XAUUSD 10-Minute StrategyThis XAUUSD 10-Minute Strategy is designed for trading Gold vs. USD on a 10-minute timeframe. By combining multiple technical indicators (MACD, RSI, Bollinger Bands, and ATR), the strategy effectively captures both trend-following and reversal opportunities, with adaptive risk management for varying market volatility. This approach balances high-probability entries with robust volatility management, making it suitable for traders seeking to optimise entries during significant price movements and reversals.
Key Components and Logic:
MACD (12, 26, 9):
Generates buy signals on MACD Line crossovers above the Signal Line and sell signals on crossovers below the Signal Line, helping to capture momentum shifts.
RSI (14):
Utilizes oversold (below 35) and overbought (above 65) levels as a secondary filter to validate entries and avoid overextended price zones.
Bollinger Bands (20, 2):
Uses upper and lower Bollinger Bands to identify potential overbought and oversold conditions, aiming to enter long trades near the lower band and short trades near the upper band.
ATR-Based Stop Loss and Take Profit:
Stop Loss and Take Profit levels are dynamically set as multiples of ATR (3x for stop loss, 5x for take profit), ensuring flexibility with market volatility to optimise exit points.
Entry & Exit Conditions:
Buy Entry: T riggered when any of the following conditions are met:
MACD Line crosses above the Signal Line
RSI is oversold
Price drops below the lower Bollinger Band
Sell Entry: Triggered when any of the following conditions are met:
MACD Line crosses below the Signal Line
RSI is overbought
Price moves above the upper Bollinger Band
Exit Strategy: Trades are closed based on opposing entry signals, with adaptive spread adjustments for realistic exit points.
Backtesting Configuration & Results:
Backtesting Period: July 21, 2024, to October 30, 2024
Symbol Info: XAUUSD, 10-minute timeframe, OANDA data source
Backtesting Capital: Initial capital of $700, with each trade set to 10 contracts (equivalent to approximately 0.1 lots based on the broker’s contract size for gold).
Users should confirm their broker's contract size for gold, as this may differ. This script uses 10 contracts for backtesting purposes, aligned with 0.1 lots on brokers offering a 100-contract specification.
Key Backtesting Performance Metrics:
Net Profit: $4,733.90 USD (676.27% increase)
Total Closed Trades: 526
Win Rate: 53.99%
Profit Factor: 1.44 (1.96 for Long trades, 1.14 for Short trades)
Max Drawdown: $819.75 USD (56.33% of equity)
Sharpe Ratio: 1.726
Average Trade: $9.00 USD (0.04% of equity per trade)
This backtest reflects realistic conditions, with a spread adjustment of 38 points and no slippage or commission applied. The settings aim to simulate typical retail trading conditions. However, please adjust the initial capital, contract size, and other settings based on your account specifics for best results.
Usage:
This strategy is tuned specifically for XAUUSD on a 10-minute timeframe, ideal for both trend-following and reversal trades. The ATR-based stop loss and take profit levels adapt dynamically to market volatility, optimising entries and exits in varied conditions. To backtest this script accurately, ensure your broker’s contract specifications for gold align with the parameters used in this strategy.
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[ETH] Optimized Trend Strategy - Lorenzo SuperScalpStrategy Title: Optimized Trend Strategy - Lorenzo SuperScalp
Description:
The Optimized Trend Strategy is a comprehensive trading system tailored for Ethereum (ETH) and optimized for the 15-minute timeframe but adaptable to various timeframes. This strategy utilizes a combination of technical indicators—RSI, Bollinger Bands, and MACD—to identify and act on price trends efficiently, providing traders with actionable buy and sell signals based on market conditions.
Key Features:
Multi-Indicator Approach:
RSI (Relative Strength Index): Identifies overbought and oversold conditions to time market entries and exits.
Bollinger Bands: Acts as a dynamic support and resistance level, helping to pinpoint precise entry and exit zones.
MACD (Moving Average Convergence Divergence): Detects momentum changes through bullish and bearish crossovers.
Signal Conditions:
Buy Signal:
RSI is below 45 (indicating an oversold condition).
Price is near or below the lower Bollinger Band.
MACD bullish crossover occurs.
Sell Signal:
RSI is above 55 (indicating an overbought condition).
Price is near or above the upper Bollinger Band.
MACD bearish crossunder occurs.
Trade Execution Logic:
Long Trades: Opened when a buy signal flashes. If there’s an open short position, it is closed before opening a long.
Short Trades: Opened when a sell signal flashes. If there’s an open long position, it is closed before opening a short.
The strategy also ensures a minimum number of bars between consecutive trades to avoid rapid trading in choppy conditions.
Pyramiding Support:
Up to 3 consecutive trades in the same direction are allowed, enabling traders to scale into positions based on strong signals.
Visual Indicators:
RSI Levels: Dotted lines at 45 and 55 for quick reference to oversold and overbought levels.
Buy and Sell Signals: Visual markers on the chart indicate where trades are executed, ensuring clarity on entry and exit points.
Best Used For:
Swing Trading & Scalping: While optimized for the 15-minute timeframe, this strategy works across various timeframes, making it suitable for both short-term scalping and swing trading.
