -100 to 100.
This script has been heavily modified from 'Ichimoku Cloud Signal Score v2.0.0 '. Credit to user 'dashed' for the initial implementation.
This has been modified with several refinements:
Clean/Organized Code
Simplified Inputs
Improved Style
Scores normalized to a range (-100, 100)
Bugfixes and Improvements
Script Inputs: i.imgur.com
Volume RatioDefinition:
Volume ratio can be obtained in a similar way to RSI.
Volume Ratio (%) = 100 - 100/(1+vr)
The parameter "vr" is defined as
vr=(A+U/2)/(D+U/2)
A=Total volume of the periods when the price advanced
D=Total volume of the periods when the price declined
U=Total volume of the periods when the price unchanged
After substitution, following expression can be derived and the denominator represents total volume of all periods.
Volume Ratio (%) = 100 x (A+U/2)/(A+D+U)
Notes:
A similar method to interpret RSI can be employed.
1) Overbought level over 70% and oversold level under 30%. These levels need to be adjusted according to the periods, time frames and issues.
2) Bullish picture over 50% line and bearish picture under 50% line.
3) Crossing oversold level to the upside can be taken as a confirmation of bullish reversal. - and vice versa for a bearish reversal.
4) After a long-term bearish market, the increase of volume can happen in the early stage of a bullish market.
5) Buying opportunity can be suggested when the volume ratio is declining and the price is either advancing or leveling off.
CCI with Volume Weighted EMA Here is an attempt to improve on the CCI using a volume weighted ema which is then plugged into the CCI formula.
Use:
The CCI with VW EMA is an oscillator that gives readings between -100 and +100. The usual use is to 'go long' with values over +100 and short on values less than -100.
Another use of this oscillator is a countertrend indicator where one sells at crosses under +100 and buys on crosses over -100.
Multi-Functional Fisher Transform MTF with MACDL TRIGGERWhat this indicator gives you is a true signal when price is exhausted and ready for a fast turnaround. Fisher Transform is set for multi-time frame and also allows the user to change the length. This way a user can compare two or more time spans and lengths to look for these MACDL divergent triggers after a Fisher exhaustion. With so many indicators, it's probably best to merge these indicators and change the Fisher and Trigger colors so you can still have a look at price action (remember to scale right after merger). I've noticed from time to time when you have Fisher 34 100 and 300 up and running on two different time frames such as 5 and 15 min charts, with MACDL triggers on the 100/300 or 34/100 you get a high probability trade trigger. However, there are rare exceptions such as when price moves in a parabolic state up or down for a long period where this indication does not work. Ideally this indicator works best in a sideways market or slow rising/descending moving market.
This indicator was worked on by Glaz, nmike and myself
LazyBear also introduced the MACDL indicator
CCI Crossover AlertThis very simple indicator will give you a blue background where the CCI crossed from below -100 to above -100, and a red background where it crossed from above 100 to below 100.
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
"\nDate: " + date_str + " " + time_str +
"\nTrade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
"\nRank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
"\nPercentile: " + str.tostring(percentile, "#.#") + "%" +
"\nMagnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
Commodity Channel Index DualThe CCI Dual is a custom TradingView indicator built in Pine Script v5, designed to help traders identify potential buy and sell signals using two Commodity Channel Index (CCI) oscillators. It combines a shorter-period CCI (default: 14) for quick momentum detection with a longer-period CCI (default: 50) for confirmation, focusing on mean-reversion opportunities in overbought or oversold conditions.
This setup is particularly suited for volatile markets like cryptocurrencies on higher timeframes (e.g., 3-day charts), where it highlights reversals by requiring both CCIs to cross out of extreme zones within a short window (default: 3 bars).
The indicator plots the CCIs, customizable bands (inner: 100, OB/OS: 175, outer: 200), dynamic fills for visual emphasis, background highlights for signals, and alert conditions for notifications.
How It Works
The indicator calculates two CCIs based on user-defined lengths and source (default: close price):
CCI Calculation: CCI measures price deviation from its average, using the formula: CCI = (Typical Price - Simple Moving Average) / (0.015 * Mean Deviation). The short CCI reacts faster to price changes, while the long CCI provides smoother, trend-aware confirmation.
Overbought/Oversold Levels: Customizable thresholds define extremes (Overbought at +175, Oversold at -175 by default). Bands are plotted at inner (±100), mid (±175 dashed), and outer (±200) levels, with gray fills for the outer zones.
