Heatmap MACD StrategyHello traders
A customer gave me the idea indirectly after I made an update to that script:
Supertrend MTF Heatmap
Important Notes
The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
I wanted to showcase that any Heatmap script can be converted into a strategy.
The strategy default settings are:
Initial Capital: 100000 USD
Position Size: 1 contract
Commission Percent: 0.075%
Slippage: 1 tick
No margin/leverage used
For example, those are realistic settings for trading CFD indices with low timeframes, but not the best possible settings for all assets/timeframes.
Concept
The Heatmap MACD Strategy allows selecting one MACD in five different timeframes.
You'll get an exit signal whenever one of the 5 MACDs changes direction.
Then, the strategy re-enters whenever all the MACDs are in the same direction again.
It takes:
long trades when all the 5 MACD histograms are bullish
short trades when all the 5 MACD histograms are bearish
You can select the same timeframe multiple times if you don't need five timeframes.
For example, if you only need the 30min, the 1H, and 2H, you can set your timeframes as follow:
30m
30m
30m
1H
2H
Risk Management Features
Nothing too fancy
All the features below are pips-based
Stop-Loss
Trailing Stop-Loss
Stop-Loss to Breakeven after a certain amount of pips has been reached
Take Profit 1st level and closing X% of the trade
Take Profit 2nd level and close the remaining of the trade
What's next?
I'll publish this script's open-source Pineconnector, ProfitView, and AutoView versions for educational purposes.
Thank you
Dave
Cari dalam skrip untuk "the strat"
Stochastic StrategyThis strategy is designed to make trading decisions based on the Stochastic Oscillator (Stoch) indicator with settings of (7,2,2). The strategy opens a long (buy) position when the Stoch indicator crosses above the 50 level from below. Conversely, it opens a short (sell) position when the Stoch indicator crosses below the 50 level from above. Additionally, when a long position is opened, any existing short position is closed, and vice versa.
Key Parameters:
Stochastic Oscillator Settings: Length = 7, SmoothK = 2, SmoothD = 2.
Overbought Level: 80.
Oversold Level: 20.
Strategy Description:
The Stochastic Oscillator (Stoch) is calculated based on the closing price, high price, and low price with a period of 7, and both the %K and %D lines are smoothed with periods of 2.
When the %K line crosses above the oversold level (20), it generates a long (buy) signal.
When the %K line crosses below the overbought level (80), it generates a short (sell) signal.
The strategy visually marks long and short signals on the chart using upward and downward triangles, respectively.
The strategy automatically enters long or short positions when the respective conditions are met.
If a long position is opened, any existing short position is closed, and vice versa.
Please note that this is a basic example of a trading strategy and does not take into account all possible risk factors or optimizations. Before using this strategy in live trading, it's essential to thoroughly test and customize it to suit your specific needs, and carefully analyze the results. Trading carries risks, and it's important to use proper risk management techniques when implementing any trading strategy.
Market Breadth Strategy/Introduction
The Market Breadth Strategy (MBS) is a versatile strategy for trading the US stock market. MBS is suitable for traders with low, medium and high risk tolerance who prefer trading equities as an asset class on the 1 day timeframe. It combines mean reversion with trend following to keep you participating in the stock market for as long as is profitable.
/Signals
The strategy is long only. Four different signals are generated to ensure all opportunities the market presents are seized for profit. The first category of signals are triggered after a prolonged period of falling prices; usually during a bear market or severe correction, open your largest positions on this signal. The second category of signals are triggered at the end of the bear market, early in the recovery. They ensure you do not miss out on an early entry if you get stopped out of your initial positions, size them equal to the first category signal positions. The third category of signals are triggered late in the recovery from a bear market, severe correction or deep pullback. Open your smallest positions on this signal. The fourth category of signals are triggered at all times when the market experiences a significant pullback or time correction, these positions should be medium sized.
For optimum performance, whenever signals are triggered, traders are advised to open at least, a new long position. Buying the index is recommended for traders with low risk tolerance, buying sector, industry or thematic ETFs (after sufficient analysis) is recommended for traders with medium risk tolerance, while buying stocks (after sufficient analysis) is recommended for traders who want to take on higher risk for higher returns. Such traders may also combine positions in indices, groups and individual stocks for better performance.
