Nifty scalping 3 minutes options on Dhan
Strategy Description for Publishing: Nifty Scalping 3 Minutes Options on Dhan
Overview:
The Nifty Scalping 3 Minutes Options on Dhan strategy is an enhanced version tailored for trading Nifty Options, building on the core logic used in the previously published Nifty Scalping 3 Minutes Strategy. This strategy provides automated order execution via JSON alerts for seamless integration with the Dhan platform, enabling hands-free options trading.
This system is designed to capture short-term market moves using a combination of technical indicators like the Jurik Moving Average (JMA), Exponential Moving Average (EMA), and Bollinger Bands, while also allowing traders to manage risk effectively with custom inputs for maximum loss per lot and partial profit booking.
For more details on the core logic and performance of the strategy, please refer to our earlier published strategy:
Nifty Scalping 3 Minutes Strategy
Key Features:
JMA and EMA Crossovers: Trades are executed when the Jurik Moving Average (JMA) crosses over (for long trades) or under (for short trades) the Exponential Moving Average (EMA), signaling trend direction.
Price-Volume Spike Detection: Ensures that trades are executed only when significant market activity is detected, avoiding low-momentum conditions. Price-volume relationships are monitored to confirm the strength of market movements.
Bollinger Band Noise Filter: Filters out low-volatility periods by executing trades only when prices break through the upper or lower Bollinger Bands, confirming high volatility.
Customizable Risk Management: Traders can set their own maximum risk per lot (e.g., ₹650), and the strategy adjusts the stop-loss accordingly to ensure that no trade exceeds this threshold.
Partial Profit Booking: A predefined percentage (e.g., 60%) of the position can be booked as profit once the first profit target is reached, with the remaining position trailed using an ATR-based stop.
STBT/BTST Support: The strategy offers the flexibility to carry trades overnight, supporting Sell Today, Buy Tomorrow (STBT) and Buy Today, Sell Tomorrow (BTST).
Time-Based Exit: The strategy automatically closes any open positions by 3:20 PM to avoid the volatile end-of-day market conditions.
Inputs for Traders:
Option Quantity: Select the number of contracts to trade (e.g., 10).
Maximum Risk Per Lot: Set your maximum allowable loss per lot (e.g., ₹650), ensuring that your risk is managed effectively.
Partial Profit Booking Percentage: Define what percentage of your position to book as profit (e.g., 60%) when the first target is hit.
STBT/BTST Option: Choose whether to allow positions to be carried overnight.
Alert Secret Key: Input your secret key for the Dhan platform to trigger automated orders via JSON alerts.
Option Expiry Date: Specify the expiry date for the options being traded.
Trade Logic:
Long Trades: Triggered when JMA crosses above EMA, supported by filters like price-volume spikes and Bollinger Band breakouts. The strategy waits for momentum confirmation before entering long trades, with stop-loss and profit-taking mechanisms in place.
Short Trades: Triggered when JMA crosses below EMA, with confirmation through additional filters to ensure strong market trends before entering short positions.
Risk Management:
Stop-Loss: A dynamic stop-loss is placed for each trade based on the trader's maximum risk per lot. The stop-loss adapts to market conditions using ATR trailing stops to capture further gains as the trade progresses.
Partial Profit Booking: Once the first profit target is hit (2.1x risk for long trades and 2.5x risk for short trades), a percentage of the position is booked as profit, and the remainder is trailed using an ATR stop.
Automation via JSON Alerts:This strategy sends automated JSON alerts to the Dhan platform for seamless execution of orders. The alerts support multi-leg orders for both entry and exit, ensuring that trades are executed efficiently without manual intervention.
Why Use This Strategy?
The Nifty Scalping 3 Minutes Options on Dhan strategy is perfect for traders who want to capitalize on quick market moves in options, backed by strong risk management and automation. With automated alerts, customizable inputs, and advanced technical filters, this strategy is ideal for traders looking to engage in high-probability options trades with minimal effort.
For more detailed information about the underlying logic, you can refer to the previously published Nifty Scalping 3 Minutes Strategy here.
Disclaimer:
This strategy is provided as an educational tool, and we are not affiliated with or sponsored by Dhan. The strategy integrates with the Dhan platform for automated trading, but there is no formal relationship between this strategy and Dhan.
ابحث في النصوص البرمجية عن "momentum"
Averaging Down Strategy1. Averaging Down:
Definition: "Averaging Down" is a strategy in which an investor buys more shares of a declining asset, thus lowering the average purchase price. The main idea is that, by averaging down, the investor can recover faster when the price eventually rebounds.
Risk Considerations: This strategy assumes that the asset will recover in value. If the price continues to decline, however, the investor may suffer larger losses. Academic research highlights the psychological bias of loss aversion that often leads investors to engage in averaging down, despite the increased risk (Barberis & Huang, 2001).
2. RSI (Relative Strength Index):
Definition: The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions. A reading below 30 (or in this case, 35) typically indicates an oversold condition, which might suggest a potential buying opportunity (Wilder, 1978).
Risk Considerations: RSI-based strategies can produce many false signals in range-bound or choppy markets, where prices do not exhibit strong trends. This can lead to multiple losing trades and an overall negative performance (Gencay, 1998).
3. Combination of RSI and Price Movement:
Approach: The combination of RSI for entry signals and price movement (previous day's high) for exit signals aims to capture short-term market reversals. This hybrid approach attempts to balance momentum with price confirmation.
Risk Considerations: While this combination can work well in trending markets, it may struggle in volatile or sideways markets. Additionally, a significant risk of averaging down is that the trader may continue adding to a losing position, which can exacerbate losses if the price keeps falling.
Risk Warnings:
Increased Losses Through Averaging Down:
Averaging down involves buying more of a falling asset, which can increase exposure to downside risk. Studies have shown that this approach can lead to larger losses when markets continue to decline, especially during prolonged bear markets (Statman, 2004).
A key risk is that this strategy may lead to significant capital drawdowns if the price of the asset does not recover as expected. In the worst-case scenario, this can result in a total loss of the invested capital.
False Signals with RSI:
RSI-based strategies are prone to generating false signals, particularly in markets that do not exhibit strong trends. For example, Gencay (1998) found that while RSI can be effective in certain conditions, it often fails in choppy or range-bound markets, leading to frequent stop-outs and drawdowns.
Psychological Bias:
Behavioral finance research suggests that the "Averaging Down" strategy may be influenced by loss aversion, a bias where investors prefer to avoid losses rather than achieve gains (Kahneman & Tversky, 1979). This can lead to poor decision-making, as investors continue to add to losing positions in the hope of a recovery.
