Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Volume
Gann + Laplace Smoothed Hybrid Volume Spread AnalysisThe Gann + Laplace Smoothed Hybrid Volume Spread Analysis ( GannLSHVSA ) Strategy/Indicator is an trading tool designed to fuse volume analysis with trend detection, offering traders a view of market dynamics.
This Strategy/Indicator stands apart by integrating the principles of the upgraded Discrete Fourier Transform (DFT), the Laplace Stieltjes Transform and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
The length of EMA and Strategy Entries are modified with the Gann swings .
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the GannLSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS GannLSHVSA INDICATOR:
The GannLSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
ORIGINALITY & USEFULNESS:
The GannLSHVSA Strategy is unique because it applies upgraded DFT, the Laplace Stieltjes Transform for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Fine-tune Inputs: Gann + Laplace Smooth Volume Zone OscillatorUse this Strategy to Fine-tune inputs for the GannLSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Laplace with Gann Swing Entries and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When Indicator/Strategy returns 0 or natural trend, Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator.
The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Laplace Stieltjes Transform approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs.
Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
zavaUnni-bitcoin signals(1day)
📌 This strategy predicts price movements based on trading volume and enters positions accordingly. It calculates the expected price increase based on bullish volume and the expected price decrease based on bearish volume to determine the direction of the position.
Top predicted price based on declining bullish volume: top_ifpricebull
Bottom predicted price based on declining bearish volume: top_ifpricebear
Top predicted price based on increasing bullish volume: bot_ifpricebull
Bottom predicted price based on increasing bearish volume: bot_ifpricebear
Using these four values, the strategy calculates the final maxprice and minprice based on volume. If the price settles above the max value, it indicates an upward trend; if it settles below the min value, it indicates a downward trend.
📌 The indicator does not solely rely on the maxprice and minprice conditions. It incorporates complex and sophisticated analysis by considering average volume and candle size.
During a decline, if the average volume and spread of bullish candles exceed those of bearish candles and the price settles above the max value, a long position is entered.
During a rise, if the average volume and spread of bearish candles exceed those of bullish candles and the price settles below the min value, a short position is entered.
Even if the above conditions are met, if the buying pressure significantly outweighs the selling pressure, the position will be closed, but a reverse position will not be entered.
Reviewing historical data shows that while there are instances where the position switches from long to short immediately, there are also cases where the position is closed and re-entered after a few candles.
📌 Trading volume is one of the most traditional yet essential indicators, accurately reflecting price direction. This strategy, which simultaneously predicts fundamental trading volume and price changes, consistently achieves a profit factor above 3.
Characteristics and Historical Data of the Strategy
🔴 Short position entry: April 11, 2022
🟢 Long position entry after closing short: January 11, 2023
⚫ Short position holding period: 270 days
🟢 Long position entry: October 9, 2020
🔵 Long position exit: November 30, 2019
⚫ Long position holding period: 52 days
🟢 Long position entry: November 30, 2019
🔵 Long position exit: February 22, 2021
⚫ Long position holding period: 84 days
Settings Explanation
🛠️ In the input, you can choose between spot and futures. Buy and sell signals are generated in spot trading, while long and short signals are generated in futures trading.
🌈 You can configure the screen view.
Fibonacci Trend
Falling Fibonacci levels from the top: 382 and 618 levels (Red lines)
Rising Fibonacci levels from the bottom: 382 and 618 levels (Green lines)
When the price stays within the 382 and 618 levels of the falling Fibonacci, the background turns red; when it stays within the 382 and 618 levels of the rising Fibonacci, the background turns green.
Real-time Volume Strength of Bullish and Bearish Candles
Red arrow: Appears when the strength of bearish candles increases
Green arrow: Appears when the strength of bullish candles increases
Cumulative Volume of Bullish and Bearish Candles during the Trend
Cumulative data of falling bullish and bearish candles from the top
Cumulative data of rising bullish and bearish candles from the bottom
Profit Table
Provides annual and monthly profit tables.
Setting Options
You can change the options in the attributes to test different configurations.
📌 Trading Data
Although Binance data starts from 2017, limiting the number of trades to 60 as of July 2024, this does not undermine the validity of the strategy. Binance provides reliable volume data, which is crucial for evaluating the strategy's performance. In contrast, exchanges like Bitstamp may have longer trading histories but insufficient volume to properly assess the strategy's actual performance. A volume-based strategy cannot be reliably tested on an exchange with low trading volume. Therefore, despite the limited number of trades on Binance, its reliable volume data justifies its use for this strategy.
► Backtesting Details:
Timeframe: 1D / Bitcoin / TetherUS
Initial Balance: $50,000 (Enter the initial capital you will invest)
Order Size: 10% (Enter the percentage of your account balance you will trade)
Commission: 0.04% (Enter the trading commission)
Slippage: 10 ticks (Enter the slippage you want to test)
When using the strategy:
📢 Timeframe: While the strategy performs well on timeframes lower than daily, it is particularly profitable on the daily timeframe.
📢 Exchange: It is recommended to use Binance due to its reliable volume data.
📢 This strategy is suitable for traders who have the patience to hold positions for extended periods, as it calculates the size of bullish and bearish candles carefully and does not change positions easily.
📢 Spot trading is recommended over futures, and if using futures, leverage should be limited to a maximum of 2x.
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.
Entry Fragger - Strategy
For basic instructions please visit my other script "Entry Fragger".
The Signal Logic is explained there.
v1.4:
- Added advanced backtesting with fully customizable entries.
- Fully automated Buy Signals (profitable).
- Adjustable timeframes for signal logic. (requested)
Every setting affects the accuracy and profitability greatly now, based on settings applied.
The strategy performs best on high timeframes with larger capital and no leverage.
Useless for Forex, but absolutely smashes stocks and crypto on mid to high timeframes.