Crypto Trading: Tailored for Ethereum but effective for other cryptocurrencies due to its dynamic indicator setup.
Fibonacci & Bollinger Bands StrategyThis strategy combines Bollinger Bands and Fibonacci retracement/extension levels to identify potential entry and exit points in the market. Here’s a breakdown of each component and how the strategy works:
1. Bollinger Bands:
Bollinger Bands consist of a simple moving average (SMA) and two standard deviations (upper and lower bands) plotted above and below the SMA. The bands expand and contract based on market volatility.
Purpose in Strategy:
The lower band represents an area where the market might be oversold.
The upper band represents an area where the market might be overbought.
The price crossing these bands suggests overextended market conditions, which can be used to identify potential reversals.
2. Fibonacci Retracement and Extension Levels:
Fibonacci retracement levels are horizontal lines that indicate where price might find support or resistance as it retraces some of its previous movement. Common retracement levels are 61.8% and 78.6%.
Fibonacci extension levels are used to project areas where the price might extend after completing a retracement. These levels can help determine potential targets after a significant price movement.
Purpose in Strategy:
The strategy calculates the most recent swing high (fibHigh) and swing low (fibLow) over a lookback period. It then plots Fibonacci retracement and extension levels based on this range.
The Fibonacci levels are used as key support and resistance areas. The price approaching or touching these levels signals potential turning points in the market.
3. Entry Criteria:
A long position (buy) is triggered when:
The price crosses below the lower Bollinger Band, indicating an oversold condition.
The price is near or above a Fibonacci extension level (calculated based on the most recent price swing).
This suggests that the price is potentially reaching a strong support area, where a reversal is likely.
4. Exit Criteria:
The long position is closed (exit trade) when either:
The price touches or crosses the upper Bollinger Band, signaling an overbought condition.
The price reaches a Fibonacci retracement level or exceeds the recent swing high (fibHigh), indicating a potential exhaustion point or a reversal area.
5. General Strategy Logic:
The strategy takes advantage of market volatility (captured by the Bollinger Bands) and key support/resistance levels (determined by Fibonacci retracement and extension levels).
By combining these two techniques, the strategy identifies potential entry points at oversold levels with the expectation that the market will retrace or reverse upward, especially when near key Fibonacci extension levels.
Exit points are identified by potential overbought levels (Bollinger upper band) or key Fibonacci retracement levels, where the price might reverse downward.
6. Conditions to Execute the Strategy:
The Fibonacci levels are only calculated once the price has made a significant movement, establishing a recent high and low over a 50-bar period (which you can adjust). This ensures the Fibonacci levels are based on meaningful swings.
The entry and exit signals are filtered using both Bollinger Bands and Fibonacci levels to ensure that trades are not taken solely based on one indicator, thus reducing false signals.
Key Features of the Strategy:
Trend-following with reversal: It tries to catch reversals when the price hits extreme levels (Bollinger Bands) while respecting important Fibonacci levels.
Dynamic market adaptation: The strategy adapts to market conditions as it recalculates Fibonacci levels based on recent price swings and adjusts the Bollinger Bands for market volatility.
Confirmation through multiple indicators: It uses both the volatility-based signals from Bollinger Bands and the price structure from Fibonacci levels to confirm trade entries and exits.
Summary of the Strategy:
The strategy looks to buy low and sell high based on oversold/overbought signals from Bollinger Bands and Fibonacci levels that indicate key support and resistance zones.
By combining these two technical indicators, the strategy aims to reduce risk and increase accuracy by only entering trades when both indicators suggest favorable conditions.
Fibonacci Swing Trading BotStrategy Overview for "Fibonacci Swing Trading Bot"
Strategy Name: Fibonacci Swing Trading Bot
Version: Pine Script v5
Purpose: This strategy is designed for swing traders who want to leverage Fibonacci retracement levels and candlestick patterns to enter and exit trades on higher time frames.
Key Components:
1. Multiple Timeframe Analysis:
The strategy uses a customizable timeframe for analysis. You can choose between 4hour, daily, weekly, or monthly time frames to fit your preferred trading horizon. The high and low-price data is retrieved from the selected timeframe to identify swing points.
2. Fibonacci Retracement Levels:
The script calculates two key Fibonacci retracement levels:
0.618: A common level where price often retraces before resuming its trend.
0.786: A deeper retracement level, often used to identify stronger support/resistance areas.
These levels are dynamically plotted on the chart based on the highest high and lowest low over the last 50 bars of the selected timeframe.
3. Candlestick Based Entry Signals:
The strategy uses candlestick patterns as the only indicator for trade entries:
Bullish Candle: A green candle (close > open) that forms between the 0.618 retracement level and the swing high.
Bearish Candle: A red candle (close < open) that forms between the 0.786 retracement level and the swing low.
When these candlestick patterns align with the Fibonacci levels, the script triggers buy or sell signals.
4. Risk Management:
Stop Loss: The stop loss is set at 1% below the entry price for long trades and 1% above the entry price for short trades. This tight risk management ensures controlled losses.