Empirical Studies:
Gencay (1998): The study "The Predictability of Security Returns with Simple Technical Trading Rules" found that technical indicators like RSI can provide predictive value in certain markets, particularly in volatile environments. However, they are less reliable in markets that lack clear trends.
Barberis & Huang (2001): Their research on behavioral biases, including loss aversion, explains why investors are often tempted to average down despite the risks, as they attempt to avoid realizing losses.
Statman (2004): In "The Diversification Puzzle," Statman discusses how strategies like averaging down can increase risk exposure without necessarily improving long-term returns, especially if the underlying asset continues to perform poorly.
Conclusion:
The "Averaging Down Strategy with RSI" combines elements of technical analysis with a psychologically-driven averaging down approach. While the strategy may offer opportunities in trending or oversold markets, it carries significant risks, particularly in volatile or declining markets. Traders should be cautious when using this strategy, ensuring they manage risk effectively and avoid overexposure to a losing position.
Price-Volume w Trendline - Strategy [presentTrading]█ Introduction and How it is Different
The Price-Volume with Trendline Strategy is an innovative strategy that combines volume profile analysis, price-based Z-scores, and dynamic trendline filtering to identify optimal entry and exit points in the market. What sets this strategy apart is the integration of volume concentration (Point of Control or PoC) with dynamic volatility thresholds. Additionally, this strategy introduces a multi-step take profit (TP) mechanism that adjusts based on predefined levels, allowing traders to exit trades progressively while capitalizing on market momentum.
BTCUSD 6hr LS Performance
█ Strategy, How it Works: Detailed Explanation
The combination of multiple indicators and methodologies serves to create a more robust and reliable trading system. Each element is carefully chosen for its complementary role in providing accurate signals while minimizing false entries and exits. Here’s why the different components were chosen and how they work together:
- PoC and Z-Scores: The volume profile identifies key price areas, while the Z-score measures deviations from the mean. Together, they highlight points where the market is likely to react. For example, when the Z-score indicates an oversold condition near a PoC support level, it increases the probability of a reversal, providing a clear entry signal.
- Trendlines and Z-Scores: Trendlines serve as a secondary filter to ensure that price deviations identified by Z-scores align with broader market trends. This ensures that trades are only entered when the price has both deviated from its average and broken through a significant trendline level, reducing the likelihood of false signals.
- Multi-Step TP and Risk Management: Finally, the multi-step take profit logic works in tandem with the entry signals generated by the PoC, Z-scores, and trendlines. As the price moves in favor of the trade, profits are gradually locked in, ensuring the trader captures gains while still leaving room for further upside.
🔶 Point of Control (PoC) and Volume Profile Analysis
The PoC identifies the price level with the highest volume concentration within a specified lookback period. This price level represents where the most trading activity has occurred, often acting as a strong support or resistance. By breaking down the range into several rows (bins), the strategy identifies how much volume was traded at each price level.
🔶 Z-Score Calculation
The Z-score is a statistical metric that measures how far the current price is from its mean, expressed in terms of standard deviations. This is calculated both for price deviation and PoC-based deviation.
🔶 Trendline Breakout Filtering
The trendline filtering is a crucial aspect that refines entry signals by confirming trend continuation or reversals. It calculates trendlines based on pivot highs and lows using the selected method (e.g., ATR or standard deviation).
🔶 Multi-Step Take Profit
The multi-step take profit mechanism allows the strategy to take partial profits at several predefined levels. For example, when the price reaches 3%, 8%, 14%, or 21% above (or below) the entry price, it exits portions of the position. This is a useful technique for locking in profits as the market moves favorably.
Local
█ Usage
The Price-Volume with Trendline Strategy can be applied to various asset classes, including stocks, cryptocurrencies, and commodities. It is particularly effective in volatile markets where price deviations and volume concentrations signal potential reversals or trend continuations. By adjusting the settings for volatility and the lookback period, this strategy can be tailored to both short-term intraday trades and longer-term swing trades.
█ Default Settings
The default settings in the strategy play a vital role in shaping its performance.
- POC_lookbackLength (144): This defines the number of bars used to calculate the PoC. A longer lookback captures more data, leading to a more stable PoC, but may result in delayed signals. A shorter lookback increases responsiveness but may introduce noise.
- priceDeviationLength (200): This determines the period for calculating the standard deviation of price. A higher length smooths out the volatility, reducing the likelihood of false signals. Shorter lengths make the strategy more sensitive to sudden price movements.
- TL_length (14): Controls the swing detection period for trendline calculation. A shorter length will generate more frequent trendline breakouts, while a longer length captures only significant moves.
- Stop Loss and Take Profit: The strategy offers both fixed and SuperTrend-based stop losses. SuperTrend is adaptive to volatility, while fixed stop losses provide simpler risk control. The multi-step take profit ensures that profits are secured progressively, which can improve performance in trending markets by reducing the risk of full reversals.
Each of these settings can significantly affect the strategy’s risk-reward balance. For instance, increasing the stop loss level or the take profit percentages allows the strategy to stay in trades longer, potentially increasing profit per trade but at the cost of larger drawdowns. Conversely, tighter stops and smaller profit targets result in more frequent trades with lower average profit per trade.
Fractal Proximity MA Aligment Scalping StrategyFractal Analysis
Fractals in trading help identify potential reversal points by marking significant price changes. Our strategy calculates a "fractal value" by comparing the current price to recent high and low fractal points. This is done by evaluating the sum of distances from the current closing price to the recent highs and lows. A positive fractal value suggests proximity to recent lows, hinting at upward momentum. Conversely, a negative value indicates closeness to recent highs, signaling potential downward movement.
Moving Averages for Confirmation
We use a series of 20 moving averages ranging from 5 to 100 to confirm trend directions indicated by fractal analysis. An entry signal is considered bullish when shorter-term moving averages are all above a long-term moving average, aligning with a positive fractal value.
Exit Strategy
The strategy employs dynamic stop-loss levels set at various moving averages, allowing for partial exits when the price crosses below specific thresholds. This helps manage the trade by locking in profits gradually. A full exit might be triggered by strong reversal signals suggested by both fractal values and moving average trends.
This open-source strategy is available for the community to test, adapt, and utilize. Your feedback and modifications are welcome as we refine the approach based on collective user experiences.
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Negroni Opening Range StrategyStrategy Summary:
This tool can be used to help identify breakouts from a range during a time-zone of your choosing. It plots a pre-market range, an opening range, it also includes moving average levels that can be used as confluence, as well as plotting previous day SESSION highs and lows.
There are several options on how you wish to close out the trades, all described in more detail below.
Back-testing Inputs:
You define your timezone.
You define how many trades to open on any given day.
You decide to go: long only, short only, or long & short (CAREFUL: "Long & Short" can open trades that effectively closes-out existing ones, for better AND worse!)
