HMA Buy Sell Signals - Profit ManagerNote : Settings should be adjusted according to the selected time frame. Try to find the best setting according to the profitability rate
Overall Functionality
This script combines several trading tools to create a comprehensive system for trend analysis, trade execution, and performance tracking. Users can identify market trends using specific moving averages and RSI indicators while managing profit and loss levels automatically.
Trend Detection and Trade Signals
Hull Moving Averages (HMA):
Two HMAs (a faster one and a slower one) are used to determine the market trend.
A buy signal is generated when the faster HMA crosses above the slower HMA.
Conversely, a sell signal is triggered when the faster HMA crosses below the slower one.
Visual Feedback:
Trend lines on the chart change color to reflect the trend direction (e.g., green for upward trends and red for downward trends).
Trade Levels and Management
Entry, Take-Profit, and Stop-Loss Levels:
When the trend shifts upwards, the script calculates entry, take-profit, and stop-loss levels based on the opening price.
Similarly, for downward trends, these levels are determined for short trades.
Commission Tracking:
Each trade includes a commission cost, which is factored into net profit and loss calculations.
Dynamic Labels:
Entry, take-profit, and stop-loss levels are visually marked on the chart for easier tracking.
Performance Tracking
Profit and Loss Tracking:
The script keeps a running total of profits, losses, and commissions for both long and short trades.
It also calculates the net profit after all costs are considered.
Performance Table:
A table is displayed on the chart summarizing:
The number of trades.
Total profit and loss for long and short positions.
Commission costs.
Net profit.
Fractal Support and Resistance
Dynamic Lines:
The script identifies the most recent significant highs and lows using fractals.
It draws support and resistance lines that automatically update as new fractals form.
Simplified Visuals:
The chart always shows the last two support and resistance lines, keeping the visualization clean and focused.
RSI-Based Signals
Overbought and Oversold Levels:
RSI is used to identify overbought (above 80) and oversold (below 20) conditions.
The script generates buy signals at oversold levels and sell signals at overbought levels.
Chart Indicators:
Arrows and labels appear on the chart to highlight these RSI-based opportunities.
Customization
The script allows users to customize key parameters such as:
Moving average lengths for trend detection.
Take-profit and stop-loss percentages.
Timeframes for backtesting.
Starting capital and commission rates.
Conclusion
This script is a versatile tool for traders, combining trend detection, automated trade management, and visual feedback. It simplifies decision-making by providing clear signals and tracking performance metrics, making it suitable for both beginners and experienced traders.
* The most recently drawn fractals represent potential support and resistance levels. If the price aligns with these levels at the time of entering a trade, it may indicate a likelihood of reversal. In such cases, it’s advisable to either avoid entering the trade altogether or proceed with increased caution.
Cari dalam skrip untuk "stop loss"
Gold Trade Setup Strategy
Title: Profitable Gold Setup Strategy with Adaptive Moving Average & Supertrend
Introduction:
This trading strategy for Gold (XAU/USD) combines the Adaptive Moving Average (AMA) and Supertrend, tailored for high-probability setups during specific trading hours. The AMA identifies the trend, while the Supertrend confirms entry and exit points. The strategy is optimized for swing and intraday traders looking to capitalize on Gold’s price movements with precise trade timing.
Strategy Components:
1. Adaptive Moving Average (AMA):
• Reacts dynamically to market conditions, filtering noise in choppy markets.
• Serves as the primary trend indicator.
2. Supertrend:
• Confirms entry signals with clear buy and sell levels.
• Acts as a trailing stop-loss to protect profits.
Trading Rules:
Trading Hours:
• Only take trades between 8:30 AM and 10:30 PM IST.
• Avoid trading outside these hours to reduce noise and low-volume setups.
Buy Setup:
1. Trend Confirmation: The Adaptive Moving Average (AMA) must be green.
2. Signal Confirmation: The Supertrend should turn green after the AMA is green.
3. Trigger: Take the trade when the high of the trigger candle (the candle that turned Supertrend green) is broken.
Sell Setup (Optional if included):
• Reverse the rules for a short trade: AMA and Supertrend should both indicate bearish conditions (red), and take the trade when the low of the trigger candle is broken.
Stop-Loss and Targets:
• Place the stop-loss at the low of the trigger candle for long trades.
• Set a 1:2 risk-reward ratio or use the Supertrend line as a trailing stop-loss.
Timeframes:
• Recommended timeframes: 1H, 4H, or Daily for swing trading.
• For intraday trading, use 15-minute or 30-minute charts.
Why This Strategy Works:
• Combines trend-following (AMA) with momentum-based entries (Supertrend).
• Focused trading hours filter out low-probability setups.
• Provides precise entry, stop-loss, and target levels for disciplined trading.
Conclusion:
This Gold Setup Strategy is designed for traders seeking a structured approach to trading Gold. Follow the rules strictly, backtest the strategy extensively, and share your results. Let’s master the Gold market together!
Tags: #Gold #XAUUSD #SwingTrading #Intraday #Supertrend #AMA #TechnicalAnalysis #GoldStrategy
IU open equal to high/low strategyIU open equal to high/low strategy:
The "IU Open Equal to High/Low Strategy" is designed to identify and trade specific market conditions where the day's first price action shows a strong directional bias. This strategy automatically enters trades based on the relationship between the market's open price and its first high or low of the day.
Entry Conditions:
1. Long Entry: A long position is initiated when the first open price of the session equals the day's first low. This signals a potential upward move.
2. Short Entry: A short position is initiated when the first open price of the session equals the day's first high. This signals a potential downward move.
Exit Conditions:
1. Stop Loss (SL): For both long and short trades, the stop loss is calculated based on the low or high of the candle where the position was entered.
2. Take Profit (TP): The take profit is set using a Risk-to-Reward (RTR) ratio, which is customizable by the user. The TP is calculated relative to the entry price and the distance between the entry and the stop loss.
Additional Features:
- Plots are used to visualize the entry price, stop loss, and take profit levels directly on the chart, providing clear and actionable insights.
- Labels are displayed to indicate the occurrence of the "Open == Low" or "Open == High" conditions for easier identification of potential trade setups.