Dynamic Fills: The longer CCI is used to shade areas beyond OB/OS levels in red (overbought) or green (oversold) for quick visual cues.
Signals:
Buy Signal: Triggers when both CCIs cross above the Oversold level (-175) within the signal window (3 bars). This suggests a potential upward reversal from an oversold state.
Sell Signal: Triggers when both cross below the Overbought level (+175) within the window, indicating a possible downward reversal.
Visuals and Alerts: Buy signals highlight the background green, sells red. Separate alertconditions allow setting TradingView alerts for buys or sells independently.
Customization: Adjust lengths, levels, and window via inputs to fit your timeframe or asset—e.g., higher OB/OS for crypto volatility.
This logic reduces noise by requiring dual confirmation, but like all oscillators, it can produce false signals in strong trends where prices stay extended.
To mitigate false signals (e.g., in trending markets), layer the CCI Dual with MACD (default: 12,26,9) and RSI (default: 14) for multi-indicator confirmation:
With MACD: Only take CCI buys if the MACD line is above the signal line (or histogram positive), confirming bullish momentum. For sells, require MACD bearish crossover. This filters counter-trend signals by aligning with trend strength—e.g., ignore CCI sells if MACD shows upward momentum.
With RSI: Confirm CCI oversold buys only if RSI is below 30 and rising (or shows bullish divergence). For overbought sells, RSI above 70 and falling. This adds overextension validation, reducing whipsaws in crypto trends.
I made this customizable for you to find what works best for your asset you are trading. I trade the 6 hour and 3 day timeframe mainly on major cryptocurrency pairs. I hope you enjoy this script and it serves you well.
Advanced Range Analyzer ProAdvanced Range Analyzer Pro – Adaptive Range Detection & Breakout Forecasting
Overview
Advanced Range Analyzer Pro is a comprehensive trading tool designed to help traders identify consolidations, evaluate their strength, and forecast potential breakout direction. By combining volatility-adjusted thresholds, volume distribution analysis, and historical breakout behavior, the indicator builds an adaptive framework for navigating sideways price action. Instead of treating ranges as noise, this system transforms them into opportunities for mean reversion or breakout trading.
How It Works
The indicator continuously scans price action to identify active range environments. Ranges are defined by volatility compression, repeated boundary interactions, and clustering of volume near equilibrium. Once detected, the indicator assigns a strength score (0–100), which quantifies how well-defined and compressed the consolidation is.
Breakout probabilities are then calculated by factoring in:
Relative time spent near the upper vs. lower range boundaries
Historical breakout tendencies for similar structures
Volume distribution inside the range
Momentum alignment using auxiliary filters (RSI/MACD)
This creates a live probability forecast that updates as price evolves. The tool also supports range memory, allowing traders to analyze the last completed range after a breakout has occurred. A dynamic strength meter is displayed directly above each consolidation range, providing real-time insight into range compression and breakout potential.
Signals and Breakouts
Advanced Range Analyzer Pro includes a structured set of visual tools to highlight actionable conditions:
Range Zones – Gradient-filled boxes highlight active consolidations.
Strength Meter – A live score displayed in the dashboard quantifies compression.
Breakout Labels – Probability percentages show bias toward bullish or bearish continuation.
Breakout Highlights – When a breakout occurs, the range is marked with directional confirmation.
Dashboard Table – Displays current status, strength, live/last range mode, and probabilities.
These elements update in real time, ensuring that traders always see the current state of consolidation and breakout risk.
Interpretation
Range Strength : High scores (70–100) indicate strong consolidations likely to resolve explosively, while low scores suggest weak or choppy ranges prone to false signals.
Breakout Probability : Directional bias greater than 60% suggests meaningful breakout pressure. Equal probabilities indicate balanced compression, favoring mean-reversion strategies.
Market Context : Ranges aligned with higher timeframe trends often resolve in the dominant direction, while counter-trend ranges may lead to reversals or liquidity sweeps.
Volatility Insight : Tight ranges with low ATR imply imminent expansion; wide ranges signal extended consolidation or distribution phases.
Strategy Integration
Advanced Range Analyzer Pro can be applied across multiple trading styles:
Breakout Trading : Enter on probability shifts above 60% with confirmation of volume or momentum.
Mean Reversion : Trade inside ranges with high strength scores by fading boundaries and targeting equilibrium.
