Martingale — Penunjuk dan Strategi

martingle trading bot ⚙️ Martingle Trading Bot — Complete Description The Martingle Trading Bot is a fully automated volatility-band visualization system that demonstrates the principles of breakout-based market logic combined with martingale-style position scaling. It is designed purely for educational, analytical, and backtesting visualization purposes on TradingView. This tool shows how a simple mathematical band system can be used to define intraday breakout regions, evaluate sequential trade logic, and visualize how martingale-style compounding affects a trade sequence when price fluctuates around daily reference levels. 🧠 Conceptual Overview The system works on a simple yet powerful market observation: markets oscillate within short-term ranges and occasionally break out beyond expected volatility envelopes. To capture and visualize these events, the Martingle Trading Bot uses a daily reset mechanism that defines a reference price, builds trading bands around it, and triggers theoretical buy/sell signals when price exceeds certain thresholds. 📅 1️⃣ Daily Reference Price (Central Core) Every trading day begins with a reference price — typically the daily open. This reference acts as the neutral center for the system’s calculations. The indicator resets this reference daily and adjusts when target zones are hit, maintaining realistic adaptive logic. 📊 2️⃣ Dynamic Bands and Target Zones From the reference price, the indicator constructs two key structures: - Primary Band Range – defines the immediate trading zone using the “band range.” - Target Band Range – extends beyond the primary band to define logical take-profit zones. Price action beyond these regions indicates directional expansion and potential breakout strength. 📈 3️⃣ Breakout Logic (Trade Signal Simulation) - When price crosses the upper band → bullish breakout condition. - When price crosses the lower band → bearish breakout condition. Each breakout is visualized on the chart and represents a theoretical position change. 🧮 4️⃣ Martingale Position Scaling When a breakout occurs against the prior position, the system multiplies or increments position size based on user-defined settings. This models martingale-style compounding and resets when a target is reached. It helps illustrate how scaling affects drawdown and recovery potential. 💹 5️⃣ Virtual PnL Tracking The indicator keeps virtual stats of profit/loss, win rate, and trade count. These metrics are illustrative only — no live or guaranteed results are implied. 🧭 6️⃣ Visual Chart Elements Buy/Sell labels, take-profit labels, quantities, and color-coded zones appear on the chart to clearly display trade logic and band structure. ⚙️ 7️⃣ User Inputs - Band Range - Target Distance - Initial Quantity - Martingle Quantity - Gap Detection Point - Label Display Toggles - Optional end-of-day reset 🧩 8️⃣ Use Cases Ideal for traders, developers, and educators who want to study breakout systems, risk progression, and position scaling. ⚠️ 9️⃣ Risk Disclosure This is not a live trading bot. It does not execute trades or guarantee profit. Martingale logic carries significant risk — consecutive losses can exponentially increase exposure. Use for study purposes only. 📜 License and Credits Developed by @algo_coders. Licensed under the Mozilla Public License 2.0 (MPL 2.0). Uses internal bar-counting functions for session management. 🧠 Summary The Martingle Trading Bot combines volatility envelopes, daily resets, and martingale scaling to visualize compounding risk behavior. It is an educational research tool for understanding probability-based trading concepts — not financial advice or a trading signal provider.