Take Profit: The strategy uses a 2:1 risk-to-reward ratio. The take profit is automatically calculated based on this ratio relative to the stop loss.
5. Buy/Sell Logic:
Buy Signal: Triggered when a bullish candle forms above the 0.618 retracement level and below the swing high. The bot then places a long position.
Sell Signal: Triggered when a bearish candle forms below the 0.786 retracement level and above the swing low. The bot then places a short position.
The stop loss and take profit levels are automatically managed once the trade is placed.
Strengths of This Strategy:
Swing Trading Focus: The strategy is ideal for swing traders, targeting longer-term price moves that can take days or weeks to play out.
Simple Yet Effective Indicators: By only relying on Fibonacci retracement levels and basic candlestick patterns, the strategy avoids complexity while capitalizing on well-known support and resistance zones.
Automated Risk Management: The built-in stop loss and take profit mechanism ensures trades are protected, adhering to a strict 2:1 risk/reward ratio.
Multiple Timeframe Analysis: The script adapts to various market conditions by allowing users to switch between different timeframes (4hour, daily, weekly, monthly), giving traders flexibility.
Strategy Use Cases:
Retracement Traders: Traders who focus on entering the market at key retracement levels (0.618 and 0.786) will find this strategy especially useful.
Trend Reversal Traders: The strategy’s reliance on candlestick formations at Fibonacci levels helps traders spot potential reversals in price trends.
Risk Conscious Traders: With its 1% risk per trade and 2:1 risk/reward ratio, the strategy is ideal for traders who prioritize risk management in their trades.
Smart Money Concept Strategy - Uncle SamThis strategy combines concepts from two popular TradingView scripts:
Smart Money Concepts (SMC) : The strategy identifies key levels in the market (swing highs and lows) and draws trend lines to visualize potential breakouts. It uses volume analysis to gauge the strength of these breakouts.
Smart Money Breakouts : This part of the strategy incorporates the idea of "Smart Money" – institutional traders who often lead market movements. It looks for breakouts of established levels with significant volume, aiming to catch the beginning of new trends.
How the Strategy Works:
Identification of Key Levels: The script identifies swing highs and swing lows based on a user-defined lookback period. These levels are considered significant points where price has reversed in the past.
Drawing Trend Lines: Trend lines are drawn connecting these key levels, creating a visual representation of potential support and resistance zones.
Volume Analysis: The script analyzes the volume during the formation of these levels and during breakouts. Higher volume suggests stronger moves and increases the probability of a successful breakout.
Entry Conditions:
Long Entry: A long entry is triggered when the price breaks above a resistance line with significant volume, and the moving average trend filter (optional) is bullish.
Short Entry: A short entry is triggered when the price breaks below a support line with significant volume, and the moving average trend filter (optional) is bearish.
Exit Conditions:
Stop Loss: Customizable stop loss percentages are implemented to protect against adverse price movements.
Take Profit: Customizable take profit percentages are used to lock in profits.
Credits and Compliance:
This strategy is inspired by the concepts and code from "Smart Money Concepts (SMC) " and "Smart Money Breakouts ." I've adapted and combined elements of both scripts to create this strategy. Full credit is given to the original authors for their valuable contributions to the TradingView community.
To comply with TradingView's House Rules, I've made the following adjustments:
Clearly Stated Inspiration: The description explicitly mentions the original scripts and authors as the inspiration for this strategy.
No Direct Copying: The code has been modified and combined, not directly copied from the original scripts.
Educational Purpose: The primary purpose of this strategy is for learning and backtesting. It's not intended as financial advice.
Important Note:
This strategy is intended for educational and backtesting purposes only. It should not be used for live trading without thorough testing and understanding of the underlying concepts. Past performance is not indicative of future results.
Bollinger and Stochastic with Trailing Stop - D.M.P.This trading strategy combines Bollinger Bands and the Stochastic indicator to identify entry opportunities in oversold and overbought conditions in the market. The aim is to capitalize on price rebounds from the extremes defined by the Bollinger Bands, with the confirmation of the Stochastic to maximize the probability of success of the operations.
Indicators Used
- Bollinger Bands Used to measure volatility and define oversold and overbought levels. When the price touches or breaks through the lower band, it indicates a possible oversold condition. Similarly, when it touches or breaks through the upper band, it indicates a possible overbought condition.
- Stochastic: A momentum oscillator that compares the closing price of an asset with its price range over a certain period. Values below 20 indicate oversold, while values above 80 indicate overbought.
Strategy Logic
- Long Entry (Buy): A purchase operation is executed when the price closes below the lower Bollinger band (indicating oversold) and the Stochastic is also in the oversold zone.
- Short Entry (Sell): A sell operation is executed when the price closes above the upper Bollinger band (indicating overbought) and the Stochastic is in the overbought zone.
Adaptive SMI Ergodic StrategyThe Adaptive SMI Ergodic Strategy aims to capture the momentum and direction of a financial asset by leveraging the Stochastic Momentum Index Indicator (SMI) in an ergodic form. The strategy uses two lengths for the SMI, a shorter and a longer one, and an Exponential Moving Average (EMA) to serve as the signal line. Additionally, the strategy incorporates customizable overbought and oversold thresholds to improve the probability of successful trade execution.