Please read through my other scripts description.
Set values as preferred and try your assets.
It does NOT work on low timeframes and forex!
Hint: BTC 4H, Custom Timeframe 1h, Moon Mode and Show Sell Signals enabled, R2R: 2.
Price-Volume Dynamic - Strategy [presentTrading]█ Introduction and How it is Different
The "Price-Volume Dynamic - Strategy" leverages a unique blend of price action, volume analysis, and statistical z-scores to establish trading positions. This approach differentiates itself by integrating the concept of the Point of Control (POC) from volume profile analysis with price-based z-score indicators to create a dynamic trading strategy. It tailors entry and exit thresholds based on current market volatility, providing a responsive and adaptive trading method. This strategy stands out by considering both historical volatility and price trends to adjust trading decisions in real-time, enhancing its effectiveness in various market conditions.
BTCUSD 4h LS Performance
█ Strategy: How It Works – Detailed Explanation
🔶 Calculating Point of Control (POC)
The Point of Control (POC) represents the price level with the highest traded volume over a specified lookback period. It's calculated by dividing the price range into a number of rows, each representing a price level. The volume at each price level is tallied and the level with the maximum volume is designated as the POC.
🔶 Dynamic Thresholds Adjustments
The entry and exit thresholds are dynamically adjusted based on normalized volatility, which is derived from the current, minimum, and maximum ATR over a specified period. This normalization ensures that the thresholds adapt to changes in market conditions, making the strategy sensitive to shifts in market volatility.
BTCUSD local performance
█ Trade Direction
The strategy can be configured to trade in three different directions: Long, Short, or Both. This flexibility allows traders to align their trading strategy with their market outlook or risk preferences. By adjusting the `POC_tradeDirection` input, traders can selectively participate in market movements that match their trading style and objectives.
█ Usage
To deploy this strategy, traders should apply it within a trading software that supports scripting and backtesting, such as TradingView's Pine Script environment. Users can input their parameters based on their analysis of the market conditions and their risk tolerance. It is essential for traders to backtest the strategy using historical data to evaluate its performance and make necessary adjustments before applying it in live trading scenarios.
█ Default Settings
- Lookback Length: Sets the period over which the highest and lowest prices, and the volume per price level, are calculated. A higher lookback length smoothens the volatility but may delay response to recent market movements.
- Number of Rows: Determines the granularity of price levels within the price range. More rows provide a more detailed volume profile but require more computational resources.
- Entry Z-Score Threshold Base: Influences the sensitivity of the strategy to enter trades. Higher values make the strategy more conservative, requiring stronger deviation from the mean to trigger a trade.
- Exit Z-Score Threshold Base: Sets the threshold for exiting trades, with lower values allowing trades to close on smaller price retractions, thereby potentially preserving profits or reducing losses.
- Trading Direction: Allows selection between Long, Short, or Both, enabling traders to tailor the strategy to their market view or risk preferences.
Price and Volume Breakout Buy Strategy [TradeDots]The "Price and Volume Breakout Buy Strategy" is a trading strategy designed to identify buying opportunities by detecting concurrent price and volume breakouts over a specified range of candlesticks.
This strategy is optimized for assets demonstrating high volatility and significant momentum spikes.
HOW IT WORKS
The strategy first takes the specific number of candlesticks as the examination window for both price and volume.
These values are used as benchmarks to identify breakout conditions.
A trade is initiated when both the closing price and the trading volume surpass the maximum values observed within the predetermined window.
Price must be above a designated moving average, serving as the trend indicator, ensuring that all trades align with the prevailing market trend.
APPLICATION
This strategy is particularly effective for highly volatile assets such as Bitcoin and Ethereum, capitalizing on the cues from sudden price and volume breakouts indicative of significant market movement, often driven by market smart money traders.
However, for broader markets like the S&P 500, this strategy may be less effective due to less pronounced volume and price shifts compared to the cryptocurrency markets.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Backtest result sometimes gives fewer than 100 trades under certain higher timeframes, as most trades tend to have a long holding period. Entry conditions are also more stringent, which, combined with the relatively brief history of cryptocurrencies, results in fewer trades on longer timeframes.
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
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.
Channels With NVI Strategy [TradeDots]The "Channels With NVI Strategy" is a trading strategy that identifies oversold market instances during a bullish trading market. Specifically, the strategy integrates two principal indicators to deliver profitable opportunities, anticipating potential uptrends.
2 MAIN COMPONENTS
1. Channel Indicators: This strategy gives users the flexibility to choose between Bollinger Band Channels or Keltner Channels. This selection can be made straight from the settings, allowing the traders to adjust the tool according to their preferences and strategies.
2. Negative Volume Indicator (NVI): An indicator that calculates today's price rate of change, but only when today's trading volume is less than the previous day's. This functionality enables users to detect potential shifts in the trading volume with time and price.
ENTRY CONDITION
First, the assets price must drop below the lower band of the channel indicator.
Second, NVI must ascend above the exponential moving average line, signifying a possible flood of 'smart money' (large institutional investors or savvy traders), indicating an imminent price rally.
EXIT CONDITION
Exit conditions can be customized based on individual trading styles and risk tolerance levels. Traders can define their ideal take profit or stop loss percentages.
Moreover, the strategy also employs an NVI-based exit policy. Specifically, if the NVI dips under the exponential moving average – suggestive of a fading trading momentum, the strategy grants an exit call.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Footprint strategyThis strategy uses imbalance volume data obtained by footprint calculation technology.
There are two signals to enter a trade:
trend - the current buy volume on the bar is greater than the current sell volume and there is at least one imbalance line.
reversal - the current bar is falling, but the general market trend is positive (growing) and the imbalance buy volume exceeds the imbalance sell volume.