You define between which times the strategy will open trades.
You define when it closes any open trades (preventing overnight trades, or leaving trades open into US data times!!).
This hopefully helps make back-testing reflect YOUR trading hours.
NOTE: Renko or Heikin-Ashi charts
For ALL strategies, don’t use Renko or Heikin-Ashi charts unless you know EXACTLY the implications.
Specific to my strategy, using a renko chart can make this 85-90% profitable (I wish it was!!) Although they can be useful, renko charts don’t always capture real wicks, so the renko chart may show your trade up-only but your broker (who is not using renko!!) will have likely stopped you out on a wick somewhere along the line.
NOTE: TradingView ‘Deep backtesting’
For ALL strategies, be cynical of all backtesting (e.g. repainting issues etc) as well as ‘Deep backtesting’ results.
Specific to this strategy, the default settings here SHOULD BE OK, but unfortunately at the time of writing, we can’t see on the chart what exactly ‘deep backtesting’ is calculating. In the past I have noted a number of trades that were not closed at the end of the day, despite my ‘end of day’ trade closing being enabled, so there were big winners and losers that would not have materialized otherwise. As I say, this seems ok at these settings but just always be cynical!!
Opening Range Inputs
You define a pre-market range (example: 08:00 - 09:00).
You define an opening range (example: 09:00 - 09:30).
The strategy will give an update at the close of the opening range to let you know if the opening range has broken out the pre-market range (OR Breakout), or if it has remained inside (OR Inside). The label appears at the end of the opening range NOT at the bar that ‘broke-out’.
This is just a visual cue for you, it has no bearing on what the strategy will do.
The strategy default will trade off the pre-market range, but you can untick this if you prefer to trade off the opening range.
Opening Trades:
Strategy goes long when the bar (CLOSE) crosses-over the ‘pre-market’ high (not the ‘opening range’ high); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Strategy goes short when the bar (CLOSE) crosses-under the ‘pre-market’ low (not the ‘opening range low); and the time is within your trading session, and you have not maxed out your number of trades for the day!
Remember, you can untick this if you prefer to trade off the opening range instead.
NOTES:
Using momentum indicators can help (RSI and MACD): especially to trade range plays in failed breakouts, when momentum shifts… but the strategy won’t do this for you!
Using an anchored vwap at the session open can also provide nice confluence, as well as take-profit levels at the upper/lower of 3x standard deviation.
CLOSING TRADES:
You have 6 take-profit (TP) options:
1) Full TP: uses ATR Multiplier - Full TP at the ATR parameters as defined in inputs.
2) Take Partial profits: ATR Multiplier - Takes partial profits based on parameters as defined in inputs (i.e close 40% of original trade at TP1, close another 40% of original trade at TP2, then the remainder at Full TP as set in option 1.).
3) Full TP: Trailing Stop - Applies a Trailing Stop at the number of points, as defined in inputs.
4) Full TP: MA cross - Takes profit when price crosses ‘Trend MA’ as defined in inputs.
5) Scalp: Points - closes at a set number of points, as defined in inputs.
6) Full TP: PMKT Multiplier - places a SL at opposite pre-market Hi/Low (we go long at a break-out of the pre-market high, 50% would place a SL at the pre-market range mid-point; 100% would place a SL at the pre-market low)'. This takes profit at the input set in option 1).
TASC 2024.08 Volume Confirmation For A Trend System█ OVERVIEW
This script demonstrates the use of volume data to validate price movements based on the techniques Buff Pelz Dormeier discusses in his "Volume Confirmation For A Trend System" article from the August 2024 edition of TASC's Traders' Tips . It presents a trend-following system implementation that utilizes a combination of three indicators: the Average Directional Index (ADX), the Trend Thrust Indicator (TTI), and the Volume Price Confirmation Indicator (VPCI).
█ CONCEPTS
In his article, Buff Pelz Dormeier recounts his search for an optimal trend-following strategy enhanced with volume data, starting with a simple system combining the ADX , MACD , and OBV indicators. Even in these early tests, the author observed that the volume confirmation from OBV notably improved trading performance. Subsequently, the author replaced OBV with his VPCI, which considers the proportional weights of volume and price, to enhance the validation of trend momentum. Lastly, the author explored the inclusion of his TTI, a modified MACD that features volume-based enhancements, as a strategy component for improved trend-following performance.
According to the author's research, the ADX+TTI+VPCI system outperformed similar strategies he tested in the article, yielding significantly higher returns and enhanced perceived reliability. Because the system's design revolves around catching pronounced trends, it performs best with a portfolio of individual stocks. The author applies the system in the article by allocating 5% of the equity to long positions in S&P 500 components that meet the ADX+TTI+VPCI entry criteria (see the Calculations section below for details). He uses the proceeds from closing positions to enter new positions in other stocks meeting the screening criteria, holding any excess proceeds in cash.
█ CALCULATIONS
The TTI is similar to the MACD. Its calculation entails the following steps:
Calculate fast (short-term) and slow (long-term) volume-weighted moving averages (VWMAs).
Compute the volume multiple (VM) as the square of the ratio of the fast VWMA to the slow VWMA.
Adjust these averages by multiplying the fast VWMA by the VM and dividing the slow VWMA by the VM.
Calculate the difference between the adjusted VWMAs to determine the TTI value, and take the average of that series to determine the signal line value.
The VPCI utilizes differences and ratios between VWMAs and corresponding simple moving averages (SMAs) to provide an alternative volume-price confirmation tool. Its calculation is as follows:
Subtract the slow SMA from the VWMA of the same length to calculate the volume-price confirmation/contradiction (VPC) value.
Divide the fast VWMA by the corresponding fast SMA to determine the volume-price ratio (VPR).
Divide the short-term VWMA by the long-term VWMA to calculate the VM.
Compute the VPCI as the product of the VPC, VPR, and VM values.
The long entry criteria of the ADX+TTI+VPCI system are as follows:
The ADX is above 30.
The TTI crosses above its signal line.
The VPCI is above 0, confirming the trend.
Signals to close positions occur when the VPCI is below 0, indicating a contradiction .
NOTE: Unlike in the article, this script applies the ADX+TTI+VPCI system to one stock at a time , not a portfolio of S&P 500 constituents.
█ DISCLAIMER
This strategy script educates users on the trading system outlined by the TASC article. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
CCI and MACD Auto Trading Strategy with Risk/RewardOverview:
This strategy combines the Commodity Channel Index (CCI) and the Moving Average Convergence Divergence (MACD) indicators to automate trading decisions. It dynamically sets stop-loss and take-profit levels based on recent lows and highs, ensuring a risk/reward ratio of 1:1.5. This script aims to leverage trend and momentum signals while maintaining effective risk management.