Advanced Grid Trading System - [WOLONG X DBG]Overview This sophisticated grid trading system combines Bollinger Bands breakout analysis with RSI filtering to create a comprehensive automated trading approach. The system implements advanced grid management with dynamic lot sizing, intelligent ATR-based spacing, and comprehensive risk management features including drawdown protection, time-based trading controls, and multi-level position management. Methodology The indicator employs a multi-layered analytical approach based on established technical analysis principles: Core Signal Generation Bollinger Bands Breakout Engine: Utilizes customizable period Bollinger Bands (default 35) with highest/lowest price detection over the calculation period to identify potential reversal points when price breaks below recent lows or above recent highs RSI Confirmation Filter: Implements RSI-based signal filtering with customizable maximum RSI values to avoid entries during overbought/oversold conditions, requiring RSI below (50 - max_rsi_value) for buy signals and above (50 + max_rsi_value) for sell signals Grid Management System: Advanced progressive grid system with configurable pip-based spacing, intelligent ATR-based distance calculation, and cumulative lot sizing with customizable multipliers Advanced Features Dynamic Lot Sizing: Eight calculation methods including Fixed Lot, Dynamic by Balance/Equity, and risk-based percentage approaches (Low Risk 20%, Medium Risk 40%, High Risk 80%, Extreme Risk 120%, Margin Loading) Comprehensive Risk Management: Multi-layered drawdown protection with percentage and absolute value limits, automatic position closure options, and trading suspension features with time-based recovery Time-Based Controls: Configurable GMT-based trading hours with start/stop times for session-specific trading and market condition adaptation Key Components Signal Types Primary Entry Signals: Buy signals when price breaks below recent lowest values within Bollinger period with RSI confirmation; Sell signals when price breaks above recent highest values with RSI confirmation Grid Expansion Logic: Automatic additional entries based on configurable pip distances from base price, triggered when price moves against initial position by specified intervals Take Profit Systems: Dual-mode TP calculation using either weighted average across all positions or individual level TP with customizable pip values Stop Loss Protection: Grid-wide SL with customizable pip distances or default 1000-pip protection Visual Elements Bollinger Bands Display: Three-line Bollinger Bands system with upper, middle (SMA), and lower bands for trend and volatility analysis Grid Base Line: Yellow dashed line showing initial grid entry level with right extension for reference Comprehensive TP/SL Lines: Dual-line system showing both first order reference levels (dotted, light colors) and official Martingale weighted average levels (solid, bold colors) Entry Point Labels: Detailed entry markers showing BUY/SELL direction, grid level, and lot size information Dual Dashboard System: Main control panel (top-right) and dark theme entry log (bottom-right) with real-time status updates Usage Instructions Basic Configuration Capital Management: Select lot calculation method from dropdown (recommended: "Low Risk 20%" for conservative approach) Grid Parameters: Configure trading distance (default 35 pips) and enable smart distance for ATR-based dynamic adjustments Strategy Settings: Set Bollinger period (35), RSI period (20), and maximum RSI value (15) for signal filtering Risk Controls: Configure maximum drawdown percentage and action when limits are exceeded Signal Interpretation Buy Entry Conditions: Generated when current close price breaks below the lowest price in the Bollinger calculation period, with RSI below (50 - max_rsi_value) Sell Entry Conditions: Generated when current close price breaks above the highest price in the Bollinger calculation period, with RSI above (50 + max_rsi_value) Grid Expansion: Automatic additional entries when price moves against position by configured pip distances, with progressive lot sizing using multipliers Exit Conditions: Weighted average TP achievement, breakeven after specified grid levels, or manual cycle completion Dashboard Analysis Main Control Panel: Displays current grid level, trading direction, open orders count, total volume, next lot size, grid P&L, current balance, floating drawdown, RSI status, trading hours, and system locks Dark Theme Entry Log: Shows recent entry history with timestamps, entry types (BUY/SELL), prices, lot sizes, and grid levels for trade tracking Risk Monitoring: Real-time drawdown tracking with color-coded warnings and automatic protection activation Risk Management Features Automatic Protections Drawdown Limits: Configurable percentage (default 100%) and absolute USD drawdown limits with four response options: Close Orders and Stop 24h/Until Restart, or Prevent New Grid/Until Restart Position Sizing: Eight dynamic lot calculation methods based on account equity, balance, or risk tolerance with maximum lot size limits Grid Limitations: Maximum number of grid levels (default 9) to prevent excessive exposure accumulation Time Controls: GMT-based trading hour restrictions to avoid high-volatility periods or specific market sessions Confirmation Requirements Multi-Indicator Alignment: Requires both Bollinger Bands breakout and RSI confirmation before signal generation Intelligent Spacing: ATR-based grid spacing adjustment using short-term (96-period) vs long-term (672-period) ATR ratio for market volatility adaptation Progressive Sizing: Configurable lot multipliers for different grid levels (Order 2: 1.0x, Orders 3-5: 2.0x, Orders 6+: 1.5x default) Optimal Settings Timeframe Recommendations Scalping: 1M-5M charts with reduced grid spacing (20-25 pips) and tighter RSI filters Day Trading: 15M-1H charts with standard settings (35 pips) and default RSI parameters Swing Trading: 4H-Daily charts with increased spacing (50+ pips) and relaxed RSI filters Market Conditions Trending Markets: Reduce RSI maximum value to 10-12, increase grid spacing to 40-50 pips, enable breakeven functionality Ranging Markets: Standard settings with weighted TP enabled and moderate grid spacing High Volatility: Enable smart distance, reduce maximum grid levels to 6-7, increase drawdown limits Advanced Features Customization Options Lot Calculation Methods: Eight different approaches from fixed lot (0.01) to risk-based percentage calculations with margin loading options Grid Multipliers: Separate multiplier settings for different grid levels (2nd order, 3rd-5th orders, 6th+ orders) with decimal precision TP/SL Configuration: Individual or weighted average TP calculation with positive/negative pip values, breakeven after specified levels Visual Controls: Toggle options for dashboard display, entry labels, TP/SL lines, lot information, and dark theme components Technical Specifications Grid Management: Up to 50 configurable grid levels with progressive lot sizing and cumulative position tracking Risk Controls: Dual drawdown limits (percentage and absolute) with four different response actions and time-based recovery Time Management: GMT-based trading hours with flexible start/end times supporting overnight sessions Alert System: Five comprehensive alert conditions for new signals, drawdown warnings, maximum levels, and cycle completion Important Limitations Lagging Nature: Signals may appear after optimal entry points due to confirmation requirements and breakout validation Grid Risk: Progressive lot sizing can lead to significant exposure accumulation during extended adverse price movements Market Dependency: Performance varies significantly between trending and ranging market conditions, requiring parameter adjustments Computational Load: Complex multi-array calculations and real-time dashboard updates may impact performance on slower devices No Guarantee: All signals are suggestions based on technical analysis calculations and may be incorrect Educational Disclaimers This indicator is designed for educational and analytical purposes only. It represents a technical analysis tool based on mathematical calculations of historical price data and should not be considered as financial advice or trading recommendations. Risk Warning: Grid trading involves substantial risk of loss and is not suitable for all investors. The progressive lot sizing methodology can lead to significant exposure accumulation during adverse market movements. Past performance of any trading system or methodology is not necessarily indicative of future results. Important Notes: Always conduct your own analysis before making trading decisions Use appropriate position sizing and risk management strategies Never risk more than you can afford to lose Consider your investment objectives, experience level, and risk tolerance Seek advice from qualified financial professionals when needed Grid trading can result in multiple simultaneous positions with compounding risk exposure Performance Disclaimer: Backtesting results do not guarantee future performance. Market conditions change constantly, and what worked in the past may not work in the future. The indicator's mathematical calculations are based on historical data patterns that may not repeat. Always paper trade new strategies before risking real capital. System Limitations: The indicator relies on technical analysis principles and may produce false signals during unusual market conditions, news events, or periods of extreme volatility. Users should implement additional confirmation methods and maintain strict risk management protocols.

Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator Purpose This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns. What a martingale is A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged: Lose one leg → increase next position size Lose again → increase again Win → reset to the base size The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops. What it plots Equity – simulated portfolio equity including compounding Buy & Hold – equity from holding the chart symbol for context Optional helpers – last trade outcome, current streak length, current allocation fraction Optional diagnostics – daily portfolio return, rolling drawdown, metrics table Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands Model assumptions Bar-close execution with no slippage or commissions Shorting allowed and frictionless No margin interest, borrow fees, or position limits No intrabar moves or gaps within a bar (returns are close-to-close) Sizing applies to equity fraction only and is capped by your setting All results are hypothetical and for education only. How the simulator applies it 1) Directional signal You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts. 2) Sizing after losses and wins Position size is a fraction of equity: Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double Reset after win – return to the initial allocation Max allocation cap – hard ceiling to prevent runaway growth At a high level the size after k consecutive losses is alloc(k) = min( cap , base × factor^k ) . In practice the simulator changes size only when a leg ends and its PnL is known. 3) Equity update Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds: eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) . This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled. Why traders experiment with martingale sizing Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live Why martingale is dangerous Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic: Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N. Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible. No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels. Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest. Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs. Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected. The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty. Interpreting losing streaks with numbers A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check: If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare. If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap. This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests.. Using the simulator productively Parameter studies Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond. Initial allocation – lower base reduces volatility and drawdowns across the board Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive Max cap – the most important brake; many users keep it between 20 and 50 percent Signal selection Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each. Diagnostics to watch Use the built-in metrics to quantify risk: Max Drawdown – worst peak-to-trough equity loss Sharpe and Sortino – volatility and downside-adjusted return VaR 95 percent and CVaR – tail risk measures from the realized distribution Alpha and Beta – relationship to your chosen benchmark If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see Monte Carlo exploration When enabled, the forecast draws many synthetic paths from your realized daily returns: Choose a horizon and a number of runs Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path Use the table to read the expected return over the horizon and the tail outcomes Remember it is a sketch based on your recent distribution, not a predictor Concrete examples Example A: Modest martingale Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing. Example B: Aggressive martingale Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk. Strengths Bar-by-bar, transparent computation of equity from stance and size Explicit handling of wins, losses, streaks, and caps Portable signal inputs so you can A–B test ideas quickly Risk diagnostics and forward uncertainty visualization in one place Example, Rolling Max Drawdown Limitations and important notes Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs. No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled. Signals are evaluated on closes. Real execution and fills will differ. Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes. All results are hypothetical. Use this as an educational tool, not a production risk engine. Practical tips Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples. Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg. Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear. Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off. If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop. Settings recap Backtest start date and initial capital Initial allocation, increase-after-loss factor, max allocation cap Signal source selector Trading days per year and risk-free rate Benchmark symbol for Alpha and Beta UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown Monte Carlo controls for enable, runs, horizon, and result table Final thoughts A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.