When any of the conditions is triggered, two orders are placed: Take Profit and Stop loss (according to the percentage value from the inputs).
A little advice on use:
The strategy performs best on a 15 minute timeframe.
It is necessary to choose acceptable values of Take Profit and Stop loss depending on the order of symbol prices.
Inputs related to the strategy:
Stop loss - percentage size of stop loss to exit the trade.
Enable stop loss - stop loss activation.
Take Profit - percentage size of Take Profit.
Calculation timeframe - this is the timeframe from which the volume will be collected for distribution to buy and sell (if you do not have access to the seconds chart, set here 1 minute, the accuracy will be less, but it will work).
Trend timeframe - this is the timeframe from which the trend will be calculated.
Enable trend - activation of trend calculation.
Inputs related to the calculation of footprints (collection of the volume of purchases and sales):
Count show bars - Number of bars from rt bar to history to calculate.
Display all available bars - Strategy calculation on all available bars (based on the available amount of data with reduced resolution (set in Calculation timeframe)).
Ticks Per Row - Sets the price step, calculated by multiplying the entered value by syminfo.mintick.
Auto - The automatic "Ticks Per Row" calculation is based on the first available bar and applied to subsequent bars.
Max row - sets the acceptable number of rows within a bar.
Imbalance Percent - A percentage coefficient to determine the Imbalance of price levels.
Stacked levels - And minimum number of consecutive Imbalance levels required to draw extended lines.
If you have suggestions for improving the strategy and adding new conditions for entering and exiting the trade, please write).
OBVious MA Strategy [1000X Trader]Exploring OBV: The OBVious MA Strategy
Are you using On Balance Volume (OBV) effectively? OBV is a gift to traders. OBV often provides a leading signal at the outset of a trend, when compression in the markets produces a surge in OBV prior to increased volatility.
This strategy demonstrates one method of utilizing OBV to your advantage. I call it the "OBVious MA Strategy ” only because it is so simple in its mechanics. This is meant to be a demonstration, not a strategy to utilize in live trading, as the primary utility of the OBVious MA indicator is as a volume confirmation filter that complements other components of a strategy. That said, I felt useful to present this indicator in isolation in this strategy to demonstrate the power it holds.
Strategy Features:
• OBV is the core signal: this strategy revolves around the On Balance Volume indicator. OBV is a straightforward indicator: it registers a value by adding total volume traded on up candles, and subtracts total volume on down candles, generating a line by connecting those values. OBV was described in 1963 by Joe Granville in his book "Granville's New Key to Stock Market Profits” in which the author argues that OBV is the most vital key to success as a trader, as volume changes are a major predictor of price changes.
• Dual Moving Averages: here we use separate moving averages for entries and exits. This allows for more granular trade management; for example, one can either extend the length of the exit MA to hold positions longer, or shorten the MA for swifter exits, independently of the entry signals.
Execution: long trades are taken when the OBV line crosses above the Long Entry Moving Average of the OBV. Long exits occur when the OBV line crosses under the Long Exit MA of the OBV. Shorts enter on a cross below the Short Entry MA, and exit on a cross above the Short Exit MA.
• Directional Trading: a direction filter can be set to "long" or "short," but not “both”, given that there is no trend filter in this strategy. When used in a bi-directional strategy with a trend filter, we add “both” to the script as a third option.
Application:
While this strategy outlines entry and exit conditions based on OBV crossovers with designated moving averages, is is, as stated, best used in conjunction with a supporting cast of confirmatory indicators (feel free to drop me a note and tell me how you've used it). It can be used to confirm entries, or you might try using it as a sole exit indicator in a strategy.
Visualization:
The strategy includes conditional plotting of the OBV MAs, which plot based on the selected trading direction. This visualization aids in understanding how OBV interacts with the set moving averages.
Further Discussion:
We all know the importance of volume; this strategy demonstrates one simple yet effective method of incorporating the OBV for volume analysis. The OBV indicator can be used in many ways - for example, we can monitor OBV trend line breaks, look for divergences, or as we do here, watch for breaks of the moving average.
Despite its simplicity, I'm unaware of any previously published cases of this method. The concept of applying MAs or EMAs to volume-based indicators like OBV is not uncommon in technical analysis, so I expect that work like this has been done before. If you know of other similar indicators or strategies, please mention in the comments.
One comparable strategy that uses EMAs of the OBV is QuantNomad’s "On Balance Volume Oscillator Strategy ", which uses a pair of EMAs on a normalized-range OBV-based oscillator. In that strategy, however, entries and exits occur on one EMA crossing the other, which places trades at distinctly different times than crossings of the OBV itself. Both are valid approaches with strength in simplicity.
Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Fine-Tune Inputs: Fourier Smoothed Hybrid Volume Spread AnalysisUse this Strategy to Fine-tune inputs for the HSHVSA Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Fourier Smoothed Hybrid Volume Spread Analysis (FSHVSA) Strategy/Indicator is an innovative trading tool designed to fuse volume analysis with trend detection capabilities, offering traders a comprehensive view of market dynamics.
This Strategy/Indicator stands apart by integrating the principles of the Discrete Fourier Transform (DFT) and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the FSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
WHAT IS FSHVSA INDICATOR:
The FSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
ORIGINALITY & USEFULNESS:
The FSHVSA Strategy is unique because it applies DFT for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread?
It results in a neutral, not trending price action.
Thus the Indicator/Strategy returns 0 and Closes all long and short positions.
In the next Image you can see that trend is negative on 4h, we just move Negative on 12h and Positive on 1D. That means trend/Strategy flipped negative .
I am sorry, the chart is a bit messy. The idea is to use the indicator/strategy over more than 1 Timeframe.
Use this Strategy to fine-tune inputs for the HSHVSA Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
CVD Divergence Strategy.1.mmThis is the matching Strategy version of Indicator of the same name.