/Interpretation
MBS will display an upward blue arrow signifying a buy signal after the candle closes. A label below the arrow will describe which signal was triggered and a number depicting the number of positions (they can be deactivated in the style settings). MBS will also display a downwards pink arrow above the candle, after a specified decline from the high, again when the candle closes. All open positions will be closed on this signal, it is the risk management feature of the strategy.
/Construction
The strategy is built using market breadth data from the US Exchanges where stocks are listed, it is not a mash-up of different indicators. A combination of the following data is used:
(i) the number of advancing and declining issues
(ii) the number of issues reaching new highs
(iii) the closing prices of issues relative to key moving averages
This data is analysed and used to generate the four categories of signals described previously, they are named;
(i) Bottom Signal - for buying at the market's potential bottom
(ii) Follow-Up Signal - for ensuring you do not miss the bottom
(iii)Follow-Through Signal - for buying strength after a downtrend
(iv) Buy-The-Dip Signal - for buying throwbacks in uptrends and pullbacks in downtrends
/Settings
This strategy works best with the default settings. Although the input parameters can be changed to suit your needs, it is not advisable to do so as it may affect the strategy's performance.
(i) The market regime filter checks to see if the market is in a regime of rising prices (bull market) or falling prices (bear market), long signals are avoided in bear market conditions.
(ii) The risk size is equivalent to a stop loss. It triggers an exit when price declines by a certain amount.
(iii) 'Downside' measures the participation of issues to the downside during a decline while 'Upside' measures the participation of issues to the upside after the decline; this is called 'follow through'.
(iv) The bottom interval determines the frequency of bottom signals issued in days.
(v) Dip size quantifies the dip to determine if it is large enough for a buy signal, the lower the number, the larger the dip.
(vi) Following interval sets the duration for following up on the bottom.
(vii) Bottoming interval resets the bottom for the next follow-up
/Strategy Results
The backtest results are based on a starting capital of $13,700 (convenient amount for retail traders) with $1000 position size (7% of equity and enough for two shares of SPY) and pyramiding of 10 consecutive positions. Commissions of 0.03% and slippage of 2 ticks are used to ensure the results are representative of real world trading conditions. The backtest results are available to view at the bottom of this page.
Note that past results are not indicative of future results. The strategy is backtested in ideal conditions, it has no predictive abilities and results from live trading may not achieve the 2.235 profit factor shown here as each trader may introduce subjectivity or interfere with its performance or market conditions might change significantly. Since the strategy was designed for the US stock market, it has been backtested on the SPY (representative of the US stock market) ETF (for consistency in price across brokers).
/Tickers
This strategy should be used preferably with the SPY ticker which is the ETF for the S&P500. Alternatively, it could be used with VOO and several other S&P500 ETFs or a CFD ticker such as SPX500USD and several others which are based on the futures product. The strategy may not be suitable for futures tickers like ES according to TradingView.
/Access
The MBS is an Invite-Only script hence, traders interested in this strategy should contact me privately to request access.
3kilos BTC 15mThe "3kilos BTC 15m" is a comprehensive trading strategy designed to work on a 15-minute timeframe for Bitcoin (BTC) or other cryptocurrencies. This strategy combines multiple indicators, including Triple Exponential Moving Averages (TEMA), Average True Range (ATR), and Heikin-Ashi candlesticks, to generate buy and sell signals. It also incorporates risk management features like take profit and stop loss.
Indicators
Triple Exponential Moving Averages (TEMA): Three TEMA lines are used with different lengths and sources:
Short TEMA (Red) based on highs
Long TEMA 1 (Blue) based on lows
Long TEMA 2 (Green) based on closing prices
Average True Range (ATR): Custom ATR calculation with EMA smoothing is used for volatility measurement.
Supertrend: Calculated using ATR and a multiplier to determine the trend direction.
Simple Moving Average (SMA): Applied to the short TEMA to smooth out its values.
Heikin-Ashi Close: Used for additional trend confirmation.
Entry & Exit Conditions
Long Entry: Triggered when the short TEMA is above both long TEMA lines, the Supertrend is bullish, the short TEMA is above its SMA, and the Heikin-Ashi close is higher than the previous close.
Short Entry: Triggered when the short TEMA is below both long TEMA lines, the Supertrend is bearish, the short TEMA is below its SMA, and the Heikin-Ashi close is lower than the previous close.