How It Works:
Long Entry: A long position is taken when the ergodic SMI crosses over the EMA signal line, and both the SMI and EMA are below the oversold threshold.
Short Entry: A short position is initiated when the ergodic SMI crosses under the EMA signal line, and both the SMI and EMA are above the overbought threshold.
The strategy plots the SMI in yellow and the EMA signal line in purple. Horizontal lines indicate the overbought and oversold thresholds, and a colored background helps in visually identifying these zones.
Parameters:
Long Length: The length of the long EMA in SMI calculation.
Short Length: The length of the short EMA in SMI calculation.
Signal Line Length: The length for the EMA serving as the signal line.
Oversold: Customizable threshold for the oversold condition.
Overbought: Customizable threshold for the overbought condition.
Historical Context: The SMI Indicator
The Stochastic Momentum Index (SMI) was developed by William Blau in the early 1990s as an enhancement to traditional stochastic oscillators. The SMI provides a range of values like a traditional stochastic, but it differs in that it calculates the distance of the current close relative to the median of the high/low range, as opposed to the close relative to the low. As a result, the SMI is less erratic and more responsive, offering a clearer picture of market trends.
In recent years, the SMI has been adapted into ergodic forms to facilitate smoother data analysis, reduce lag, and improve trading accuracy. The Adaptive SMI Ergodic Strategy leverages these modern enhancements to offer a more robust, customizable trading strategy that aligns with various market conditions.
MTF Diagonally Layered RSI - 1 minute Bitcoin Bot [wbburgin]This is a NON-REPAINTING multi-timeframe RSI strategy (long-only) that enters a trade only when two higher timeframes are oversold. I wrote it on BTC/USD for 1min, but the logic should work on other assets as well. It is diagonally layered to be profitable for when the asset is in a downtrend.
Diagonal layering refers to entry and exit conditions spread across different timeframes. Normally, indicators can become unprofitable because in downtrends, the overbought zones of the current timeframe are not reached. Rather, the overbought zones of the faster timeframes are reached first, and then a selloff occurs. Diagonally-layered strategies mitigate this by selling diagonally, that is, selling once the faster timeframe reaches overbought and buying once the slower timeframe reaches oversold.
Thus this strategy is diagonally layered down . I may create a separate script that alternates between diagonal-up and diagonal-down based off of overall trend, as in extended trend periods up this indicator may not flash as frequently. This can be visualized in a time series x timeframe chart as an "X" shape. Something to consider...
Let me know if you like this strategy. Feel free to alter the pyramiding entries, initial capital, and entry size, as well as commission regime. My strategies are designed to maximize average profit instead of flashing super frequently, as the fees will eat you up. Additionally, at the time of publication, all of my strategy scripts are intended to have profitable Sharpe and Sortino ratios.
Timeframes, RSI period, and oversold/overbought bounds are configurable.
I11L - Meanreverter 4h---Overview---
The system buys fear and sells greed.
Its relies on a Relative Strength Index (RSI) and moving averages (MA) to find oversold and overbought states.
It seems to work best in market conditions where the Bond market has a negative Beta to Stocks.
Backtests in a longer Timeframe will clearly show this.
---Parameter---
Frequency: Smothens the RSI curve, helps to "remember" recent highs better.
RsiFrequency: A Frequency of 40 implies a RSI over the last 40 Bars.
BuyZoneDistance: Spacing between the different zones. A wider spacing reduces the amount of signals and icnreases the holding duration. Should be finetuned with tradingcosts in mind.
AvgDownATRSum: The multiple of the Average ATR over 20 Bars * amount of opentrades for your average down. I choose the ATR over a fixed percent loss to find more signals in low volatility environments and less in high volatility environments.
---Some of my thoughts---
Be very careful about the good backtesting performance in many US-Stocks because the System had a favourable environment since 1970.
Be careful about the survivorship bias as well.
52% of stocks from the S&P500 were removed since 2000.
I discount my Annual Results by 5% because of this fact.
You will find yourself quite often with very few signals because of the high market correlation.
My testing suggests that there is no expected total performance difference between a signal from a bad and a signal from a good market condition but a higher volatility.
I am sharing this strategy because i am currently not able to implement it as i want to and i think that meanreversion is starting to be taken more serious by traders.
The challange in implementing this strategy is that you need to be invested 100% of the time to retrieve the expected annual performance and to reduce the fat tail risk by market crashes.
V Bottom & V Top Pattern [Misu]█ This indicator shows V bottom & V top patterns as well as potential V bottom & V top.
These V bottom & V top are chart powerful reversal patterns.
They appear in all markets and time-frames, but due to the nature of the aggressive moves that take place when a market reverses direction, it can be difficult to identify this pattern in real-time.
To address this problem, I added potential V pattern as well as the confirmed one.
█ Usages:
You can use V top & V bottoms for reversal zones.
You can use it for scalping strategies, as a main buy & sell signal.
Potential V patterns can be used to anticipate the market, in addition to volatility or momentum indicators, for example.
█ How it works?