As a member of the K1m6a Lions discussion community we often use versions of the Cumulative Volume Delta indicator
as one of our primary tools along with RSI, RSI Divergences, Open interest, Volume Profile, TPO and Fibonacci levels.
We also discuss visual interpretations of CVD Divergences across multiple time frames much like RSI divergences.
RSI Divergences can be identified as possible Bullish reversal areas when the RSI is making higher low points while
the price is making lower low points.
RSI Divergences can be identified as possible Bearish reversal areas when the RSI is making lower high points while
the price is making higher high points.
CVD Divergences can also be identified the same way on any timeframe as possible reversal signals. As with RSI, these Divergences
often occur as a trend's momentum is giving way to lower volume and areas when profits are being taken signaling a possible reversal
of the current trending price movement.
Hidden Divergences are identified as calculations that may be signaling a continuation of the current trend.
Having not found any public domain versions of a CVD Divergence indicator I have combined some public code to create this
indicator and matching strategy. The calculations for the Cumulative Volume Delta keep a running total for the differences between
the positive changes in volume in relation to the negative changes in volume. A relative upward spike in CVD is created when
there is a large increase in buying vs a low amount of selling. A relative downward spike in CVD is created when
there is a large increase in selling vs a low amount of buying.
In the settings menu, the is a drop down to be used to view the results in alternate timeframes while the chart remains on current timeframe. The Lookback settings can be adjusted so that the divs show on a more local, spontaneous level if set at 1,1,60,1. For a deeper, wider view of the divs, they can be set higher like 7,7,60,7. Adjust them all to suit your view of the divs.
To create this indicator/strategy I used a portion of the code from "Cumulative Volume Delta" by @ contrerae which calculates
the CVD from aggregate volume of many top exchanges and plots the continuous changes on a non-overlay indicator.
For the identification and plotting of the Divergences, I used similar code from the Tradingview Technical "RSI Divergence Indicator"
This indicator should not be used as a stand-alone but as an additional tool to help identify Bullish and Bearish Divergences and
also Bullish and Bearish Hidden Divergences which, as opposed to regular divergences, may indicate a continuation.
Ironman [Decentrader]Ironman
What is it? how it does it? And how to use it:
i) Ironman is a multifaceted strategy builder, which uses coloured candles which represent certain customisable inputs being in confluence with one another and the set scenario.
ii) There are 7 customised technical indicators which can be input as a basis for the analytical review.
iii) Determine a primary indicator which dictates a bullish or bearish trend (and colour) and then optionally add up to 6 other indicators to be required to be in confluence which adds another colour to be represented.
An example might be two moving averages crossing as the main trend determination. The primary determinant is dictated as the trend being “bullish or bearish” and the added confluence adds an additional layer being “very bullish or very bearish”
iv) Users select which conditions they wish to enter and exit trades on using the Bullish / Very Bullish and Bearish / Very Bearish settings. This can be combined with other timeframes.
v) The selected inputs for each indicator will show in a table contained in the bottom right-hand corner. Active indicators within the system will be highlighted.
vi) Ironman is built to include various take profit and stop loss options such as trailing stops, and fixed percentage targets which can be included in the strategy. Different timeframes can be used to determine the stop if users wish to do so.
vii) Users can require that there is also confluence with a differing time period or choose long and short-only options which can be dictated independently or based upon filtering criteria using moving averages.
viii) Using the strategy settings, users are also able to choose backtesting periods.
ix) Position label settings allow users to show various backtesting options such as profit by position, total backtesting results and results for the active position.
x) Ironman enables users to automate trading easily using the input boxes under Alert messages which also allows connection to a third party which can conduct execution. Always make sure to thoroughly test the strategy if it is being automated.
xi) To get the best out of Ironman, build up a strategy for the timeframe and asset you are looking at and back-test outcomes as variables are layered in. Ensure to backtest over a suitable length of time.
xii) When optimising input variables, it can sometimes visually assist in having the underlying inputs on the screen via the standard indicators.
xiii) There are many boxes of information in the input variables, which explain how to use each part. Users can also add features such as a marker showing on the chart where all indicators are bullish/bearish, or where RSI is overbought / over sold.
xiv) Users can further customise the style of the tool under the style tab in the indicator settings.
SOFEX Strong Volatility Trend Follower + BacktestingWhat is the SOFEX Strong Volatility Trend Follower + Backtesting script?
🔬 Trading Philosophy
This script is trend-following, attempting to avoid choppy markets.
It has been developed for Bitcoin and Ethereum trading, on 1H timeframe.
The strategy does not aim to make a lot of trades, or to always remain in a position and switch from long to short. Many times there is no direction and the market is in "random walk mode", and chasing trades is futile.
Expectations of performance should be realistic.
The script focuses on a balanced take-profit to stop-loss ratio. In the default set-up of the script, that is a 2% : 2% (1:1) ratio. A relatively low stop loss and take profit build onto the idea that positions should be exited promptly. There are many options to edit these values, including enabling trailing take profit and stop loss. Traders can also completely turn off TP and SL levels, and rely on opposing signals to exit and enter new trades.
Extreme scenarios can happen on the cryptocurrency markets, and disabling stop-loss levels completely is not recommended. The position size should be monitored since all of it is at risk with no stop-loss.
⚙️ Logic of the indicator
The Strong Volatility Trend Follower indicator aims at evading ranging market conditions. It does not seek to chase volatile, yet choppy markets. It aims at aggressively following confirmed trends. The indicator works best during strong, volatile trends, however, it has the downside of entering trades at trend tops or bottoms.