- A dynamic fill highlights the areas between the entry price and the stop loss or take profit, offering a clear visual representation of the trade's risk and reward zones.
This strategy is designed for traders looking to capitalize on directional momentum at the start of the trading session. It is customizable, allowing users to set their desired Risk-to-Reward ratio and tailor the strategy to fit their trading style.
R-based Strategy Template [Daveatt]Have you ever wondered how to properly track your trading performance based on risk rather than just profits?
This template solves that problem by implementing R-multiple tracking directly in TradingView's strategy tester.
This script is a tool that you must update with your own trading entry logic.
Quick notes
Before we dive in, I want to be clear: this is a template focused on R-multiple calculation and visualization.
I'm using a basic RSI strategy with dummy values just to demonstrate how the R tracking works. The actual trading signals aren't important here - you should replace them with your own strategy logic.
R multiple logic
Let's talk about what R-multiple means in practice.
Think of R as your initial risk per trade.
For instance, if you have a $10,000 account and you're risking 1% per trade, your 1R would be $100.
A trade that makes twice your risk would be +2R ($200), while hitting your stop loss would be -1R (-$100).
This way of measuring makes it much easier to evaluate your strategy's performance regardless of account size.
Whenever the SL is hit, we lose -1R
Proof showing the strategy tester whenever the SL is hit: i.imgur.com
The magic happens in how we calculate position sizes.
The script automatically determines the right position size to risk exactly your specified percentage on each trade.
This is done through a simple but powerful calculation:
risk_amount = (strategy.equity * (risk_per_trade_percent / 100))
sl_distance = math.abs(entry_price - sl_price)
position_size = risk_amount / (sl_distance * syminfo.pointvalue)
Limitations with lower timeframe gaps
This ensures that if your stop loss gets hit, you'll lose exactly the amount you intended to risk. No more, no less.
Well, could be more or less actually ... let's assume you're trading futures on a 15-minute chart but in the 1-minute chart there is a gap ... then your 15 minute SL won't get filled and you'll likely to not lose exactly -1R
This is annoying but it can't be fixed - and that's how trading works anyway.
Features
The template gives you flexibility in how you set your stop losses. You can use fixed points, ATR-based stops, percentage-based stops, or even tick-based stops.
Regardless of which method you choose, the position sizing will automatically adjust to maintain your desired risk per trade.
To help you track performance, I've added a comprehensive statistics table in the top right corner of your chart.
It shows you everything you need to know about your strategy's performance in terms of R-multiples: how many R you've won or lost, your win rate, average R per trade, and even your longest winning and losing streaks.
Happy trading!
And remember, measuring your performance in R-multiples is one of the most classical ways to evaluate and improve your trading strategies.
Daveatt
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
MicuRobert EMA Cross StrategyThis is a repost of a old strategy that cant be updated anymore, it was a request for a user made in Oct, 6, 2015
Here's a possible engaging description for the tradingview script:
**MicuRobert EMA Cross V2: A Powerful Trading Strategy**
Join the ranks of successful traders with this advanced strategy, designed to help you profit from market trends. The MicuRobert EMA Cross V2 combines two essential indicators - Exponential Moving Average (EMA) and Divergence EMA (DEMA) - to generate buy and sell signals.
**Key Features:**
* **Trading Session Filter**: Only trade during your preferred session, ensuring you're in sync with market conditions.
* **Trailing Stop**: Automatically adjust stop-loss levels to lock in profits or limit losses.
* **Customizable Trade Size**: Set the size of each trade based on your risk tolerance and trading goals.
**How it Works:**
The script uses two EMAs (5-period and 34-period) to identify trends. When the shorter EMA crosses above the longer one, a buy signal is generated. Conversely, when the shorter EMA falls below the longer one, a sell signal is triggered. The strategy also incorporates divergence analysis between price action and the EMAs.
**Visual Aids:**
* **EMA Plots**: Visualize the two EMAs on your chart to gauge market momentum.
* **Buy/Sell Signals**: See when buy or sell signals are generated, along with their corresponding entry prices.
* **Trailing Stop Lines**: Monitor stop-loss levels as they adjust based on price action.
**Get Started:**
Download this script and start trading like a pro! With its robust features and customizable settings, the MicuRobert EMA Cross V2 is an excellent addition to any trader's arsenal.
~Llama3
Position Sizing Calculator (Real-Time)█ SUMMARY
The following indicator is a Position Sizing Calculator based on Average True Range (ATR), originally developed by market technician J. Welles Wilder Jr., intended for real-time trading.
This script utilizes the user's account size, acceptable risk percentage, and a stop-loss distance based on ATR to dynamically calculate the appropriate position size for each trade in real time.
█ BACKGROUND
Developed for use on the 5-minute timeframe, this script provides traders with continuously updated, dynamic position sizes. It enables traders to instantly determine the exact number of shares and dollar amount to use for entering a trade within their acceptable risk tolerance whenever a trade opportunity arises.
This real-time position sizing tool helps traders make well-informed decisions when planning trade entries and calculating maximum stop-loss levels, ultimately enhancing risk management.
█ USER INPUTS
Trading Account Size: Total dollar value of the user's trading account.
Acceptable Risk (%): Maximum percentage of the trading account that the user is willing to risk per trade.
ATR Multiplier for Stop-Loss: Multiplier used to determine the distance of the stop-loss from the current price, based on the ATR value.
ATR Length: The length of the lookback period used to calculate the ATR value.
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
ATT Model with Buy/Sell SignalsIndicator Summary
This indicator is based on the ATT (Arithmetic Time Theory) model, using specific turning points derived from the ATT sequence (3, 11, 17, 29, 41, 47, 53, 59) to identify potential market reversals. It also integrates the RSI (Relative Strength Index) to confirm overbought and oversold conditions, triggering buy and sell signals when conditions align with the ATT sequence and RSI level.
Turning Points: Detected based on the ATT sequence applied to bar count. This suggests high-probability areas where the market could turn.
RSI Filter: Adds strength to the signals by ensuring buy signals occur when RSI is oversold (<30) and sell signals when RSI is overbought (>70).