EMA Grid + Martingale Indicator (Long-Only)Title: EMA Grid + Martingale Indicator (Long-Only) Short Summary: A 4-EMA trend filter combined with a grid-based entry system and optional martingale sizing to visualize staged long entries and exits in bullish markets. Full Description: This indicator combines a 4-EMA trend filter with a grid-based entry system and optional martingale-style position sizing to help traders visualize staged long entries and exits in trending markets. How It Works 1. Trend Detection: Uses two sets of EMAs (fast/slow pairs) to confirm bullish momentum. A long signal is generated when both EMA groups align in an uptrend. 2. Grid Entries: After the initial long entry, additional grid levels are triggered every time price drops by the specified grid step (in pips). 3. Martingale Sizing (Optional): Each subsequent entry can increase in size based on the defined martingale factor. 4. Weighted-Average Exit: Calculates the weighted average of all grid entries and signals an exit when the price reaches or surpasses this level plus an optional buffer. Key Features • 4 EMA Trend Filter with fully customizable lengths. • Dynamic grid entries with visual labels (L1, L2, etc.). • Optional martingale position sizing. • Weighted-average exit with adjustable buffer. • Customizable parameters for EMAs, grid steps, max entries, and buffer pips. • Clear chart visualization of EMAs and entry/exit levels. Use Cases • For traders using cost-averaging or grid strategies in bullish markets. • Visualizes multiple entry levels and profit targets. • Useful for backtesting and strategy planning. Note: This indicator is for visualization and planning purposes only. It does not execute trades automatically. It does not guarantee profits and is not financial advice.