This indicator also leverages proprietary adaptive moving averages to identify and follow strong trend volatility effectively. Furthermore, it uses the Average Directional Index, Awesome Oscillator, ATR and a modified version of VWAP, to categorize trends into weak or strong ones. The VWAP indicator is used to identify the monetary (volume) inflow into a given trend, further helping to avoid short-term manipulations. It also helps to distinguish choppy-market volatility with a trending market one.
📟 Parameters Menu
The script has a comprehensive parameter menu:
Preset Selection : Choose between Bitcoin or Ethereum presets to tailor the indicator to your preferred cryptocurrency market.
Indicator Sensitivity Parameter : Adjust the sensitivity to adapt the indicator, particularly to make it seek higher-strength trends.
Indicator Signal Direction : Set the signal direction as Long, Short, or Both, depending on your preference.
Exit of Signals : You have options regarding Take-Profit (TP) and Stop-Loss (SL) levels. Enable TP/SL levels to exit trades at predetermined levels, or disable them to rely on direction changes for exits. Be aware that removing stop losses can introduce additional risk, and position sizing should be carefully monitored.
By enabling Trailing TP/SL, the system switches to a trailing approach, allowing you to:
- Place an initial customizable SL.
- Specify a level (%) for the Trailing SL to become active.
- When the activation level is reached, the system moves the trailing stop by a given Offset (%).
Additionally, you can enable exit at break-even, where the system places an exit order when the trail activation level is reached, accounting for fees and slippage.
Alert Messages : Define the fields for alert messages based on specific conditions. You can set up alerts to receive email, SMS, and in-app notifications. If you use webhooks for alerts, exercise caution, as these alerts can potentially execute trades without human supervision.
Backtesting : Default backtesting parameters are set to provide realistic backtesting performance:
- 0.04% Commission per trade (for both entries and exits)
- 3 ticks Slippage (highly dependent on exchange)
- Initial capital of $1000
- Order size of $1000
While the order size is equal to the initial capital, the script employs a 2% stop-loss order to limit losses and attempts to prevent risky trades from creating big losses. The order size is a set dollar value, so that the backtesting performance is linear, instead of using % of capital which may result in unrealistic backtesting performance.
Risk Disclaimer
Please be aware that backtesting results, while valuable for statistical overview, do not guarantee future performance in any way. Cryptocurrency markets are inherently volatile and risky. Always trade responsibly and do not risk more than you can afford to lose.
YinYang RSI Volume Trend StrategyThere are many strategies that use RSI or Volume but very few that take advantage of how useful and important the two of them combined are. This strategy uses the Highs and Lows with Volume and RSI weighted calculations on top of them. You may be wondering how much of an impact Volume and RSI can have on the prices; the answer is a lot and we will discuss those with plenty of examples below, but first…
How does this strategy work?
It’s simple really, when the purchase source crosses above the inner low band (red) it creates a Buy or Long. This long has a Trailing Stop Loss band (the outer low band that's also red) that can be adjusted in the Settings. The Stop Loss is based on a % of the inner low band’s price and by default it is 0.1% lower than the inner band’s price. This Stop Loss is not only a stop loss but it can also act as a Purchase Available location.
You can get back into a trade after a stop loss / take profit has been hit when your Reset Purchase Availability After condition has been met. This can either be at Stop Loss, Entry or None.
It is advised to allow it to reset in case the stop loss was a fake out but the call was right. Sometimes it may trigger stop loss multiple times in a row, but you don’t lose much on stop loss and you gain lots when the call is right.
The Take Profit location is the basis line (white). Take Profit occurs when the Exit Source (close, open, high, low or other) crosses the basis line and then on a different bar the Exit Source crosses back over the basis line. For example, if it was a Long and the bar’s Exit Source closed above the basis line, and then 2 bars later its Exit Source closed below the basis line, Take Profit would occur. You can disable Take Profit in Settings, but it is very useful as many times the price will cross the Basis and then correct back rather than making it all the way to the opposing zone.
Longs:
If for instance your Long doesn’t need to Take Profit and instead reaches the top zone, it will close the position when it crosses above the inner top line (green).
Please note you can change the Exit Source too which is what source (close, open, high, low) it uses to end the trades.
The Shorts work the same way as the Long but just opposite, they start when the purchase source crosses under the inner upper band (green).
Shorts:
Shorts take profit when it crosses under the basis line and then crosses back.
Shorts will Stop loss when their outer upper band (green) is crossed with the Exit Source.
Short trades are completed and closed when its Exit Source crosses under the inner low red band.
So, now that you understand how the strategy works, let’s discuss why this strategy works and how it is profitable.
First we will discuss Volume as we deem it plays a much bigger role overall and in our strategy:
As I’m sure many of you know, Volume plays a huge factor in how much something moves, but it also plays a role in the strength of the movement. For instance, let’s look at two scenarios:
Bitcoin’s price goes up $1000 in 1 Day but the Volume was only 10 million
Bitcoin’s price goes up $200 in 1 Day but the Volume was 40 million
If you were to only look at the price, you’d say #1 was more important because the price moved x5 the amount as #2, but once you factor in the volume, you know this is not true. The reason why Volume plays such a huge role in Price movement is because it shows there is a large Limit Order battle going on. It means that both Bears and Bulls believe that price is a good time to Buy and Sell. This creates a strong Support and Resistance price point in this location. If we look at scenario #2, when there is high volume, especially if it is drastically larger than the average volume Bitcoin was displaying recently, what can we decipher from this? Well, the biggest take away is that the Bull’s won the battle, and that likely when that happens we will see bullish movement continuing to happen as most of the Bears Limit Orders have been fulfilled. Whereas with #2, when large price movement happens and Bitcoin goes up $1000 with low volume what can we deduce? The main takeaway is that Bull’s pressured the price up with Market Orders where they purchased the best available price, also what this means is there were very few people who were wanting to sell. This generally dictates that Whale Limit orders for Sells/Shorts are much higher up and theres room for movement, but it also means there is likely a whale that is ready to dump and crash it back down.