Trend Continuation : Focus on ranges that form mid-trend, anticipating continuation after consolidation.
Liquidity Sweeps : Use failed breakouts at boundaries to capture reversals.
Multi-Timeframe : Apply on higher timeframes to frame market context, then execute on lower timeframes.
Advanced Techniques
Combine with volume profiles to identify areas of institutional positioning within ranges.
Track sequences of strong consolidations for trend development or exhaustion signals.
Use breakout probability shifts in conjunction with order flow or momentum indicators to refine entries.
Monitor expanding/contracting range widths to anticipate volatility cycles.
Custom parameters allow fine-tuning sensitivity for different assets (crypto, forex, equities) and trading styles (scalping, intraday, swing).
Inputs and Customization
Range Detection Sensitivity : Controls how strictly ranges are defined.
Strength Score Settings : Adjust weighting of compression, volume, and breakout memory.
Probability Forecasting : Enable/disable directional bias and thresholds.
Gradient & Fill Options : Customize range visualization colors and opacity.
Dashboard Display : Toggle live vs last range, info table size, and position.
Breakout Highlighting : Choose border/zone emphasis on breakout events.
Why Use Advanced Range Analyzer Pro
This indicator provides a data-driven approach to trading consolidation phases, one of the most common yet underutilized market states. By quantifying range strength, mapping probability forecasts, and visually presenting risk zones, it transforms uncertainty into clarity.
Whether you’re trading breakouts, fading ranges, or mapping higher timeframe context, Advanced Range Analyzer Pro delivers a structured, adaptive framework that integrates seamlessly into multiple strategies.
Smart Multi-Confirm Reversal DetectorHow the Smart Multi-Confirm Reversal Detector Works
The indicator works by analyzing candlestick patterns, trend, and technical confirmations and then scoring each bar to determine the strength of a potential reversal. Here’s the step-by-step logic:
Step 1: Analyze Candlestick Patterns
For each new candle, the indicator checks if any of the selected patterns occur:
Wick Reversal (Long Lower Wick):
Looks for candles with a small body and a long lower shadow.
Indicates buying pressure (potential bullish reversal).
Inverted Wick (Long Upper Wick):
Looks for candles with a small body and a long upper shadow.
Indicates selling pressure (potential bearish reversal).
Body Engulf:
The current candle completely “engulfs” the previous candle.
Signals a strong change in momentum.
Tweezer Patterns:
Two consecutive candles with almost identical highs or lows.
Suggests a potential reversal zone.
3-Bar Pattern:
Three consecutive bullish or bearish candles in a row.
Shows strong momentum continuation or exhaustion, used to confirm reversal.
Each pattern can be turned on/off by the user. If a pattern is detected, it contributes points to the overall signal score.
Step 2: Confirm Trend Direction
The indicator checks EMA trend alignment:
Fast EMA vs Slow EMA:
Fast EMA above Slow EMA → bullish trend.
Fast EMA below Slow EMA → bearish trend.
Optional Higher Timeframe EMA (HTF) Alignment:
Checks if the trend on a higher timeframe matches the current trend.
Adds extra weight to the signal if alignment is true.
This ensures the signal goes in the direction of the prevailing trend, reducing false signals.
Step 3: Check Technical Confirmations
Optional filters increase reliability:
ADX (Average Directional Index):
Measures the strength of the current trend.
Only strong trends contribute to the score.
RSI (Relative Strength Index):
Bullish confirmation: RSI is oversold.
Bearish confirmation: RSI is overbought.
Volume Spike:
Compares current volume to the average volume.
High volume validates the signal’s momentum.
Body Momentum:
Compares current candle’s body size to its average.
Larger than average body indicates stronger momentum.
Each of these confirmations can be enabled/disabled and has a weight in the scoring system.
Step 4: Calculate Score
Each pattern and confirmation has a user-defined weight (0–100).
The indicator sums the active weights that pass conditions and normalizes to 100.
Example:
Wick Reversal detected → 30 points
Trend EMA confirmed → 15 points
ADX confirmed → 10 points
Score = 55/100 → may or may not trigger a signal depending on threshold.
Score Threshold:
Only bars above the user-defined threshold are considered a confirmed signal.
Bars above a lower “label threshold” still show a label, even if not strong enough for alerts.
Step 5: Visualize Signals
Bullish Signals: Green triangle below the candle.
