Dual RSI Differential - Strategy [presentTrading]█ Introduction and How it is Different
The Dual RSI Differential Strategy introduces a nuanced approach to market analysis and trading decisions by utilizing two Relative Strength Index (RSI) indicators calculated over different time periods. Unlike traditional strategies that employ a single RSI and may signal premature or delayed entries, this method leverages the differential between a shorter and a longer RSI. This approach pinpoints more precise entry and exit points, providing a refined tool for traders to exploit market conditions effectively, particularly in overbought and oversold scenarios.
Most important: it is a good eductional code for swing trading.
For beginners, this Pine Script provides a complete function that includes crucial elements such as holding days and the option to configure take profit/stop loss settings:
- Hold Days: This feature ensures that trades are not exited too hastily, helping traders to ride out short-term market volatility. It's particularly valuable for swing trading where maintaining positions slightly longer can lead to capturing significant trends.
- TPSL Condition (None by default): This setting allows traders to focus solely on the strategy's robust entry and exit signals without being constrained by preset profit or loss limits. This flexibility is crucial for learning to adjust strategy settings based on personal risk tolerance and market observations.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 RSI Calculation:
The RSI is a momentum oscillator that measures the speed and change of price movements. It is calculated using the formula:
RSI = 100 - (100 / (1 + RS))
Where RS (Relative Strength) = Average Gain of up periods / Average Loss of down periods.
🔶 Dual RSI Setup:
This strategy involves two RSI indicators:
RSI_Short (RSI_21): Calculated over a short period (21 days).
RSI_Long (RSI_42): Calculated over a longer period (42 days).
Differential Calculation:
The strategy focuses on the differential between these two RSIs:
RSI Differential = RSI_Long - RSI_Short
This differential helps to identify when the shorter-term sentiment diverges from longer-term trends, signaling potential trading opportunities.
BTCUSD Local picuture
🔶 Signal Triggers:
Entry Signal: A buy (long) signal is triggered when the RSI Differential exceeds -5, suggesting strengthening short-term momentum. Conversely, a sell (short) signal occurs when the RSI Differential falls below +5, indicating weakening short-term momentum.
Exit Signal: Trades are generally exited when the RSI Differential reverses past these thresholds, indicating a potential momentum shift.
█ Trade Direction
This strategy accommodates various trading preferences by allowing selections among long, short, or both directions, thus enabling traders to capitalize on diverse market movements and volatility.
█ Usage
The Dual RSI Differential Strategy is particularly suited for:
Traders who prefer a systematic approach to capture market trends.
Those who seek to minimize risks associated with rapid and unexpected market movements.
Traders who value strategies that can be finely tuned to different market conditions.
█ Default Settings
- Trading Direction: Both — allows capturing of upward and downward market movements.
- Short RSI Period: 21 days — balances sensitivity to market movements.
- Long RSI Period: 42 days — smoothens out longer-term fluctuations to provide a clearer market trend.
- RSI Difference Level: 5 — minimizes false signals by setting a moderate threshold for action.
Use Hold Days: True — introduces a temporal element to trading strategy, holding positions to potentially enhance outcomes.
- Hold Days: 5 — ensures that trades are not exited too hastily, helping to ride out short-term volatility.
- TPSL Condition: None — enables traders to focus solely on the strategy's entry and exit signals without preset profit or loss limits.
- Take Profit Percentage: 15% — aims for significant market moves to lock in profits.
- Stop Loss Percentage: 10% — safeguards against large losses, essential for long-term capital preservation.
Penunjuk dan strategi
Price-Volume Dynamic - Strategy [presentTrading]█ Introduction and How it is Different
The "Price-Volume Dynamic - Strategy" leverages a unique blend of price action, volume analysis, and statistical z-scores to establish trading positions. This approach differentiates itself by integrating the concept of the Point of Control (POC) from volume profile analysis with price-based z-score indicators to create a dynamic trading strategy. It tailors entry and exit thresholds based on current market volatility, providing a responsive and adaptive trading method. This strategy stands out by considering both historical volatility and price trends to adjust trading decisions in real-time, enhancing its effectiveness in various market conditions.
BTCUSD 4h LS Performance
█ Strategy: How It Works – Detailed Explanation
🔶 Calculating Point of Control (POC)
The Point of Control (POC) represents the price level with the highest traded volume over a specified lookback period. It's calculated by dividing the price range into a number of rows, each representing a price level. The volume at each price level is tallied and the level with the maximum volume is designated as the POC.
🔶 Dynamic Thresholds Adjustments
The entry and exit thresholds are dynamically adjusted based on normalized volatility, which is derived from the current, minimum, and maximum ATR over a specified period. This normalization ensures that the thresholds adapt to changes in market conditions, making the strategy sensitive to shifts in market volatility.
BTCUSD local performance
█ Trade Direction
The strategy can be configured to trade in three different directions: Long, Short, or Both. This flexibility allows traders to align their trading strategy with their market outlook or risk preferences. By adjusting the `POC_tradeDirection` input, traders can selectively participate in market movements that match their trading style and objectives.
█ Usage
To deploy this strategy, traders should apply it within a trading software that supports scripting and backtesting, such as TradingView's Pine Script environment. Users can input their parameters based on their analysis of the market conditions and their risk tolerance. It is essential for traders to backtest the strategy using historical data to evaluate its performance and make necessary adjustments before applying it in live trading scenarios.
█ Default Settings
- Lookback Length: Sets the period over which the highest and lowest prices, and the volume per price level, are calculated. A higher lookback length smoothens the volatility but may delay response to recent market movements.
- Number of Rows: Determines the granularity of price levels within the price range. More rows provide a more detailed volume profile but require more computational resources.
- Entry Z-Score Threshold Base: Influences the sensitivity of the strategy to enter trades. Higher values make the strategy more conservative, requiring stronger deviation from the mean to trigger a trade.
- Exit Z-Score Threshold Base: Sets the threshold for exiting trades, with lower values allowing trades to close on smaller price retractions, thereby potentially preserving profits or reducing losses.
- Trading Direction: Allows selection between Long, Short, or Both, enabling traders to tailor the strategy to their market view or risk preferences.
Trailing Take Profit - Close Based📝 Description
This script demonstrates a new approach to the trailing take profit.
Trailing Take Profit is a price-following technique. When used, instead of setting a limit order for the take profit target exiting from your position at the specified price, a stop order is conditionally set when the take profit target is reached. Then, the stop price (a.k.a trailing price), is placed below the take profit target at a distance defined by the user percentagewise. On regular time intervals, the stop price gets updated by following the "Trail Barrier" price (high by default) upwards. When the current price hits the stop price you exit the trade. Check the chart for more details.
This script demonstrates how to implement the close-based Trailing Take Profit logic for long positions, but it can also be applied for short positions if the logic is "reversed".
📢 NOTE
To generate some entries and showcase the "Trailing Take Profit" technique, this script uses the crossing of two moving averages. Please keep in mind that you should not relate the Backtesting results you see in the "Strategy Tester" tab with the success of the technique itself.
This is not a complete strategy per se, and the backtest results are affected by many parameters that are outside of the scope of this publication. If you choose to use this new approach of the "Trailing Take Profit" in your logic you have to make sure that you are backtesting the whole strategy.
⚔️ Comparison
In contrast to my older "Trailing Take Profit" publication where the trailing take profit implementation was tick-based, this new approach is close-based, meaning that the update of the stop price occurs at the bar close instead of every tick.
While comparing the real-time results of the two implementations is like comparing apples to oranges, because they have different dynamic behavior, the new approach offers better consistency between the backtesting results and the real-time results.
By updating the stop price on every bar close, you do not rely on the backtester assumptions anymore (check the Reasoning section below for more info).