Max Signals Per Session: Limits signals to two per session to reduce over-trading.
Entry Criteria
Buy Signal: Enter a buy trade if:
The indicator displays a green "BUY" marker.
RSI is below the oversold level (default <30), suggesting a potential upward reversal.
Sell Signal: Enter a sell trade if:
The indicator displays a red "SELL" marker.
RSI is above the overbought level (default >70), indicating a potential downward reversal.
Exit Criteria
Take Profit (TP):
Define TP as a fixed percentage or point value based on the asset's volatility. For example, set TP at 1.5-2x the risk, or a predefined point target (like 50-100 points).
Alternatively, exit the position when price approaches a key support/resistance level or the next significant swing high/low.
Stop Loss (SL):
Place the SL below the recent low (for buys) or above the recent high (for sells).
Set a fixed SL in points or percentage based on the asset’s average movement range, like an ATR-based stop, or limit it to a specific risk amount per trade (1-2% of account).
Trailing into Profit
Use a trailing strategy to lock in profits and let winning trades run further. Two main options:
ATR Trailing Stop:
Set the trailing stop based on the ATR (Average True Range), adjusting every time a new candle closes. This can help in volatile markets by keeping the stop at a consistent distance based on recent price movement.
Break-Even and Partial Profits:
When the price moves in your favor by a set amount (e.g., 1:1 risk/reward), move SL to the entry (break-even).
Take partial profit at intermediate levels (e.g., 50% at 1:1 RR) and trail the remainder.
Risk Management for Prop Firm Evaluation
Prop firms often have strict rules on daily loss limits, max drawdowns, and minimum profit targets. Here’s how to align your strategy with these:
Limit Risk per Trade:
Keep risk per trade to a conservative level (e.g., 1% or lower of your account balance). This allows for more room in case of a drawdown and aligns with most prop firm requirements.
Daily Loss Limits:
Set a daily stop-loss that ensures you don’t exceed the firm’s rules. For example, if the daily limit is 5%, stop trading once you reach a 3-4% drawdown.
Avoid Over-Trading:
Stick to the max signals per session rule (one or two trades). Taking only high-probability setups reduces emotional and reactive trades, preserving capital.
Stick to a Profit Target:
Aim to meet the evaluation’s profit goal efficiently but avoid risky or oversized trades to reach it faster.
Avoid Major Economic Events:
News events can disrupt technical setups. Avoid trading around significant releases (like FOMC or NFP) to reduce the chance of sudden losses due to high volatility.
Summary
Using this strategy with discipline, a structured entry/exit approach, and tight risk management can maximize your chances of passing a prop firm evaluation. The ATT model’s turning points, combined with the RSI, provide an edge by highlighting reversal zones, while limiting trades to 1-2 per session helps maintain controlled risk.
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
Dynamic Trading Strategy with Key Levels, Entry/Exit ManagementThis indicator provides a complete rule-based trading system, combining key levels, entry conditions, stop loss (SL), and take profit (TP) management. It’s designed to dynamically adapt to market conditions by identifying crucial support and resistance zones, determining entry points based on price action and volume, and calculating risk-based exit targets.
Key Features
Key Level Identification:
The indicator automatically identifies support and resistance levels based on recent price highs and lows within a customizable lookback period.
It adds a dynamic buffer around these levels using the Average True Range (ATR) to account for market volatility, ensuring the zones adjust to changing conditions.
Entry Conditions:
Bullish Entry: Triggers near the support zone when there’s upward price action, confirmed by volume spikes and bullish candlestick patterns (e.g., hammers, engulfing candles).
Bearish Entry: Triggers near the resistance zone when signs of rejection appear, confirmed by volume spikes and bearish candlestick patterns (e.g., shooting stars, bearish engulfing).
Entry zones are highlighted visually on the chart using green (bullish) and red (bearish) shaded boxes.
Stop Loss (SL) and Take Profit (TP):
Stop Loss: Calculated based on ATR multipliers, allowing you to set a volatility-adjusted risk level beyond the entry range.
Take Profit: Includes two profit-taking levels (TP1 and TP2), allowing for partial position exits. TP levels are calculated based on a reward-to-risk ratio, ensuring consistent profitability targets.
SL and TP levels are clearly marked with horizontal lines and labeled as SL, TP1, and TP2, helping you manage trade exits effectively.
Market Context Adaptability:
The indicator adapts to both trending and ranging market conditions. In trending markets, it favors trades that follow the trend, while in ranging markets, it focuses on reversals within the range boundaries.
Visual Aids:
Entry zones are highlighted with shaded boxes to indicate potential buy/sell regions.
SL, TP1, and TP2 levels are clearly drawn with labels, allowing for easy identification of exit points.
How to Use
Identify Key Levels: Look for support and resistance zones highlighted by the indicator on your chart.
Wait for Entry Conditions: When the price enters the entry range (marked by green or red boxes), wait for confirmation signals—such as volume spikes and candlestick patterns.
Manage Exits: Use the SL, TP1, and TP2 levels for structured trade management. Consider scaling out partially at TP1 and exiting fully at TP2.
Ideal For:
This indicator is suitable for traders who prefer a systematic approach to trading, with clear entry and exit rules. It is particularly helpful for those looking to balance risk and reward with well-defined take profit and stop loss levels.
Stoch RSI and RSI Buy/Sell Signals with MACD Trend FilterDescription of the Indicator
This Pine Script is designed to provide traders with buy and sell signals based on the combination of Stochastic RSI, RSI, and MACD indicators, enhanced by the confirmation of candle colors. The primary goal is to facilitate informed trading decisions in various market conditions by utilizing different indicators and their interactions. The script allows customization of various parameters, providing flexibility for traders to adapt it to their specific trading styles.
Usefulness
This indicator is not just a mashup of existing indicators; it integrates the functionality of multiple momentum and trend-detection methods into a cohesive trading tool. The combination of Stochastic RSI, RSI, and MACD offers a well-rounded approach to analyzing market conditions, allowing traders to identify entry and exit points effectively. The inclusion of color-coded signals (strong vs. weak) further enhances its utility by providing visual cues about the strength of the signals.