You may be wondering, what did this example have to do with YinYang RSI Volume Trend Strategy? Well the reason we’ve discussed this is because we use Volume multiple times to apply multiplications in our calculations to add large weight to the price when there is lots of volume (this is applied both positively and negatively). For instance, if the price drops a little and there is high volume, our strategy will move its bounds MUCH lower than the price actually dropped, and if there was low volume but the price dropped A LOT, our strategy will only move its bounds a little. We believe this reflects higher levels of price accuracy than just price alone based on the examples described above.
Don’t believe us?
Here is with Volume NOT factored in (VWMA = SMA and we remove our Volume Filter calculation):
Which produced -$2880 Profit
Here is with our Volume factored in:
Which produced $553,000 (55.3%)
As you can see, we wen’t from $-2800 profit with volume not factored to $553,000 with volume factored. That's quite a big difference! (Please note previous success does not predict future success we are simply displaying the $ amounts as example).
Now how about RSI and why does it matter in this strategy?
As I’m sure most of you are aware, RSI is one of the leading indicators used in trading. For this reason we figured it would only make sense to incorporate it into our calculations. We fiddled with RSI for quite awhile and sometimes what logically seems to be the right way to use it isn’t. Now, because of this, our RSI calculation is a little odd, but basically what we’re doing is we calculate the RSI, then turn it into a percentage (between 0-1) that can easily be multiplied to the price point we need. The price point we use is the difference between our high purchase zone and our low purchase zone. This allows us to see how much price movement there is between zones. We multiply our zone size with our RSI multiplication and we get the amount we will add +/- to our basis line (white line). This officially creates the NEW high and low purchase zones that we are actually using and displaying in our trades.
If you found that confusing, here are some examples to why it is an important calculation for this strategy:
Before RSI factored in:
Which produced 27.8% Profit
After RSI factored in:
Which produced 553% Profit
As you can see, the RSI makes not only the purchase zones more accurate, but it also greatly increases the profit the strategy is able to make. It also helps ensure an relatively linear profit slope so you know it is reliable with its trades.
This strategy can work on pretty much anything, but you should tweak the values a bit for each pair you are trading it with for best results.
We hope you can find some use out of this simple but effective strategy, if you have any questions, comments or concerns please let us know.
HAPPY TRADING!
Hoffman Heiken BiasThis indicator uses a couple of different things including the Hoffman moving averages applied with heiken ashi bar data and some volatility to help determine when the bias of the market has shifted for the timeframe you are looking at.
SOFEX High-End Indicators + BacktestingBINANCE:BTCUSDT.P BINANCE:ETHUSDT.P
Introducing the first publicly available suite of indicators for Bitcoin and Ethereum by Sofex - the High-End Indicators & Backtesting System.
🔬 Trading Philosophy
The High-End Indicators & Backtesting system offers both trend-following and mean-reversal algorithms to provide traders with a deep insight into the highly volatile cryptocurrency markets, known for their market noise and vulnerability to manipulation.
With these factors in mind, our indicators are designed to sidestep most potentially false signals. This is facilitated further by the "middle-ground" time frame (1 Hour) we use. Our focus is on the two largest cryptocurrencies: Bitcoin and Ethereum , which provide high liquidity, necessary for reliable trading.
Therefore, we recommend using our suite on these markets.
The backtesting version of the Sofex High-End Indicators includes mainly trend-following indicators. This is because our trading vision is that volatility in cryptocurrency markets is a tool that should be used carefully, and many times avoided. Furthermore, mean-reversal trading can lead to short-term profits, but we have found it less than ideal for long-term trading.
The script does not aim to make a lot of trades, or to always remain in a position and switch from long to short. Many times there is no direction and the market is in "random walk mode", and chasing trades is futile.
Based on our experience, it is preferable if traders remain neutral the majority of the time and only enter trades that can be exited in the foreseeable future. Trading just for the sake of it ultimately leads to loss in the long-run.
Expectations of performance should be realistic.
We also focus on a balanced take-profit to stop-loss ratio. In the default set-up of the script, that is a 2% : 2% (1:1) ratio. A relatively low stop loss and take profit build onto our idea that positions should be exited promptly. There are many options to edit these values, including enabling trailing take profit and stop loss. Traders can also completely turn off TP and SL levels, and rely on opposing signals to exit and enter new trades.
Extreme scenarios can happen on the cryptocurrency markets, and disabling stop-loss levels completely is not recommended. The position size should be monitored since all of it is at risk with no stop-loss.
We take pride in presenting this comprehensive suite of trading indicators, designed for both manual and automated use. Although automated use leads to increased efficiency, traders are free to incorporate any of our indicators into their own manual trading strategy.
⚙️ Indicators
By default, all indicators are enabled for both Long and Short trades.
Extreme Trend Breakouts
The Extreme Trend Breakouts indicator seeks to follow breakouts of support and resistance levels, while also accounting for the unfortunate fact that false signals can be generated on these levels. The indicator combines trend-breakout strategies with various other volatility and direction measurements. It works best in the beginning of trends.
Underpinning this indicator are renowned Perry Kaufman's Adaptive Moving Averages (PKAMA) alongside our proprietary adaptive moving averages. These dynamic indicators adjust their parameters based on recent price movements, attempting to catch trends while maintaining consistent performance in the long run.
In addition, our modification of the TTM Squeeze indicator further enhances the Extreme Trend Breakouts indicator, making it more responsive, especially during the initial stages of trends and filtering of "flat" markets.
High-Volatility Trend Follower
The High-Volatility Trend Follower indicator is based around the logic of evading market conditions where volatility is low (choppy markets) and aggressively following confirmed trends. The indicator works best during strong trends, however, it has the downside of entering trades at trend tops or bottoms.
