Flat Combo DetectorFlat Combo Detector (FCD)
Introduction:
The Flat Combo Detector is a unique tool crafted to aid traders in identifying potential trend reversals. Unlike standard indicators that primarily focus on moving averages or oscillators, the FCD bases its signals on specific candlestick patterns that manifest at crucial trend pivot points.
I use it mostly on OANDA:XAUUSD Gold
How It Works:
The logic of the Flat Combo Detector revolves around the formation of consecutive bearish and bullish candles with particular attributes:
Bearish to Bullish Transition:
Primary Candle : A bearish candle where the close is lower than the open and its close is equal to its low.
Following Candle: A bullish candle where the close is higher than the open, and the open approximates its low (within a user-defined tolerance).
Signal : A green triangle plotted below the price bar, indicating a potential shift from a bearish to bullish trend.
Bullish to Bearish Transition:
Primary Candle: A bullish candle where the close is higher than the open and equals its high.
Following Candle : A bearish candle where the close is lower than the open, and the open approximates its high (within a user-defined tolerance).
Signal : A red triangle plotted above the price bar, indicating a potential transition from a bullish to bearish trend.
Usage Guidance:
For traders unfamiliar with Pine Script, using this indicator is straightforward. Once added to the chart, look for the green and red triangle signals. A green triangle below a price bar suggests a possible bullish reversal, while a red triangle above a price bar hints at a potential bearish reversal. Always consider these signals in conjunction with other technical analysis tools and the broader market context to optimize decision-making.
Associated Strategy:
I've also developed a trading strategy that utilizes these specific entry points identified by the FCD. If you find the signals from this indicator helpful, you might also be interested in exploring the strategy for a comprehensive trading approach. Always remember to backtest and validate any strategy before live trading.
Chart Presentation:
The published chart associated with this script has been kept clean to ensure clarity. Users will only observe the main price bars/candles along with the green and red triangle signals generated by the FCD.
Conclusion:
The Flat Combo Detector provides traders with a fresh perspective on trend reversal points. Its focus on specific candlestick patterns makes it a valuable tool, especially when used in combination with other technical indicators. Always ensure to practice prudent risk management and consult multiple analysis methods before making trading decisions.
Komut dosyalarını "the strat" için ara
Three Candle Rolling Pivot Range**Strategy Description: Three Previous Candle Rolling Pivot Range**
**Introduction:**
This trading strategy is based on the concept of the rolling pivot range calculated from the high, low, and close prices of the three previous candles. The rolling pivot range serves as a dynamic support and resistance level, and this strategy aims to capture potential trading opportunities based on the price relationship with this range.
**Strategy Components:**
**1. Rolling Pivot Range Calculation:**
- **Rolling Pivot:** Calculate the rolling pivot by averaging the high, low, and close prices of the three previous candles.
- **Second Number:** Find the midpoint between the high and low of the three previous candles.
- **Pivot Differential:** Measure the difference between the rolling pivot and the second number.
- **Rolling Pivot Range High:** Set as rolling pivot + pivot differential.
- **Rolling Pivot Range Low:** Set as rolling pivot - pivot differential.
**2. Entry Rules:**
- **Long Entry:**
- Initiate a long entry when the current close is above both the rolling pivot range high and the rolling pivot.
- Continue the long entry as long as both the rolling pivot range high and low are higher than the corresponding values of the previous candle.
- **Short Entry:**
- Start a short entry when the current close is below both the rolling pivot range high and the rolling pivot.
- Continue the short entry as long as both the rolling pivot range high and low are lower than the corresponding values of the previous candle.
**Visualization:**
- **Plotting:**
- The rolling pivot range high, rolling pivot, and rolling pivot range low are plotted on the chart for visual reference.
- Long entry points are marked with a green triangle below the corresponding candle.
- Short entry points are marked with a red triangle above the corresponding candle.
