Dual-Supertrend with MACD - Strategy [presentTrading]## Introduction and How it is Different
The Dual-Supertrend with MACD strategy offers an amalgamation of two trend-following indicators (Supertrend 1 & 2) with a momentum oscillator (MACD). It aims to provide a cohesive and systematic approach to trading, eliminating the need for discretionary decision-making.
Key advantages over traditional single-indicator strategies:
- Dual Supertrend Validation: Utilizes two Supertrend indicators with different ATR periods and factors to confirm the trend direction. This double-check mechanism minimizes false signals.
- Momentum Confirmation: The MACD histogram acts as a momentum filter, confirming entries and exits, thus adding an extra layer of validation.
- Objective Entry and Exit: The strategy generates buy and sell signals based on a combination of trend direction and momentum, leaving no room for subjective interpretation.
- Automated Trade Management: The strategy includes built-in settings for commission, slippage, and initial capital, automating the trade execution process.
- Adaptability: The strategy allows for easy customization of all its parameters, adapting to a trader's specific needs and varying market conditions.
BTCUSD 8hr chart Long Condition
BTCUSD 6hr chart Long Short Condition
## Strategy, How it Works
The strategy operates on a set of clearly defined rules, primarily focusing on the trend direction confirmed by the Dual-Supertrend and the momentum as indicated by the MACD histogram.
### Entry Rules
- Long Entry: When both Supertrend indicators are bullish and the MACD histogram is above zero.
- Short Entry: When both Supertrend indicators are bearish and the MACD histogram is below zero.
### Exit Rules
- Exit long positions when either of the Supertrends turn bearish or the MACD histogram drops below zero.
- Exit short positions when either of the Supertrends turn bullish or the MACD histogram rises above zero.
### Trade Management
- The strategy uses a fixed commission rate and slippage in its calculations.
- Automated risk management features are integrated to avoid overexposure.
## Trade Direction
The strategy allows for trading in both bullish and bearish markets. Users can select their preferred trading direction ("long", "short", or "both") to align with their market outlook and trading objectives.
## Usage
- The strategy is best applied on timeframes where the trend is evident.
- Users can modify the ATR periods, factors for Supertrends, and MACD settings to suit their trading needs.
## Default Settings
- ATR Period for Supertrend 1: 10
- Factor for Supertrend 1: 3.0
- ATR Period for Supertrend 2: 20
- Factor for Supertrend 2: 5.0
- MACD Fast Length: 12
- MACD Slow Length: 26
- MACD Signal Smoothing: 9
- Commission: 0.1%
- Slippage: 1 point
- Trading Direction: Both
The strategy comes with these default settings to offer a balanced trading approach but can be customized according to individual trading preferences.
Индикаторы и стратегии
Strategy:Reversal-CatcherWhat
This is a plain and vanilla reversal based strategy for intraday (15m) timeframe on Futures prices of the assets.
Now what all it comprises of?
It finds out the dynamic support & resistance from Bollinger Band (20 period, 1.5 std dev).
It finds out the potential divergence of price deviation from 5 period exponential moving average (EMA).
If the previous candle (N-1) shows a divergence it confirms the reversal by checking the present candle (N) to be closed inside the Bollinger Band.
It confirms the momentum by checking RSI shows a crossover/crossunder to oversold (30) / overbought (70) region.
It also confirms whether the trend is up (then only reversal trade to short) or down (then only reversal trade to long). The trend is checked with EMA-21 and EMA-50.
Re-affirmation Condition : It re-affirms the position of two successive candles called as `hhLLong` and `hhLLShort` in the script.
Why
In Indian context, retail participants are pre-dominantly (yes- 80% of Indian daily volume) Options buyers mainly in weekly indices (Nifty, BankNifty, FinNifty, CNXMidcap, Sensex, Bankx .. well everyday is expiry now in India, except -- Thank God -- Saturday & Sunday).
And in Index Options the momentum plays a big role.
If one can catch a good reversal point the potential of high Risk-to-Reward trade (hence earn handsomely) is very likely (please note: there is no holy grail in trading. Nothing works 100%).
So this is the attempt to catch a reversal.
Re-affirmation of Reversal
hhLLong : It's a reversal point after an uptrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLong in script.
hhLLShort : It's a reversal point after a downtrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLShort in script.
Unique-ness
What's unique in it? Why we decided to publicly share this:
Already given the context of The Great Indian Options Buyers community. It should be helpful to them, we believe.
It takes Very Less Number of Trades with High Accuracy . Please check the result in NSE:NIFTY1! in 15m timeframe. 71% accuracy with roughly a trade in a month.