This indicator uses pivot points to determine potential V patterns and confirm them.
Paramaters are available to filter breakouts of varying strengths.
Patterns also have a "max number bars" to be validated.
█ Why a Strategy type indicator?
Due to the many different parameters, this indicator is a strategy type.
This way you can overview the best settings depending on your pair & timeframe.
Parameters are available to filter.
█ Parameters:
Deviation: Parameter used to calculate parameters.
Depth: Parameter used to calculate parameters.
Confirmation Type: Type of signal used to confirme the pattern.
> Mid Pivot: pattern will confirm on mid pivot breakout.
> Opposit Pivot: pattern will confirm on opposit pivot breakout.
> No confirmation: no confirmation.
Lenght Avg Body: Lenght used to calculate the average body size.
First Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout of potential V pattern.
Confirmation Breakout Factor: This factor multiplied by the "body avg" filters out the non-significant breakout for the confirmation.
Max Bars Confirmation: The maximum number of bars needed to validate the pattern.
Weis BB StrategyThis is a strategy based on Weis Wave & EMA. Weis Wave Volume is used to determine the overall trend and Bollinger Band to determine the Price breaking out from resistance zones.
[VJ]Thor for MFIThis is a simple intraday strategy for working on Stocks or commodities . You can modify the start time and end time based on your timezones. Session value should be from market start to the time you want to square-off
Important: The end time should be at least 2 minutes before the intraday square-off time set by your broker
Comment below if you get good returns
Strategy:
Indicators used :
Moving average (MA) is a widely used technical indicator that smooths out price trends by filtering out the “noise” from random short-term price fluctuations. Here moving averages are used to identify trend direction and to determine support and resistance levels. Overbought and oversold regions are also taken into consideration
The Money Flow Index ( MFI ) is a momentum indicator that measures the flow of money into and out of a security over a specified period of time. It is related to the Relative Strength Index ( RSI ) but incorporates volume , whereas the RSI only considers price. The MFI is calculated by accumulating positive and negative Money Flow values (see Money Flow ), then creating a Money Ratio. The Money Ratio is then normalized into the MFI oscillator form.
Using the combination of Overbought and Oversold values and varying MFI and using the MA filter to ensure the direction , we can buy/sell when conditions are met
Buying with MFI
1. MFI drops below 20 and enters inside oversold zone.
2. MFI bounces back above 20.
3. MFI pulls back but remains above 20.
4. A MFI break out above its previous high is a good buy signal.
Selling with MFI
1. MFI rises above 80 and enters inside overbought zone.
2. MFI drops back below 80.
3. MFI rises slightly but remains below 80.
4. MFI drops lower than its previous low is a signal to short sell or profit booking
Usage & Best setting :
Choose a good volatile stock and a time frame - 5m.
MFI factor : 3
Moving Average : 80
Overbought & Oversold - can be varied as per user
There is stop loss and take profit that can be used to optimise your trade
The template also includes daily square off based on your time.
[VJ]War Machine PAT IntraThis is a simple intraday strategy for working on Stocks . You can modify the values on the stock and see what are your best picks. Comment below if you found something with good returns
Strategy:
Indicators used :
The Choppiness Index is designed to determine whether the market is choppy or trading sideways, or not choppy and trading within a trend in either direction. Using a scale from 1 - 100, the market is considered to be choppy as values near 100 (over 61.80) and trending when values are lower than 38.20)
The Money Flow Index (MFI) is a momentum indicator that measures the flow of money into and out of a security over a specified period of time. It is related to the Relative Strength Index (RSI) but incorporates volume, whereas the RSI only considers price. The MFI is calculated by accumulating positive and negative Money Flow values (see Money Flow), then creating a Money Ratio. The Money Ratio is then normalized into the MFI oscillator form.
Using the combination of CI (trend factor as constant) and varying MFI, we can buy/sell when conditions are met
Buying with MFI
1. MFI drops below 20 and enters inside oversold zone.
2. MFI bounces back above 20.
3. MFI pulls back but remains above 20.
4. A MFI break out above its previous high is a good buy signal.
Selling with MFI
1. MFI rises above 80 and enters inside overbought zone.
2. MFI drops back below 80.
3. MFI rises slightly but remains below 80.
4. MFI drops lower than its previous low is a signal to short sell or profit booking
Usage & Best setting :
Choose a good volatile stock and a time frame - 5m.
Trending factor : 50
Overbought & Oversold - can be varied as per user
There is stop loss and take profit that can be used to optimise your trade
The template also includes daily square off based on your time.
MACD, EMA, Know sure thing, Chopy Market - high adaptabilityHey there :)
This is the free version of the script. The following indicators / settings are missing:
- Support and resistance zones
- dynamic textboxes for alarms when using bots (3 Commas, Alertatron, etc.)
- a table showing the current position, indicators and other important information
With this script there is the possibility to completely customize the MACD . Starting with the MACD and signal line, the histogram and the color of the histogram.
Since the Pinecoders team has previously deleted the script, I will mention the fee settings in a bit more detail:
In this script a fee of 0.01% and a slipage of 15 was used. With each trade the total capital (100%) is used with a risk reward of 1 to 1.5.