Take Profit and Stop Loss: Both are calculated as a percentage of the entry price, and they are set for both long and short positions.
Risk Management
Take Profit: Set at 1% above the entry price for long positions and 1% below for short positions.
Stop Loss: Set at 3% below the entry price for long positions and 3% above for short positions.
Commission and Pyramiding
Commission: A 0.07% commission is accounted for in the strategy.
Pyramiding: The strategy does not allow pyramiding.
Note
This strategy is designed for educational purposes and should not be considered as financial advice. Always do your own research and consider consulting a financial advisor before engaging in trading.
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.
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 !
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.
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
CC Trend strategy 2- Downtrend ShortTrend Strategy #2
Indicators:
1. EMA(s)
2. Fibonacci retracement with a mutable lookback period
Strategy:
1. Short Only
2. No preset Stop Loss/Take Profit
3. 0.01% commission
4. When in a profit and a closure above the 200ema, the position takes a profit.
5. The position is stopped When a closure over the (0.764) Fibonacci ratio occurs.
* NO IMMEDIATE RE-ENTRIES EVER!*
How to use it and what makes it unique:
This strategy will enter often and stop quickly. The goal with this strategy is to take losses often but catch the big move to the downside when it occurs through the Silvercross/Fibonacci combination. This is a unique strategy because it uses a programmed Fibonacci ratio that can be used within the strategy and on any program. You can manipulate the stats by changing the lookback period of the Fibonacci retracement and looking at different assets/timeframes.
This description tells the indicators combined to create a new strategy, with commissions and take profit/stop loss conditions included, and the process of strategy execution with a description of how to use it. If you have any questions feel free to PM me and boost if you found it helpful. Thank you, pineUSERS!
CHEATCODE1
Dynamic Trendline Break - Strategy [presentTrading]- Introduction and How It Is Different
The Dynamic Trendline Break Strategy is a unique trading algorithm that leverages the power of trendlines and swing detection to identify potential trading opportunities.
Unlike traditional trendline strategies that rely on static trendlines, this strategy dynamically calculates trendlines based on pivot highs and lows.
This dynamic approach allows the strategy to adapt to changing market conditions (especially 24hr markets like Crypto) and potentially identify trading opportunities that static trendlines might miss.
BTCUSD 6hr chart
Tencent 700.HK 1D chart
- Strategy, How It Works
The strategy works by first identifying pivot highs and lows using a lookback period defined by the user. These pivot points are then used to calculate the slope of the trendlines. The slope calculation method can be chosen from three options: Average True Range (ATR), Standard Deviation (Stdev), or Linear Regression (Linreg), providing flexibility to the trader.
Once the trendlines are calculated, the strategy identifies potential trading opportunities when the price crosses over the upper trendline (for long trades) or crosses under the lower trendline (for short trades). The strategy also allows the user to define the trade direction (Long, Short, or Both) and the stop loss method (Fixed or SuperTrend).
- Trade Direction
The trade direction parameter allows the user to define the direction of the trades that the strategy will take. If set to "Long", the strategy will only take long trades when the price crosses over the upper trendline. If set to "Short", the strategy will only take short trades when the price crosses under the lower trendline. If set to "Both", the strategy will take both long and short trades.
- Usage
To use this strategy, simply input your desired parameters for the swing detection lookback, slope, slope calculation method, trade direction, stop loss method, and stop loss level. Once these parameters are set, the strategy will automatically calculate the trendlines and identify potential trading opportunities based on the defined parameters.
- Default Settings
The default settings for the strategy are as follows:
Swing Detection Lookback: 30
Slope: 0.618
Slope Calculation Method: ATR
Trade Direction: Both
Stop Loss Method: SuperTrend
Stop Loss Level: 15%
SuperTrend Factor: 3
SuperTrend Lookback: 21
These settings can be adjusted to suit your trading style and risk tolerance. Always remember to backtest any changes to the settings before live trading.
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!
Crunchster's Normalised Trend StrategyThis is a unique rules-based, systematic trading strategy - in the trend following category.
The strategy is designed for use on the daily timeframe. Specific features of this strategy are outlined below:
1. Uses a transformed price series (which I dub "real price") to generate signals rather than ticker price
2. Uses advanced position sizing and risk management, usually reserved for institutional portfolio management, a proven technique utilised by Commodity Trading Advisors and Managed Futures funds (Algo/Quant funds).