Bearish Signals: Red triangle above the candle.
Labels: Show the type of pattern and the score.
Purpose: Quickly identify potential reversals and assess their strength visually.
Step 6: Optional Alerts
Fixed alert messages can be enabled for confirmed bullish or bearish signals.
Alerts do not recommend trades; they just notify you of pattern confirmations.
Complies with TradingView’s policy for safe alert use.
Step 7: Weighted Decision
The final decision is not binary.
Instead, the indicator combines multiple signals into a score, so stronger signals are more reliable.
This reduces false positives and gives traders a professional, multi-confirmation approach to detect potential reversals.
Volume Heat ZoneVolume Zones Indicator
This Pine Script creates a volume-based zone analysis tool for TradingView.
Function:
Divides the price range (high to low) into 20 levels over a 100-candle lookback period
Measures volume activity at each price level
Draws boxes at levels with above-average volume (1.5x threshold)
Key Settings:
Lookback Period (100): Number of candles analyzed
Price Levels (20): Price range subdivisions
Volume Threshold (1.5): Minimum volume multiplier for zones
Candle Offset (1): Excludes current candle from analysis
Projection Bars (10): Extends boxes 10 bars into the future
How it works:
The indicator identifies price levels where significant trading volume occurred historically, highlighting potential support/resistance zones. Boxes are redrawn on each confirmed candle, showing dynamic volume concentration areas that traders can use for entry/exit decisions.
Adaptive Rolling Quantile Bands [CHE] Adaptive Rolling Quantile Bands
Part 1 — Mathematics and Algorithmic Design
Purpose. The indicator estimates distribution‐aware price levels from a rolling window and turns them into dynamic “buy” and “sell” bands. It can work on raw price or on *residuals* around a baseline to better isolate deviations from trend. Optionally, the percentile parameter $q$ adapts to volatility via ATR so the bands widen in turbulent regimes and tighten in calm ones. A compact, latched state machine converts these statistical levels into high-quality discretionary signals.
Data pipeline.
1. Choose a source (default `close`; MTF optional via `request.security`).
2. Optionally compute a baseline (`SMA` or `EMA`) of length $L$.
3. Build the *working series*: raw price if residual mode is off; otherwise price minus baseline (if a baseline exists).
4. Maintain a FIFO buffer of the last $N$ values (window length). All quantiles are computed on this buffer.
5. Map the resulting levels back to price space if residual mode is on (i.e., add back the baseline).
6. Smooth levels with a short EMA for readability.
Rolling quantiles.
Given the buffer $X_{t-N+1..t}$ and a percentile $q\in $, the indicator sorts a copy of the buffer ascending and linearly interpolates between adjacent ranks to estimate:
* Buy band $\approx Q(q)$
* Sell band $\approx Q(1-q)$
* Median $Q(0.5)$, plus optional deciles $Q(0.10)$ and $Q(0.90)$
Quantiles are robust to outliers relative to means. The estimator uses only data up to the current bar’s value in the buffer; there is no look-ahead.
Residual transform (optional).
In residual mode, quantiles are computed on $X^{res}_t = \text{price}_t - \text{baseline}_t$. This centers the distribution and often yields more stationary tails. After computing $Q(\cdot)$ on residuals, levels are transformed back to price space by adding the baseline. If `Baseline = None`, residual mode simply falls back to raw price.
Volatility-adaptive percentile.
Let $\text{ATR}_{14}(t)$ be current ATR and $\overline{\text{ATR}}_{100}(t)$ its long SMA. Define a volatility ratio $r = \text{ATR}_{14}/\overline{\text{ATR}}_{100}$. The effective quantile is:
Smoothing.
Each level is optionally smoothed by an EMA of length $k$ for cleaner visuals. This smoothing does not change the underlying quantile logic; it only stabilizes plots and signals.
Latched state machines.
Two three-step processes convert levels into “latched” signals that only fire after confirmation and then reset:
* BUY latch:
(1) HLC3 crosses above the median →
(2) the median is rising →
(3) HLC3 prints above the upper (orange) band → BUY latched.
* SELL latch:
(1) HLC3 crosses below the median →
(2) the median is falling →
(3) HLC3 prints below the lower (teal) band → SELL latched.
Labels are drawn on the latch bar, with a FIFO cap to limit clutter. Alerts are available for both the simple band interactions and the latched events. Use “Once per bar close” to avoid intrabar churn.