How to Use This Indicator
Input Settings: Adjust the parameters for the Stochastic RSI, RSI, and MACD to fit your trading style. Set the overbought/oversold levels according to your risk tolerance.
Signal Colors:
Strong Buy Signal: Indicated by a green label and confirmed by a green candle (close > open).
Weak Buy Signal: Indicated by a blue label and confirmed by a green candle (close > open).
Strong Sell Signal: Indicated by a red label and confirmed by a red candle (close < open).
Weak Sell Signal: Indicated by an orange label and confirmed by a red candle (close < open).
Example Trading Strategy Using This Indicator
To effectively use this indicator as part of your trading strategy, follow these detailed steps:
Setup:
Timeframe : Select a timeframe that aligns with your trading style (e.g., 15-minute for intraday, 1-hour for swing trading, or daily for longer-term positions).
Indicator Settings : Customize the Stochastic RSI, RSI, and MACD parameters to suit your trading approach. Adjust overbought/oversold levels to match your risk tolerance.
Strategy:
1. Strong Buy Entry Criteria :
Wait for a strong buy signal (green label) when the RSI is at or below the oversold level (e.g., ≤ 35), indicating a deeply oversold market. Confirm that the MACD shows a decreasing trend (bearish momentum weakening) to validate a potential reversal. Ensure the current candle is green (close > open) if candle color confirmation is enabled.
Example Use : On a 1-hour chart, if the RSI drops below 35, MACD shows three consecutive bars of decreasing negative momentum, and a green candle forms, enter a buy position. This setup signals a robust entry with strong momentum backing it.
2. Weak Buy Entry Criteria :
Monitor for weak buy signals (blue label) when RSI is above the oversold level but still below the neutral (e.g., between 36 and 50). This indicates a market recovering from an oversold state but not fully reversing yet. These signals can be used for early entries with additional confirmations, such as support levels or higher timeframe trends.
Example Use : On the same 1-hour chart, if RSI is at 45, the MACD shows momentum stabilizing (not necessarily negative), and a green candle appears, consider a partial or cautious entry. Use this as an early warning for a potential bullish move, especially when higher timeframe indicators align.
3. Strong Sell Entry Criteria :
Look for a strong sell signal (red label) when RSI is at or above the overbought level (e.g., ≥ 65), signaling a strong overbought condition. The MACD should show three consecutive bars of increasing positive momentum to indicate that the bullish trend is weakening. Ensure the current candle is red (close < open) if candle color confirmation is enabled.
Example Use : If RSI reaches 70, MACD shows increasing momentum that starts to level off, and a red candle forms on a 1-hour chart, initiate a short position with a stop loss set above recent resistance. This is a high-confidence signal for potential price reversal or pullback.
4. Weak Sell Entry Criteria :
Use weak sell signals (orange label) when RSI is between the neutral and overbought levels (e.g., between 50 and 64). These can indicate potential short opportunities that might not yet be fully mature but are worth monitoring. Look for other confirmations like resistance levels or trendline touches to strengthen the signal.
Example Use : If RSI reads 60 on a 1-hour chart, and the MACD shows slight positive momentum with signs of slowing down, place a cautious sell position or scale out of existing long positions. This setup allows you to prepare for a possible downtrend.
Trade Management:
Stop Loss : For buy trades, place stop losses below recent swing lows. For sell trades, set stops above recent swing highs to manage risk effectively.
Take Profit : Target nearby resistance or support levels, apply risk-to-reward ratios (e.g., 1:2), or use trailing stops to lock in profits as price moves in your favor.
Confirmation : Align these signals with broader trends on higher timeframes. For example, if you receive a weak buy signal on a 15-minute chart, check the 1-hour or daily chart to ensure the overall trend is not bearish.
Real-World Example: Imagine trading on a 15-minute chart :
For a buy:
A strong buy signal (green) appears when the RSI dips to 32, MACD shows declining bearish momentum, and a green candle forms. Enter a buy position with a stop loss below the most recent support level.
Alternatively, a weak buy signal (blue) appears when RSI is at 47. Use this as a signal to start monitoring the market closely or enter a smaller position if other indicators (like support and volume analysis) align.
For a sell:
A strong sell signal (red) with RSI at 72 and a red candle signals to short with conviction. Place your stop loss just above the last peak.
A weak sell signal (orange) with RSI at 62 might prompt caution but can still be acted on if confirmed by declining volume or touching a resistance level.
These strategies show how to blend both strong and weak signals into your trading for more nuanced decision-making.
Technical Analysis of the Code
1. Stochastic RSI Calculation:
The script calculates the Stochastic RSI (stochRsiK) using the RSI as input and smooths it with a moving average (stochRsiD).
Code Explanation : ta.stoch(rsi, rsi, rsi, stochLength) computes the Stochastic RSI, and ta.sma(stochRsiK, stochSmoothing) applies smoothing.
2. RSI Calculation :
The RSI is computed over a user-defined period and checks for overbought or oversold conditions.
Code Explanation : rsi = ta.rsi(close, rsiLength) calculates RSI values.
3. MACD Trend Filter :
MACD is calculated with fast, slow, and signal lengths, identifying trends via three consecutive bars moving in the same direction.
Code Explanation : = ta.macd(close, macdLengthFast, macdLengthSlow, macdSignalLength) sets MACD values. Conditions like macdLine < macdLine confirm trends.
4. Buy and Sell Conditions :
The script checks Stochastic RSI, RSI, and MACD values to set buy/sell flags. Candle color filters further confirm valid entries.
Code Explanation : buyConditionMet and sellConditionMet logically check all conditions and toggles (enableStochCondition, enableRSICondition, etc.).
5. Signal Flags and Confirmation :
Flags track when conditions are met and ensure signals only appear on appropriate candle colors.
Code Explanation : Conditional blocks (if statements) update buyFlag and sellFlag.
6. Labels and Alerts :
The indicator plots "BUY" or "SELL" labels with the RSI value when signals trigger and sets alerts through alertcondition().
Code Explanation : label.new() displays the signal, color-coded for strength based on RSI.