Buysell Martingale Signal - Custom Buysell Martingale Signal - Custom Indicator Introduction: This indicator provides a dynamic buy and sell signal system incorporating an adaptive Martingale logic. Built upon the signalLib_yashgode9/2 library, it is designed for use across various markets and timeframes. Key Features: Primary Buy & Sell Signals: Identifies initial buy and sell opportunities based on directional changes derived from the signalLib. Martingale Signals: For Short (Sell) Positions: A Martingale Sell signal is triggered when the price moves against the existing short position by a specified stepPercent from the last entry price, indicating a potential opportunity to average down or increase position size. For Long (Buy) Positions: Similarly, a Martingale Buy signal is triggered when the price moves against the existing long position by a stepPercent from the last entry price. On-Chart Labels: Displays clear, customizable labels on the chart for primary Buy, Sell, Martingale Buy, and Martingale Sell signals. Customizable Colors: Allows users to set distinct colors for primary signals and Martingale signals for better visual distinction. Adjustable Sensitivity: Features configurable parameters (DEPTH_ENGINE, DEVIATION_ENGINE, BACKSTEP_ENGINE) to fine-tune the sensitivity of the underlying signal generation. Webhook Support (Static Message Alerts): This indicator provides alerts with static messages for both primary and Martingale buy/sell signals. These alerts can be leveraged for automation by external systems (such as trading bots or exchange-provided Webhook Signal Trading services). Important Note: When using these alerts for automation, an external system is required to handle the complex Martingale logic and position management (e.g., tracking steps, PnL calculation, hedging, dynamic quantity sizing), as this indicator solely focuses on signal generation and sending predefined messages. How to Use: Add the indicator to your desired chart. Adjust the input parameters in the indicator's settings to match your specific trading symbol and timeframe. For automation, you can set up TradingView alerts for the Buy Signal (Main/Martingale) and Sell Signal (Main/Martingale) conditions, pointing them to your preferred Webhook URL. Configurable Parameters: DEPTH_ENGINE: (e.g., 30) Controls the depth of analysis for the signal algorithm. DEVIATION_ENGINE: (e.g., 5) Defines the allowable deviation for signal generation. BACKSTEP_ENGINE: (e.g., 5) Specifies the number of historical bars to look back. Martingale Step Percent: (e.g., 0.5) The percentage price movement against the current position that triggers a Martingale signal. Labels Transparency: Adjusts the transparency of the on-chart signal labels. Buy-Color / Sell-Color: Sets the color for primary Buy and Sell signal labels. Martingale Buy-Color / Martingale Sell-Color: Sets the color for Martingale Buy and Sell signal labels. Label size: Controls the visual size of the labels. Label Offset: Adjusts the vertical offset of the labels from the candlesticks. Risk Warning: Financial trading inherently carries significant risk. Martingale strategies are particularly high-risk and can lead to substantial losses or even complete liquidation of capital if the market moves strongly and persistently against your position. Always backtest thoroughly and practice with a demo account, fully understanding the associated risks, before engaging with real capital.

Alferow_pnl_up_short This script allows you to determine the leverage required to enter one position based on the set entry price, the price of the expected take profit, stop loss and risk per transaction. It also allows you to schedule this transaction for 5 possible transactions, with different shoulders and a martingale coefficient for each subsequent gain at the same risk, allowing you to qualitatively improve the pnl of the transaction with price fluctuations after entering the transaction. The script is designed for short positions.

Alferow_pnl_up_long This script allows you to determine the leverage required to enter one position based on the set entry price, the price of the expected take profit, stop loss and risk per transaction. It also allows you to schedule this transaction for 5 possible transactions, with different shoulders and a martingale coefficient for each subsequent gain at the same risk, allowing you to qualitatively improve the pnl of the transaction with price fluctuations after entering the transaction. The script is designed for long positions.

Martingale Template A template example on how to apply the famous Martingale gambling strategy. When your strategy gets an exit signal for your long position that leaves you without profit, you re-enter on the next entry long condition with double the capital of the previous amount entered with. You keep doubling the amount of capital entered with until you finally exit with a profit. If the strategy isn't sound enough then it could take several attempts and it can take only as much as a dozen tries to eat away at all your capital as the capital required to double on the next entry increases greatly over time by consecutive products of 2. The strategy used is just a simple moving average crossover, above the moving average is going long, below the moving average is going short. It can be replaced with whatever strategy that you want. The colored vertical bars show long and short positions and exits. The default option on the tick box under the settings show the number of attempts at entering before finally exiting with a profit, the other option shows the amount of capital it took starting from 1.

MMP Indicator 4-step Weekly Fading levels using martingale (limit orders, rebate venue) with no stop-loss orders, long the wings at the end of Support and Resist levels from prior week Friday right before the close. Re-hedge the order book units when there is a breakout.

SMA Stochastic Forecast This tool uses a discrete-time non-Markovian Martingale stochastic process (Please do not confuse with the strategy of the same name) under the hood to forecast a future (up to 28 bars, customizable) behaviour of the Simple Moving Average. The longer the average period, the more accurate the forecast. The common cases are the next: You can apply two instances of this indicator to your chart to obtain a crossover forecast You can decrease an interval between forecasts to obtain a bunch of possible traectories Decreasing a forecast interval for two instances, you will get the Kraken This is the further improvement of my research work on forecasting Mr. @syrinxflunki was the only one who provided a clear and useful feedback after testing, so he get a free lifetime access. I respect a fair play. If you have any questions you can concat me via private messages. Good luck.