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MTF EMA Pane with Diagnostics30 sec chart, 1 min EMA goes flat, I buy, 1 min EMA stays inside the group, I stay in the trade. Not financial advice. I am working on an Algo killer, stay tuned. I am dedicating the rest of my life, as short as it my be, to beating the Men behind the Algo's. Buy me some coffee. Send USDT thru ETH or Base to BYDFi 0x20391e32afd61dc9e1ec027651391b56ceade4e0 Join BYDFi Referral Link: Spin for a possible $100 partner.bydfi.com Deposit: USDT via; ETH (ERC20) 0x20391e32afd61dc9e1ec027651391b56ceade4e0 Tron (TRC20) TUs5u2YxtQrQfRwYK2CsMmSDGvND6Uopdj BNB/Base (BEP20) 0x20391e32afd61dc9e1ec027651391b56ceade4e0 Solana 696LAngiQBbdk4m6k1ZBiKZrFtjTJo6dxCnVXMEePQea
Индикатор Pine Script®
от Karman1320
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal: Yearly Quarters = 4 quarters of three months each. Monthly Quarters = 4 quarters of one week each. Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function. Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day. Sessions Quarters = 4 quarters of 90 minutes each. 90 Minute Quarters = 4 quarters of 22.5 minutes each. Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each: Q1 - January, February, March. Q2 - April, May, June (True Open, April Open). Q3 - July, August, September. Q4 - October, November, December. S&P 500 E-mini Futures (daily candles) — Monthly Cycle. Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day): Q1 - Week 1: first Monday of the month. Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price). Q3 - Week 3: third Monday of the month. Q4 - Week 4: fourth Monday of the month. S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle. Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action: Q1 - Monday. Q2 - Tuesday (True Open, Daily Candle Open Price). Q3 - Wednesday. Q4 - Thursday. S&P 500 E-mini Futures (1 hour candles) — Daily Cycle. Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity: Q1 - 18:00 - 00:00 Asia. Q2 - 00:00 - 06:00 London (True Open). Q3 - 06:00 - 12:00 NY AM. Q4 - 12:00 - 18:00 NY PM. S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle. 6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT): Asian Session Q1 - 18:00 - 19:30 Q2 - 19:30 - 21:00 (True Open) Q3 - 21:00 - 22:30 Q4 - 22:30 - 00:00 London Session Q1 - 00:00 - 01:30 Q2 - 01:30 - 03:00 (True Open) Q3 - 03:00 - 04:30 Q4 - 04:30 - 06:00 NY AM Session Q1 - 06:00 - 07:30 Q2 - 07:30 - 09:00 (True Open) Q3 - 09:00 - 10:30 Q4 - 10:30 - 12:00 NY PM Session Q1 - 12:00 - 13:30 Q2 - 13:30 - 15:00 (True Open) Q3 - 15:00 - 16:30 Q4 - 16:30 - 18:00 S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle. Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters: Asian Session Q1/1 18:00:00 - 18:22:30 Q2 18:22:30 - 18:45:00 Q3 18:45:00 - 19:07:30 Q4 19:07:30 - 19:30:00 Q2/1 19:30:00 - 19:52:30 (True Session Open) Q2/2 19:52:30 - 20:15:00 Q2/3 20:15:00 - 20:37:30 Q2/4 20:37:30 - 21:00:00 Q3/1 21:00:00 - 21:23:30 etc. 21:23:30 - 21:45:00 London Session 00:00:00 - 00:22:30 (True Daily Open) 00:22:30 - 00:45:00 00:45:00 - 01:07:30 01:07:30 - 01:30:00 01:30:00 - 01:52:30 (True Session Open) 01:52:30 - 02:15:00 02:15:00 - 02:37:30 02:37:30 - 03:00:00 03:00:00 - 03:22:30 03:22:30 - 03:45:00 03:45:00 - 04:07:30 04:07:30 - 04:30:00 04:30:00 - 04:52:30 04:52:30 - 05:15:00 05:15:00 - 05:37:30 05:37:30 - 06:00:00 New York AM Session 06:00:00 - 06:22:30 06:22:30 - 06:45:00 06:45:00 - 07:07:30 07:07:30 - 07:30:00 07:30:00 - 07:52:30 (True Session Open) 07:52:30 - 08:15:00 08:15:00 - 08:37:30 08:37:30 - 09:00:00 09:00:00 - 09:22:30 09:22:30 - 09:45:00 09:45:00 - 10:07:30 10:07:30 - 10:30:00 10:30:00 - 10:52:30 10:52:30 - 11:15:00 11:15:00 - 11:37:30 11:37:30 - 12:00:00 New York PM Session 12:00:00 - 12:22:30 12:22:30 - 12:45:00 12:45:00 - 13:07:30 13:07:30 - 13:30:00 13:30:00 - 13:52:30 (True Session Open) 13:52:30 - 14:15:00 14:15:00 - 14:37:30 14:37:30 - 15:00:00 15:00:00 - 15:22:30 15:22:30 - 15:45:00 15:45:00 - 15:37:30 15:37:30 - 16:00:00 16:00:00 - 16:22:30 16:22:30 - 16:45:00 16:45:00 - 17:07:30 17:07:30 - 18:00:00 S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Индикатор Pine Script®
от dmaru1209
2