There is no point giving brokers' the brokerages taking 10 trades a day and ending not-so-good EoD. Better lets take less trades with better result possibility. .
Mention
There are many people uses this variation of Bolling Band, 5EMA
Many people use RSI, trends and relative positioning of candles.
--> We are grateful to all of them. It's really difficult to mention everyone's name. But all people somehow influence the thought process. Thanks for all of them.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context : We are not SEBI registered, will never be SEBI registered.
Linear Cross Trading StrategyLinear Cross Trading Strategy
The Linear Cross trading strategy is a technical analysis strategy that uses linear regression to predict the future price of a stock. The strategy is based on the following principles:
The price of a stock tends to follow a linear trend over time.
The slope of the linear trend can be used to predict the future price of the stock.
The strategy enters a long position when the predicted price crosses above the current price, and exits the position when the predicted price crosses below the current price.
The Linear Cross trading strategy is implemented in the TradingView Pine script below. The script first calculates the linear regression of the stock price over a specified period of time. The script then plots the predicted price and the current price on the chart. The script also defines two signals:
Long signal: The long signal is triggered when the predicted price crosses above the current price.
Short signal: The short signal is triggered when the predicted price crosses below the current price.
The script enters a long position when the long signal is triggered and exits the position when the short signal is triggered.
Here is a more detailed explanation of the steps involved in the Linear Cross trading strategy:
Calculate the linear regression of the stock price over a specified period of time.
Plot the predicted price and the current price on the chart.
Define two signals: the long signal and the short signal.
Enter a long position when the long signal is triggered.
Exit the long position when the short signal is triggered.
The Linear Cross trading strategy is a simple and effective way to trade stocks. However, it is important to note that no trading strategy is guaranteed to be profitable. It is always important to do your own research and backtest the strategy before using it to trade real money.
Here are some additional things to keep in mind when using the Linear Cross trading strategy:
The length of the linear regression period is a key parameter that affects the performance of the strategy. A longer period will smooth out the noise in the price data, but it will also make the strategy less responsive to changes in the price.
The strategy is more likely to generate profitable trades when the stock price is trending. However, the strategy can also generate profitable trades in ranging markets.
The strategy is not immune to losses. It is important to use risk management techniques to protect your capital when using the strategy.
I hope this blog post helps you understand the Linear Cross trading strategy better. Booost and share with your friend, if you like.
Linear On MACDUnlocking the Magic of Linear Regression in TradingView
In the ever-evolving world of financial markets, traders and investors seek effective tools to gauge price movements, make informed decisions, and achieve their financial goals. One such tool that has proven its worth over time is linear regression, a mathematical concept that has found its way into technical analysis and trading strategies. In this blog post, we will explore the magic behind linear regression, delve into its history, and understand how it's widely used as a technical indicator.
The Birth of Linear Regression: From Mathematics to Trading
Linear regression is a statistical method that aims to model the relationship between two variables by fitting a linear equation to observed data. The formula for a linear regression line is typically expressed as y = a + bx, where y is the dependent variable, x is the independent variable, a is the intercept, and b is the slope.
While the roots of linear regression trace back to the field of statistics, it didn't take long for traders and investors to recognize its potential in the financial world. By applying linear regression to historical price data, traders can identify trends, assess the relationship between variables, and even predict potential future price levels.
The Linear On MACD Strategy
Let's take a closer look at a powerful example of how linear regression is employed in a trading strategy right within TradingView. The "Linear On MACD" strategy harnesses the potential of linear regression in conjunction with the Moving Average Convergence Divergence (MACD) indicator. The goal of this strategy is to generate buy and sell signals based on the interactions between the predicted stock price and the MACD indicator.
Here's a breakdown of the strategy's components:
Calculation of Linear Regression: The strategy begins by calculating linear regression coefficients for the historical stock price based on volume. This helps predict potential future price levels.
Predicted Stock Price: The linear regression results are then used to plot the predicted stock price on the chart. This provides a visual representation of where the price could trend based on historical data.
Buy and Sell Signals: The strategy generates buy signals when certain conditions are met. These conditions include the predicted stock price being between the open and close prices, a rising MACD, and other factors that suggest a potential bullish trend. On the other hand, sell signals are generated based on MACD trends and predicted price levels.
Risk Management: The strategy also incorporates risk tolerance levels to determine entry and exit points. This ensures that traders take into account their risk appetite when making trading decisions.
Embracing the Magic of Linear Regression
As we explore the "Linear On MACD" strategy, we uncover the power of linear regression in aiding traders and investors. Linear regression, a mathematical marvel, seamlessly merges with technical analysis to provide insights into potential price movements. Its historical significance in statistics blends perfectly with the demands of modern financial markets.