This indicator also leverages our proprietary adaptive moving averages to identify and follow high-volatility trends effectively. Furthermore, it uses the Average Directional Index, Aroon Oscillator, ATR and a modified version of VWAP, to categorize trends into weak or strong ones. The VWAP indicator is used to identify the monetary (volume) inflow into a given trend, further helping to avoid short-term manipulations.
Low-Volatility Reversal
The Low-Volatility Reversal aims at plugging the holes that trend-following indicators ignore. It specifically looks for choppy markets. Using proven concepts such as Relative Strength Index and volume measurements, among others, this indicator finds local tops and bottoms with good accuracy. It works best in choppy markets with low to medium volatility. It has a downside that all reversals have, losing trades at the end of choppy markets and in the beginning of big trends.
This indicator, like the others, employs PKAMA in conjunction with our proprietary adaptive moving averages, and an Average PSAR indicator to seek out "sideways" markets. Furthermore, Bollinger Bands with an adaptive basis line is used, with the idea of trading against the short-term trends by looking at big deviations in price movement. The above mentioned indicators attempt to catch local tops and bottoms in markets.
Adaptive Trend Convergence
The Adaptive Trend Convergence aims at following trends while avoiding entering positions at local bottoms and tops. It does so by comparing a number of adaptive moving averages and looking for convergence among them. Adaptive filtering techniques for avoiding choppy markets are also used.
This indicator utilizes our proprietary adaptive moving averages, and an Average Price Range indicator to identify trend convergence and divergence effectively, preventing false signals during volatile market phases. It also makes use of Bollinger Bands with an adaptive moving average basis line and price-action adjusted deviation. Contrasting to the Low-Volatility Reversal condition described above, the Bollinger Bands used here attempt to follow breakouts outside of the lower and upper bands.
Double-Filtered Channel Breakouts
The Double-Filtered Channel Breakouts indicator is made out of adaptive channel-identifying indicators. The indicator then follows trends that significantly diverge from the established channels. This aims at following extreme trends, where rapid, continuous movements in either direction occur. This indicator works best in very strong trends and follows them relentlessly. However, these strong trends can end in strong reversals, and the indicator can be stopped out on the last trade.
Our Double-Filtered Channel Breakouts indicator is built on a foundation of adaptive channel indicators. We've harnessed the power of Keltner Channels and Bollinger Band Channels, with a similar approach used in the Adaptive Trend Convergence indicator. The basis and upper/lower bands of the channels do not rely on fixed deviation parameters, rather on adaptive ones, based on price action and volatility. This combination seeks to identify and follows extreme trends.
Direction Tracker
The Direction Tracker indicator is made out of a central slower, adaptive moving average that clearly recognizes global, long-term trends. Combined with direction and range indicators, among others, this indicator excels at finding the long-term trend and ignoring temporary pullbacks in the opposite direction. It works best at the beginning and middle of long and strong trends. It can fail at the end of trends and on very strong historical resistance lines (where sharp reversals are common).
Our Direction Tracker indicator integrates an adaptive SuperTrend indicator into its core, alongside our proprietary adaptive moving averages, to accurately identify and track long-term trends while mitigating temporary pullbacks. Furthermore, it uses Average True Range, ADX and other volatility indicators to attempt to catch unusual moves on the market early-on.
📟 Parameters Menu
To offer traders flexibility, our system comes with a comprehensive parameter menu:
Preset Selection : Choose between Bitcoin or Ethereum presets to tailor the indicators to your preferred cryptocurrency market.
Global Signal Direction: Set the global signal direction as Long, Short, or Both, depending on your trading strategy.
Global Sensitivity Parameter : Adjust the system's sensitivity to adapt to different trend-following conditions, particularly beneficial during higher-strength trends.
Source of Signals : Toggle individual indicators on or off according to your preference. By default, all indicators are enabled. Customize the indicators to trade Long, Short, or Both, aligning them with your desired market exposure.
Confirmation of Signals : Set the minimum number of confirmed signals on the same bar, ensuring signals are generated only when specific confirmation criteria are met. The default value is one, and it can be adjusted for both Long and Short signals.
Exit of Signals : You have options regarding Take-Profit (TP) and Stop-Loss (SL) levels. Enable TP/SL levels to exit trades at predetermined levels, or disable them to rely on direction changes for exits. Be aware that removing stop losses can introduce additional risk, and position sizing should be carefully monitored.
By enabling Trailing TP/SL, the system switches to a trailing approach, allowing you to:
- Place an initial customizable SL.
- Specify a level (%) for the Trailing SL to become active.
- When the activation level is reached, the system moves the trailing stop by a given Offset (%).
Additionally, you can enable exit at break-even, where the system places an exit order when the trail activation level is reached, accounting for fees and slippage.
Alert Messages : Define the fields for alert messages based on specific conditions. You can set up alerts to receive email, SMS, and in-app notifications. If you use webhooks for alerts, exercise caution, as these alerts can potentially execute trades without human supervision.
Backtesting : Default backtesting parameters are set to provide realistic backtesting performance:
- 0.04% Commission per trade (for both entries and exits)
- 3 ticks Slippage (highly dependent on exchange)
- Initial capital of $1000
- Order size of $1000
While the order size is equal to the initial capital, the script employs a 2% stop-loss order to limit losses and attempts to prevent risky trades from creating big losses. The order size is a set dollar value, so that the backtesting performance is linear, instead of using % of capital which may result in unrealistic backtesting performance.
Risk Disclaimer
Please be aware that backtesting results, while valuable for statistical overview, do not guarantee future performance in any way. Cryptocurrency markets are inherently volatile and risky. Always trade responsibly and do not risk more than you can afford to lose.
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 !