MTF behavior and repainting.
MTF sourcing uses `lookahead_off`. Quantiles and baselines are computed from completed data only; however, any *intrabar* cross conditions naturally stabilize at close. As with all real-time indicators, values can update during a live bar; prefer bar-close alerts for reliability.
Complexity and parameters.
Each bar sorts a copy of the $N$-length window (practical $N$ values keep this inexpensive). Typical choices: $N=50$–$100$, $q_0=0.15$–$0.25$, $k=2$–$5$, baseline length $L=20$ (if used), adaptation strength $s=0.2$–$0.7$.
Part 2 — Practical Use for Discretionary/Active Traders
What the bands mean in practice.
The teal “buy” band marks the lower tail of the recent distribution; the orange “sell” band marks the upper tail. The median is your dynamic equilibrium. In residual mode, these tails are deviations around trend; in raw mode they are absolute price percentiles. When ATR adaptation is on, tails breathe with regime shifts.
Two core playbooks.
1. Mean-reversion around a stable median.
* Context: The median is flat or gently sloped; band width is relatively tight; instrument is ranging.
* Entry (long): Look for price to probe or close below the buy band and then reclaim it, especially after HLC3 recrosses the median and the median turns up.
* Stops: Place beyond the most recent swing low or $1.0–1.5\times$ ATR(14) below entry.
* Targets: First scale at the median; optional second scale near the opposite band. Trail with the median or an ATR stop.
* Symmetry: Mirror the rules for shorts near the sell band when the median is flat to down.
2. Continuation with latched confirmations.
* Context: A developing trend where you want fewer but cleaner signals.
* Entry (long): Take the latched BUY (3-step confirmation) on close, or on the next bar if you require bar-close validation.
* Invalidation: A close back below the median (or below the lower band in strong trends) negates momentum.
* Exits: Trail under the median for conservative exits or under the teal band for trend-following exits. Consider scaling at structure (prior swing highs) or at a fixed $R$ multiple.
Parameter guidance by timeframe.
* Scalping / LTF (1–5m): $N=30$–$60$, $q_0=0.20$, $k=2$–3, residual mode on, baseline EMA $L=20$, adaptation $s=0.5$–0.7 to handle micro-vol spikes. Expect more signals; rely on latched logic to filter noise.
* Intraday swing (15–60m): $N=60$–$100$, $q_0=0.15$–0.20, $k=3$–4. Residual mode helps but is optional if the instrument trends cleanly. $s=0.3$–0.6.
* Swing / HTF (4H–D): $N=80$–$150$, $q_0=0.10$–0.18, $k=3$–5. Consider `SMA` baseline for smoother residuals and moderate adaptation $s=0.2$–0.4.
Baseline choice.
Use EMA for responsiveness (fast trend shifts) and SMA for stability (smoother residuals). Turning residual mode on is advantageous when price exhibits persistent drift; turning it off is useful when you explicitly want absolute bands.
How to time entries.
Prefer bar-close validation for both band recaptures and latched signals. If you must act intrabar, accept that crosses can “un-cross” before close; compensate with tighter stops or reduced size.
Risk management.
Position size to a fixed fractional risk per trade (e.g., 0.5–1.0% of equity). Define invalidation using structure (swing points) plus ATR. Avoid chasing when distance to the opposite band is small; reward-to-risk degrades rapidly once you are deep inside the distribution.
Combos and filters.
* Pair with a higher-timeframe median slope as a regime filter (trade only in the direction of the HTF median).
* Use band width relative to ATR as a range/trend gauge: unusually narrow bands suggest compression (mean-reversion bias); expanding bands suggest breakout potential (favor latched continuation).
* Volume or session filters (e.g., avoid illiquid hours) can materially improve execution.
Alerts for discretion.
Enable “Cross above Buy Level” / “Cross below Sell Level” for early notices and “Latched BUY/SELL” for conviction entries. Set alerts to “Once per bar close” to avoid noise.
Common pitfalls.
Do not interpret band touches as automatic signals; context matters. A strong trend will often ride the far band (“band walking”) and punish counter-trend fades—use the median slope and latched logic to separate trend from range. Do not oversmooth levels; you will lag breaks. Do not set $q$ too small or too large; extremes reduce statistical meaning and practical distance for stops.
A concise checklist.