The new approach resembles the conditional "Trailing Exit" technique, where the condition is true when the current price crosses over the take profit target. Then, the stop order is placed at the trailing price and it gets updated on every bar close to "follow" the barrier price (high). On the other hand, the older tick-based approach had more "tight" dynamics since the trailing price gets updated on every tick leaving less room for price fluctuations by making it more probable to reach the trailing price.
🤔 Reasoning
This new close-based approach addresses several practical issues the older tick-based approach had. Those issues arise mainly from the technicalities of the TV Backtester. More specifically, due to the assumptions the Broker Emulator makes for the price action of the history bars, the backtesting results in the TV Backtester are exaggerated, and depending on the timeframe, the backtesting results look way better than they are in reality.
The effect above, and the inability to reason about the performance of a strategy separated people into two groups. Those who never use this feature, because they couldn't know for sure the actual effect it might have in their strategy, (even if it turned out to be more profitable) and those who abused this type of "repainting" behavior to show off, and hijack some boosts from the community by boasting about the "fake" results of their strategies.
Even if there are ways to evaluate the effectiveness of the tick-based approach that is applied in an existing strategy (this is out of the topic of this publication), it requires extra effort to do the analysis. Using this closed-based approach we can have more predictable results, without surprises.
⚠️ Caveats
Since this approach updates the trailing price on bar close, you must wait for at least one bar to close after the price crosses over the take profit target.
Turn of the Month Strategy [Honestcowboy]The end of month effect is a well known trading strategy in the stock market. Quite simply, most stocks go up at the end of the month. What's even better is that this effect spills over to the next phew days of the next month.
In this script we backtest this theory which should work especially well on SP500 pair.
By default the strategy buys 2 days before the end of each month and exits the position 3 days into the next month.
The strategy is a long only strategy and is extremely simple. The SP500 is one of the #1 assets people use for long term investing due to it's "9.8%" annualised return. However as a trader you want the best deal possible. This strategy is only inside the market for about 25% of the time while delivering a similar return per exposure with a lower drawdown.
Here are some hypothesis why turn of the month effect happens in the stock markets:
Increased inflow from savings accounts to stocks at end of month
Rebalancing of portfolios by fund managers at end of month
The timing of monthly cash flows received by pension funds, which are reinvested in the stock market.
The script also has some inputs to define how many days before end of the month you want to buy the asset and how long you want to hold it into the next month.
It is not possible to buy the asset exactly on this day every month as the market closes on the weekend. I've added some logic where it will check if that day is a friday, saturdady or sunday. If that is the case it will send the buy signal on the end of thursday, this way we enter on the friday and don't lose that months trading opportunity.
The backtest below uses 4% exposure per trade as to show the equity curve more clearly and because of publishing rules. However, most fund managers and investors use 100% exposure. This way you actually risk money to earn money. Feel free to adjust the settings to your risk profile to get a clearer picture of risks and rewards before implementing in your portfolio.
Moving average strategyNAME : Moving average strategy
SUMMARY
Long when Short MA period > Long MA period
Exit when Short MA period < Long MA period
Long only strategy, but you can modify this script.
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This strategy uses a moving average line.
It buys when the short-term moving average crosses the long-term moving average and sells when the long-term moving average crosses the short-term moving average.
You can use different moving average lines by setting the MA type.
You can use SMA, EMA, DEMA, TEMA, WMA, and VWMA.
You can also adjust the period of the moving average line.
Price Type sets the type of price that will be used for the moving average line. The options are Close price, Open price, High price, Low price, Typical price, and center price.
High MDD and long periods of sideways movement make it difficult to use in practice, even though the returns may seem high.
Hopefully, you can combine it with other indicators to create a good strategy.
Thank you.
Price and Volume Breakout Buy Strategy [TradeDots]The "Price and Volume Breakout Buy Strategy" is a trading strategy designed to identify buying opportunities by detecting concurrent price and volume breakouts over a specified range of candlesticks.
This strategy is optimized for assets demonstrating high volatility and significant momentum spikes.
HOW IT WORKS
The strategy first takes the specific number of candlesticks as the examination window for both price and volume.
These values are used as benchmarks to identify breakout conditions.
A trade is initiated when both the closing price and the trading volume surpass the maximum values observed within the predetermined window.
Price must be above a designated moving average, serving as the trend indicator, ensuring that all trades align with the prevailing market trend.
APPLICATION
This strategy is particularly effective for highly volatile assets such as Bitcoin and Ethereum, capitalizing on the cues from sudden price and volume breakouts indicative of significant market movement, often driven by market smart money traders.
However, for broader markets like the S&P 500, this strategy may be less effective due to less pronounced volume and price shifts compared to the cryptocurrency markets.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Backtest result sometimes gives fewer than 100 trades under certain higher timeframes, as most trades tend to have a long holding period. Entry conditions are also more stringent, which, combined with the relatively brief history of cryptocurrencies, results in fewer trades on longer timeframes.
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Support and Resistance RoboTBINANCE:ETHUSDT
Algorithmic Trader
Coded by Pinescript V5
Best strategy you can find in trading cryptocurrencies
With the ability to adjust settings
Profitable each year
This strategy uses supports and resistances combined with ichimoku
This automated strategy trades on ETH/USD
(ranks second in cryptocurrency marketcap).
We have had real trade results for more than 10
months and backtesting for more than 8 years.
The results are for mid-risk
settings. If the settings are changed, you can
potentially achieve more profit or a lower
drawdown.
Default settings : EMA,EMA,14,1.5,1.5,23,0.5,31,10,W
“An investment in knowledge pays the best interest”
Benjamin Franklin
If you're interested, we can
provide you with access to
examine the strategy.
Thanks!
Alligator + MA Trend Catcher [TradeDots]The "Alligator + MA Trend Catcher" is a trading strategy that integrates the William Alligator indicator with a Moving Average (MA) to establish robust entry and exit conditions, optimized for capturing trends.
HOW IT WORKS
This strategy combines the traditional William Alligator set up with an additional Moving Average indicator for enhanced trend confirmation, creating a user-friendly backtesting tool for traders who prefer the Alligator method.
The original Alligator strategy can frequently present fluctuations, even in well-established trends, leading to potentially premature exits. To mitigate this, we incorporate a Moving Average as a secondary confirmation measure to ensure the market trend has indeed shifted.
Here’s the operational flow for long orders:
Entry Signal: When the price rises above the Moving Average, it confirms a bullish market state. Enter if Alligator spread in an upward direction. The trade remains active even if the Alligator indicator suggests a trend reversal.
Exit Signal: The position is closed when the price falls below the Moving Average, and the Alligator spreads in the downward direction. This setup helps traders to maintain positions through the entirety of the trend for maximum gain.
APPLICATION
This strategy is tailored for assets with significant, well-defined trends, such as Bitcoin and Ethereum, which are known for their high volatility and substantial price movements.
This strategy offers a low win-rate but high reward configuration, making asset selection critical for long-term profitability. If you choose assets that lack strong price momentum, there's a high chance that this strategy may not be effective.
For traders seeking to maximize gains from large trends without exiting prematurely, this strategy provides an aggressive yet controlled approach to riding out substantial market waves.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Multi Timeframe RSI Buy Sell Strategy [TradeDots]The "Multi Timeframe RSI Buy/Sell Strategy" is a trading strategy that utilizes Relative Strength Index (RSI) indicators from multiple timeframes to provide buy and sell signals.
This strategy allows for extensive customization, supporting up to three distinct RSIs, each configurable with its own timeframe, length, and data source.
HOW DOES IT WORK
This strategy integrates up to three RSIs, each selectable from different timeframes and customizable in terms of length and source. Users have the flexibility to define the number of active RSIs. These selections visualize as plotted lines on the chart, enhancing interpretability.
Users can also manage the moving average of the selected RSI lines. When multiple RSIs are active, the moving average is calculated based on these active lines' average value.
The color intensity of the moving average line changes as it approaches predefined buying or selling thresholds, alerting users to potential signal generation.