NOTE : All strategies can be enabled or disabled in the settings, allowing traders to customize the indicator to their preferences and trading styles.
Trade Manager 2Hi Traders,
this manager will make it easier for you to enter lots into your trading platform. Just go to the indicator settings, set your trading account amount, RRR, % risk and then give ok. If you then know where you want to put the stop loss then reopen, enter the value and hit ok again. The chart will show you exactly the stop loss and take profit as you wanted. The stop loss will always stay where you enter it and the take profit will move with the lot size as the price goes further or closer to the stop loss.
This should help when entering the number of lots, TP, SL into the platform.
Price Action StrategyThe **Price Action Strategy** is a tool designed to capture potential market reversals by utilizing classic reversal candlestick patterns such as Hammer, Shooting Star, Doji, and Pin Bar near dinamic support and resistance levels.
***Note to moderators
- The moving average was removed from the strategy because it was not suitable for the strategy and not participating in the entry or exit criteria.
- The moving average length has been replaced/renamed by the support/resistance lenght.
- The bullish engulfing and bearish engulfing patterns were also removed because in practice they were not working as entry criteria, since the candle price invariably closes far from the support/resistance level even considering the sensitivity range. There was no change in the backtest results after removing these patterns.
### Key Elements of the Strategy
1. Support and Resistance Levels
- Support and resistance are pivotal price levels where the asset has previously struggled to move lower (support) or higher (resistance). These levels act as psychological barriers where buying interest (at support) or selling interest (at resistance) often increases, potentially causing price reversals.
- In this strategy, support is calculated as the lowest low and resistance as the highest high over a 16-period length. When the price nears these levels, it indicates possible zones for a reversal, and the strategy looks for specific candlestick patterns to confirm an entry.
2. Candlestick Patterns
- This strategy uses classic reversal patterns, including:
- **Hammer**: Indicates a buy signal, suggesting rejection of lower prices.
- **Shooting Star**: Suggests a sell signal, showing rejection of higher prices.
- **Doji**: Reflects indecision and potential reversal.
- **Pin Bar**: Represents price rejection with a long shadow, often signaling a reversal.
By combining these reversal patterns with the proximity to dinamic support or resistance levels, the strategy aims to capture potential reversal movements.
3. Sensitivity Level
- The sensitivity parameter adjusts the acceptable range (Default 0.018 = 1.8%) around support and resistance levels within which reversal patterns can trigger trades (i.e. the closing price of the candle must occur within the specified range defined by the sensitivity parameter). A higher sensitivity value expands this range, potentially leading to less accurate signals, as it may allow for more false positives.
4. Entry Criteria
- **Buy (Long)**: A Hammer, Doji, or Pin Bar pattern near support.
- **Sell (Short)**: A Shooting Star, Doji, or Pin Bar near resistance.
5. Exit criteria
- Take profit = 9.5%
- Stop loss = 16%
6. No Repainting
- The Price Action Strategy is not subject to repainting.
7. Position Sizing by Equity and risk management
- This strategy has a default configuration to operate with 35% of the equity. The stop loss is set to 16% from the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity and stop loss can be adjusted by the user according to their risk management.
8. Backtest results
- This strategy was subjected to deep backtest and operations in replay mode on **1000000MOGUSDT.P**, with the inclusion of transaction fees at 0.12% and slipagge of 5 ticks, and the past results have shown consistent profitability. Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
9. Chart Visualization
- Support and resistance levels are displayed as green (support) and red (resistance) lines.
- Only the candlestick pattern that generated the entry signal to triger the trade is identified and labeled on the chart. During the operation, the occurrence of new Doji, Pin Bar, Hammer and Shooting Star patterns will not be demonstrated on the chart, since the exit criteria are based on percentage take profit and stop loss.
Doji:
Pin Bar and Doji
Shooting Star and Doji
Hammer
10. Default settings
Chart timeframe: 20 min
Moving average lenght: 16
Sensitivity: 0.018
Stop loss (%): 16
Take Profit (%): 9.5
BYBIT:1000000MOGUSDT.P
The Exact IndicatorStruggling to get in on a trade? Don't know where to take profits? This indicator might help - it only displays the Buy, Stop Loss and Take profit points when certain conditions are met.
The indicator combines a moving average crossover strategy with trend analysis to identify potential buy opportunities in the market. It utilises a short-term and long-term Simple Moving Average (SMA) to generate buy signals when the short-term SMA crosses above the long-term SMA. Additionally, it displays take profit and stop loss levels, along with a background colour indicating the overall trend strength.
Pros :
Clear Signals : Provides straightforward buy signals based on a well-known crossover strategy, making it easy for traders to identify entry points.
Visual Aids : The inclusion of take profit and stop loss levels, along with background trend colors, enhances decision-making and risk management.
Trend Awareness : The background colour changes based on trend strength, allowing traders to quickly assess market conditions.
Cons :
Lagging Indicator : Moving averages are inherently lagging, which can result in delayed signals, especially in volatile markets.
False Signals : Crossover strategies can produce false signals during sideways or choppy market conditions, leading to potential losses.
Limited Scope : The indicator focuses primarily on buy signals, potentially missing out on other trading opportunities (like short-selling) in a bearish market.
Overall, while this indicator can be a useful tool for identifying bullish trends and potential entry points, traders should use it in conjunction with other analysis methods and risk management strategies to mitigate its limitations.
E9 Shark-32 Pattern Strategy The E9 Shark-32 Pattern is a powerful trading tool designed to capitalize on the Shark-32 pattern—a specific Candlestick pattern.
The Shark-32 Pattern: What Is It?
The Shark-32 pattern is a technical formation that occurs when the following conditions are met:
Higher Highs and Lower Lows: The low of two bars ago is lower than the previous bar, and the previous bar's low is lower than the current bar. At the same time, the high of two bars ago is higher than the previous bar, and the previous bar’s high is higher than the current bar.
This unique setup forms the "Shark-32" pattern, which signals potential volume squeezes and trend changes in the market.
How Does the Strategy Work?