1. Is the median flat (range) or sloped (trend)?
2. Is band width expanding or contracting vs ATR?
3. Are we near the tail level aligned with the intended trade?
4. For continuation: did the 3 steps for a latched signal complete?
5. Do stops and targets produce acceptable $R$ (≥1.5–2.0)?
6. Are you trading during liquid hours for the instrument?
Summary. ARQB provides statistically grounded, regime-aware bands and a disciplined, latched confirmation engine. Use the bands as objective context, the median as your equilibrium line, ATR adaptation to stay calibrated across regimes, and the latched logic to time higher-quality discretionary entries.
Disclaimer
No indicator guarantees profits. Adaptive Rolling Quantile Bands is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Best regards
Chervolino
Fear & Greed Oscillator — LEAP Puts (v6, manual DMI/ADX)Fear & Greed Oscillator — LEAP Puts (v6, manual DMI/ADX) is a Puts-focused mirror of the Calls version, built to flag top risk and momentum rollovers for timing LEAP Put entries. It outputs a smoothed composite from −100 to +100 using slower MACD, manual DMI/ADX (Wilder), RSI and Stoch RSI extremes, OBV distribution vs. accumulation, and volume spike & direction, with optional Put/Call Ratio and IV Rank inputs. All thresholds, weights, and smoothing match the Calls script for 1:1 customization, and a component table shows what’s driving the score. Reading is simple: higher values = rising top-risk (red shading above “Top-Risk”); lower values = deep dip / bounce risk (green shading). Built-in alerts cover Top-Risk, Deep Dip, and zero-line crosses for clear, actionable cues.
LEAP Put Edge — Top Risk Oscillator (v6, divergences + HTF)Pinpoint market tops with precision — a composite oscillator built to spot exhaustion, bearish divergences, and high-probability LEAP Put entry zones.
The LEAP Put Edge — Top Risk Oscillator is designed specifically to help identify high-probability entry points for long-dated Put options (LEAPs) by highlighting exhaustion at market tops. Unlike generic overbought/oversold tools, it combines slower MACD and DMI/ADX for trend quality, RSI and Stochastic RSI for momentum extremes, volume spike and upper-wick exhaustion signals for capitulation risk, and optional bearish divergences in RSI and MACD to confirm weakening strength. The output is a smoothed composite score scaled from -100 to +100, where higher values indicate rising top-risk and bearish edge conditions. Clear thresholds, color-coded plots, and built-in alerts make it straightforward and practical for traders seeking simple, actionable signals to time Put entries with confidence.
Aroon ADX/DIUnified trend-strength (ADX/DI) + trend-age (Aroon) with centered scaling, gated signals, regime tints, and a compact readout.
What is different about this script:
- Purpose-built mashup of ADX/DI tells trend strength and side, while Aroon Oscillator tracks trend emergence/aging. Combining them into a scaled chart creates a way to separate “strong-but-late” trends from “newly-emerging” ones.
- Unified scale: Centering the maps into a common +/- 100 range so all lines are directly comparable at a glance (no units mismatch or fumbling with scales).
- Signal quality gating: DI cross signals can be gated by minimum ADX so crosses in chop are filtered out.
- Regime context: Background tints show low-strength chop, developing, and strong regimes using your ADX thresholds.
- Operator-focused UI: Clean fills, color-blind palette, and a two-column table summarizing DI+, DI−, ADX, Aroon, and a plain-English Bias/Trend status.
How it works:
- DI+/DI−/ADX: Wilder’s DI is smoothed; DX → ADX via SMA smoothing.
- Aroon Oscillator: highlights new highs/lows frequency to infer trend
- Centering: Maps DI/ADX from 5-95 and ±100, with your Midpoint controlling where “0” sits in raw mode.
- Signals:
- Bullish/Bearish DI crosses, optionally allowed only when ADX ≥ Min.
- ADX crosses of your Low/High thresholds.
- Aroon crosses of 0, +80, −80 (fresh trend thresholds).
- Display aids: Optional fill between DI+/DI−; thin guides for thresholds; single-pane table summary.
How to use:
- For this to be useful, centering should stay on, modify ADX Low/High and monitor DI crosses with ADX.
- Interpretations:
Bias: DI+ above DI− = bull; below = bear.
Strength level: ADX < Low = chop, Low–High = developing, > High = strong.