A buy or sell signal is generated when all active RSI lines simultaneously cross their respective threshold lines. Concurrently, a label will appear on the chart to signify the order placement.
For those preferring not to display order information or activate the strategy, an "Enable backtest" option is provided in the settings for toggling activation.
APPLICATION
The strategy leverages multiple RSIs to detect extreme market conditions across various timeframes without the need for manual timeframe switching.
This feature is invaluable for identifying divergences across timeframes, such as detecting potential short-term reversals within broader trends, thereby aiding traders in making better trading decisions and potentially avoiding losses.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 60%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TradeDots Stochastic Z-Score
Khaled Tamim's Avellaneda-Stoikov StrategyDescription:
This strategy applies the Avellaneda-Stoikov (A-S) model to generate buy and sell signals for underlying assets based on option pricing theory. The A-S model estimates bid and ask quotes for options contracts considering factors like volatility (sigma), time to expiration (T), and risk aversion (gamma).
Key Concepts:
Avellaneda-Stoikov Model: A mathematical framework for option pricing that incorporates volatility, time decay, and risk tolerance.
Bid-Ask Quotes: The theoretical buy and sell prices for an option contract.
Inventory Management: The strategy tracks its long or short position based on signals.
How it Works:
A-S Model Calculation: The avellanedaStoikov function calculates bid and ask quotes using the underlying asset's closing price, user-defined parameters (gamma, sigma, T, k, and M), and a small fee (adjustable).
Signal Generation: The strategy generates long signals when the closing price falls below the adjusted bid quote and short signals when it exceeds the adjusted ask quote.
Trade Execution: Buy and sell orders are triggered based on the generated signals (long for buy, short for sell).
Inventory Tracking: The strategy's net profit reflects the current inventory level (long or short position).
Customization:
Gamma (γ): Controls risk aversion in the A-S model (higher values imply lower risk tolerance).
Sigma (σ): Represents the underlying asset's expected volatility.
T: Time to expiration for the hypothetical option (defaults to a short-term option).
k: A constant factor in the A-S model calculations.
M: Minimum price buffer for buy/sell signals (prevents excessive churn).
Important Note:
This strategy simulates option pricing behavior for a theoretical option and does not directly trade options contracts. Backtesting results may not reflect actual market conditions.
Further Considerations:
The 0.1% fee is a placeholder and may need adjustment based on real-world trading costs.
Consider using realistic timeframes for T (e.g., expiry for a real option)
Disclaimer: This strategy is for educational purposes only and does not constitute financial advice.
Volume-Supported Linear Regression Trend Modified StrategyHi everyone, this will be my first published script on Tradingview, maybe more to come.
For quite some time I have been looking for a script that performs no matter if price goes up or down or sideways. I believe this strategy comes pretty close to that. Although nowhere near the so called "buy&hold equity" of BTC, it has produced consistent profits even when price goes down.
It is a strategy which seems to work best on the 1H timeframe for cryptocurrencies.
Just by testing different settings for SL and TP you can customize it for each pair.
THE STRATEGY:
Basically, I used the Volume Supported Linear Regression Trend Model that LonesomeTheBlue has created and modified a few things such as entry and exit conditions. So all credits go to him!
LONG ENTRY: When there is a bullish cross of the short term trend (the histogram/columns), while the long term trend is above 0 and rising.
SHORT ENTRY: When there is a bearish cross (green to red) of the short-term trend (the histogram/columns), while the long term trend is beneath 0 and decreasing.
LONG EXIT: Bearish crossover of short-term trend while long term trend is below 0
SHORT EXIT: Bullish crossover of short-term trend while long term trend is above 0
Combining this with e.g. a SL of 2% and a TP of 20% (as used in my backtesting), combined with pyramiding and correct risk management, it gives pretty consistent results.
Be aware, this is only for educational purpose and in no means financial advise. Past results do not guarantee future results. This strategy can lose money!
Enjoy :)
PS: It works not only on BTC of course, works even better on some other major crypto pairs. I'll leave it to you to find out which ones ;)
Trend Crawler with Dynamic TP and Trailing Stop### Description of "Trend Crawler with Dynamic TP and Trailing Stop"
#### Overview
The "Trend Crawler with Dynamic TP and Trailing Stop" is a comprehensive trading strategy designed for medium-frequency trading on various timeframes and markets. It utilizes a combination of trend identification and volatility analysis to determine optimal entry and exit points, aiming to maximize profitability by adapting to changing market conditions.
#### Strategy Mechanics
1. **Moving Averages**: Users can select between Simple Moving Average (SMA) and Exponential Moving Average (EMA) to define the trend. The strategy uses two moving averages (fast and slow) to identify the trend direction. A crossover of the fast MA above the slow MA signals a potential bullish trend, while a crossunder signals a bearish trend.
2. **Volume Analysis**: The strategy incorporates volume analysis to confirm the strength of the trend. It calculates a standard deviation of volume from its moving average to detect significant increases in trading activity, which supports the trend direction indicated by the MAs.
3. **Price Spread and RSI**: It uses the price spread (difference between the close and open of each bar) and the Relative Strength Index (RSI) to filter entries based on market momentum and overbought/oversold conditions. This helps in refining the entries to avoid weak or overly extended moves.
4. **Dynamic Take Profit and Trailing Stop**:
- **Trailing Stop**: As the position moves into profit, the strategy adjusts the stop loss dynamically to protect gains, using a trailing stop mechanism.
- **Dynamic Take Profit**: The take profit levels are adjusted based on the volatility (measured by the standard deviation of the price spread) to capture maximum profit from significant moves.
#### Usage
To use the strategy:
- Set the desired moving average type and lengths according to the asset and timeframe being traded.
- Adjust the RSI thresholds to match the market's volatility and trading style.
- Set the base take profit and stop loss levels along with the trailing stop distance based on risk tolerance and trading objectives.
#### Justification for Originality
While the use of moving averages, RSI, and volume analysis may be common, the integration of these elements with dynamic adjustments for take profit and trailing stops based on real-time volatility analysis offers a unique approach. The strategy adapts not just to trend direction but also to the market's momentum and volatility, providing a tailored trading solution that goes beyond standard indicator-based strategies.
#### Strategy Results and Settings
Backtesting should be conducted with realistic account sizes and include considerations for commission and slippage to ensure that the results are not misleading. Risk per trade should be kept within a sustainable range (ideally less than 5% of account equity), and the strategy should be tested over a sufficient sample size (at least 100 trades) to validate its effectiveness.
#### Chart Presentation
The script’s output includes:
- Colored backgrounds to indicate bullish or bearish market conditions.
- Plots of trailing stops to visually manage risk.
- Entry points are marked with shapes on the chart, providing clear visual cues for trading decisions.
#### Conclusion
This strategy offers traders a robust framework for trend following with enhanced risk management through dynamic adjustments based on real-time market analysis. It's designed to be versatile and adaptable to a wide range of markets and trading styles, providing traders with a tool that not only follows trends but also adapts to market changes to secure profits and reduce losses.
[Support and Resistance with Trend Lines] with Backtest (TSO) with Backtest (TSO)
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This indicator serves as a comprehensive full-cycle trading system, providing alerts at each stage of the trade, from opening to closure. The algorithm uses most recent and historical S&R (Support and Resistance) levels with most recent and historical Trend Lines, generating signals for trades when Breaks/Bounces occur (Trade Open Signal triggers can be configured via very customizable indicator Input "Signal Trigger Matrix" settings). With signal for trade open, TP (Take Profit and SL (Stop Loss) levels are calculated as well and marked on the chart including alerts for each action of the trade. The indicator offers a variety of automated approaches for TP (Take-Profit) and SL (Stop-Loss) settings. These include static current/historical S&R (Support and Resistance) levels or S&R/Trend Lines dynamic breaks for TP (Take-Profit) and various SL (Stop-Loss) approaches, including ATR Trailing SL, opposite S&R (Support and Resistance) levels SL, opposite Trend Lines SL and more. This diverse set of tools ensure flexibility in tailoring TP (Take-Profit) and SL (Stop-Loss) parameters to different market conditions, contributing to a more adaptive and robust trading system. Additionally, a series of signal analysis tools, including market sentiment, candle bar analysis, divergence, and volume, enhance the precision of trading signals.