Quarterly Theory ICT 02 [TradingFinder] True Open Session 90 Min🔵 Introduction The Quarterly Theory ICT indicator is an advanced analytical system built on ICT (Inner Circle Trader) concepts and fractal time. It divides time into four quarters (Q1, Q2, Q3, Q4), and is designed based on the consistent repetition of these phases across all trading timeframes (annual, monthly, weekly, daily, and even shorter trading sessions). Each cycle consists of four distinct phases: the first phase (Q1) is the Accumulation phase, characterized by price consolidation; the second phase (Q2), known as Manipulation or Judas Swing, is marked by initial false movements indicating a potential shift; the third phase (Q3) is Distribution, where price volatility peaks; and the fourth phase (Q4) is Continuation/Reversal, determining whether the previous trend continues or reverses. 🔵 How to Use The central concept of this strategy is the "True Open," which refers to the actual starting point of each time cycle. The True Open is typically defined at the beginning of the second phase (Q2) of each cycle. Prices trading above or below the True Open serve as a benchmark for predicting the market's potential direction and guiding trading decisions. The practical application of the Quarterly Theory strategy relies on accurately identifying True Open points across various timeframes. True Open points are defined as follows : Yearly Cycle : Q1: January, February, March Q2: April, May, June (True Open: April Monthly Open) Q3: July, August, September Q4: October, November, December Monthly Cycle : Q1: First Monday of the month Q2: Second Monday of the month (True Open: Daily Candle Open price on the second Monday) Q3: Third Monday of the month Q4: Fourth Monday of the month Weekly Cycle : Q1: Monday Q2: Tuesday (True Open: Daily Candle Open Price on Tuesday) Q3: Wednesday Q4: Thursday Daily Cycle : Q1: 18:00 - 00:00 (Asian session) Q2: 00:00 - 06:00 (True Open: Start of London Session) Q3: 06:00 - 12:00 (NY AM) Q4: 12:00 - 18:00 (NY PM) 90 Min Asian Session : Q1: 18:00 - 19:30 Q2: 19:30 - 21:00 (True Open at 19:30) Q3: 21:00 - 22:30 Q4: 22:30 - 00:00 90 Min London Session : Q1: 00:00 - 01:30 Q2: 01:30 - 03:00 (True Open at 01:30) Q3: 03:00 - 04:30 Q4: 04:30 - 06:00 90 Min New York AM Session : Q1: 06:00 - 07:30 Q2: 07:30 - 09:00 (True Open at 07:30) Q3: 09:00 - 10:30 Q4: 10:30 - 12:00 90 Min New York PM Session : Q1: 12:00 - 13:30 Q2: 13:30 - 15:00 (True Open at 13:30) Q3: 15:00 - 16:30 Q4: 16:30 - 18:00 Micro Cycle (22.5-Minute Quarters) : Each 90-minute quarter is further divided into four 22.5-minute sub-segments (Micro Sessions). True Opens in these sessions are defined as follows : Asian Micro Session : True Session Open : 19:30 - 19:52:30 London Micro Session : T rue Session Open : 01:30 - 01:52:30 New York AM Micro Session : True Session Open : 07:30 - 07:52:30 New York PM Micro Session : True Session Open : 13:30 - 13:52:30 By accurately identifying these True Open points across various timeframes, traders can effectively forecast the market direction, analyze price movements in detail, and optimize their trading positions. Prices trading above or below these key levels serve as critical benchmarks for determining market direction and making informed trading decisions. 🔵 Setting Show True Range : Enable or disable the display of the True Range on the chart, including the option to customize the color. Extend True Range Line : Choose how to extend the True Range line on the chart, with the following options: None: No line extension Right: Extend the line to the right Left: Extend the line to the left Both: Extend the line in both directions (left and right) Show Table : Determines whether the table—which summarizes the phases (Q1 to Q4)—is displayed. Show More Info : Adds additional details to the table, such as the name of the phase (Accumulation, Manipulation, Distribution, or Continuation/Reversal) or further specifics about each cycle. 🔵 Conclusion The Quarterly Theory ICT, by dividing time into four distinct quarters (Q1, Q2, Q3, and Q4) and emphasizing the concept of the True Open, provides a structured and repeatable framework for analyzing price action across multiple time frames. The consistent repetition of phases—Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal—allows traders to effectively identify recurring price patterns and critical market turning points. Utilizing the True Open as a benchmark, traders can more accurately determine potential directional bias, optimize trade entries and exits, and manage risk effectively. By incorporating principles of ICT (Inner Circle Trader) and fractal time, this strategy enhances market forecasting accuracy across annual, monthly, weekly, daily, and shorter trading sessions. This systematic approach helps traders gain deeper insight into market structure and confidently execute informed trading decisions.
Индикатор Pine Script®
от TFlab
4
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
Индикатор Pine Script®
от Fractalyst