The total capital, i.e. the risk, can be changed at any time under the "Settings" tab at "Equity".
I also added an EMA , the Know sure thing indicator and the Chopy Market indicator (by TradingRush) to the script to filter out bad trades.
The EMA:
Since the EMA is very reliable and shows whether there is an upward or downward trend, it should be used with the indicators in any case. It prevents long trades in downward movements and vice versa.
The KST Indicator:
The KST indicator has a similar movement as the MACD, but is by and large a bit more time delayed. It filters out false swings of the MACD and thus prevents bad trades.
The Chopy Market Indicator by Tradingrush:
The Chopy Market indicator, which was introduced by TradingRush in one of its videos, has the ability to detect sideways markets and block zones below this line for trades by means of a fixed value (the line).
To exit the trades, I added the following options:
ATR Exits. Exits based on past candles (lowest low, highest high).
Static exits based on set percentages.
In the next days I will create a tutorial for the script, just have a look on my profile.
If you have any questions about the script, let me know.
True Strength Indicator BTCUSD 2HScript based on True Strength Index (TSI) and RSI
A technical momentum indicator that helps traders determine overbought and oversold conditions of a security by incorporating the short-term purchasing momentum of the market with the lagging benefits of moving averages. Generally a 25-day exponential moving average (EMA) is applied to the difference between two share prices, and then a 13-day EMA is applied to the result, making the indicator more sensitive to prevailing market conditions.
!!! IMPORTANT IN ORDER TO AVOID REPAITING ISSUES
!!! USE Chart resolution >= resCustom parameter, suggestion 2H
Yellow zones indicates that you can claim position for better profits even before a claim confirmation.
Dark zones indicates areas where RSI shows overbought and oversold conditions.
BTCUSD
Backtesting Period Selector | ComponentDescription
It's nice to quickly be able to set the backtesting period when writing strategies.
To make this process faster I wrote a simple 'component'.
So this is not a strategy but rather code you can plug-into your strategy and use
if you need that specific functionality.
Then it's just a matter of selecting which dates you want to backtest.
You can also chose to color the background to visually show the testing period.
Unfortunately, the background color is fixed at 'blue' for now.
Ps. I like the idea of writing small components to be pluged into other strategies
I'll try to develop this idea a bit further and see how small pieces of code can
easily provide specific functionality to assist and make deving strategies a bit less 'Pineful'.
Usage
First copy the instructed part of the component code over to your strategy.
Next, use the testPeriod() function to limit strategies to the specified backtesting period.
Example usage:
if testPeriod()
strategy.entry("LE", strategy.long)
Todo / Improvements
There are many ways to improve this component and I'm not a very good coder so this is a very crude solutions.
Anyway, here are some things which would be nice to improve:
1. Enable color selection so that the user can choose the background color of his own liking.
2. Improve naming of variables.
3. Test for ilogical choices, such as test period start being at a later date, than test period stop.
4. Account for time zones.
As always, any feedback, corrections or thoughts are very much welcome!
/pbergden
Break & Retest Strategy V2 (Clean Visuals)This strategy is built on a high-probability EMA breakout and retest model, designed for traders who want clean structure-based entries filtered by trend alignment and strong price action. It leverages:
• ✅ A 44 EMA trend filter on the 4H chart
• ✅ HTF directional bias from the Daily 44 EMA
• ✅ Breakout above the EMA followed by a wick-based retest
• ✅ Strong bullish candle confirmation (body > 50% of range)
• ✅ Dynamic stop loss using either the pivot low or a buffer below the EMA
• ✅ Fixed 1:3 Risk:Reward ratio for consistent reward targeting
• ✅ Cooldown system to prevent overtrading
• ✅ Clean, minimal visuals using smart RR boxes instead of chart clutter
This system is fully backtestable and designed with prop firm challenge criteria in mind — prioritizing risk control, clarity, and high-quality trade conditions.
⸻
🔧 Current Development Goals (V3 Roadmap)
We’re actively refining the system to improve win rate and profit factor, while keeping drawdown low. Key upgrades in progress:
1. 📈 Liquidity Trap Filter
• Add logic to confirm a wick below recent lows (liquidity sweep) before retesting the EMA
2. 🧠 Partial Take Profits + Breakeven Logic
• TP1 at 1.5R → move SL to breakeven
• TP2 at 3R → close remaining position
3. 🔁 Trade Session Filter
• Limit entries to London & New York AM sessions to avoid false signals in low volume periods
4. 📉 Short Entry Engine
• Mirror logic for bearish break + retest setups below the EMA
5. 🔔 Live Alerts System
• Entry signal alerts for hands-free, real-time trading decisions
6. 📊 Optimizer Toolkit (future)
• Add ATR/volatility filters
• Add market structure confluence zones (HH/HL filters)
• Smart cooldown timer based on wins/losses or volatility shifts
High Accuracy Volume Breakout StrategyHigh Accuracy Volume Breakout Strategy (EMA + RSI Filter)
🧠 Description:
This is a high-accuracy breakout strategy based on volume surges, trend confirmation, and momentum filtering, designed for intraday and short-term trading.