**Conclusion:**
This strategy leverages the rolling pivot range to identify potential reversal points in the market. By considering the relative position of the current price compared to the dynamic support and resistance levels, the strategy aims to capture favorable trading opportunities. However, like all trading strategies, it should be used cautiously and backtested thoroughly on historical data to ensure its effectiveness before implementation in a live trading environment. Additionally, risk management techniques should always be applied to safeguard trading capital.
MA RSI @KINGThis Pine Script is designed to create a trading indicator with moving averages (MA) and relative strength index (RSI), along with arrow signals and background color changes based on those signals. Here's a description of its functions:
1. Moving Averages and RSI Calculation:
- Two moving averages (`fastMA` and `slowMA`) are calculated based on user-input lengths.
- The Relative Strength Index (`rsi`) is calculated based on a user-defined length.
2. Crossover Conditions:
- `crossoverUp` is true when the fastMA crosses above the slowMA and RSI is above an overbought level.
- `crossoverDown` is true when the fastMA crosses below the slowMA and RSI is below an oversold level.
3. Arrow Signals:
- Triangle-shaped arrows (`arrowUp` and `arrowDown`) are plotted below and above bars, indicating buy (green) and sell (red) signals, respectively.
4. Background Color Changes:
- The background color (`bgColor`) changes based on buy and sell signals.
- If there's a buy signal (`crossoverUp`), the background color is set to a light blue with 40% transparency.
- If there's a sell signal (`crossoverDown`), the background color is set to a light red with 40% transparency.
- On the next opposite signal, the background color is scaled up (transparency set to 80%) to indicate a stronger signal.
In summary, this script provides visual cues through arrows and background color changes to assist traders in identifying potential buy and sell signals based on moving average crossovers and RSI conditions. The background color variations aim to highlight the strength of the signal, with scaling based on consecutive signals in the same direction.
********************************************************************************
1. Buy Signal:
- Condition: The arrow points up (green) with a background color indicating a buy signal.
- Confirmation: Ensure that there is a strong upward crossover (fastMA above slowMA) and RSI is above the overbought level.
2. Sell Signal:
- Condition: The arrow points down (red) with a background color indicating a sell signal.
- Confirmation: Ensure that there is a strong downward crossover (fastMA below slowMA) and RSI is below the oversold level.
3. Exit Signal:
- Condition: No arrow is present, and the background color is reset.
- Confirmation: Confirm that there is no active buy or sell signal.
Example Trading Rules:
Opening a Long Position (Buy):
- Enter a long (buy) position when:
- The green arrow appears with a light blue background.
- Confirm that the fastMA is above the slowMA.
- Confirm that RSI is above the overbought level.
Opening a Short Position (Sell):
- Enter a short (sell) position when:
- The red arrow appears with a light red background.
- Confirm that the fastMA is below the slowMA.
- Confirm that RSI is below the oversold level.
Exiting a Position:
- Close the position when:
- There is no arrow present (neither green nor red).
- The background color is reset, indicating no active signal.
Risk Management:
Position Sizing: Determine the size of your positions based on your risk tolerance and the size of your trading account.
Stop-Loss and Take-Profit: Set stop-loss orders to limit potential losses and take-profit orders to secure profits.
Risk-Reward Ratio: Consider maintaining a favorable risk-reward ratio in your trades.
Notes:
Backtesting: Before applying this strategy in a live market, it's crucial to backtest it using historical data to assess its performance.
Market Conditions: Adapt the strategy to different market conditions, and be aware that no strategy is guaranteed to be profitable.
Continuous Monitoring: Regularly monitor the performance of the strategy and make adjustments as needed.
Educational Purpose: This strategy is for educational purposes only. Always consult with financial professionals and use your judgment when making trading decisions.
Remember that trading involves risk, and past performance is not indicative of future results. It's recommended to paper trade or use a demo account to test the strategy before risking real capital.
Best wishes on your trading journey! May your strategies be profitable, your risks well-managed, and your decisions guided by wisdom and success. Happy trading!