Whether you're a seasoned trader or a curious investor, the Linear On MACD strategy exemplifies how a robust mathematical concept can be harnessed to make informed trading decisions. By embracing the magic of linear regression, you're tapping into a tool that continues to evolve alongside the financial world it empowers.
Disclaimer: The information provided in this blog post is for educational purposes only and does not constitute financial advice. Trading and investing carry risks, and it's important to conduct thorough research and consider seeking professional advice before making any trading decisions.
Trend Confirmation StrategyThe profitability and uniqueness of a trading strategy depend on various factors including market conditions, risk management, and the strategy's ability to capitalize on price movements. I'll describe the strategy provided and highlight its potential benefits and differences compared to other strategies:
Strategy Overview:
The provided strategy combines three technical indicators: Supertrend, MACD, and VWAP. It aims to identify potential entry and exit points by confirming trend direction and considering the proximity to the VWAP level. The strategy also incorporates stop-loss and take-profit mechanisms, as well as a trailing stop.
Unique Aspects and Potential Benefits:
Trend Confirmation: The strategy uses both Supertrend and MACD to confirm the trend direction. This dual confirmation can increase the likelihood of accurate trend identification and filter out false signals.
VWAP Confirmation: The strategy considers the proximity of the price to the VWAP level. This dynamic level can act as a support or resistance and provide additional context for entry decisions.
Adaptive Stop Loss: The strategy sets a stop-loss range, which helps provide some tolerance for minor price fluctuations. This adaptive approach considers market volatility and helps prevent premature stop-loss triggers.
Trailing Stop: The strategy incorporates a trailing stop mechanism to lock in profits as the trade moves in the desired direction. This can potentially enhance profitability during strong trends.
Partial Profit Booking: While not explicitly implemented in the provided code, you could consider booking partial profits when the MACD shows a crossover in the opposite direction. This aspect could help secure gains while still keeping exposure to potential further price movements.
Key Differences from Other Strategies:
Dual Indicator Confirmation: The combination of Supertrend and MACD for trend confirmation is a unique aspect of this strategy. It adds an extra layer of filtering to enhance the accuracy of entry signals.
Dynamic VWAP: Incorporating the VWAP level into the decision-making process adds a dynamic element to the strategy. VWAP is often used by institutional traders, and its inclusion can provide insights into the market sentiment.
Adaptive Stop Loss and Trailing: The strategy's use of an adaptive stop-loss range and a trailing stop can help manage risk and protect profits more effectively during changing market conditions.
Partial Profit Booking: The suggestion to consider partial profit booking upon MACD crossovers in the opposite direction is a practical approach to secure gains while staying in the trade.
Caution and Considerations:
Backtesting: Before deploying any strategy in real trading, it's crucial to thoroughly backtest it on historical data to understand its performance under various market conditions.
Risk Management: While the strategy has built-in risk management mechanisms, it's essential to carefully manage position sizes and overall portfolio risk.
Market Conditions: No strategy works well in all market conditions. It's important to be flexible and adjust the strategy or refrain from trading during particularly volatile or unpredictable periods.
Continuous Monitoring: Even though the strategy includes automated components, continuous monitoring of the trades and market conditions is necessary.
Adaptability: Markets can change over time. Traders need to be prepared to adapt the strategy as necessary to stay aligned with evolving market dynamics.
Financial Ratios Fundamental StrategyWhat are financial ratios?
Financial ratios are basic calculations using quantitative data from a company’s financial statements. They are used to get insights and important information on the company’s performance, profitability, and financial health.
Common financial ratios come from a company’s balance sheet, income statement, and cash flow statement.
Businesses use financial ratios to determine liquidity, debt concentration, growth, profitability, and market value.
The common financial ratios every business should track are
1) liquidity ratios
2) leverage ratios
3)efficiency ratio
4) profitability ratios
5) market value ratios.
Initially I had a big list of 20 different ratios for testing, but in the end I decided to stick for the strategy with these ones :
Current ratio: Current Assets / Current Liabilities
The current ratio measures how a business’s current assets, such as cash, cash equivalents, accounts receivable, and inventories, are used to settle current liabilities such as accounts payable.
Interest coverage ratio: EBIT / Interest expenses
Companies generally pay interest on corporate debt. The interest coverage ratio shows if a company’s revenue after operating expenses can cover interest liabilities.
Payables turnover ratio: Cost of Goods sold (or net credit purchases) / Average Accounts Payable
The payables turnover ratio calculates how quickly a business pays its suppliers and creditors.
Gross margin: Gross profit / Net sales
The gross margin ratio measures how much profit a business makes after the cost of goods and services compared to net sales.