* Works with popular timeframes: 1M, 3M, 5M, 15M, 30M, 45M, 1H.
* Works well with Futures and Indices, can be used to trade Stocks, Crypto and FOREX.
* Includes LIVE alert/labels Breakouts and Bounces signal trigger feature, which can be used for scalping (NOTE: This approach cannot be backtested).
* Every action of the trade is calculated on a confirmed closed candle bar state (barstate.isconfirmed), so the indicator will never repaint.
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Indicator examples:
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Strategy Config: SRTL_MES_15M3Y_EODoff_ALL
Here is a nice example of MES (Micro E-Mini S&P 500 Index Futures) configuration, which uses S&R (Support and Resistance) breakouts as signal trigger with Elliot Wave confirmation and previous S&R historical levels for TP (Take-Profit).
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An example of an intraday Tesla trade. Also the green arrows will be displayed IMMEDIATELY when Breakout/Reverse Bounce occurs (same an Alert will be triggered immediately).
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Trading open/close/TP/SL labels, plots and colors explanations:
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>>> S&R (Support and Resistance) levels/lines: orange - support, blue - resistance (can be hidden).
>>> Trend Lines: yellow - support, green - resistance (can be hidden).
>>> Blue labels show resistance breakouts and bounces, light-blue - bullish, dark-blue - bearish
>>> Yellow labels show resistance breakouts and bounces, light-yellow - bullish, dark-yellow - bearish
>>> Green/Red arrows on top/bottom of candle bar will show LIVE breakouts (if turned on)
>>>>> LONG open: green "house" looking arrow below candle bar.
>>>>> SHORT open: red "house" looking arrow above candle bar.
>>>>> LONG/SHORT take-profit target: green/red circles (multi-profit > TP2/3/4/5 smaller circles).
>>>>> LONG/SHORT stop-loss target: green/red + crosses.
>>>>> LONG/SHORT take-profit hits: green/red diamonds.
>>>>> LONG/SHORT stop-loss hits: green/red X-crosses.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (profitable trade): green/red squares.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (loss trade): green/red PLUS(+)-crosses.
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STATS TABLE ///////////////////////////////////////////////////////////////
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>>> Trading STATS table on the chart showing current trade direction, Last TP (Take-Profit) Taken, Current Trade PL (profit/loss in price difference from trade open to the very current state).
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CUSTOM TRADING DATE RANGE /////////////////////////////////////////////////
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>>>>> This feature can be used to manually set indicator trading range from and to a specific date and time. NOTE: This is not intended for a very long date range backtesting, utilize TradingView Strategy Tester for that.
* Use TradingView “Strategy Tester” to see Backtesting results
NOTE: If Strategy Tester does not show any results with Date Ranged fully unchecked, there may be an issue where a script opens a trade, but there is not enough TradingView power to set the Take-Profit and Stop-Loss and somehow an open trade gets stuck and never closes, so there are “no trades present”. In such case - manually check “Start”/“End” dates or use “Deep Backtesting” feature!
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INTRADAY ACTIVE TRADING SESSION CONFIGURATION /////////////////////////////
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>>> Regional Active Trading Session Hours Schedule: If selected - trades will only open during regional active trading session, if 'OFF', there will be no trading schedule and trades will open 24/7.
>>> EOD(End of Day) Close - On/Off: Close the trade if it's still open at the end of active trading session (on the very last candle bar). NOTE: If no region is selected at 'Regional Active Trading Session Schedule' - there will be no EOD(End of Day) Close and trades will run overnight until either SL(Stop-Loss) or TP(Take-Profit) is hit!
>>>>> EOD(End of Day) Close - 1 candle bar before last: This is specifically for stocks as while usually indices can be closed 15minutes after the market closes, for stocks - the last candle bar closes at the same time with the market active trading session, which if closed - trades can't be closed until next day/session! Enable this setting for the trade to close/alert 1 candle bar before the last one, so there is still time to close the trade at the Broker (NOTE: depending on the timeframe, 1 candle bar can be: 15sec, 30sec, 1min, 3min, 5min, 15min, 30min, 45min, 1h).
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SIGNAL TRIGGER MATRIX ////////////////////////////////////////////////
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>>> Trading Engine: This setting turns on TradingView Strategy trading engine for backtesting.
>>> Market Session Only: With this setting turned on, all signal trigger Breaks/Bounces will be hidden during Pre/Post market time.
>>> Plot S&R Levels/Lines: Plot S&R (Support and Resistance) on chart. Note: historical levels/lines will only be plotted if hit (Break/Bounce).
>>> Plot Trend Lines Levels/Lines: Plot Trend Lines levels/lines on chart. Note: historical levels/lines will only be plotted if hit (Break/Bounce).
>>> Use S&R Current Levels | Use S&R Historical Levels | Use Trend Lines Current Levels | Use Trend Lines Historical Levels |: Choose which levels should be used for Breaks/Bounces to be captured on. If all triggers are turned on/checked - whatever happens 1st wins the trigger.
>>> Breaks | Bounces: 'Breaks': Turn on Breaks through levels/lines signal trigger. | 'Bounces': Turn on Bounces off levels/lines signal trigger.
>>> Signal: Regular | Signal: S&R Combo | Signal: TL Combo | Signal: S&R + TL Combo | Signal: Repeat Action |: Trade open signal trigger execution approach MATRIX (If 1 or more turned on at the same time - whatever comes first will be the trade signal trigger). 'Regular': A single Break/Bounce must occur on a closed bar for signal trigger. 'S&R Combo': A combination of 2 Current + Historical S&R (Support and Resistance) Break/Bounce must happen in the same direction on same bar for signal trigger. 'TL Combo': A combination of 2 Current + Historical Trend Lines Break/Bounce must happen in the same direction on same bar for signal trigger. 'S&R + TL Combo': a combination of ANY S&R and Trend Line Break/Bounce must happen in the same direction on same bar for signal trigger. 'Repeat Action': Initial and then confirmation (2nd/3rd/etc. consecutive occurence) Break/Bounce must occur on same level/line for signal trigger.
>>> Historical - Look Back (# of days): How far back (in # of days) will historical S&R/Trend Lines will be used for Trade Open signals/TP/SL/etc.
>>> Historical - Look Back Invalidation (# of days): IF THERE IS TOO MUCH HISTORICAL LEVELS/LINES ON CHART - LOWER THIS SETTING + MAKE SURE IT'S SMALLER THAN 'Historical - Look Back (# of days)'. With big Look back period (5+ days) - it can become very messy with too many historical levels/lines. To clear oldest historical levels/lines - set Look Back Invalidation # of days to less than Historical Look Back # of days. (After X # of Look Back Invalidation days - older levels/lines will become invalidated and no longer used for opening trades/TP (Take-Profit)/SL (Stop-Loss), while newer levels/lines will still be discovered.
>>> S&R/Trend Lines - Support/Resistance combined into 1 entity: Every level or a line becomes simply a level or a line, regardless if it originally was a support or resistance. By default, depending on the level/line originally being support or resistance - the signal direction will be such as: Resistance is broken > LONG / bounced > SHORT; Support is broken > SHORT / bounced > LONG; with this setting on, either level or line can be both broken or bounced off in ANY direction, trade open direction will depend on current market sentiment only.
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S&R CONFIGURATION ////////////////////////////////////////////////
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>>> S&R Search - Left Bars (current): This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with below - Right Bars).
>>> S&R Search - Right Bars (current): This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with above - Left Bars).