"Real Price" is a transformed price series derived from the sum of volatility adjusted (daily) returns, over the entire price series of an asset. The lookback period of the volatility adjustment is user defined.
A Hull moving average (HMA) is derived from the real price, and used as the main trend determinant. The lookback period of the HMA is user defined. Default lookback of 100 periods (days) ensures a responsive trend indicator, but without leading to over-trading from frequent crossovers (average holding period 14 days on BTC).
The core strategy is very simple, go long when real price crosses over HMA, go short when real price crosses under HMA. New position triggers automatically close open positions in the counter direction.
Position sizing is based on recent price volatility and the user defined annualised risk target. In essence positions are inverse volatility weighted, so larger size is opened during lower volatility and smaller size during increased volatility. Recent volatility is calculated as the standard deviation of returns with 14 period lookback, then extrapolated into an annualised volatility of expected returns. Annualised recent volatility is then referenced to the risk target set by the user to adjust the position size. The default settings are a very conservative 10% annual risk target. Initial capital should be set as the maximum risk capital per trade (ie if $10,000 total capital and 10% risk per trade, initial capital should be $1000). Maximum leverage per position can be set independently, to facilitate hitting risk targets that are greater than the natural volatility of the traded asset, and to accommodate low volatility conditions, whilst maintaining overall risk controls.
Hard stop losses are based on multiples of the average true range of recent price (14 period lookback), user configurable.
Please leave comments regarding further features or refinements. I plan to develop further adding alternative moving average selections and the ability to select/deselect long and short strategies.
3 hours ago
Release Notes:
Added option to compound profits versus using a fixed position capital. Be mindful that compounding will potentially increase profits, but also increase drawdowns and overall risk. Leverage will still cap overall exposure with compounding and therefore provides an additional layer of risk control.
2 hours ago
Release Notes:
Added function to toggle long/short strategy legs on and off.
Premium VWAP Trendfollow Strategy [wbburgin]This is a strongly-revised version of my VWAP Trendfollow Strategy, which follows a substantial reworking to address various structural inefficiencies with the script, such as the narrowing of the standard deviation band upon anchor reset. I will continue updating the original script with planned adjustments, this is a different proof-of-concept that builds off of the original script thesis with a different calculation method and execution.
This strategy is not built for any specific asset or timeframe, and has been backtested on crypto and equities from 1 min-1 day. The previous experimental strategy was heavily-correlated with the actual movement of the asset, which added unpalatable risk to the strategy and increased drawdown. This revised form has a more stable backtesting curve, but I want to heavily emphasize that I cannot guarantee that the strategy will be profitable for your circumstances. Backtesting only goes so far and every exchange has a different fee schedule, which can substantially eat into your profits. At the bottom I will explain the parameters behind the strategy results.
**********
The VWAP Trendfollow Strategy begins with a simple premise: to enter long when the price breaks above the upper standard deviation of a VWAP, and to close the position when the price breaks below the lower standard deviation of the VWAP. This is more effective than initiating the same strategy for a VWMA because the VWAP resets its anchor depending on your chosen anchor period, and the act of resetting its anchor also resets its standard deviation value. As a consequence, in sustained uptrends, the standard deviation is pulled upward to meet the price when the anchor resets, instead of requiring the price to fall all the way back down, as in the lower standard deviation band of the VWMA. This essentially acts as the VWAP itself raising the stop loss at each anchor period, which works well for the overall trend-following strategy.
However, this narrowing can still have consequences for a simple breakout strategy; as the price gradually oscillates towards above or below its standard deviation band, it may cross over the other and produce false signals. This oscillation is worrisome especially when fees are taken into account.
Thus, the premium VWAP Trendfollow strategy has a variable width which detects abnormal narrowing of the band, and adjusts it until it is reasonable to close the variability period. Additionally, a filter is added to the open/close signals to soften the frequency of signals without impacting performance significantly.