Volume ValueWhen VelocityTitle: Volume ValueWhen Velocity Trading Strategy
▶ Introduction:
The " Volume ValueWhen Velocity " trading strategy is designed to generate long position signals based on various technical conditions, including volume thresholds, RSI (Relative Strength Index), and price action relative to the Simple Moving Average (SMA). The strategy aims to identify potential buy opportunities when specific criteria are met, helping traders capitalize on potential bullish movements.
▶ How to use and conditions
★ Important : Only on Spot Binance BINANCE:BTCUSDT
Name: Volume ValueWhen Velocity
Operating mode: Long on Spot BINANCE BINANCE:BTCUSDT
Timeframe: Only one hour
Market: Crypto
currency: Bitcoin only
Signal type: Medium or short term
Entry: All sections in the Technical Indicators and Conditions section must be saved to enter (This is explained below)
Exit: Based on loss limit and profit limit It is removed in the settings section
Backtesting:
⁃ Exchange: BINANCE BINANCE:BTCUSDT
⁃ Pair: BTCUSDT
⁃ Timeframe:1h
⁃ Fee: 0.1%
- Initial Capital: 1,000 USDT
- Position sizing: 500 usdt
-Trading Range: 2022-07-01 11:30 ___ 2023-07-21 14:30
▶ Strategy Settings and Parameters:
1. `strategy(title='Volume ValueWhen Velocity', ...`: Sets the strategy title, initial capital, default quantity type, default quantity value, commission value, and trading currency.
↬ Stop-Loss and Take-Profit Settings:
1. long_stoploss_value and long_stoploss_percentage : Define the stop-loss percentage for long positions.
2. long_takeprofit_value and long_takeprofit_percentage : Define the take-profit percentage for long positions.
↬ ValueWhen Occurrence Parameters:
1. occurrence_ValueWhen_1 and occurrence_ValueWhen_2 : Control the occurrences of value events.
2. `distance_value`: Specifies the minimum distance between occurrences of ValueWhen 1 and ValueWhen 2.
↬ RSI Settings:
1. rsi_over_sold and rsi_length : Define the oversold level and RSI length for RSI calculations.
↬ Volume Thresholds:
1. volume_threshold1 , volume_threshold2 , and volume_threshold3 : Set the volume thresholds for multiple volume conditions.
↬ ATR (Average True Range) Settings:
1. atr_small and atr_big : Specify the periods used to calculate the Average True Range.
▶ Date Range for Back-Testing:
1. start_date, end_date, start_month, end_month, start_year, and end_year : Define the date range for back-testing the strategy.
▶ Technical Indicators and Conditions:
1. rsi: Calculates the Relative Strength Index (RSI) based on the defined RSI length and the closing prices.
2. was_over_sold: Checks if the RSI was oversold in the last 10 bars.
3. getVolume and getVolume2 : Custom functions to retrieve volume data for specific bars.
4. firstCandleColor : Evaluates the color of the first candle based on different timeframes.
5. sma : Calculates the Simple Moving Average (SMA) of the closing price over 13 periods.
6. numCandles : Counts the number of candles since the close price crossed above the SMA.
7. atr1 : Checks if the ATR_small is less than ATR_big for the specified security and timeframe.
8. prevClose, prevCloseBarsAgo, and prevCloseChange : ValueWhen functions to calculate the change in the close price between specific occurrences.
9. atrval: A condition based on the ATR_value3.
▶ Buy Signal Condition:
Condition: A combination of multiple volume conditions.
buy_signal: The final buy signal condition that considers various technical conditions and their interactions.
▶ Long Strategy Execution:
1. The strategy will enter a long position (buy) when the buy_signal condition is met and within the specified date range.
2. A stop-loss and take-profit will be set for the long position to manage risk and potential profits.
▶ Conclusion:
The " Volume ValueWhen Velocity " trading strategy is designed to identify long position opportunities based on a combination of volume conditions, RSI, and price action. The strategy aims to capitalize on potential bullish movements and utilizes a stop-loss and take-profit mechanism to manage risk and optimize potential returns. Traders can use this strategy as a starting point for their own trading systems or further customize it to suit their preferences and risk appetite. It is crucial to thoroughly back-test and validate any trading strategy before deploying it in live markets.
↯ Disclaimer:
Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
BTFD strategy [3min]Hello
I would like to introduce a very simple strategy to buy lows and sell with minimal profit
This strategy works very well in the markets when there is no clear trend and in other words, the trend going sideways
this strategy works very well for stable financial markets like spx500, nasdaq100 and dow jones 30
two indicators were used to determine the best time to enter the market:
volume + rsi values
volume is usually the number of stocks or contracts traded over a certain period of time. Thus, it is an important indicator of market activity and liquidity. Each transaction constitutes an individual exchange between the buyer and the seller and constitutes the trading volume of a given instrument or asset.
The RSI measures the strength of uptrends versus downtrends. The signal is the entry or exit of the indicator value of the oversold or overbought level of the market. It is assumed that a value below or equal 30 indicates an oversold level of the market, and an RSI value above or equal 70 indicates an overbought level.
the strategy uses a maximum of 5 market entries after each candle that meets the condition
uses 5 target point levels to close the position:
tp1= 0.4%
tp2= 0.6%
tp3= 0.8%
tp4= 1.0%
tp5= 1.2%
after reaching a given profit value, a piece of the position is cut off gradually, where tp5 closes 100% of the remaining position
each time you enter a position, a stop loss of 5.0% is set, which is quite a high value, however, when buying each, sometimes very active downward price movement, you need a lot of space for market decisions in which direction it wants to go
to determine the level of stop loss and target point I used a piece of code by RafaelZioni , here is the script from which a piece of code was taken
this strategy is used for automation, however, I would recommend brokers that have the lowest commission values when opening and closing positions, because the strategy generates very high commission costs
Enjoy and trade safe ;)