With this data, I have created the long and long exit strategy:
For long, if any of the 4 listed ratios,such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is ascending after a quarter, its a potential long entry.
For example in january the gross margin ratio is at 10% and in april is at 15%, this is an increase from a quarter to another, so it will get a long entry trigger.
The same could happen if any of the 4 listed ratios follow the ascending condition since they are all treated equally as important
For exit, if any of the 4 listed ratios are descending after a quarter, such as current ratio or interest coverage ratio or payable turn ratio or gross margin ratio is descending after a quarter, its a potential long exit.
For example in april we entered a long trade, and in july data from gross margin comes as 12% .
In this case it fell down from 15% to 12%, triggering an exit for our trade.
However there is a special case with this strategy, in order to make it more re active and make use of the compound effect:
So lets say on july 1 when the data came in, the gross margin data came descending (indicating an exit for the long trade), however at the same the interest coverage ratio came as positive, or any of the other 3 left ratios left . In that case the next day after the trade closed, it will enter a new long position and wait again until a new quarter data for the financial is being published.
Regarding the guidelines of tradingview, they recommend to have more than 100 trades.
With this type of strategy, using Daily timeframe and data from financials coming each quarter(4 times a year), we only have the financial data available since 2016, so that makes 28 quarters of data, making a maximum potential of 28 trades.
This can however be "bypassed" to check the integrity of the strategy and its edge, by taking for example multiple stocks and test them in a row, for example, appl, msft, goog, brk and so on, and you can see the correlation between them all.
At the same time I have to say that this strategy is more as an educational one since it miss a risk management and other additional filters to make it more adapted for real live trading, and instead serves as a guiding tool for those that want to make use of fundamentals in their trades
If you have any questions, please let me know !
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
TASC 2023.09 The Weekly Factor█ OVERVIEW
TASC's September 2023 edition of Traders' Tips features an article written by Andrea Unger titled “The Weekly Factor", discussing the application of price patterns as filters for trade entries. This script implements a sample trading strategy presented in the article for demonstration purposes only. It explores how the strategy's equity curve might benefit from filtering trade entries using a specific price pattern.
█ CONCEPTS
Pattern filters represent valuable tools that assess current market conditions based on price movements and determine when those conditions become more favorable for trade entries.
The filter used and tested in this article is a metric called the "weekly factor", which measures the price range over the last five trading days and compares it to the open of the session five days ago and the close of the session one day ago (i.e., the "body" of the five-day period). When the five-day body is small compared to the five-day range, this could indicate "indecision" or "compression", potentially followed by a price expansion. Thus, the weekly factor metric can help identify areas in the market where a period of compression might signal a potential breakout.
This script demonstrates the use of the weekly factor for a sample intraday trading strategy (intended for educational and exploratory purposes only). In this strategy, the entry signal is triggered when a 15-minute bar breaks out of the previous day's high-low range, and the position is closed at the end of the day.
█ CALCULATIONS
The script uses two timeframes:
• The strategy entries are processed on the 15-minute timeframe.
• The weekly factor is obtained from the daily timeframe using the request.security function and the following formula:
math.abs(open - close ) < RangeFilter * (ta.highest(5) - ta.lowest(5) )
Here, RangeFilter is an input that can be optimized to find the favorable ratio between the five-day body and the five-day range. Smaller RangeFilter values will lead to fewer trade entries. A RangeFilter value of 1 is equivalent to turning off the filtering altogether.
Merovinh - Mean Reversion Lowest lowThe "Merovinh - Mean Reversion Lowest Low" strategy is a mean reversion trading approach that aims to identify potential reversal points based on the updated lowest low of the specified number of bars. This strategy focuses on the detection of bullish price movements. Works well on Tech giant's shares.
Strategy Overview:
The strategy detects the lowest low and highest high over a specified number of bars.
It uses a mean reversion concept where it expects the price to revert back towards the updated lowest low.
The strategy enters a long position when the current lowest low breaks the previous lowest low (based on the specified number of broken lows).
It closes the long position when the highest high breaks the previous highest high.
The strategy aims to capitalize on potential reversals in the market by buying at lower price levels and selling at higher price levels.
Strategy Parameters:
Minimum number of bars: Specifies the minimum number of bars considered for calculating the lowest low and highest high.
Number of broken lows: Determines the number of previous lows that need to be broken for entering a long position.
How It Works:
The strategy calculates the lowest low and highest high based on the specified number of bars.
It compares the current lowest low with the previous lowest low.
If the current lowest low breaks the previous lowest low (based on the specified number of broken lows), a long position is entered.