>>> S&R Search - Custom Resolution (current): This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
>>> S&R Search - Left Bars (historical): This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with below - Right Bars).
>>> S&R Search - Right Bars (historical): This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with above - Left Bars).
>>> S&R Search - Custom Resolution (historical): This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
>>> S&R - Historical S&R Levels - Extend to the right: Extend all S&R lines to the right.
>>> S&R (Current/Historical) - Live Breakout/Bounce - ALERT/SHOW: NOTE: Alert wlil trigger immediately at price Breaking thru or Bouncing off level/line and an arrow above /below the bar will show the direction of breakout/bounce. If on that same live bar - price comes back causing the Breakout/Bounce become no longer valid - the arrow will disappear as the condition of the Break/Bounce will no longer be valid.
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TREND LINES CONFIGURATION ////////////////////////////////////////////////
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>>> Show: Trend Line development (where it 'did not exist' yet): It takes 2 pivots to develop a trend line, pivot is established at least 3 candle bars later from where the pivot is. With this setting turned on - it will plot dashed lines where trend lines originated connecting the 1st and 2nd pivot point up to where the trend line became established (where in reality you would now be able to draw a certain trend line). Established already generated trend line are plotted with a solid line.
>>> Trend Lines - Line Slope Confirmation: LONG breakout will only be shown if trend line is goind downslope \. SHORT breakout will only be shown if trend line is goind upslope /.
>>> Trend Lines - Search - Left Bars (current): This setting is for calculating optimal Trend Lines.
>>> Trend Lines - Search - Right Bars (current): This setting is for calculating optimal Trend Lines.
>>> Trend Lines - Custom Resolution (current): This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
>>> Trend Lines - Search - Left Bars (historical): This setting is for calculating optimal Trend Lines.
>>> Trend Lines - Search - Right Bars (historical): This setting is for calculating optimal Trend Lines.
>>> Trend Lines - Custom Resolution (historical): This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
>>> Trend Lines - Historical Trend Lines - Extend to the right: Extend all Trend Lines to the right.
>>> Trend Lines (Current/Historical) - Live Breakout/Bounce - ALERT/SHOW: NOTE: Alert will trigger immediately at price Breaking thru or Bouncing off level/line and an arrow above /below the bar will show the direction of breakout/bounce. If on that same live bar - price comes back causing the Breakout/Bounce become no longer valid - the arrow will disappear as the condition of the Break/Bounce will no longer be valid.
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TAKE-PROFIT/STOP-LOSS CONFIGURATION ///////////////////////////////////////
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>>> TP (Take-Profit) System: 'S&R Static Current/Historical': TP (Take-Profit) is calculated using current/historical S&R (Support & Resistance) levels at trade open and remains static. 'S&R/Trend Lines Dynamic Breaks': TP (Take-Profit) is fully dynamic and will be trigger at price above trade open price and with Breakout occurence (S&R or Trend Line current/historical breakout).
>>> TP (Take-Profit) # of targets: It is wise to divide the trade into several profit targets. With this setting - up to 5 TP (Take-Profit) targets can be approached. The trade will be equally divided up by the selected # of TP (Take-Profit) targets.
>>> SL (Stop-Loss) System: 'ATR-Trailing-SL': SL (Stop-Loss) is trail-following the ATR (Average True Range) line, NOTE: If at signal trigger, ATR will be against the trade direction - trade open signal will be skipped; 'S&R-Static-SL': SL (Stop-Loss) is set at trade open per optimal most recent S&R level and remains there until trade closes; 'TrendLines-Static-SL': SL (Stop-Loss) is set at trade open per optimal most recent trend line and remains there until trade closes; 'TrendLines-Dynamic-SL': SL (Stop-Loss) will be set per current opposite trend line and follow it until trade is open.; 'Oppos-Sig-Trd-in-Loss': SL (Stop-Loss) will trigger at opposite signal with trade currently at loss.
>>> SL (Stop-Loss) - On/Off: Without SL (Stop-Loss), unless EOD (End of Day) Close is turned on - there will be no SL (Stop-Loss) at all!
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MARKET SENTIMENT CONFIRMATION ///////////////////////////////////////
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>>> Market Sentiment: Signal is confirmed per Market Sentiment direction. If Market Sentiment is turned off - whatever signal comes 1st will be the trade open trigger.
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SIGNAL ANALYSIS AND CLEANUP ///////////////////////////////////////////////
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>>> Signal Cleanup - Bar Color: Include Bar Color (bullish/bearish) confirmation, LONG signal will only be opened if signal bar is green/bullish, SHORT if red/bearish.
>>> Signal Cleanup - Bar Directional Structure: Skip opposite bar structure types signals (For example: bearish green hammer).
>>> Signal Cleanup - Bar Doji Skip: Skip doji (indecisive) candles signals.
>>> Signal Cleanup - EWO (Elliott Wave Oscillator): Include EWO (Elliott Wave Oscillator), LONG will only be opened if EWO is bullish / SHORT if EWO is bearish.
>>> Signal Cleanup - VWAP (Volume-Weighted Average Price): Include VWAP (Volume-Weighted Average Price), LONG will only be opened if price is above VWAP / SHORT if price is below VWAP.
>>> Signal Cleanup - MA (Moving Average) Confirmation: Include MA (Moving Average), LONG will only be opened if MA is bullish / SHORT if MA is bearish.
>>> Signal Cleanup - ATR (Average True Range): Include ATR (Average True Range) confirmation, LONG will only be opened if ATR is bullish / SHORT if ATR is bearish.
>>> Signal Cleanup - Divergence(RSI + MACD): Include Divergence (RSI + MACD ) confirmation, LONG will only be opened if Divergence is bullish / SHORT if Divergence is bearish.
>>> Signal Cleanup - Volume % Strength: Include Volume strength/percentage confirmation, LONG/SHORT will only be opened with strong Volume matching the signal direction | By default, strong Volume percentage is set to 150% and weak to 50%.
>>> Signal Cleanup - Volume Above Average: Include Volume Above Moving Average (Volume closing bar closes above volume moving average) confirmation, LONG/SHORT will only be opened with Volume above average - Volume closed bar color must match the closed price color (bullish/bearish direction) + Volume bar must be closed above volume MA line).
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TP System - VERY IMPORTANT INFO!
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"TP PERCENTAGE" - amount by which current trade/position needs to be reduced/partially closed/sold.
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TP System: Dynamic
"TP PERCENTAGE" - will always be the same amount (trade/position size divided by the # of take-profit(TP) targets) and percentage to be closed will always be of the ORIGINAL trade/position.
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TP System: Static
"TP PERCENTAGE" - will always be the same amount IF take-profit(TP) targets are hit 1-by-1 (TP1 > TP2 > TP3 > TP4 > TP5), otherwise it will vary and unless it is a 1st take-profit(TP1), the REMAINING trade/position size will always be smaller than original and therefore the percentage to be closed will always be of the REMAINING trade/position and NOT the original one!
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"TP PERCENTAGE" CheatSheet (these are the only percentages you may see)
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TP PERCENTAGE---Close/Sell Amount-------------Example (trade size: 50 stocks)
20%-------------trade size * 0.2--------------50 * 0.2 = 10 stocks
25%-------------trade size * 0.25-------------50 * 0.25 = 12.5(~13) stocks
34%-------------trade size * 0.34-------------50 * 0.34 = 17 stocks
40%-------------trade size * 0.4--------------50 * 0.4 = 20 stocks
50%-------------trade size * 0.5--------------50 * 0.5 = 25 stocks
60%-------------trade size * 0.6--------------50 * 0.6 = 30 stocks
66%-------------trade size * 0.66-------------50 * 0.66 = 33 stocks
75%-------------trade size * 0.75-------------50 * 0.75 = 37.5(~38) stocks
80%-------------trade size * 0.8--------------50 * 0.8 = 40 stocks
100%------------trade size--------------------50 = 50 stocks
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If for any reason a portion of the current/remaining trade closed at such occurrence was slightly wrong, it is not an issue. Such occurrences are rare and with slight difference in partial TP closed is not significant to overall performance of our algorithms.