Freshness: Aroon > +80 or crossing up 0 suggests new or continued bull push; < −80 or crossing down 0 suggests new or continued bear push.
- Alerts: Use built-ins for DI crosses, ADX regime changes, and Aroon thresholds.
Fear & Greed Oscillator — LEAPs (v6, manual DMI/ADX)Fear & Greed Oscillator for LEAPs — a composite sentiment/trend tool that highlights long-term fear/greed extremes and trend quality for better LEAP entries and exits.
This custom Fear & Greed Oscillator (FGO-LEAP) is designed for swing trades and long-term LEAP option entries. It blends multiple signals — MACD (trend), ADX/DMI (trend quality), OBV (accumulation/distribution), RSI & Stoch RSI (momentum), and volume spikes — into a single score that ranges from –100 (extreme fear) to +100 (extreme greed). The weights are tuned for LEAPs, emphasizing slower trend and accumulation signals rather than short-term noise.
Use Weekly charts for the main signal and Daily only for entry timing. Entries are strongest when the score is above zero and rising, with both MACD and DMI positive. Extreme Fear (< –60) can mark long-term bottoms when followed by a recovery, while Extreme Greed (> +60) often signals overheated conditions. A cross below zero is an early warning to reduce or roll positions.
Donchian Squeeze Oscillator# Donchian Squeeze Oscillator (DSO) - User Guide
## Overview
The Donchian Squeeze Oscillator is a technical indicator designed to identify periods of low volatility (squeeze) and high volatility (expansion) in financial markets by measuring the distance between Donchian Channel bands. The indicator normalizes this measurement to a 0-100 scale, making it easy to interpret across different timeframes and instruments.
## How It Works
The DSO calculates the width of Donchian Channels as a percentage of the middle line, smooths this data, and then normalizes it using historical highs and lows over a specified lookback period. The result is inverted so that:
- **High values (80+)** = Narrow channels = Low volatility = Squeeze
- **Low values (20-)** = Wide channels = High volatility = Expansion
## Key Parameters
### Core Settings
- **Donchian Channel Period (20)**: The number of bars used to calculate the highest high and lowest low for the Donchian Channels
- **Smoothing Period (5)**: Applies moving average smoothing to reduce noise in the oscillator
- **Normalization Lookback (200)**: Historical period used to normalize the oscillator between 0-100
### Threshold Levels
- **Over Squeeze (80)**: Values above this level indicate strong squeeze conditions
- **Over Expansion (20)**: Values below this level indicate strong expansion conditions
## Reading the Indicator
### Color Coding
- **Red Line**: Squeeze condition (above 80 threshold) - Markets are consolidating
- **Orange Line**: Neutral/trending condition with upward momentum
- **Green Line**: Expansion condition or downward momentum
### Visual Elements
- **Red Dashed Line (80)**: Squeeze threshold - potential breakout zone
- **Gray Dotted Line (50)**: Middle line - neutral zone
- **Green Dashed Line (20)**: Expansion threshold - high volatility zone
- **Red Background**: Highlights active squeeze periods
## Trading Applications
### 1. Breakout Trading
- **Setup**: Wait for DSO to reach 80+ (squeeze zone)
- **Entry**: Look for breakouts when DSO starts declining from squeeze levels
- **Logic**: Prolonged low volatility often precedes significant price movements
### 2. Volatility Cycle Trading
- **Squeeze Phase**: DSO > 80 - Prepare for potential breakout
- **Breakout Phase**: DSO declining from 80 - Trade the direction of breakout
- **Expansion Phase**: DSO < 20 - Expect trend continuation or reversal
### 3. Trend Confirmation
- **Orange Color**: Suggests bullish momentum during expansion
- **Green Color**: Suggests bearish momentum or consolidation
- Use in conjunction with price action for trend confirmation
## Best Practices
### Timeframe Selection
- **Higher Timeframes (Daily, 4H)**: More reliable signals, fewer false breakouts
- **Lower Timeframes (1H, 15M)**: More frequent signals but higher noise
- **Multi-timeframe Analysis**: Confirm squeeze on higher TF, enter on lower TF
### Parameter Optimization
- **Volatile Markets**: Increase Donchian period (25-30) and smoothing (7-10)
- **Range-bound Markets**: Decrease Donchian period (15-20) for more sensitivity
- **Trending Markets**: Use longer normalization lookback (300-400)
### Signal Confirmation
Always combine DSO signals with:
- **Price Action**: Support/resistance levels, chart patterns
- **Volume**: Confirm breakouts with increasing volume
- **Other Indicators**: RSI, MACD, or momentum oscillators
## Alert System
The indicator includes built-in alerts for:
- **Squeeze Started**: When DSO crosses above the squeeze threshold
- **Expansion Started**: When DSO crosses below the expansion threshold
## Common Pitfalls to Avoid
1. **False Breakouts**: Don't trade every squeeze - wait for confirmation
2. **Parameter Over-optimization**: Stick to default settings initially
3. **Ignoring Market Context**: Consider overall market conditions and news
4. **Single Indicator Reliance**: Always use additional confirmation tools
## Advanced Tips
- Monitor squeeze duration - longer squeezes often lead to bigger moves
- Look for squeeze patterns at key support/resistance levels
- Use DSO divergences with price for potential reversal signals
- Combine with Bollinger Band squeezes for enhanced accuracy
## Conclusion
The Donchian Squeeze Oscillator is a powerful tool for identifying volatility cycles and potential breakout opportunities. Like all technical indicators, it should be used as part of a comprehensive trading strategy rather than as a standalone signal generator. Practice with the indicator on historical data before implementing it in live trading to understand its behavior in different market conditions.