Originality and Usefulness:
This script is not just a simple mashup of CCI and MACD indicators; it incorporates dynamic risk management by setting stop-loss and take-profit levels based on recent price action. This approach helps traders to:
・Identify potential trend reversals using the combination of CCI and MACD signals.
・Manage trades effectively by setting realistic stop-loss and take-profit levels based on recent market data.
・Maintain a balanced risk/reward ratio, which is essential for sustainable trading.
Indicators Used:
・CCI (Commodity Channel Index):
・Measures the deviation of the price from its average over a specified period, typically ranging from -100 to +100.
・Helps identify overbought and oversold conditions.
・MACD (Moving Average Convergence Divergence):
・Utilizes the difference between short-term and long-term moving averages to indicate trend strength and direction.
・Provides momentum signals that can be used for timing entries and exits.
How It Works:
Entry Conditions:
Long Entry:
・The MACD histogram is above zero.
・The CCI crosses above the -100 line.
Short Entry:
・The MACD histogram is below zero.
・The CCI crosses below the +100 line.
Exit Conditions:
Long Positions:
・The stop-loss is set at the recent low.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Short Positions:
・The stop-loss is set at the recent high.
・The take-profit is set at 1.5 times the distance between the entry price and the stop-loss.
Risk Management:
・The script dynamically adjusts stop-loss and take-profit levels based on recent market data, ensuring that the risk/reward ratio is maintained at 1:1.5.
・This approach helps in managing the risk effectively while aiming for consistent profits.
Strategy Properties:
・Account Size: Configured for a realistic account size suitable for the average trader.
・Commission and Slippage: Includes settings for realistic commission and slippage to reflect real market conditions.
・Risk per Trade: Designed to risk no more than 5-10% of equity per trade, aligning with sustainable trading practices.
・Backtesting Results: Configured to generate a sufficient sample size (ideally more than 100 trades) for reliable backtesting results.
Revised Backtesting Settings
Ensure that your backtesting settings are realistic:
・Account Size: Set a realistic initial capital suitable for the average trader.
・Commission and Slippage: Include realistic commission fees and slippage.
・Risk Management: Ensure that each trade risks no more than 5-10% of the account equity.
・Sufficient Sample Size: Choose a dataset that will generate more than 100 trades to provide a robust sample size.
KumoTrade Ichimoku StrategyThe KumoTrade Ichimoku Strategy is an advanced trading strategy designed to help users identify market trends and potential trading opportunities using the Ichimoku Kinko Hyo technical analysis indicator. This strategy leverages the Ichimoku cloud (Kumo) along with other crucial indicators such as the Tenkan-sen and Kijun-sen lines to generate strong signals.
Main Components of the Strategy:
Tenkan-sen (Conversion Line): Indicates the short-term direction of the price, typically calculated as the average of the highest high and the lowest low over the past 9 periods.
Kijun-sen (Base Line): Indicates the medium-term direction of the price, usually calculated as the average of the highest high and the lowest low over the past 26 periods.
Senkou Span A and Senkou Span B: These two lines form the cloud (Kumo), which projects future support and resistance levels.
Chikou Span (Lagging Span): Plots the current closing price 26 periods back to measure the market's momentum.
Strategy Rules:
Bullish Bias (Bias Bull): Indicates that the prices are in a long-term uptrend. In this strategy, this is confirmed if the low prices are above the daily EMA (Exponential Moving Average).
Kijun Sen Touch Down: Occurs when prices cross below the Kijun-sen line and then close back above it, indicating a potential bullish reversal.
Tenkan-Kijun Cross Up: A bullish signal generated when the Tenkan-sen line crosses above the Kijun-sen line.
Close Over Tenkan and Kijun: A strong bullish signal when the close price crosses above both the Tenkan-sen and Kijun-sen lines.
Trading Setups:
Long Setup: Generated when the Kijun-sen is above the highest point of the Kumo (senkou_max) and the closing price is below the lowest point of the Kumo (senkou_min). This setup is checked over the last 21 bars.
Short Setup: Generated when the Kijun-sen is below the lowest point of the Kumo (senkou_min) and the closing price is above the highest point of the Kumo (senkou_max). This setup is also checked over the last 21 bars. (Not avalible yet)
Entry Conditions:
Ultra Long Entry: This condition checks for a bullish bias, the Tenkan-Kijun cross up or Kijun Sen touch down, high volume, and that the price is not within the Kumo cloud.
Main Long Entry: This condition requires the closing price to be above the Kumo cloud, a green Kumo cloud, a bullish bias, the Tenkan rule, and that the price is not within the Kumo cloud.
Exit Conditions:
A trailing stop loss is implemented to protect profits. The stop loss level is dynamically updated based on the highest high of the last 5 bars minus three times the ATR (Average True Range) value.
Visuals on the Chart:
The Tenkan-sen and Kijun-sen lines are plotted for visual reference.
The Kumo cloud is displayed with different colors indicating bullish (green) or bearish (red) conditions.
Entry points are marked on the chart, and the trailing stop loss levels are plotted as well.
The KumoTrade Ichimoku Strategy aims to provide a comprehensive approach to trading by combining multiple aspects of the Ichimoku indicator to generate reliable trading signals and manage risk effectively.
Kaufman Adaptive Moving Average (KAMA) Strategy [TradeDots]"The Kaufman Adaptive Moving Average (KAMA) Strategy" is a trend-following system that leverages the adaptive qualities of the Kaufman Adaptive Moving Average (KAMA). This strategy is distinguished by its ability to adjust dynamically to market volatility, enhancing trading accuracy by minimizing the effects of false and delayed signals often associated with the Simple Moving Average (SMA).
HOW IT WORKS
This strategy is centered around use of the Kaufman Adaptive Moving Average (KAMA) indicator, which refines the principles of the Exponential Moving Average (EMA) with a superior smoothing technique.
KAMA distinguishes itself by its responsiveness to changes in market prices through an "Efficiency Ratio (ER)." This ratio is computed by dividing the recent absolute net price change by the cumulative sum of the absolute price changes over a specified period. The resulting ER value ranges between 0 and 1, where 0 indicates high market noise and 1 reflects stronger market momentum.
Using ER, we could get the smoothing constant (SC) for the moving average derived using the following formula:
fastest = 2/(fastma_length + 1)
slowest = 2/(slowma_length + 1)
SC = math.pow((ER * (fastest-slowest) + slowest), 2)
The KAMA line is then calculated by applying the SC to the difference between the current price and the previous KAMA.
APPLICATION
For entering long positions, this strategy initializes when there is a sequence of 10 consecutive rising KAMA lines. Conversely, a sequence of 10 consecutive falling KAMA lines triggers sell orders for long positions. The same logic applies inversely for short positions.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
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.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
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.