The strategy aims to capture strong directional moves triggered by sudden increases in volume, with entry filters to avoid low-quality or choppy signals.
✅ Entry Logic:
🔺 Buy Entry Conditions:
Current candle closes above previous high
Volume is greater than 1.5× the 20-period average
Price is above 50 EMA (uptrend confirmation)
RSI is below 70 (not overbought)
🔻 Sell Entry Conditions:
Current candle closes below previous low
Volume is greater than 1.5× the 20-period average
Price is below 50 EMA (downtrend confirmation)
RSI is above 30 (not oversold)
🎯 Exit Logic:
Stop Loss: 1.2 × ATR(14)
Take Profit: 2.0 × ATR(14)
🧪 Recommended Settings:
Parameter Value
Timeframe 5-minute, 15-minute
Markets Gold (XAUUSD), Nifty, BankNifty, BTC, NASDAQ
Risk/Reward ~1:1.6
Expected Accuracy ~65–75% in trending markets
📊 Features:
🔸 ATR-based dynamic stoploss and target
🔸 Volume spike confirmation to detect real breakouts
🔸 EMA 50 trend filter to reduce false signals
🔸 RSI filter to avoid extreme zones (overbought/oversold)
🔸 Plotted buy/sell arrows for clarity
⚠️ Disclaimer:
This strategy is for educational purposes only. Please backtest and paper trade before using in live markets. Performance may vary depending on asset and timefram
plot(ema50, color=color.orange)
ARSI – (VWAP & ATR) 3QKRAKThe ARSI Long & Short – Dynamic Risk Sizing (VWAP & ATR) indicator combines three core components—an adjusted RSI oscillator (ARSI), Volume‐Weighted Average Price (VWAP), and Average True Range (ATR)—so that entry/exit signals and position sizing are always tailored to current market conditions. ARSI, plotted from 0 to 100 with clearly marked overbought and oversold zones, is the primary signal driver: when ARSI falls below the lower threshold it indicates an excessive sell‐off and flags a long opportunity, whereas a break above the upper threshold signals overextended gains and foreshadows a short. A midpoint line at 50 can serve as an early exit or reduction signal when crossed against your position.
VWAP, showing the volume‐weighted average price over the chosen period, acts as a trend filter—long trades are only taken when price sits above VWAP, and shorts only when it’s below—ensuring each trade aligns with the prevailing market momentum. ATR measures current volatility and is used both to set safe stop‐loss levels and to dynamically size each position. In practice, this means positions automatically shrink in high‐volatility environments and grow in quieter markets, all while risking a fixed percentage of your capital.
Everything appears on a single chart: the ARSI pane below the price window with its reference levels; VWAP overlaid on the price; and the ATR‐based stop‐loss distances graphically displayed. Traders thus get a comprehensive, at-a-glance view of entries, exits, trend confirmation, and exactly how large a position they can safely take. The indicator runs in real time, removing the need for manual parameter calculations and letting you focus on strategic decision-making.
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range
Overview:
This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets.
🔍 Strategy Components:
EMA Crossover (Fast/Slow)
Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum.
RSI Filter
RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met.
Long entry requires RSI ≥ Long Threshold
Short entry requires RSI ≤ Short Threshold
ATR-Based SL & TP
Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price.
Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure.
Opening Range Filter (Optional)
If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves.
Session Filters
No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods.
All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options.
⚙️ Built-in Presets:
You can choose one of the built-in ticker-specific presets for optimal conditions:
Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL
SPY 8/28 56 / 26 14 1.4× 4.0×
TSLA 23/27 56 / 33 13 1.4× 3.6×
AAPL 6/13 61 / 26 23 1.4× 2.1×
MSFT 25/32 54 / 26 14 1.2× 2.2×
META 25/32 53 / 26 17 1.8× 2.3×
AMZN 28/32 55 / 25 16 1.8× 2.3×
You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences.