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Alert Settings (you don’t have to touch this section unless you will be using TradingView alerts through a Webhook to use with trading bot)
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Here is how a LONG OPEN alert looks like.
NOTE: Each label , , etc. is customizable, you can change the text of it within indicator Input settings.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: OPEN
ENTRY: 20000
TP1: 20500
TP2: 21000
TP3: 21500
TP4: 22500
TP5: 23500
SL: 19000
Leverage: 0
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Here is how a TP1 alert will look with 5 TPs breakdown of the trade.
NOTE1: Next to TP1 taken it will show at which price it was triggered.
NOTE2: Next to "TP Percentage" it shows how much of the CURRENT/ACTIVE/REMAINING trade needs to be closed.
NOTE2: If TP2/3/4/5 comes before TP1 - the alert will tell you exactly how many percent of the trade needs to be closed!
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: TP1
TP1: 20500
TP Percentage: 20%
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Here is how an alert will look for LONG - STOP-LOSS.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
ENTRY: 20000
LONG: SL
SL: 19000
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Here is how an alert will look for LONG - EOD (End of Day) In Profit close.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: EOD-Close (profit)
ENTRY: 20000
EOD-Close: 21900
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Adding Alerts in TradngView
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-Add indicator to chart and make sure the correct strategy is configured (check Backtesting results)
-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Immediately below, change it to "alert() function calls only", as other wise there will be 2 alerts for every alert!
-Expiration: Open-ended (that may require higher tier TradingView account, otherwise the alert will need to be occasionally re-triggered)
-Alert name: Whatever you desire
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
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Good Luck! (NOTE: Trading is very risky, past performance is not necessarily indicative of future results, so please trade responsibly!)
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NOTE: There seems to be a strange glitch when strategy is running live, it will show "double-take" take-profits labels on the chart. This is not affecting the script logic and backtesting results, if you simply change the timeframe real quick to something else then back - it will no longer show the duplicate orders... this must be some sort of a glitch as every alert was thoroughly tested to make sure everything is working!
Stochastic Z-Score Oscillator Strategy [TradeDots]The "Stochastic Z-Score Oscillator Strategy" represents an enhanced approach to the original "Buy Sell Strategy With Z-Score" trading strategy. Our upgraded Stochastic model incorporates an additional Stochastic Oscillator layer on top of the Z-Score statistical metrics, which bolsters the affirmation of potential price reversals.
We also revised our exit strategy to when the Z-Score revert to a level of zero. This amendment gives a much smaller drawdown, resulting in a better win-rate compared to the original version.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
Following this, the Stochastic Oscillator is utilized to affirm the Z-Score overbought and oversold indicators. This indicator operates within a 0 to 100 range, so a base adjustment to match the Z-Score scale is required. Post Stochastic Oscillator calculation, we recalibrate the figure to lie within the -4 to 4 range.
Finally, we compute the average of both the Stochastic Oscillator and Z-Score, signaling overpriced or underpriced conditions when the set threshold of positive or negative is breached.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURAUD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Stochastic Length: 14
Stochastic Smooth Period: 7
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 40%
FURTHER IMPLICATION
The Stochastic Oscillator imparts minimal impact on the current strategy. As such, it may be beneficial to adjust the weightings between the Z-Score and Stochastic Oscillator values or the scale of Stochastic Oscillator to test different performance outcomes.
Alternative momentum indicators such as Keltner Channels or RSI could also serve as robust confirmations of overbought and oversold signals when used for verification.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
Pullback_Power [JackTz]Welcome to Pullback_Power
Pullback_Power is a scalping strategy designed to capitalize on market retracements while incorporating unique dynamic features to enhance profitability.
Calculation
Pullback_Power purely uses moving averages to calculate both entry and exits. Exits can also be set to fixed percentages for both take profit and stop loss.
How the Strategy Works
Statistics show that markets normally do a recovery after each drop. Crypto markets can easily drop up to 20% within a few hours and then do a complete or partial recovery. Pullback_Power utilizes this known pattern alongside pyramiding. The strategy aims to catch one or more entries when the price drops, hoping to make profits when the market recovers from the drop. The fixed take profit and stop loss can be used to define your risk management, while the dynamic exit opportunity is riskier but provides the ability to stay in the trade longer while it recovers. Pullback_Power can make up to four entries. This means it utilizes pyramiding to spread out the entry points, but every exit is a full exit. It is not possible to partially exit.
Utility
Pullback_Power is a scalping strategy suitable for traders who operate with small trades and don't want to stay in the market for too long. Pullback_Power offers precise signals with no repainting. The strategy thrives in volatility, so crypto pairs might yield the best results, although this strategy can be adapted to work on all pairs and markets.
How to Automate It
Pullback_Power utilizes the standard placeholders of strategies on TradingView. This enables the trader to add every data point into a webhook, making it fully flexible to suit every trader's needs. To automate, create an alert, set the webhook URL, and add the JSON body needed for the webhook. An example of a simple JSON webhook with some of the standard strategy placeholders:
{
"side": "{{strategy.order.action}}",
"symbol": "{{ticker}}",
"amount": "{{strategy.order.contracts}}"
}
Read about all the standard placeholders that you can use here: TradingView - Standard strategy placeholders
Originality
Pullback_Power is unique in its ability to create precise signals without repainting while maintaining a solid approach to the pullback strategy. Its simplicity not only makes the strategy easy to use and understand but also highly effective. The simplicity reduces inputs, eliminating overfitting and limits each input to avoid incorrect usage. Many times, default settings are enough to achieve good backtesting results on almost all pairs available. Pullback_Power also differs from many other strategies by its solid code, which enhances performance and provides more reliable backtesting. The clean code increases the resilience and precision of the entries, making it less prone to errors.
Many pullback/scalping strategies normally only works on specific scopes of timeframes or pairs. Pullback_Power can easily be adapted to work on almost every scenario. The biggest change needed is the length of the moving average. The lower the timeframe, the higher a length is needed for proper results. I.e. on a 2H timeframe a length of 3 can yield good results. On a 5min timeframe the length might need to be as high as 70.
How to Use
To use Pullback_Power, add the script to your trading chart. By default, Pullback_Power opens four orders to optimize trade opportunities with a default fee value set at 0.1%. You can change these default settings in the Settings window under the Properties tab. To tailor Pullback_Power to your individual trading style, navigate to the Settings under the Input tab. Here you can configure various inputs to fit your trading style.
- Backtest settings , Start Date:
Defines the date of when the calculation starts. Use this to set the date of when the first trade could potentially emit.
- Backtest settings , End Date:
Defines the date of when the calculation ends. If there are any open trades after this date the close calculations are still live. It only makes sure that new orders cannot be opened after this date.
- Backtest settings , Only trade on weekdays:
This is a toggle you can enable or disable. If enabled it only allows new entries to happen during the normal week days, meaning Monday, Tuesday, Wednesday, Thursday and Friday.
Disable this to enable the script to open trades on all 7 days of the week.
- Open settings , Use dynamic long positions:
This toggle allows you to enable or disable the pullback level calculations after first trade.
If enabled, the calculations of level 2, 3 and 4 continues to happen after each bar, making the levels follow the price with the moving averages calculations.
If disabled, the calculations of the levels stop after the first trade. This means that the levels calculation at the point of the first trade stay fixed until all trades are closed.
You can see the difference of the green lines on the chart when you toggle this flag.
- Open settings , Data type:
This is the bar data used for the moving average calculation when opening trades. The possible data types are Open, High, Low, Close, HL2, HLC3, OHLC4, OC2 and HC2.