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.
Strategy Container_Variable Pyramiding & Leverage [Tradingwhale]This is a strategy container . It doesn’t provide a trading strategy. What it does is provide functionality that is not readily available with standard strategy ’shells.’
More specifically, this Strategy Container enables Tradingview users to create trading strategies without knowing any Pine Script code .
Furthermore, you can use most indicators on tradingview to build a strategy without any coding at all, whether or not you have access to the code.
To illustrate a possible output in the image (buy and sell orders) of this strategy container, we are using here an indicator that provides buy and sell signals, only for illustration purposes. Again, this is a strategy container, not a strategy. So we need to include an indicator with this published strategy to be able to show the strategy execution.
What can you do with this strategy container? Please read below.
Trade Direction
You can select to trade Long trades only, Short trades only, or both, assuming that whatever strategy you create with this container will produce buy and sell signals.
Exit on Opposite
You can select if Long signals cause the exit of Short positions and vice versa. If you turn this on, then a sell/short signal will cause the closing of your entire long position, and a buy/long signal will cause the closing of your entire short position.
Use external data sources (indicators) to (a) import signals, or (b) create trading signals using almost any of the indicators available on Tradingview.
Option 1:
When you check the box ‘Use external indicator Buy & Sell signals?’ and continue to select an external indicator that plots LONG/BUY signals as value '1' and SHORT/SELL signals as value '-1, then this strategy container will use those signals for the strategy, in combination with all other available settings.
Here an example of code in an indicator that you could use to import signals with this strategy container:
buy = long_cond and barstate.isconfirmed
sell = short_cond and barstate.isconfirmed
//—------- Signal for Strategy
signal = buy ? 1 : sell ? -1 : 0
plot(plot_connector? signal : na, title="OMEGA Signals", display = display.none)
Option 2:
You can create buy/long and sell/short signals from within this strategy container under the sections called “ Define 'LONG' Signal ” and “ Define 'SHORT' Signal .”
You can do this with a single external indicator, by comparing two external indicators, or by comparing one external indicator with a fixed value. The indicator/s you use need to be on the same chart as this strategy container. You can add up to two (2) external indicators that can be compared to each other at a time. A checkbox allows you to select whether the logical operation is executed between Source #1 and #2, between Source # 1 and an absolute value, or just by analyzing the behavior of Source #1.
Without an image of the strategy container settings it’s a bit hard to explain. However, below you see a list of all possible operations.
Operations available , whenever possible based on source data, include:
- "crossing"
- "crossing up"
- "crossing down"
- "rejected from resistance (Source #1) in the last bar", which means ‘High’ was above Source #1 (resistance level) in the last completed bar and 'Close' (current price of the symbol) is now below Source #1" (resistance level).
- "rejected from resistance (Source #1) in the last 2 bars", which means ‘High’ was above Source #1 (resistance level) in one of the last two (2) completed bars and 'Close' (current price of the symbol) is now below Source #1" (resistance level).
- "rejected from support (Source #1) in the last bar" --- similar to above except with Lows and rejection from support level
- "rejected from support (Source #1) in the last 2 bars" --- similar to above except with Lows and rejection from support level
- "greater than"
- "less than"
- "is up"
- "is down"
- "is up %"
- "is down %"
Variable Pyramiding, Leverage, and Pyramiding Direction
Variable Pyramiding
With this strategy container, you can define how much capital you want to invest for three consecutive trades in the same direction (pyramiding). You can define what percentage of your equity you want to invest for each pyramid-trade separately, which means they don’t have to be identical.
As an example: You can invest 5% in the first trade let’s call this pyramid trade #0), 10% in the second trade (pyramid trade #1), and 7% in the third trade (pyramid trade #2), or any other combination. If your trading strategy doesn’t produce pyramid trading opportunities (consecutive trades in the same direction), then the pyramid trade settings won’t come to bear for the second and third trades, because only the first trade will be executed with each signal.
Leverage
You can enter numbers for the three pyramid trades that are combined greater than 100%. Once that is the case, you are using leverage in your trades and have to manage the risk that is associated with that.
Pyramiding Direction
You can decide to scale only into Winners, Losers, or Both. Pyramid into a:
- Losers : A losing streak occurs when the price of the underlying security at the current signal is lower than the average cost of the position.
- Winners : A winning streak occurs when the price of the underlying security at the current signal is higher than the average cost of the position.
- Both means that you are selecting to scale/pyramid into both Winning and Losing streaks.
Other Inputs that influence signal execution:
You can choose to turn these on or off.
1. Limit Long exits with a WMA to stay longer in Long positions: If you check this box and enter a Length number (integer) for the WMA (Weighted Moving Average), then Long positions can only be exited with short signals when the current WMA is lower than on the previous bar/candle. Short signals sometimes increase with uptrends. We’re using this WMA here to limit short signals by adding another condition (WMA going down) for the short signal to be valid.
2. Maximum length of trades in the number of candles. Positions that have been in place for the specified number of trades are excited automatically.
3. Set the backtest period (from-to). Only trades within this range will be executed.
4. Market Volatility Adjustment Settings
- Use ATR to limit when Long trades can be entered (enter ATR length and Offset). We’re using the 3-day ATR here, with your entries for ATR length and offset. When the 3-day ATR is below its signal line, then Long trades are enabled; otherwise, they are not.
- Use VIX to limit when Short trades can be entered (enter VIX). If you select this checkbox, then Short trades will only be executed if the daily VIX is above your set value.
- Use Momentum Algo functions to limit Short trades. This uses the average distance of Momentum Highs and Lows over the lookback period to gauge whether markets are calm or swinging more profoundly. Based on that you can limit short entries to more volatile market regimes.
Set:
- Fast EMA and Slow EMA period lengths
- Number of left and right candles for High and Low pivots
- Lookback period to calculate the High/Low average and then the distance between the two.
The assumption here is that greater distances between momentum highs and lows correlate positively with greater volatility and greater swings in the underlying security.
Stop-Loss
Set separate stop-losses based on % for Long and Short positions. If the position loses X% since entry, then the position will be closed.
Take-Profit
Set separate take-profit levels based on % for Long and Short positions. If the position wins X% since entry, then the position will be closed.
Brilliance Academy Secret StrategyThe Brilliance Academy Secret Strategy is a powerful trading strategy designed to identify potential trend reversals and optimize entry and exit points in the market. This strategy incorporates a combination of technical indicators, including Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), Pivot Points, and Bollinger Bands.
Key Features:
MACD Indicator: A momentum oscillator that helps identify changes in trend strength and direction.