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
Moving Average Cross trade PLAbstract
This script evaluates the potential trading proceeding and loss of the moving average cross strategy and plot it as a chart.
We can use it as a reference to whether we follow the original trading signals or not.
Introduction
Moving average cross is a popular trading strategy.
The strategy suggests traders buy when the short term moving average is above the long term moving average and sell when the short term moving average is below the long term moving average.
However, just like the most technical indicators, the signals are not always accurate.
This problem causes traders don't have sufficient confidence to trade with these signals.
On the other hand, the natural risk management suggests us only invest after major risks are past.
Therefore, we wait until many counterexamples of trading signals are past.
What will happen if we imagine that following a specific trading signal is a fund?
We can evaluate the potential trading proceeding and loss and plot it as a chart.
And then, we can measure how much loss may encounter in many worst cases and regard it as a reference to whether we follow the original trading signals or not.
How it works
1. Determine the instruments and time frames we are interested in.
2. Determine the long term moving average and the short term moving average.
3. The strategy suggests traders buy when the short term moving average is above the long term moving average and sell when the short term moving average is below the long term moving average.
4. The potential trading proceeding and loss is plotted as a chart.
5. There are two colors in the chart. One is when the short term moving average is above the long term moving average and the other is when the short term moving average is below the long term moving average.
6. We can observe the local maximum and the local minimum or apply other indicators we are interested in on the numbers it provides.
Parameters
x_type1 = How to compute the short term moving average. The option diff means the price several days ago.
x_src1 = How to summarize the price of a trading day. It depends on the open, high, low or close prices.
x_ma1 = How many days included in the short term moving average. When it is 1, the signal becomes when the price is above or below a single moving average.
x_type2 = How to compute the long term moving average
x_src2 = How to summarize the price of a trading day. It depends on the open, high, low or close prices.
x_ma2 = How many days included in the long term moving average
Conclusion
This indicator can quantize the potential trading proceeding and loss and can imply when following the original trading signals is good or not.
Combining the instruments which are long term investible and use this indicator to avoid potential risks, we can make proceeding better than holding the major stock markets.
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.
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.
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.
Greedy DCA█ OVERVIEW
Detect price crashes in volatile conditions. This is an indicator for a greedy dollar cost average (DCA) strategy. That is, for people who want to repeatedly buy an asset over time when its price is crashing.
█ CONCEPTS
Price crashes are indicated if the price falls below one or more of the 4 lower Bollinger Bands which are calculated with increasing multipliers for the standard deviation.
In these conditions, the price is far below the average. Therefore they are considered good buying opportunities.
No buy signals are emitted if the Bollinger Bands are tight, i.e. if the bandwidth (upper -lower band) is below the value of the moving average multiplied with a threshold factor. This ensures that signals are only emitted if the conditions are highly volatile.
The Bollinger Bands are calculated based on the daily candles, irrespective the chart time frame. This allows to check the strategy on lower time frames
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
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.
QuantBot 3:Ultimate MA CrossoverTHIS IS A SAMPLE CODE TO AUTOMATE WITH QUANTBOT
The moving average strategy is a popular and widely used technique in financial analysis and trading. It involves the calculation and analysis of moving averages, which are mathematical indicators that smooth out price data over a specified period. This strategy is primarily applied in the context of stock trading, but it can be used for other financial instruments as well.
The concept behind the moving average strategy is to identify trends and potential entry or exit points in the market. By calculating and analyzing moving averages of different timeframes, traders aim to capture the overall direction of the price movement and filter out short-term fluctuations or noise.
To implement the moving average strategy, a trader typically selects two or more moving averages with different periods. The most common combinations include the 50-day and 200-day moving averages. The shorter-term moving average is considered more reactive to price changes, while the longer-term moving average provides a smoother trend line. When the shorter-term moving average crosses above the longer-term moving average, it generates a buy signal, indicating a potential upward trend. Conversely, when the shorter-term moving average crosses below the longer-term moving average, it generates a sell signal, indicating a potential downward trend.