- Open settings , Source type:
This is the source used to calculate the moving average. The types available are: SMA, PCMA, EMA, WMA, DEMA, ZLEMA and HMA.
- Open settings , Length:
This is the length used for the moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Open settings , Offset:
This defines if the calculation should use an offset for the historical data. This does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Leverage settings , Leverage liquidation (1-125):
The script itself does not handle any custom leverage calculation – this must be done in the Properties tabs and increasing the order size.
This setting is made to test a possible liquidation event if using leverage.
By setting this to higher than 1, a red line is visible after the first trade on the chart. This indicates the liquidation price.
If this setting is set to 25, the script will calculate the liquidation price from a x25 leverage. If this price is hit, the scripts stops emitting any orders and the background turns red.
You can use this to test if your settings could handle a certain level of leverage.
- Pullback settings , Pullback 1, 2, 3 and 4:
Each of these settings defines the entry price of each pullback level. If Pullback 1 is set to -6 it means that the moving average calculation should be 6% lower than the actual price.
The same logic applies to Pullback 2, 3 and 4.
Setting any level to 0 will disable the level – eliminating any orders to emit on that level.
This can be used to change the level of pyramiding down from 4 if needed.
If you do this, remember to also change the order size and the pyramiding value in the Properties tab accordingly.
- Close settings , Use dynamic TP and SL:
If enabled, script will exit all orders using the same but separate algorithm for moving averages. This enables the user to define if you want the orders to be closed if the price level of this moving average is hit. The price level for this calculation is visible on the chart by the blue line.
Although you can change the length and offset, as described underneath, this calculation uses the same data and source type defined in the Open settings area.
- Close settings , Length, Close:
This is the length used for the closing moving average calculations. 3 means it takes the last 3 bars of historical data for the calculation.
- Close settings , Offset, Close:
This defines if the calculation for the closing moving average should use an offset for the historical data. Just as the offset used for opening order, this does not use a look-forward feature, but a look-backward feature. To prevent any possible repaints the offset can only be positive, not negative.
For instance, if the length is 3 and the offset is 0 the calculation is made from the last 3 bars, making it bar1, bar2 and bar3. If the length is 3 and the offset is 1 the calculation is made from bar2, bar3, and bar4 – offsetting the calculation by 1 bar.
- Close settings , Use TakeProfit:
This toggle enables/disables a fixed take profit percentage.
- Close settings , TP %:
This sets the wanted % to reach on a take profit. This setting is ignored if the toggle above is disabled.
- Close settings , Use StopLoss:
This toggle enables/disables a fixed stop loss percentage.
- Close settings , SL %:
This sets the wanted % to reach on a stop loss. This setting is ignored if the toggle above is disabled.
Exit on Same Bar as Entry
By default, the script doesn't emit any exit orders on the same bar as the first entry order. Enable "Recalculation: After order is filled" to change this behavior.
Troubleshooting
While Pullback_Power is designed to provide reliable trading signals, you may encounter rare issues. One such issue could be receiving an error message stating "can't open orders with 0 or negative qty." If you encounter this error, it is likely due to specific conditions on the selected timeframe. To resolve this issue, change the timeframe on your trading chart.
Underlying Principles and Value Proposition
Pullback_Power leverages moving averages and volatility behavior to identify market retracements and capitalize on them. The strategy is rooted in the understanding that markets often experience temporary reversals or "pullbacks" before resuming their primary trend. By identifying these pullbacks and entering trades at opportune moments, Pullback_Power aims to capture quick profits from short-term market movements.
The dynamic and fixed calculations of Take Profit (TP) and Stop Loss (SL) levels enhances risk management, ensuring that potential losses are controlled while allowing room for profits to grow. The adaptive approach using the moving averages considers current market conditions, making the strategy flexible and responsive to changing volatility.
Moreover, Pullback_Power's non-repainting nature ensures the reliability of its signals, eliminating hindsight bias and providing traders with actionable insights based on real-time market data.
The strategy's simplicity and effectiveness make it accessible for traders of all experience levels. Whether you're a beginner looking to start scalping or an experienced trader seeking to diversify your trading approach, Pullback_Power offers a balanced blend of simplicity and sophistication to help you navigate the markets with confidence.
By focusing on clear, transparent principles and offering practical tools for risk management, Pullback_Power aims to provide tangible value to traders, empowering them to make informed decisions and optimize their trading outcomes.
Thank you for choosing Pullback_Power. I wish you successful trading!
Buy Sell Strategy With Z-Score [TradeDots]The "Buy Sell Strategy With Z-Score" is a trading strategy that harnesses Z-Score statistical metrics to identify potential pricing reversals, for opportunistic buying and selling opportunities.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
This approach provides an estimation of the price's departure from its traditional trajectory, thereby identifying market conditions conducive to an asset being overpriced or underpriced.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURUSD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Commission: 0.03%
Initial Capital: $10,000
Equity per Trade: 30%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Fibonacci Trend Reversal StrategyIntroduction
This publication introduces the " Fibonacci Retracement Trend Reversal Strategy, " tailored for traders aiming to leverage shifts in market momentum through advanced trend analysis and risk management techniques. This strategy is designed to pinpoint potential reversal points, optimizing trading opportunities.
Overview
The strategy leverages Fibonacci retracement levels derived from @IMBA_TRADER's lance Algo to identify potential trend reversals. It's further enhanced by a method called " Trend Strength Over Time " (TSOT) (by @federalTacos5392b), which utilizes percentile rankings of price action to measure trend strength. This also has implemented Dynamic SL finder by utilizing @veryfid's ATR Stoploss Finder which works pretty well
Indicators:
Fibonacci Retracement Levels : Identifies critical reversal zones at 23.6%, 50%, and 78.6% levels.
TSOT (Trend Strength Over Time) : Employs percentile rankings across various timeframes to gauge the strength and direction of trends, aiding in the confirmation of Fibonacci-based signals.
ATR (Average True Range) : Implements dynamic stop-loss settings for both long and short positions, enhancing trade security.
Strategy Settings :
- Sensitivity: Set default at 18, adjustable for more frequent or sparse signals based on market volatility.
- ATR Stop Loss Finder: Multiplier set at 3.5, applying the ATR value to determine stop losses dynamically.
- ATR Length: Default set to 14 with RMA smoothing.
- TSOT Settings: Hard-coded to identify percentile ranks, with no user-adjustable inputs due to its intrinsic calculation method.
Trade Direction Options : Configurable to support long, short, or both directions, adaptable to the trader's market assessment.
Entry Conditions :
- Long Entry: Triggered when the price surpasses the mid Fibonacci level (50%) with a bullish TSOT signal.
- Short Entry: Activated when the price falls below the mid Fibonacci level with a bearish TSOT indication.
Exit Conditions :
- Employs ATR-based dynamic stop losses, calibrated according to current market volatility, ensuring effective risk management.
Strategy Execution :
- Risk Management: Features adjustable risk-reward settings and enables partial take profits by default to systematically secure gains.
- Position Reversal: Includes an option to reverse positions based on new TSOT signals, improving the strategy's responsiveness to evolving market conditions.
The strategy is optimized for the BYBIT:WIFUSDT.P market on a scalping (5-minute) timeframe, using the default settings outlined above.
I spent a lot of time creating the dynamic exit strategies for partially taking profits and reversing positions so please make use of those and feel free to adjust the settings, tool tips are also provided.
For Developers: this is published as open-sourced code so that developers can learn something especially on dynamic exits and partial take profits!
Good Luck!
Disclaimer
This strategy is shared for educational purposes and must be thoroughly tested under diverse market conditions. Past performance does not guarantee future results. Traders are advised to integrate this strategy with other analytical tools and tailor it to specific market scenarios. I was only sharing what I've crafted while strategizing over a Solana Meme Coin.