RSI Indicator: A momentum oscillator that measures the speed and change of price movements, indicating potential overbought or oversold conditions.
Pivot Points: Key levels used by traders to identify potential support and resistance levels in the market, aiding in trend reversal identification.
Bollinger Bands: Volatility bands placed above and below a moving average, indicating potential market volatility and overbought or oversold conditions.
How to Use:
Long Signals: Look for long signals when the market price is above the 200-period moving average, MACD line crosses below the signal line, RSI is above 30, and price is above the lower Bollinger Band or at a pivot low.
Short Signals: Look for short signals when the market price is below the 200-period moving average, MACD line crosses above the signal line, RSI is below 70, and price is below the upper Bollinger Band or at a pivot high.
Exit Strategy: Long trades are closed when the next short signal occurs or when the profit reaches a fixed take profit percentage (3% above entry price). Short trades are closed when the next long signal occurs or when the profit reaches a fixed take profit percentage (3% below entry price).
Big RunnerPresenting the "Big Runner" technique, dubbed "Sprinter," which is intended to help traders looking for momentum chances recognise important market swings. This approach maximises profit potential while controlling risk by using trend ribbons and moving averages to identify entry and exit locations.
Important characteristics:
Moving Averages: To determine the direction of the underlying trend, moving averages, both rapid and slow, are used. Depending on their preferred trading strategy, traders can alter the duration of these averages.
Trend Ribbon: Shows phases of bullish and bearish momentum by using a ribbon indicator to visualise the strength of the trend. Trend transitions are simple to spot for traders so they can make wise decisions.
Buy and Sell Signals: This tool generates buy and sell signals that indicate possible entry and exit opportunities based on the crossing and crossunder of moving averages.
Stop Loss/Take Profit Management: This feature enables traders to successfully apply risk management methods by giving them the ability to set stop loss and take profit levels as a percentage of the entry price.
Dynamic Position Sizing: Optimises capital allocation for every trade by dynamically calculating position size depending on leverage and portfolio proportion.
Implementation:
Long Entry: Started when a bullish trend is indicated by a price cross above the fast and slow moving averages. To control risk and lock in earnings, stop loss and take profit thresholds are established appropriately.
Short Entry: Indicates a bearish trend when the price crosses below both moving averages. The concepts of risk management are similar, with dynamic calculations used to determine take-profit and stop-loss levels.
Extra Personalisation:
Take Profit/Stop Loss Management: Provides the ability to select a take profit and stop loss
API Integration: This feature improves execution flexibility and efficiency by enabling traders to include custom parameters for automated trading.
Notice:
Trading entails risk, and performances in the past do not guarantee future outcomes. Before making any trades with this approach, careful analysis and risk management are necessary.
In summary:
By integrating risk management procedures with technical indicators, the "Big Runner" strategy provides a thorough method for identifying noteworthy market changes and achieving the best possible trading results. Traders can adjust parameters to suit their interests and style of trading, giving them the confidence to traverse volatile market situations.
RSI Strategy with Manual TP and SL 19/03/2024This TradingView script implements a simple RSI (Relative Strength Index) strategy with manual take profit (TP) and stop-loss (SL) levels. Let's break down the script and analyze its components:
RSI Calculation: The script calculates the RSI using the specified length parameter. RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and typically values above 70 indicate overbought conditions while values below 30 indicate oversold conditions.
Strategy Parameters:
length: Length of the RSI period.
overSold: Threshold for oversold condition.
overBought: Threshold for overbought condition.
trail_profit_pct: Percentage for trailing profit.
Entry Conditions:
For a long position: RSI crosses above 30 and the daily close is above 70% of the highest close in the last 50 bars.
For a short position: RSI crosses below 70 and the daily close is below 130% of the lowest close in the last 50 bars.
Entry Signals:
Long entry is signaled when both conditions for a long position are met.
Short entry is signaled when both conditions for a short position are met.
Manual TP and SL:
Take profit and stop-loss levels are calculated based on the entry price and the specified percentage.
For long positions, the take profit level is set above the entry price and the stop-loss level is set below the entry price.
For short positions, the take profit level is set below the entry price and the stop-loss level is set above the entry price.
Strategy Exits:
Exit conditions are defined for both long and short positions using the calculated take profit and stop-loss levels.
Chart Analysis:
This strategy aims to capitalize on short-term momentum shifts indicated by RSI crossings combined with daily price movements.
It utilizes manual TP and SL levels, providing traders with flexibility in managing their positions.
The strategy may perform well in ranging or oscillating markets where RSI signals are more reliable.
However, it may encounter challenges in trending markets where RSI can remain overbought or oversold for extended periods.
Traders should backtest this strategy thoroughly on historical data and consider optimizing parameters to suit different market conditions.
Risk management is crucial, so traders should carefully adjust TP and SL percentages based on their risk tolerance and market volatility.
Overall, this strategy provides a structured approach to trading based on RSI signals while allowing traders to customize their risk management. However, like any trading strategy, it should be used judiciously and in conjunction with other forms of analysis and risk management techniques.
Yeong RRGThe code outlines a trading strategy that leverages Relative Strength (RS) and Rate of Change (RoC) to make trading decisions. Here's a detailed breakdown of the tactic described by the code:
Ticker and Period Selection: The strategy begins by selecting a stock ticker symbol and defining a period (len) for the calculations, which defaults to 14 but can be adjusted by the user.
Stock and Index Data Retrieval: It fetches the closing price (stock_close) of the chosen stock and calculates its 25-period exponential moving average (stock_ema). Additionally, it retrieves the closing price of the S&P 500 Index (index_close), used as a benchmark for calculating Relative Strength.
Relative Strength Calculation: The Relative Strength (rs) is computed by dividing the stock's closing price by the index's closing price, then multiplying by 100 to scale the result. This metric is used to assess the stock's performance relative to the broader market.
Moving RS Ratio and Rate of Change: The strategy calculates a Simple Moving Average (sma) of the RS over the specified period to get the RS Ratio (rs_ratio). It then computes the Rate of Change (roc) of this RS Ratio over the same period to get the RM Ratio (rm_ratio).
Normalization: The RS Ratio and RM Ratio are normalized using a formula that adjusts their values based on the mean and standard deviation of their respective series over the specified window. This normalization process helps in standardizing the indicators, making them easier to interpret and compare.
Indicator Plotting: The normalized RS Ratio (jdk_rs_ratio) and RM Ratio (jdk_rm_ratio) are plotted on the chart with different colors for visual analysis. A horizontal line (hline) at 100 serves as a reference point, indicating a neutral level for the indicators.
State Color Logic: The script includes a logic to determine the state color (statecolor) based on the previous state color and the current values of jdk_rs_ratio and jdk_rm_ratio. This color coding is intended to visually represent different market states: green for bullish, red for bearish, yellow for hold, and blue for watch conditions.