The E9 Shark-32 Pattern Strategy builds upon this pattern by defining clear entry and exit rules based on the pattern's confirmation. Here's a breakdown of how the strategy operates:
1. Identifying the Shark-32 Pattern
When the Shark-32 pattern is confirmed, the strategy "locks" the high and low prices from the initial bar of the pattern. These locked prices serve as key levels for future trade entries and exits.
2. Entry Conditions
The strategy waits for the price to cross the pattern's locked high or low, signaling potential market direction.
Long Entry: A long trade is triggered when the closing price crosses above the locked pattern high (green line).
Short Entry: A short trade is triggered when the closing price crosses below the locked pattern low (red line).
The strategy ensures that only one trade is taken for each Shark-32 pattern, preventing overtrading and allowing traders to focus on high-probability setups.
3. Stop Loss and Take Profit Levels
The strategy has built-in risk management through stop-loss and take-profit levels, which are visually represented by the lines on the chart:
Stop Loss:
Stop loss can be adjusted in settings.
Take Profit:
For long trades: The take-profit target is set at the upper white dotted line, which is projected above the pattern high.
For short trades: The take-profit target is set at the lower white dotted line, which is projected below the pattern low.
These clearly defined levels help traders to manage risk effectively while maximizing potential returns.
4. Visual Cues
To make trading decisions even easier, the strategy provides helpful visual cues:
Green Line (Pattern High): This line represents the high of the Shark-32 pattern and serves as a resistance level and short entry signal.
Red Line (Pattern Low): This line represents the low of the Shark-32 pattern and serves as a support level and long entry signal.
White Dotted Lines: These lines represent potential profit targets, projected both above and below the pattern. They help traders define where the market might go next.
Additionally, the strategy highlights the pattern formation with color-coded bars and background shading to draw attention to the Shark-32 pattern when it is confirmed. This adds a layer of visual confirmation, making it easier to spot opportunities in real-time.
5. No Repeated Trades
An important aspect of the strategy is that once a trade is taken (either long or short), no additional trades are executed until a new Shark-32 pattern is identified. This ensures that only valid and confirmed setups are acted upon.
ATR+StdTR Band and Trailing StopThis Pine Script code plots the "ATR+StdTR Band and Trailing Stop," serving as a tool for volatility-based risk management and trend detection. While bands are typically set using a multiple of ATR, this script uses StdTR (the True Range standard deviation) and sets the band width based on ±(ATR + n times StdTR). StdTR is a great tool for detecting price volatility and anomalies, allowing traders to adapt to rapid changes in extreme market conditions. This helps traders proactively manage risk during sudden market fluctuations.
The following features are provided:
Table Display
A table is shown on the chart, allowing traders to visually track the current ATR value, StdTR (σ), and the long/short stop-loss levels (±ATR ± nσ). This enables real-time monitoring of risk management data.
Band Plots
The script plots bands that combine ATR with StdTR (nσ).
The upper and lower bands are calculated using the previous candle’s closing price (the source is customizable) and are plotted as ±(ATR + nσ), providing a clear visual of the price range.
ATR ± nσ Trailing Stop
The trailing stop dynamically adjusts the stop-loss levels based on price movements. In an uptrend, the stop-loss rises, while in a downtrend, it lowers, helping traders lock in profits while minimizing losses during significant reversals.
Breakout Detection
Breakouts are detected when the price exceeds the upper band or drops below the lower band. A visual marker (X) is displayed on the chart, allowing traders to quickly recognize when the price has moved beyond normal volatility ranges, making it easier to respond to trend formations or reversals.
Customization Points:
The ATR period and StdTR (n) are fully customizable.
The source for ATR band calculation can be adjusted, allowing traders to choose from close, open, high, low, etc.
The table’s display position and design (text color, size, etc.) can be customized to present the information clearly and effectively.
Descriptive Backtesting Framework (DBF)As the name suggests, this is a backtesting framework made to offer full backtesting functionality to any custom indicator in a visually descriptive way.
Any trade taken will be very clear to visualize on the chart and the equity line will be updated live allowing us to use the REPLAY feature to view the strategy performing in real time.
Stops and Targets will also get draw on the chart with labels and tooltips and there will be a table on the top right corner displaying lots of descriptive metrics to measure your strategy's performance.
IF YOU DECIDE TO USE THIS FRAMEWORK, PLEASE READ **EVERYTHING** BELOW
HOW TO USE IT
Step 1 - Insert Your Strategy Indicators:
Inside this framework's code, right at the beginning, you will find a dedicated section where you can manually insert any set of indicators you desire.
Just replace the example code in there with your own strategy indicators.
Step 2 - Specify The Conditions To Take Trades:
After that, there will be another section where you need to specify your strategy's conditions to enter and exit trades.
When met, those conditions will fire the trading signals to the trading engine inside the framework.
If you don't wish to use some of the available signals, please just assign false to the signal.
DO NOT DELETE THE SIGNAL VARIABLES
Step 3 - Specify Entry/Exit Prices, Stops & Targets:
Finally you'll reach the last section where you'll be able to specify entry/exit prices as well as add stops and targets.
On most cases, it's easier and more reliable to just use the close price to enter and exit trades.
If you decide to use the open price instead, please remember to change step 2 so that trades are taken on the open price of the next candle and not the present one to avoid the look ahead bias.
Stops and targets can be set in any way you want.
Also, please don't forget to update the spread. If your broker uses commissions instead of spreads or a combination of both, you'll need to manually incorporate those costs in this step.
And that's it! That's all you have to do.
Below this section you'll now see a sign warning you about not making any changes to the code below.
From here on, the framework will take care of executing the trades and calculating the performance metrics for you and making sure all calculations are consistent.
VISUAL FEATURES:
Price candles get painted according to the current trade.
They will be blue during long trades, purple on shorts and white when no trade is on.
When the framework receives the signals to start or close a trade, it will display those signals as shapes on the upper and lower limits of the chart:
DIAMOND: represents a signal to open a trade, the trade direction is represented by the shape's color;
CROSS: means a stop loss was triggered;
FLAG: means a take profit was triggered;
CIRCLE: means an exit trade signal was fired;
Hovering the mouse over the trade labels will reveal:
Asset Quantity;
Entry/Exit Prices;
Stops & Targets;
Trade Profit;
Profit As Percentage Of Trade Volume;
**Please note that there's a limit as to how many labels can be drawn on the chart at once.**
If you which to see labels from the beginning of the chart, you'll probably need to use the replay feature.