This script contains an ATR stop loss and an ATR take profit (which is also a difference between it and the original experimental script), with customizable inputs. The strategy results shown below are with initial capital of $1000, qty entry of 10%, and commissions of 0.06%. It works best on 24/7 instruments, like crypto, but I have found it also works with FAANG stocks or other high volatility / high volume assets. The issue with stocks, however, is that the price can jump/plummet because of abnormal events after-hours, which the strategy cannot pick up on until pre-trading begins the next morning. For that reason I suggest it be used on crypto and, because of its low % profitable (but high average winning trade in relation to its average losing trade), be used on an exchange that has minimal fees or volume-based discounts. In the unfortunate case that you cannot find a minimal fee or volume-discounted fee exchange (such as fellow Americans following the liquidity-retreat on Binance.US), I encourage you to test out the higher anchor periods for the higher timeframes, which will reduce the number of trades and increase the average % per trade.
Additionally, this is a long-term strategy used best for accumulation. It is currently long-only; that may change based off of user input.
**********
Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
METRIC-TREND-TRADERThis script is a Fully Automated trading script meant to be used with "Oanda" broker and the plug-ins for algorithmic trading automation.( FOREX ONLY)
This script is meant to capture "TREND FOLLOWING " for intraday charts (1hour) preferably and will hold for days / weeks .trading on forex markets.
(The combination of indicators includes a short high and low price channel and a longer term high and low price channel)
This script is original in description as being automated to try and capture dynamic trending markets with both long and short fractal price channels. although trend trading is not an original concept. trend trading with this dynamic indicator allows the user visualize both short term and longer term price action at the same time, helping to make better trading decisions. the channels are designed to buy breakouts in the direction of the longer term trend while trailing stop a built-in stop loss that allows normal market movement while attempting to lock in flexible profits.
The concept of this indicator is be able to quickly visualize trends by high lighting the large green areas beneath price "when trending long" which is the difference between the (user defined) short term lows and the (user defined) Long period price lows.
For "down trending" markets a large red area above price will be displayed and this is the difference between the (user defined) short term highs and the (user defined) long term highs.
This strategy uses a lower than reward profile to jump in direction of market moves for continuation,
(1 risk to 4 reward)
in the likelihood the instrument will continue (example) 200 pips before it reverts 50 pips in the counter direction.
This strategy should only be used in markets that you believe are "TRENDING" at the time of trading otherwise you risk trend trading a range market.
This script uses a (user defined period) of short term high and low price ( green/red color) and (user defined period) Long Term high and low price (green/red) chosen in the indicator settings menu.
The default parameters are 10 with a (minimum of 1 and maximum of 10000) for the short term channel and 50 with a (minimum of 1 and maximum of 10000) for the long term price channel , the default parameters = roughly 2 days "long term" and 10 hours "short term" of price action on the (1 hour) chart.
Strategy entries and exits , for Long trades the trade will be entered if the short term high crosses above the Long Term high and the Short term low is not equal to the Long term low . the trade will exit if profit or stop loss are hit or if the Short term low crosses under the long term low.
For Short trades the trade will enter short if , the short term low crosses under the long term low and the short term high is not equal to the long term high. the trade will exit if profit or stop loss are hit or the short term high crosses over the long term high
"The default parameters should be kept unless you fully understand the complete strategy"
There are two very important inputs to be selected at the user setting menu "Long Only " and "Short Only" if you are looking to place long trades only select "Long Only" or for short trades select " Short Only" it is not recommended to keep both selected as it will trade both sides!
When the trade is entered a red , a blue and green horizontal dotted line will appear on the chart.
the blue line is the strategy entry price , the red line is the stop loss price , and the green line is the take profit price . the colors will invert if the trade is long or short.
(Setting alerts should be done in the indicator settings menu, and the parameters you chose will determine the stop loss/target and the amount of "units = (position size)" you wish to trade for the (forex only) markets. using "alert() function calls only" is the only alert that should be used with this strategy.
(note : when "alert() function calls only" is set two messages will be sent, one closing any open position in the opposite direction and one placing the new order regardless if you are currently in a trade or not)
Trade targets , stoploss and trade position size are a user defined variables entered in the indicator settings menu. (target pips minimum 0 and a maximum of 1000)(stop pips minimum of 0 and maximum of 1000)
Back test date range is included in the script for back testing different data periods.
the back ground will be colored a transparent navy blue if the period you are looking trading is with in the date range( note: to place live trades the end date will need to be in the future)
this is also adjustable in the settings menu
The avoid spread filter is a user defined time in which the spread is typically higher than average, applying this filter avoids trades in the specified time. When this filter is applied there will be a transparent red back ground color in the specified time.