Alpha Spread Indicator Panel - [AlphaGroup.Live]Alpha Spread Indicator Panel –
This sub-panel plots the OLS spread between two assets, normalized into percent .
• Green area = spread above zero (Buy Leg1 / Sell Leg2)
• Red area = spread below zero (Sell Leg1 / Buy Leg2)
• The white line shows the exact % deviation of the spread from its fitted baseline
• Optional ±1% and ±2% guides give clear statistical thresholds
Because it’s expressed in percent relative to midprice , the scale remains consistent even if absolute prices change over years.
⚠️ Important: This panel is designed to be used together with the overlay chart:
👉 Alpha Spread Indicator Chart –
Pre-selected asset pairs included:
EURUSD / GBPUSD
AUDUSD / NZDUSD
USDJPY / USDCHF
USDCAD / USDNOK
EURJPY / GBPJPY
AUDJPY / NZDJPY
XAUUSD / XAGUSD
WTI (USOIL) / Brent (UKOIL)
NatGas / Crude
HeatingOil / RBOB
Corn / Wheat
Platinum / Palladium
XOM / CVX
KO / PEP
V / MA
JPM / BAC
NVDA / AMD
BHP / RIO
SHEL / BP
SPY / QQQ
Want more institutional-grade setups? Get our 100 Trading Strategies eBook free at:
alphagroup.live
Tags: pairs-trading, spread-trading, statistical-arbitrage, ols-regression, zscore, mean-reversion, arbitrage, quant, hedge, alphagroup
Alpha Spread Indicator Chart - [AlphaGroup.Live]Alpha Spread Indicator Chart –
This overlay plots the two legs of a pair trade directly on the price chart .
• Leg1 is shown in teal
• Leg2 (fitted) is shown in orange
• The green/red filled area shows the distance (spread) between the two
The spread is calculated using OLS regression fitting , which keeps Leg2 scaled to Leg1 so the overlay always sticks to the chart’s price axis. When the fill turns green , the model suggests Buy Leg1 / Sell Leg2; when it turns red , it suggests Sell Leg1 / Buy Leg2.
Optional Z-Score bands help visualize statistical stretch from the mean.
⚠️ Important: To use this tool properly, you also need to install the companion script:
👉 Alpha Spread Indicator Panel –
Pre-selected asset pairs included:
EURUSD / GBPUSD
AUDUSD / NZDUSD
USDJPY / USDCHF
USDCAD / USDNOK
EURJPY / GBPJPY
AUDJPY / NZDJPY
XAUUSD / XAGUSD
WTI (USOIL) / Brent (UKOIL)
NatGas / Crude
HeatingOil / RBOB
Corn / Wheat
Platinum / Palladium
XOM / CVX
KO / PEP
V / MA
JPM / BAC
NVDA / AMD
BHP / RIO
SHEL / BP
SPY / QQQ
Ready to take your trading further? Download our free eBook with 100 trading strategies at:
alphagroup.live
Tags: pairs-trading, spread-trading, statistical-arbitrage, ols-regression, zscore, mean-reversion, arbitrage, quant, hedge, alphagroup