The strategy continuously updates the previous lows and highs.
It closes the long position if the highest high breaks the previous highest high.
Pivot Point SuperTrend Strategy +TrendFilterIn the dynamic world of financial markets, traders are always on the lookout for innovative strategies to identify trends and make timely trades. The "Pivot Point SuperTrend strategy +TrendFilter" has emerged as an intriguing approach, combining two popular indicators - Pivot Points and SuperTrend, while introducing an additional trend filter for added precision. This strategy draws inspiration from Lonesome TheBlue's "Pivot Point SuperTrend" script, aiming to provide traders with a reliable tool for trend following while minimizing false signals.
The Core Concept:
The strategy's foundation lies in the fusion of Pivot Points and SuperTrend indicators, and the addition of a robust trend filter. It begins by calculating Pivot Highs and Lows over a specified period, serving as crucial reference points for trend analysis. Through a weighted average calculation, these Pivot Points create a center line, refining the overall indicator.
Next, based on the center line and the Average True Range (ATR) with a user-defined Factor, upper and lower bands are generated. These bands adapt to market volatility, adding flexibility to the strategy. The heart of the "Pivot Point SuperTrend" strategy lies in accurately identifying the prevailing trend, with the indicator smoothly transitioning between bullish and bearish signals as the price interacts with the SuperTrend bands.
The additional trend filter introduced into the strategy further enhances its capabilities. This filter is based on a moving average, providing a dynamic assessment of the trend's strength and direction. By combining this trend filter with the original Pivot Point SuperTrend signals, the strategy aims to make more informed and reliable trading decisions.
Advantages of "Pivot Point SuperTrend" with Trend Filter:
1. Enhanced Precision: The incorporation of a trend filter improves the strategy's accuracy by confirming the overall trend direction before generating signals.
2. Trend Continuation: The integration of Pivot Points and SuperTrend, along with the trend filter, aims to prolong trades during strong market trends, potentially maximizing profit opportunities.
3. Reduced Whipsaws: The strategy's weighted average calculation, coupled with the trend filter, helps minimize false signals and reduces whipsaws during uncertain or sideways market conditions.
4. Support and Resistance Insights: The strategy continues to provide additional support and resistance levels based on the Pivot Points, offering valuable contextual information to traders.
Buying Selling Volume StrategyFirst I would like to give the original credit and thanks to @ceyhun for his amazing volume script.
The way I decided to convert it into a strategy is divided into multiple types.
First, I decided in order to smooth out the values and make it more accurate to adapt the values to multiple timeframes.
After that I took the initial values from the buyers and sellers , and made a rest operation between them to have a flat difference between the power of both sides.
WIth that later on I decided to to apply a volatility filter,in this case bollinger bands, in order to find out potential leading trends.
At the same time in order to filter even more, I decided to make use as well for weekly VWAP values of the asset used.
Lastly I added a dynamic risk management into it , based on the ATR Daily values of the asset values.
As for the rules used, for example for long, I am looking that the price of the asset is above the weekly VWAP, after that I am checking that the MTF volume rest operation is both bullish and above the upper side of the bollinger.
For short we would want the asset to be below the weekly VWAP, and the volume to be bearish and above the upper side of bollinger.
The exit is either based on daily ATR values multipliers, or if we have a reverse condition.
If you have any questions, please let me know !
Vortex Cross w/MA ConfirmationThis script is a trading strategy that combines the Vortex Indicator and a Moving Average (MA) to generate potential entry signals for long and short positions.
1. Vortex Indicator:
The Vortex Indicator consists of two lines: Vortex Positive (VIP) and Vortex Negative (VIM). It is designed to identify trend direction and measure the strength of a trend.
2. Moving Average (MA):
The script uses a chosen type of Moving Average (SMA, EMA, SMMA, WMA, or VWMA) to smooth the price data. The smoothed line is referred to as the "Smoothing Line."
3. Determine Long and Short Conditions:
The script looks for potential long entry signals when VIP crosses above VIM, highlighting each crossover on the chart, and the closing price is above the Smoothing Line. It searches for short entry signals when VIM crosses above VIP, with the closing price is below the Smoothing Line. When the long or short conditions are met, the strategy enters either a long or short position accordingly.
Potential Usage:
The strategy can be utilized in trending markets, where the Vortex Indicator helps identify trend direction and strength, and the Moving Average smooths the price data to filter out some noise. It aims to capture trends and ride them while avoiding false signals during choppy or sideways markets.