Signal Generation: The strategy generates buy, sell, hold, and watch signals based on the state color and the indicators' values relative to 100. For example, a buy signal is generated when both jdk_rs_ratio and jdk_rm_ratio are above 100, and the background color is set to green to reflect this bullish condition.
Trade Execution: Finally, the strategy executes trades based on the generated signals. A "BUY" trade is entered when a buy signal is present, and it is closed when a sell signal occurs.
Overall, the strategy uses a combination of RS and RoC indicators, normalized for better comparison, to identify potential buy and sell opportunities based on the stock's performance relative to the market and its momentum.
Self Optimizing ROC [Starbots]Self Optimizing Rate of Change (ROC) Strategy. (non-repainting)
Script constantly tests 15 different ROC parameter combinations for maximum profitability and trades based on the best performing combination.
You will notice that signal lines switch after a bar close sometimes, this is when the strategy optimizes to the better combination and change plots, strategy is dynamic.
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The Rate-of-Change (ROC) indicator, which is also referred to as Momentum, is a pure momentum oscillator that measures the percent change in price from one period to the next. The ROC calculation compares the current price with the price “n” periods ago. The plot forms an oscillator that fluctuates above and below the zero line as the rate of change moves from positive to negative. As a momentum oscillator, ROC signals include centerline crossovers, divergences, and overbought-oversold readings.
ROC = (Close - Close n periods ago) / (Close n periods ago) * 100
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The logic of self - optimizing:
This script is always backtesting 15 different combinations of ROC settings in the background and saves the net. profit gained for every single one of them, then strategy selects and use the best performing combination of settings currently available for you to trade.
It's recalculating on every bar close - if one of the parameters starts performing better than others - have a higher net profit gain (it's literally like running 15 backtests with different settings in the background) strategy switches to that parameter and continues trading like that until one of the other indicator parameters starts performing better again and switches to that settings.
We are optimizing our strategy based on 15 different 'lengths' or also called 'periods' of ROC.
Inputs (ROC period) : (you don't need to change them, you have a nice wide variety of periods)
🔴Roc (default=9) = 5
🟢Roc2 = 6
🔵Roc3 = 7
🟡Roc4 = 8
🟣Roc5 = 9
🟠Roc6 = 10
🔴Roc7 = 11
🟢Roc8 = 12
🔵Roc9 = 13
🟡Roc10 = 14
🟣Roc11 = 15
🟠Roc12 = 16
🟡Roc13 = 17
🟣Roc14 = 18
🟠Roc15 = 20
Backtester in the background works like this:
backtest ROC1 => save net. profit
backtest ROC2 => save net. profit ;
backtest ROC3 => save net. profit ;
..........
..........
backtest ROC15 => save net. profit ;
=>
It will backtest 15 different ROC parameters and save their profits.
Your strategy then trades based on the best performing (highest net.profit) ROC Setting currently available. It will check the calculations and backtest them on every new bar close - it's like running 15 strategies at time, and manually selecting the best performing one.
________________________________________________________________________
If you wish to use it as INDICATOR - turn on 'Recalculate after every tick' in Properties tab to have this script updating constantly and use it as a normal Indicator tool for manual trading.
-- Noise Filter - This will punish the tiny trades made by certain parameters and give more advantage to big average trades. It's basically normal fee calculation, it will deduct 0.xx % fee from every trade when optimizing. You usually want it to have the same number as your fees on exchange. Large number will choose big long swing trades, small number will prioritize small scalping trades.
-- Turn on ROC Combination Profits and spot the worst/best performing combination. You can change periods to get the best performance after checking this table stats.
-- Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
-- Optimizing range - you can decrease the amount of bars/data for optimizing script. This way you can keep it up to date to more recent market by selecting optimizing range to optimize it just from the recent 3-6months of data for example. Strategy before this selected range will normally trade (backtest) based on the first ROC period ( 'Roc(default=9)' Input) parameter in your menu if you have Optimizing Range turned on.
**** I recommend 'Optimizing Range' to be turned off, use max amount of available bars in your history for optimization script.
-- Strategy is trading on the bar close without repaint. You can trade Long-Sell or Long- Short. Alerts available, insert webhook messages.
-- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
-- Recommended ROC periods: from 5 to 24.
-- Recommended Sources : close, hlc3, hlcc4
-- Recommended Chart Timeframe : 4h +
-- Notes window : add your custom comments here or save your webhook messages inside here
-- Trading Session: in a session, you have to specify the time range for every day. It will trade only within this window and close trades when it's out. Session from 9am to 5pm will look like that: 0900-1700 or 7am to 4:30pm 0700-1630. After the colon, you can specify days of the week for your trading session. 1234567 trading all days, 23456 – Monday to Friday ('1 is Sunday here'). 0000-0000:1234567 by default will trade every day nonstop. 00.00am to 00.00pm and 1234567 every day of the week for example - Cryptocurrencies.
This script is simple to use for any trader as it saves a lot of time for searching good parameters on your own. It's self-optimizing and adjusting to the markets on the go.
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
[strategy][1H] SPY slow stochastics
SPY slow stochastics
Overview
The "SPY Auto RSI Stochastics" strategy is designed to leverage a combination of Relative Strength Index (RSI) and Stochastic indicators to identify potential entry and exit points in trading the SPY $SP:SPX.
The technicals:
A simple yet effective strategy for identifying (reversal) trends on SPY (or any asset).
The logic is as follows:
1. Slow stochastics are effective at predicting momentum. They can also be used to effectively identify reversals.
2. A combination of slow and fast RSI (along with an SMA for the fast RSI) can be used to see potential changes in the directional trend of the underlying asset.
3. In order to reduce noise, a band in the middle of RSI values is ignored; think of this as the price converging and potential explosions (sometimes fake) on either side.
4. Outside this noise band, a crossover of fast RSI on slow RSI indicates an upward trend incoming.
5. A crossunder of fast RSI on slow RSI indicates a downward trend incoming.
Strategy Specific Notes -
1. Load this strategy on SPREADEX:SPX on an hourly chart for the best results.
2. This is a generic strategy, use it on anything - index, stocks, etc. You will need to adjust the parameters for the best results.
3. The RSI Upper defines the cutoff for two things -- threshold for entering a long AND exit signal for short. Likewise for RSI Lower.
4. To have alerts on the strategy, add this to your chart, be content with the backtesting results, select "strategy tester", the alert icon, replace the message body with "{{strategy.order.alert_message}}" without the ".
5. In my experience, the strategy won't be immediately profitable upon a signal but it does get there in the backtested results. Intuitively, this makes sense. Reversals take some time to kick in completely.