Channels With NVI Strategy [TradeDots]The "Channels With NVI Strategy" is a trading strategy that identifies oversold market instances during a bullish trading market. Specifically, the strategy integrates two principal indicators to deliver profitable opportunities, anticipating potential uptrends.
2 MAIN COMPONENTS
1. Channel Indicators: This strategy gives users the flexibility to choose between Bollinger Band Channels or Keltner Channels. This selection can be made straight from the settings, allowing the traders to adjust the tool according to their preferences and strategies.
2. Negative Volume Indicator (NVI): An indicator that calculates today's price rate of change, but only when today's trading volume is less than the previous day's. This functionality enables users to detect potential shifts in the trading volume with time and price.
ENTRY CONDITION
First, the assets price must drop below the lower band of the channel indicator.
Second, NVI must ascend above the exponential moving average line, signifying a possible flood of 'smart money' (large institutional investors or savvy traders), indicating an imminent price rally.
EXIT CONDITION
Exit conditions can be customized based on individual trading styles and risk tolerance levels. Traders can define their ideal take profit or stop loss percentages.
Moreover, the strategy also employs an NVI-based exit policy. Specifically, if the NVI dips under the exponential moving average – suggestive of a fading trading momentum, the strategy grants an exit call.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
RSI and ATR Trend Reversal SL/TPQuick History:
I was frustrated with a standard fixed percent TP/SL as they often were not receptive to quick market rallies/reversals. I developed this TP/SL and eventually made it into a full fledge strategy and found it did well enough to publish. This strategy can be used as a standalone or tacked onto another strategy as a TP/SL. It does function as both with a single line. This strategy has been tested with TSLA , AAPL, NVDA, on the 15 minutes timeframe.
HOW IT WORKS:
Inputs:
Length: Simple enough, it determines the length of the RSI and ATR used.
Multiplier: This multiplies the RSI and ATR calculation, more on this later.
Delay to prevent Idealization: TradingView will use the open of the bar the strategy triggers on when calculating the backtest. This can produce unrealistic results depending on the source. If your source is open, set to 0, if anything else, set to 1.
Minimum Difference: This is essentially a traditional SL/TP, it is borderline unnecessary, but if the other parameters are wacky this can be used to ensure the SL/TP. It multiplies the source by the percent, so if it is set to 10, the SL/TP is initialized at src +- 10%.
Source input: Self Explanatory, be sure to update the Delay if you use open.
CALCULATION:
Parameters Initialization:
The strategy uses Heikinashi values for calculations, this is not toggleable in parameters, but can be easily changed by changing hclose to equal src.
FUNCTION INITIALIZATION:
highest_custom and lowest_custom do the same thing as ta.highest and ta.lowest, however the built in ta library does not allow for var int input, so I had to create my own functions to be used here. I actually developed these years ago and have used them in almost every strategy since. Feel especially free to use these in your own scripts.
The rsilev is where the magic happens.
SL/TP min/max are initially calculated to be used later.
Then we begin by establishing variables.
BullGuy is used to determine the length since the last crossup or crossdown, until one happens, it returns na, breaking the function. BearGuy is used in all the calculations, and is the same as BullGuy, unless BullGuy is na, where BearGuy counts up from 1 on each bar from 0.
We create our rsi and have to modify the second one to suit the function. In the case of the upper band, we mirror the lower one. So if the RSI is 80, we want it to be 20 on the upper band.
the upper band and lower band are calculated the exact same way, but mirrored. For the purpose of writing, I'm going to talk about the lower band. Assume everything is mirrored for the upper one. It finds the highest source since the last crossup or crossdown. It then multiplies from 1 / the RSI, this means that a rapid RSI increase will increase the band dramatically, so it is able to capture quick rally/reversals. We add this to the atr to source ratio, as the general volatility is a massive factor to be included. We then multiply this number by our chosen amount, and subtract it from the highest source, creating the band.
We do this same process but mirrored with both bands and compared it to the source. If the source is above the lower band, it suggests an uptrend, so the lower band is outputted, and vice versa for the upper one.
PLOTTING:
We also determine the line color in the same manner as we do the trend direction.
STRATEGY:
We then use the source again, and if it crosses up or down relative to the selected band, we enter a long or short respectively.
This may not be the most superb independent strategy, but it can be very useful as a TP/SL for your chosen entry conditions, especially in volatile markets or tickers.
Thank you for taking the time to read, and please enjoy.
Trend Catcher Strategywhat is Trend Catcher Strategy?
it is a strategy that opens long or short positions in the direction of the trend.
what it does?
TCS detects trend formations using its own unique method. Then, it opens a position in the direction of the trend and closes a part of the opened transaction (half according to default values) when the price reaches a certain level, and moves the remaining position to the point where it thinks the trend is over. You can easily understand how it works by looking at the images:
how it does it?
It obtains a value called a "limit" by dividing the difference between the highest value and the lowest value in a certain range (that is, the vector sum) to the sum of the lengths of the candles in a certain range (the total distance traveled). then multiplies this by 100 to get a percentage value. The closer this value is to 100, the stronger the trend.
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
ORB Heikin Ashi SPY 5min Correlation StrategyOverview:
The ORB (Opening Range Breakout) strategy combined with Heikin Ashi candles and Relative Volume (RVOL) indicator aims to capitalize on significant price movements that occur shortly after the market opens. This strategy identifies breakouts above or below the opening range, using Heikin Ashi candles for smoother price visualization and RVOL to gauge the strength of the breakout.
Components:
Opening Range Breakout (ORB): The strategy starts by defining the opening range, typically the first few minutes of the trading session. It then identifies breakouts above the high or below the low of this range as potential entry points.
Heikin Ashi Candles: Heikin Ashi candles are used to provide a smoother representation of price movements compared to traditional candlesticks. By averaging open, close, high, and low prices of the previous candle, Heikin Ashi candles reduce noise and highlight trends more effectively.
Relative Volume (RVOL): RVOL compares the current volume of a stock to its average volume over a specified period. It helps traders identify abnormal trading activity, which can signal potential price movements.
Candle for correlation : In this case we are using SPY candles. It can also use different asset
Strategy Execution:
Initialization: The strategy initializes by setting up variables and parameters, including the ORB period, session timings, and Heikin Ashi candle settings.
ORB Calculation: It calculates the opening range by identifying the high and low prices during the specified session time. These values serve as the initial reference points for potential breakouts. For this we are looking for the first 30 min of the US opening session.
After that we are going to use the next 2 hours to check for breakout opportunities.
Heikin Ashi Transformation: Optionally, the strategy transforms traditional candlestick data into Heikin Ashi format for smoother visualization and trend identification.
Breakout Identification: It continuously monitors price movements within the session and checks if the current high breaches the ORB high or if the current low breaches the ORB low. These events trigger potential long or short entry signals, respectively.
RVOL Analysis: Simultaneously, the strategy evaluates the relative volume of the asset to gauge the strength of the breakout. A surge in volume accompanying the breakout confirms the validity of the signal. In this case we are looking for at least a 1 value of the division between currentVolume and pastVolume
Entry and Exit Conditions: When a breakout occurs and is confirmed by RVOL and is within our session time, the strategy enters a long or short position accordingly. It does not have a stop loss or a takie profit level, instead it will always exit at the end of the trading session, 5 minutes before
Position Sizing and Commissions: For the purpose of this backtest, the strategy allocated 10% of the capital for each trade and assumes a trading commission of 0.01$ per share ( twice the IBKR broker values)
Session End: At the end of the trading session, the strategy closes all open positions to avoid overnight exposure.
Conclusion:
The combination of ORB breakout strategy, Heikin Ashi candles, and RVOL provides traders with a robust framework for identifying and capitalizing on early trends in the market. By leveraging these technical indicators together, traders can make more informed decisions and improve the overall performance of their trading strategies. However, like any trading strategy, it's essential to backtest thoroughly and adapt the strategy to different market conditions to ensure its effectiveness over time.