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
[tradinghook] - Renko Trend Reversal Strategy V2Title: Renko Trend Reversal Strategy
Short Title: - Renko TRS
> Special thanks to for manually calculating `renkoClose` and `renkoOpen` values in order to remove the infamous repaint issue
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
Bullish Divergence Short-term Long Trade FinderThis script is a Bullish divergence trade finder built to find small periods where Bitcoin will likely rise from. It looks for bullish divergence followed by a higher low as long as the hour RSI value is below the 40 mark, if then it will enter an long. It marks out Buy signals on the RSI if the value dips below 'RSI Bull Condition Minimum' (Default 40) on the current time frame in view. It also marks out Sell signals found when the RSI is above the 'RSI Bearish Condition Minimum' (Default 50). The sell signals are bearish divergence that has occurred recently on the RSI. When a long is in play it will sell if it finds bearish divergence or the time frame in view reaches RSI value higher than the 'RSI Sell Value'(Default 75). You can set your stop loss value with the 'Stop loss Percentage' (default 5).
Available inputs:
RSI Period: relative strength measurement length(Typically 14)
RSI Oversold Level: the bottom bar of the RSI (Typically 30)
RSI Overbought Level: the top bar of the RSI (Typically 70)
RSI Bearish Condition Minimum: The minimum value the script will use to look for a pivot high that starts the Bearish condition to Sell (Default 50)
RSI Bearish Condition Sell Min: the minimum value the script will accept a bearish condition (Default 60)
RSI Bull Condition Minimum: the minimum value it will consider a pivot low value in the RSI to find a divergence buy (Default 40)
Look Back this many candles: the amount of candles thee script will look back to find a low value in the RSI (Default 25)
RSI Sell Value: The RSI value of the exit condition for a long when value is reached (Default 75)
Stop loss Percentage: Percentage value for amount to lose (Default 5)
The formula to enter a long is stated below:
If price finds a lower low and there is a higher low found following a lower low and price has just made another dip and price closes lower than the last divergence and Relative strength index hour value is less than 40 enter a long.
The formula to exit a long is stated below:
If the value drops below the stop loss percentage OR (the RSI value is greater than the value of the parameter 'RSI Sell Value' or bearish divergence is found greater than the parameter 'RSI Bearish Condition Minimum' )
This script was built from much strategy testing on BTC but works with alts (occasionally) also. It is most successful to my knowledge using the 15 min and 7 min time frames with default values. Hope it helps! Follow for further possible updates to this script or other entry or exit strategies.
snapshot:
I only have a Pro trading view account so I cannot share a larger data set about this script because the buy signals happen pretty rarely. The most amount that I could find within a view for me was 40 trades within a viewable time. The suggested/default parameters that I have do not occur very often so it limits the data set. Adjustments can be made to the parameters so that trades can be entered more often. The scripts success is dependent on the values of the parameters set by the user. This script was written to be used for BTC/USD or BTC/USDT trading. I am unable to share a larger dataset without putting out results that are intended to fail or having a premium account so reaching the 100 trade minimum is not possible with my account.
TRAX Detrended Price StrategyIn this script, the "TRAX" (TRIX) indicator is calculated using the Volume Weighted Moving Average (VWMA) instead of Exponential Moving Average (EMA) like the standard TRIX. The Detrended Price is used to identify short term cycles with a rate of change verses the rate of change from a triple smoothed TRAX VWMA . The strategy is intended for counter-trend trading, meaning it tries to capture potential reversals.
1. Indicators Used:
TRAX is calculated using the Volume Weighted Moving Average (VWMA) of the logarithm of the closing price.
DPO (Detrended Price Oscillator) is calculated by taking the closing price and subtracting a simple moving average (SMA) of the closing price shifted back.
2. Crossover Conditions:
Longs occur when DPO crosses above the TRAX, with the TRAX trending below 0, and the stock is trading above an adjustable simple moving average. Shorts occur due to the inverse conditions.
3. Visualization:
This script plots the SMA and the TRAX-DPO Combined Oscillator.
It highlights the periods of zero-line crossover using a green background for potential long positions and a red background for potential short positions. However, it will trigger verified entries/exits in accordance with the SMA.
In conclusion, this fun prototype underwent a unique alteration using the Volume Weighted Moving Average and focuses on capturing shorter counter-trend cycles. You have the freedom to fine-tune the strategy by adjusting parameters and incorporating other analysis methods that resonate with your trading style and risk tolerance.
Liquidity Breakout - Strategy [presentTrading]- Introduction and How It Is Different
The Liquidity Breakout Strategy is a unique trading strategy that focuses on identifying and leveraging patterns in market price data. This strategy, mainly inspired by the script "Master Pattern" by LuxAlgo, takes a different approach from many traditional strategies that rely on technical indicators or fundamental analysis. Instead, the Liquidity Breakout is based on the concept of contraction detection and liquidity levels. This approach allows traders to identify potential trading opportunities that other strategies might miss.