PERFORMANCE TABLE:
The performance table displays several performance metrics to evaluate the strategy.
All the performance metrics here are calculated by the framework. It does not uses the oficial pine script strategy tester.
All metrics are calculated in real time. If using the replay feature, they will be updated up to the last played bar.
Here are the available metrics and their definition:
INITIAL EQUITY: the initial amount of money we had when the strategy started, obviously...;
CURRENT EQUITY: the amount of money we have now. If using the replay feature, it will show the current equity up to the last bar played. The number on it's right side shows how many times our equity has been multiplied from it's initial value;
TRADE COUNT: how many trades were taken;
WIN COUNT: how many of those trades were wins. The percentage at the right side is the strategy WIN RATE;
AVG GAIN PER TRADE: the average percentage gain per trade. Very small values can indicate a fragile strategy that can behave in unexpected ways under high volatility conditions;
AVG GAIN PER WIN: the average percentage gain of trades that were profitable;
AVG GAIN PER LOSS: the average percentage loss on trades that were not profitable;
EQUITY MAX DD: the maximum drawdown experienced by our equity during the entire strategy backtest;
TRADE MAX DD: the maximum drawdown experienced by our equity after one single trade;
AVG MONTHLY RETURN: the compound monthly return that our strategy was able to create during the backtested period;
AVG ANNUAL RETURN: this is the strategy's CAGR (compound annual growth rate);
ELAPSED MONTHS: number of months since the backtest started;
RISK/REWARD RATIO: shows how profitable the strategy is for the amount of risk it takes. Values above 1 are very good (and rare). This is calculated as follows: (Avg Annual Return) / mod(Equity Max DD). Where mod() is the same as math.abs();
AVAILABLE SETTINGS:
SPREAD: specify your broker's asset spread
ENABLE LONGS / SHORTS: you can keep both enable or chose to take trades in only one direction
MINIMUM BARS CLOSED: to avoid trading before indicators such as a slow moving average have had time to populate, you can manually set the number of bars to wait before allowing trades.
INITIAL EQUITY: you can specify your starting equity
EXPOSURE: is the percentage of equity you wish to risk per trade. When using stops, the strategy will automatically calculate your position size to match the exposure with the stop distance. If you are not using stops then your trade volume will be the percentage of equity specified here. 100 means you'll enter trades with all your equity and 200 means you'll use a 2x leverage.
MAX LEVERAGE ALLOWED: In some situations a short stop distance can create huge levels of leverage. If you want to limit leverage to a maximum value you can set it here.
SEVERAL PLOTTING OPTIONS: You'll be able to specify which of the framework visuals you wish to see drawn on the chart.
FRAMEWORK **LIMITATIONS**:
When stop and target are both triggered in the same candle, this framework isn't able to enter faster timeframes to check which one was triggered first, so it will take the pessimistic assumption and annul the take profit signal;
This framework doesn't support pyramiding;
This framework doesn't support both long and short positions to be active at the same time. So for example, if a short signal is received while a long trade is open, the framework will close the long trade and then open a short trade;
FINAL CONSIDERATIONS:
I've been using this framework for a good time and I find it's better to use and easier to analyze a strategy's performance then relying on the oficial pine script strategy tester. However, I CANNOT GUARANTEE IT TO BE BUG FREE.
**PLEASE PERFORM A MANUAL BACKTEST BEFORE USING ANY STRATEGY WITH REAL MONEY**
Lot Size Calculator by MenolakRugiThe Lot Size Formula in forex trading is a critical tool that offers several key benefits to traders:
🟢Risk Management: By using the formula, traders can control the amount of capital they risk on each trade. This helps prevent excessive losses by aligning the lot size with a predefined risk tolerance, such as 1% or 2% of the account balance.
🟢Consistent Position Sizing: The formula ensures that position sizes are calculated based on the specific trade setup, including the distance to the stop loss. This consistency helps avoid over-leveraging and reduces the emotional aspect of trading.
🟢Adaptability: The lot size can be adjusted according to different currency pairs and market conditions. This flexibility ensures that traders can apply the formula across various trading instruments and environments.
🟢Improved Profit Potential: By managing risk effectively, traders can protect their capital while maximizing profit opportunities. When losses are controlled, traders are able to stay in the market longer and compound their gains over time.
🟢Precision in Trade Planning: Calculating the lot size allows traders to plan their trades more precisely, aligning their strategies with the amount they are willing to risk. This leads to more disciplined and structured trading, reducing impulsive decisions.
In summary, the lot size formula helps maintain a balanced approach to trading, where both risk and reward are carefully managed to increase the chances of long-term success.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
False Breakouts [TradingFinder] Fake Breakouts Failure🔵 Introduction
Technical indicators are essential tools for analysts and traders in financial markets, helping them predict price movements and make better trading decisions. One of the key concepts in technical analysis that should be carefully considered is the "False Breakout."
This phenomenon occurs when a price temporarily breaks through a significant support or resistance level but fails to hold and quickly returns to its previous range. Understanding this concept and applying it in trading can reduce risks and increase profitability.
🟣 What is a False Breakout?
A Fake Breakout, as the name suggests, refers to a breakout that appears to occur but fails to sustain, leading the price to quickly revert back to its previous range. This situation often happens when inexperienced or non-professional traders, under psychological pressure and eager to enter the market quickly, initiate trades.
This creates opportunities for professional traders to take advantage of these short-term fluctuations and execute successful trades.
🟣 The Importance of Recognizing False Breakouts
Recognizing False Breakouts is crucial for any trader aiming for success in financial markets. False Breakouts typically occur when the market approaches a critical support or resistance level.
In these situations, many traders are waiting to see if the price will break through this level. However, when the price quickly returns to its previous range, it indicates weakness in the movement and the inability to sustain the breakout.
🟣 How to identify False Breakouts?
To identify Fake Breakouts, it is important to carefully analyze price charts and look for signs of a quick price reversal after breaking a key level.