Inputs
- **slowRSILength**: Length parameter for the slow RSI calculation.
- **fastRSILength**: Length parameter for the fast RSI calculation.
- **smaRSILength**: Length parameter for the Simple Moving Average (SMA) of the fast RSI.
- **RSIUpperThreshold**: Upper threshold for the RSI, used in exit conditions.
- **RSILowerThreshold**: Lower threshold for the RSI, used in exit conditions.
- **RSIUpperDeadzone**: Upper deadzone threshold for the RSI.
- **RSILowerDeadzone**: Lower deadzone threshold for the RSI.
Strategy Logic
- **RSI Calculation**: The script calculates both slow and fast RSI values based on the provided lengths.
- **Entry Condition**: Entry conditions for long and short positions are based on the crossing of fast RSI over slow RSI and SMA RSI, respectively, along with avoidance of RSI deadzones and validation of trade time.
- **Exit Condition**: Exit conditions for both long and short positions are based on crossing RSI thresholds or opposite entry conditions.
Trade Management
- **Position Entry**: Long and short positions are entered based on predefined entry conditions.
- **Position Exit**: Positions are exited based on predefined exit conditions.
- **Alerts**: The script provides alert messages for entry and exit points.
Plotting
- **Slow RSI**: Plots the slow RSI on the chart.
- **SMA RSI**: Plots the Simple Moving Average of fast RSI on the chart.
Example Usage
The defaults work well for SPY on a 1H timeframe.
If you apply this to anything else DAX, EUSTX50, FTSE, CAC (these are what i have); tweak the input parameters.
Plotting
plot(slowRSI, "Slow RSI", color=color.green) //or fastRSI
plot(smaRSI, "SMA RSI", color=color.white)
Conclusion
The "SPY Auto RSI Stochastics" strategy combines RSI and Stochastic indicators to provide potential trade signals for the SPY ETF. Traders can use this strategy with proper risk management and analysis to enhance their trading decisions.
Octopus Nest Strategy Hello Fellas,
Hereby, I come up with a popular strategy from YouTube called Octopus Nest Strategy. It is a no repaint, lower timeframe scalping strategy utilizing PSAR, EMA and TTM Squeeze.
The strategy considers these market factors:
PSAR -> Trend
EMA -> Trend
TTM Squeeze -> Momentum and Volatility by incorporating Bollinger Bands and Keltner Channels
Note: As you can see there is a potential improvement by incorporating volume.
What's Different Compared To The Original Strategy?
I added an option which allows users to use the Adaptive PSAR of @loxx, which will hopefully improve results sometimes.
Signals
Enter Long -> source above EMA 100, source crosses above PSAR and TTM Squeeze crosses above 0
Enter Short -> source below EMA 100, source crosses below PSAR and TTM Squeeze crosses below 0
Exit Long and Exit Short are triggered from the risk management. Thus, it will just exit on SL or TP.
Risk Management
"High Low Stop Loss" and "Automatic High Low Take Profit" are used here.
High Low Stop Loss: Utilizes the last high for short and the last low for long to calculate the stop loss level. The last high or low gets multiplied by the user-defined multiplicator and if no recent high or low was found it uses the backup multiplier.
Automatic High Low Take Profit: Utilizes the current stop loss level of "High Low Stop Loss" and gets calculated by the user-defined risk ratio.
Now, follows the bunch of knowledge for the more inexperienced readers.
PSAR: Parabolic Stop And Reverse; Developed by J. Welles Wilders and a classic trend reversal indicator.
The indicator works most effectively in trending markets where large price moves allow traders to capture significant gains. When a security’s price is range-bound, the indicator will constantly be reversing, resulting in multiple low-profit or losing trades.
TTM Squeeze: TTM Squeeze is a volatility and momentum indicator introduced by John Carter of Trade the Markets (now Simpler Trading), which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
The volatility component of the TTM Squeeze indicator measures price compression using Bollinger Bands and Keltner Channels. If the Bollinger Bands are completely enclosed within the Keltner Channels, that indicates a period of very low volatility. This state is known as the squeeze. When the Bollinger Bands expand and move back outside of the Keltner Channel, the squeeze is said to have “fired”: volatility increases and prices are likely to break out of that tight trading range in one direction or the other. The on/off state of the squeeze is shown with small dots on the zero line of the indicator: red dots indicate the squeeze is on, and green dots indicate the squeeze is off.
EMA: Exponential Moving Average; Like a simple moving average, but with exponential weighting of the input data.
Don't forget to check out the settings and keep it up.
Best regards,
simwai
---
Credits to:
@loxx
@Bjorgum
@Greeny
Triple MA HTF strategy - Dynamic SmoothingThe triple MA strategy is a simple but effective method to trade the trend. The advantage of this script over the existing triple MA strategies is that the user can open a lower time frame chart and select higher time frame inputs for different MA types mainting the visibility on the chart. The dynamic smoothing code makes sure the HTF trendlines are not jagged, but a fluid line visiable on the lower time frame chart. The script comes with a MA crossover and crossunder strategy explained below.
Moving Averages (MA) Crossover for Entry:
Long Entry: A long entry signal is triggered when the moving average line 1 crosses above the moving average line 2. This crossover indicates a potential shift in market sentiment towards the upside. However, to validate this signal, the strategy checks if the moving average 3 on a higher time frame (eg. 4 hour) is in an upward trend. This additional filter ensures that the trade aligns with the prevailing trend on a broader time scale, increasing the probability of success.
Short Entry: Conversely, a short entry signal occurs when the moving average line 1 crosses below the moving average line 2. This crossover suggests a possible downturn in market momentum. However, for a short trade to be confirmed, the strategy verifies that the moving average 3 on the higher time frame is in a downward trend. This confirmation ensures that the trade is in harmony with the overarching market direction.
Exit from Long Position: The strategy triggers an exit signal from a long position when the moving average line 1 crosses below the moving average line 2. This crossover indicates a potential reversal in the market trend, prompting the trader to close their long position and take profits or minimize losses.
Exit from Short Position: Similarly, an exit signal from a short position occurs when the moving average line 1 crosses above the moving average line 2. This crossover suggests a potential shift in market sentiment towards the upside, prompting the trader to exit their short position and manage their risk accordingly.
Features of the script
This Triple MA Strategy is basically the HTF Trend Filter displayed 3 times on the chart. For more infomation on how the MA with dynamic smoothing is calculated I recommend reading the following script:
For risk management I included a simple script to opt for % of eauity or # of contracts of in the instrument. For explanation on how the risk management settings work I refer to my ealier published script:
The strategy is a simplified example for setting up an entry and exit logic based on multiple moving avarages. Hence the script is meant for educational purposes only.