BTCUSDT 6h
The strategy is different from other trading strategies because it uses a unique combination of pattern detection, liquidity levels, and user-defined trading direction. This combination allows the strategy to adapt to various market conditions and trading styles, making it a versatile tool for traders.
- Strategy: How It Works
1. Contraction Detection: The strategy uses a lookback period defined by the user (default is 10 bars) to identify contractions in the market. A contraction is a period where the market is consolidating, often followed by a significant price movement. The strategy identifies contractions by finding pivot highs and pivot lows within the lookback period. If a pivot high is lower than the previous pivot high and a pivot low is higher than the previous pivot low, a contraction is detected.
2. liquidity Levels:
What are Liquidity levels? Liquidity levels, also known as liquidity pools or zones, are price levels at which there is a significant amount of trading activity. They are often areas where large institutional traders (like banks or hedge funds) have placed orders. These levels are important because they can act as support or resistance levels, and price often reacts at these levels.
In the context of this strategy, liquidity levels are used to identify potential entry and exit points for trades. When the price reaches a liquidity level, it could indicate a potential trading opportunity. For example, if the price breaks through a liquidity level, it could signal the start of a new trend. On the other hand, if the price approaches a liquidity level and then reverses, it could signal a potential reversal.
The strategy uses these two elements to identify potential trading opportunities. When a contraction is detected, the strategy will look for a breakout in the direction of the trend. If the breakout occurs at a liquidity level, the strategy will execute a trade.
The strategy also allows traders to set their stop loss based on either the Average True Range (ATR) or a fixed percentage. This flexibility allows traders to manage their risk according to their personal risk tolerance and trading style.
- Trade Direction
One of the unique features of the Master Pattern Strategy is the ability to choose the trading direction. Traders can choose to trade in the "Long" direction, the "Short" direction, or "Both". This feature allows traders to adapt the strategy to their personal trading style and market outlook.
For example, if a trader believes that the market is in an uptrend, they can choose to trade only in the "Long" direction. Conversely, if the market is in a downtrend, they can choose to trade only in the "Short" direction. If the trader believes that the market is volatile and there are opportunities in both directions, they can choose to trade in "Both" directions.
- Usage
To use the strategy, traders need to input their preferred settings, including the contraction detection lookback period, liquidity levels, stop loss type, and trading direction. Once these settings are input, the strategy will automatically detect potential trading opportunities and execute trades according to the defined parameters.
- Default Settings
The default settings for the Master Pattern Strategy are as follows:
Contraction Detection Lookback: 10
Liquidity Levels: 20
Stop Loss Type: ATR
ATR Length: 20
ATR Multiplier: 3.0
Fixed Percentage: 0.01
Trading Direction: Both
These settings can be adjusted according to the trader's personal preferences and market conditions. It's recommended that traders experiment with different settings to find the ones that work best for their trading style and goals.
PercentX Trend Follower [Trendoscope]"Trendoscope" was born from our trading journey, where we first delved into the world of trend-following methods. Over time, we discovered the captivating allure of pattern analysis and the exciting challenges it presented, drawing us into exploring new horizons. However, our dedication to trend-following methodologies remains steadfast and continues to be an integral part of our core philosophy.
Here we are, introducing another effective trend-following methodology, employing straightforward yet powerful techniques.
🎲 Concepts
Introducing the innovative PercentX Oscillator , a representation of Bollinger PercentB and Keltner Percent K. This powerful tool offers users the flexibility to customize their PercentK oscillator, including options for the type of moving average and length.
The Oscillator Range is derived dynamically, utilizing two lengths - inner and outer. The inner length initiates the calculation of the oscillator's highest and lowest range, while the outer length is used for further calculations, involving either a moving average or the opposite side of the highest/lowest range, to obtain the oscillator ranges.
Next, the Oscillator Boundaries are derived by applying another round of high/low or moving average calculations on the oscillator range values.
Breakouts occur when the close price crosses above the upper boundary or below the lower boundary, signaling potential trading opportunities.
🎲 How to trade a breakout?
To reduce false signals, we employ a simple yet effective approach. Instead of executing market trades, we use stop orders on both sides at a certain distance from the current close price.
In case of an upper side breakout, a long stop order is placed at 1XATR above the close, and a short stop order is placed at 2XATR below the close. Conversely, for a lower side breakout, a short stop order is placed at 1XATR below the close, and a long stop order is placed at 2XATR above the ATR. As a trend following method, our first inclination is to trade on the side of breakout and not to find the reversals. Hence, higher multiplier is used for the direction opposite to the breakout.