📌 Best Use Case:
This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
TrendMaster Pro 2.3 with Alerts
Hello friends,
A member of the community approached me and asked me how to write an indicator that would achieve a particular set of goals involving comprehensive trend analysis, risk management, and session-based trading controls. Here is one example method of how to create such a system:
Core Strategy Components
Multi-Moving Average System - Uses configurable MA types (EMA, SMA, SMMA) with short-term (9) and long-term (21) periods for primary signal generation through crossovers
Higher Timeframe Trend Filter - Optional trend confirmation using a separate MA (default 50-period) to ensure trades align with broader market direction
Band Power Indicator - Dynamic high/low bands calculated using different MA types to identify price channels and volatility zones
Advanced Signal Filtering
Bollinger Bands Volatility Filter - Prevents trading during low-volatility ranging markets by requiring sufficient band width
RSI Momentum Filter - Uses customizable thresholds (55 for longs, 45 for shorts) to confirm momentum direction
MACD Trend Confirmation - Ensures MACD line position relative to signal line aligns with trade direction
Stochastic Oscillator - Adds momentum confirmation with overbought/oversold levels
ADX Strength Filter - Only allows trades when trend strength exceeds 25 threshold
Session-Based Trading Management
Four Trading Sessions - Asia (18:00-00:00), London (00:00-08:00), NY AM (08:00-13:00), NY PM (13:00-18:00)
Individual Session Limits - Separate maximum trade counts for each session (default 5 per session)
Automatic Session Closure - All positions close at specified market close time
Risk Management Features
Multiple Stop Loss Options - Percentage-based, MA cross, or band-based SL methods
Risk/Reward Ratio - Configurable TP levels based on SL distance (default 1:2)
Auto-Risk Calculation - Dynamic position sizing based on dollar risk limits ($150-$250 range)
Daily Limits - Stop trading after reaching specified TP or SL counts per day
Support & Resistance System
Multiple Pivot Types - Traditional, Fibonacci, Woodie, Classic, DM, and Camarilla calculations
Flexible Timeframes - Auto-adjusting or manual timeframe selection for S/R levels
Historical Levels - Configurable number of past S/R levels to display
Visual Customization - Individual color and display settings for each S/R level
Additional Features
Alert System - Customizable buy/sell alert messages with once-per-bar frequency
Visual Trade Management - Color-coded entry, SL, and TP levels with fill areas
Session Highlighting - Optional background colors for different trading sessions
Comprehensive Filtering - All signals must pass through multiple confirmation layers before execution
This approach demonstrates how to build a professional-grade trading system that combines multiple technical analysis methods with robust risk management and session-based controls, suitable for algorithmic trading across different market sessions.
Good luck and stay safe!
Volatility Bias ModelVolatility Bias Model
Overview
Volatility Bias Model is a purely mathematical, non-indicator-based trading system that detects directional probability shifts during high volatility market phases. Rather than relying on classic tools like RSI or moving averages, this strategy uses raw price behavior and clustering logic to determine potential breakout direction based on recent market bias.
How It Works
Over a defined lookback window (default 10 bars), the strategy counts how many candles closed in the same direction (i.e., bullish or bearish).
Simultaneously, it calculates the price range during that window.
If volatility is above a minimum threshold and a clear directional bias is detected (e.g., >60% of closes are bullish), a trade is opened in the direction of that bias.
This approach assumes that when high volatility is coupled with directional closing consistency, the market is probabilistically more likely to continue in that direction.
ATR-based stop-loss and take-profit levels are applied, and trades auto-exit after 20 bars if targets are not hit.
Key Features
- 100% non-indicator-based logic
- Statistically-driven directional bias detection
- Works across all timeframes (1H, 4H, 1D)
- ATR-based risk management
- No pyramiding, slippage and commissions included
- Compatible with real-world backtesting conditions
Realism & Assumptions
To make this strategy more aligned with actual trading environments, it includes 0.05% commission per trade and a 1-point slippage on every entry and exit.
Additionally, position sizing is set at 10% of a $10,000 starting capital, and no pyramiding is allowed.
These assumptions help avoid unrealistic backtest results and make the performance metrics more representative of live conditions.
Parameter Explanation
Bias Window (10 bars): Number of past candles used to evaluate directional closings
Bias Threshold (0.60): Required ratio of same-direction candles to consider a bias valid
Minimum Range (1.5%): Ensures the market is volatile enough to avoid noise
ATR Length (14): Used to dynamically define stop-loss and target zones
Risk-Reward Ratio (2.0): Take-profit is set at twice the stop-loss distance
Max Holding Bars (20): Trades are closed automatically after 20 bars to prevent stagnation
Originality Note
Unlike common strategies based on oscillators or moving averages, this script is built on pure statistical inference. It models the market as a probabilistic process and identifies directional intent based on historical closing behavior, filtered by volatility. This makes it a non-linear, adaptive model grounded in real-world price structure — not traditional technical indicators.
Disclaimer
This strategy is for educational and experimental purposes only. It does not constitute financial advice. Always perform your own analysis and test thoroughly before applying with real capital.
MNQ EMA StrategyThis strategy is not perfected yet. ONE MINUTE TIMEFRAME
The goal is to take Longs above the 5 ema when price is above all the 200, 30, and 5 ema.
Short side is when candle closes below the 5 ema and price is below the 300, 30, and 5 ema.
I use candle range blocks for different time zones to avoid excess orders from being triggered. As well as blocks when stoploss is hit or after a profitable trade of certain ticks.
There is an RSI to avoid trades when there isn't too much movement.
My goal is to get an entry when price trades above the 5 ema and then next candle passes it by .25 instead of entering immediately. The stoploss as the low of candle before entry and TP as 3 times the stoploss. I've tried a million times to make it like this but I don't know how to use pine script or Code.
The sell side is basically the same, enter at candle close below 5 ema wait for low to get swept to enter and stoploss above previous high, with TP 3 times the stoploss.
Publishing in hopes anyone knows how to adjust this
CAUTION THIS STRATEGY WORKS WITH CURRENT PRICE ACTION DUE TO ME USING RECENT TICK COUNT RATHER THAN BASED ON CANDLES OR PERCENTAGES. THIS WILL ONLY WORK AS LONG AS MARKET MOVES AS IT HAS BEEN SINCE 2024. CME_MINI:MNQ1!