Back test default setting are equivocal to OANDA:USDJPY
at the time of this publication placing trades with the "Oanda" broker are as follows , USD units = 2000 equal 2000 USD position size . "Oanda" current leverage is 20 to 1 for this particular pair and commission is paid in spread (1.4) pips = 0.19 USD per trade , Margin required for the trade is 100.0 USD , Position sizing = 10% of a 1000 USD account.
OANDA:USDJPY
PRICE CHANNEL MEAN REVERSIONThis script is a Fully Automated trading script meant to be used with "Oanda" broker and the plug-ins for algorithmic trading automation.( FOREX ONLY)
This script is meant to capture "MEAN REVERSION " for intraday charts (1hour) preferably and will hold for days / weeks .trading on forex markets.
(The combination of indicators includes a high and low price channel along with a fast moving average)
This script is original in the description of Alan Hulls moving average combined with the high and low closing of price action.
The concept of this mean reversion strategy is to try and capture price exhaustive moves . The moving average is fast and most times remains in the channel. when the moving average overshoots the channel the average price of the instrument is thought to be rising or falling faster then average, indicating a possibility that the instrument may revert (pull back) this strategy aims to capture that pull back.
This strategy uses a higher risk than reward profile to jump in front of market moves (4 risk to 1 reward)
in the likelihood the instrument will revert back (example) 25 pips before it continues 100 pips in the current direction.
This strategy should only be used in markets that you believe are mean reverting at the time of trading otherwise you will be jumping Infront of a possible trend and the price can continue in the trending direction for an unknown specified amount of time.
This script uses a (user defined period) fast moving average ( green/red color) and (user defined period) price channel (White/Blue) chosen in the indicator settings menu.
The default parameters are 55 with a (minimum of 1 and maximum of 10000) for the moving average and 50 with a (minimum of 1 and maximum of 10000) for the price channel , the default parameters = roughly 2 days of price action on the (1 hour) chart.
"The default parameters should be kept unless you fully understand the complete strategy"
the upper band (white line) is the highest close of the specified period and the lower band (blue line) is the lowest close of the same period.
When the fast moving average over shoots the price channel (exits) then crosses back into the price channel (enters) it will trigger a long or short trade.
The long signal is given when the the moving average crosses below the low band then crosses back above the low band . The trade long trade will be entered and the trade will exit if the stop loss or profit targets are hit or if the short signal is given the trade will close then reverse.
The short trade will be entered if the fast moving average crosses above the upper band (white line) then crosses back down through the upper band (white line) The trade short trade will be entered and the trade will exit if the stop loss or profit targets are hit or if the long signal is given the trade will close then reverse.
When the trade is entered a red , a blue and green horizontal dotted line will appear on the chart.
the blue line is the strategy entry price , the red line is the stop loss price , and the green line is the take profit price . the colors will invert if the trade is long or short.
(Setting alerts should be done in the indicator settings menu, and the parameters you chose will determine the stop loss/target and the amount of "units = (position size)" you wish to trade for the (forex only) markets. using "alert() function calls only" is the only alert that should be used with this strategy.
(note : when "alert() function calls only" is set two messages will be sent, one closing any open position in the opposite direction and one placing the new order regardless if you are currently in a trade or not)
Trade targets , stoploss and trade position size are a user defined variables entered in the indicator settings menu. (target pips minimum 0 and a maximum of 1000)(stop pips minimum of 0 and maximum of 1000)
Back test date range is included in the script for back testing different data periods.
the back ground will be colored a transparent navy blue if the period you are looking trading is with in the date range( note: to place live trades the end date will need to be in the future)
this is also adjustable in the settings menu
The avoid spread filter is a user defined time in which the spread is typically higher than average, applying this filter avoids trades in the specified time. When this filter is applied there will be a transparent red back ground color in the specified time.
Back test default setting are equivocal to OANDA:NZDUSD
at the time of this publication placing trades with the "Oanda" broker are as follows , NZD units = 3250 equal 2000 USD position size . "Oanda" current leverage is 33.3 to 1 for this particular pair and commission is paid in spread (1.7) pips = 0.55 USD per trade , Margin required for the trade is 60.50 USD , Position sizing = 6.5% of a 1000 USD account. OANDA:NZDUSD