The script provides users with the option to specify ATR multipliers for both sides.
Once a trade is initiated, the opposite side of the trade is converted into a stop-loss order. In the event of a breakout, the script will either place new long and short stop orders (if no existing trade is present) or update the stop-loss orders if a trade is currently running.
As a trend-following strategy, this script does not rely on specific targets or target levels. The objective is to run the trade as long as possible to generate profits. The trade is only stopped when the stop-loss is triggered, which is updated with every breakout to secure potential gains and minimize risks.
🎲 Default trade parameters
Script uses 10% equity per trade and up to 4 pyramid orders. Hence, the maximum invested amount at a time is 40% of the equity. Due to this, the comparison between buy and hold does not show a clear picture for the trade.
Feel free to explore and optimize the parameters further for your favorite symbols.
🎲 Visual representation
The blue line represents the PercentX Oscillator, orange and lime colored lines represent oscillator ranges. And red/green lines represent oscillator boundaries. Oscillator spikes upon breakout are highlighted with color fills.
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
Ensure that the strategy idea is clearly understandable. Provide an easy-to-read title and a thoughtful description explaining the reasoning behind the strategy.
All content should be ad-free. Avoid any form of promotion, advertising, or solicitation.
No fundraising requests or money solicitation is allowed on TradingView.
Publish in the same language as the TradingView subdomain you're on, except for script titles, which must be in English.
Don't plagiarize. Create and share only unique content, and always give credit when using someone else's work.
Be respectful, kind, and constructive when engaging with others.
Zero tolerance for contentious political discourse, defamatory, threatening, or discriminatory remarks.
Avoid sharing harmful, misleading, or inappropriate content.
Respect the moderators' work and address complaints privately.
Use only your original account and avoid creating duplicate or fake accounts.
Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
Ahsan Tufail Precise MA Crossover Filter for Reliable SignalsIntroduction:
In the ever-evolving world of Forex trading, strategies that provide a competitive edge are highly sought after. The Moving Average (MA) crossover technique is a popular long-term approach, but its vulnerability to false signals can lead to potential losses. To overcome this challenge, we introduce a game-changing MA crossover filter designed to weed out false signals and unlock the full potential of this strategy. In this article, we delve into the mechanics of this filter, providing a comprehensive analysis of its components and how it enhances the accuracy of buy and sell signals.
The Power of the MA Crossover Filter:
The essence of our MA crossover filter lies in the integration of a specialized indicator that operates on a scale of 0 to 100. This ingenious indicator dynamically measures the distance between the middle Bollinger band and either the upper or lower Bollinger band. By analyzing the values of the last 504 candlesticks, it maps the range from 50 to 100 for the largest and smallest distances between the middle and upper Bollinger bands. Similarly, for values ranging from 0 to 50, it measures the distance between the middle and lower Bollinger bands.
Unveiling the Signal Execution Process:
The brilliance of this filter is revealed in its meticulous execution of buy and sell signals, which significantly reduces false crossovers. Let's explore the process step-by-step:
Buy Signal Precision:
To initiate a buy signal, the price must be positioned above the 200-period Simple Moving Average (SMA).
The filter validates the crossover by checking the indicator's value, ensuring it falls below the threshold of 25.
Sell Signal Accuracy:
For a sell signal, the price must be below the 200-period Simple Moving Average (SMA).
The filter confirms the crossover by verifying the indicator's value, which should exceed the threshold of 75.
This selective approach ensures that only high-confidence crossovers are considered, maximizing the potential for profitable trades.
Fine-Tuning the Filter for Optimal Performance:
While the MA crossover filter exhibits its prowess in GBPUSD and EURUSD currency pairs, it may require adjustments for other pairs. Currency pairs possess unique characteristics, and adapting the filter to specific behavior is crucial for its success.
To fine-tune the filter for alternative currency pairs, traders should conduct rigorous backtesting and analyze historical price data. By experimenting with indicator threshold values, traders can calibrate the filter to accurately match the dynamics of the target currency pair. This iterative process allows for customization, ultimately resulting in a finely-tuned filter that aligns with the unique behavior of the selected market.
Conclusion:
The MA crossover filter represents a paradigm shift in long-term Forex trading strategies. By intelligently filtering false signals, this precision tool unleashes the true potential of the MA crossover technique, elevating its profitability and enhancing overall trading performance. While no strategy guarantees absolute success, incorporating this filter empowers traders with a heightened level of confidence in their buy and sell signals. Embracing the power of this innovative filter can be a transformative step towards mastering Forex profits and staying ahead in the dynamic world of currency trading.