Here are some chart patterns that may help you identify a False Breakout :
1. Pin Bar Pattern : The Pin Bar is a candlestick pattern that indicates a price reversal. This pattern usually appears near support and resistance levels, showing that the price attempted to break through a key level but failed and reversed.
2. Fakey Pattern : This pattern, which consists of several candlesticks, indicates a False Breakout and a quick price return to the previous range. It usually appears near key levels and can signal a trend reversal.
3. Using Multiple Timeframes : One way to identify False Breakouts is by using charts of different timeframes. Sometimes, a breakout on a one-hour chart may be a False Breakout on a daily chart. Analyzing charts across multiple timeframes can help you accurately identify this phenomenon.
🔵 How to Use
Once you identify a False Breakout, you can use it as a trading signal. For this, it is best to look for trading opportunities in the opposite direction of the False Breakout. In other words, if a False Breakout occurs at a resistance level, you might consider selling opportunities, and if it happens at a support level, you might look for buying opportunities.
Here are some key points for trading based on False Breakouts :
1. Patience and Discipline : Patience and discipline are crucial when trading with False Breakouts. Wait for the False Breakout to clearly form before entering a trade.
2. Use Stop Loss : Setting an appropriate stop loss is vital when trading based on False Breakouts. Typically, the stop loss can be placed near the level where the False Breakout occurred.
3. Seek Confirmations : Before entering a trade, look for additional confirmations. These can include other analyses or technical indicators that show the price is likely to return to its previous level.
🔵 Settings
🟣 Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Bac k: You can set the number of swings that will go back for checking.
🟣 Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 Alert Settings
Alert False Breakout : Enables alerts for Breakout.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵Conclusion
False Breakouts, as a key concept in technical analysis, are powerful tools for identifying sudden price changes and using them in trading. Understanding this phenomenon and applying it can help traders perform better in financial markets and avoid potential losses.
To benefit from False Breakouts, traders need to carefully analyze charts and use the appropriate analytical tools. By leveraging this strategy, traders can achieve lower-risk and higher-reward trades.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Improved Volume Based Indicator# Improved Volume Based Indicator
## Overview
The Improved Volume Based Indicator is a technical analysis tool designed to identify potential trading opportunities based on volume patterns, price action, and trend direction. This indicator combines volume analysis with moving averages and the Average True Range (ATR) to generate buy and sell signals.
## Key Components
1. Volume Analysis
- Tracks consecutive volume direction (up or down) for 3 periods
- Calculates volume ratio compared to a short-term moving average
2. Trend Direction
- Uses a 200-period Exponential Moving Average (EMA) to determine overall trend
3. Volatility Measurement
- Incorporates the Average True Range (ATR) for stop-loss and take-profit calculations
## Signal Generation
### Buy Signal Criteria
1. Three consecutive periods of up volume (close > open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is above the 200 EMA
### Sell Signal Criteria
1. Three consecutive periods of down volume (close < open)
2. Volume ratio > 1.5 (current volume is 50% higher than the short-term average)
3. Current price is below the 200 EMA
## Risk Management
The indicator calculates stop-loss and take-profit levels based on the ATR:
- Stop Loss: ATR * 1.5 (default)
- Take Profit: ATR * 2.5 (default)
These levels are adjustable through input parameters.
## Usage
1. Add the indicator to your chart
2. Adjust input parameters as needed:
- Volume Period (2-5)
- ATR Period (default 14)
- ATR Multipliers for Stop Loss and Take Profit
- EMA Period (default 200)
3. Monitor for buy and sell signals
4. Use the provided stop-loss and take-profit levels for risk management
## Interpretation
- Buy signals suggest potential upward price movement
- Sell signals suggest potential downward price movement
- Always consider other factors and perform additional analysis before making trading decisions
## Limitations
- This indicator may generate false signals in choppy or ranging markets
- It's best used in conjunction with other technical analysis tools and fundamental analysis
- Past performance does not guarantee future results
Remember to thoroughly test this indicator on historical data and in various market conditions before using it in live trading.
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# 改進的基於交易量的指標
＃＃ 概述
改進的基於成交量的指標是一種技術分析工具，旨在根據成交量模式、價格行為和趨勢方向識別潛在的交易機會。此指標將成交量分析與移動平均線和平均真實波動幅度 (ATR) 結合起來，以產生買入和賣出訊號。
＃＃ 關鍵部件
1. 成交量分析
- 追蹤 3 個週期的連續成交量方向（向上或向下）
- 計算與短期移動平均線相比的成交量比率
2. 趨勢方向
- 使用 200 週期指數移動平均線 (EMA) 來確定整體趨勢
3. 波動率測量
- 納入平均真實波動範圍 (ATR) 以進行停損和停盈計算
## 訊號生成
### 購買訊號標準
1. 連續三個週期的成交量上漲（收盤>開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 當前價格高於200 EMA
### 賣出訊號標準
1.連續三個週期的成交量下跌（收盤<開盤）
2.成交量比率>1.5（目前成交量較短期平均高50%）
3. 目前價格低於200 EMA
＃＃ 風險管理
此指標根據 ATR 計算停損和止盈水準：
- 停損：ATR * 1.5（預設）
- 止盈：ATR * 2.5（預設）
這些等級可透過輸入參數進行調整。
＃＃ 用法
1. 將指標加入您的圖表中
2. 根據需要調整輸入參數：
- 卷期 (2-5)
- ATR 週期（預設 14）
- 用於停損和止盈的 ATR 乘數
- EMA 週期（預設 200）
3. 監控買賣訊號
4. 使用提供的停損和停利水準進行風險管理
＃＃ 解釋
- 買進訊號表示價格可能上漲
- 賣出訊號表示價格可能下跌
- 在做出交易決策之前始終考慮其他因素並進行額外分析
## 限制
- 此指標可能會在波動或波動的市場中產生錯誤訊號
- 最好與其他技術分析工具和基本面分析結合使用
- 過去的表現並不能保證未來的結果
請記住，在實際交易中使用該指標之前，請根據歷史數據和各種市場條件徹底測試該指標。