Traders can use various variations of the moving average strategy based on their trading objectives and risk tolerance. For instance, some traders may prefer to use exponential moving averages (EMAs) instead of simple moving averages (SMAs) to give more weight to recent price data. Others may incorporate additional indicators or filters to confirm signals or avoid false signals.
One of the strengths of the moving average strategy is its simplicity and ease of interpretation. It provides a clear visual representation of the trend direction and potential entry or exit points. However, it's important to note that the moving average strategy is a lagging indicator, meaning that it relies on past price data. Therefore, it may not always accurately predict future market movements or capture sudden reversals.
Like any trading strategy, the moving average strategy is not foolproof and carries risks. It is crucial for traders to conduct thorough analysis, consider other relevant factors, and manage their risk through proper position sizing and risk management techniques. Additionally, it's important to adapt the strategy to specific market conditions and combine it with other complementary strategies or indicators for improved decision-making.
Overall, the moving average strategy serves as a valuable tool for traders to identify and follow trends in financial markets, aiding in the analysis of price movements and potential trading opportunities.
SMA mechanical swing tradeIndicator that compares the closing price of an asset vs a simple moving average as a mechanical swing trading strategy. It allows the user to set any asset and timeframe for the strategy, which can be different from those the user is currently viewing. The strategy also allows the user to set an upside and downside tolerance so that retests within a few % of the SMA get some space to breathe before flipping directional bias.
If the selected asset in the strategy is different from the one currently viewed, the indicator plots the MA for the currently viewed asset but keeps applying the directional bias colors from the strategy asset.
Some examples of recommended usage of this indicator: BTCUSD 120D, BTCUSD 120D applied on ETHUSD, AAVEUSD 365D.
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).
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
Trailing Stop with RSI - Momentum-Based StrategyTrailing Stop with RSI - Momentum-Based Strategy
Description:
The Trailing Stop with RSI strategy combines momentum analysis and trailing stop functionality to help traders identify potential entry and exit points in their trading decisions. This strategy is suitable for various markets and timeframes.
Key Features:
Momentum Analysis: The strategy incorporates momentum indicators to identify potential buying and selling opportunities based on momentum shifts in the price.
Trailing Stop Functionality: The strategy utilizes a trailing stop to protect profits and dynamically adjust the stop loss level as the trade moves in the desired direction.
RSI Confirmation: The Relative Strength Index (RSI) is included to provide additional confirmation for trade entries by considering overbought and oversold conditions.
How to Use:
Entry Conditions: Long positions are triggered when positive momentum is detected, and the RSI confirms an oversold condition. Short positions are triggered when negative momentum is detected, and the RSI confirms an overbought condition.
Trailing Stop Activation: Once a position is opened, the trailing stop is activated when the specified profit level (as a percentage) is reached.
Trailing Stop Level: The trailing stop maintains a stop loss level at a specified distance (as a percentage) from the highest profit achieved since opening the position.
Exit Conditions: The trailing stop will trigger an exit and close all positions when the trailing stop level is breached.
Markets and Conditions:
This strategy can be applied to various markets, including stocks, forex, cryptocurrencies, and commodities. It can be used in trending and ranging market conditions, making it versatile for different market environments.
Important Considerations:
Adjust Parameters: Traders can modify the length of the momentum and RSI indicators to suit their preferred timeframe and trading style.
Risk Management: It is recommended to consider appropriate position sizing, risk-to-reward ratios, and overall risk management practices when using this strategy.
Backtesting and Optimization: Traders are encouraged to backtest the strategy on historical data and optimize the parameters to find the best settings for their chosen market and timeframe.
By incorporating momentum analysis, trailing stop functionality, and RSI confirmation, this strategy aims to provide traders with a systematic approach to capturing profitable trades while managing risk effectively.
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
Williams %R Strategy
The Williams %R Strategy is a trading approach that is based on the Williams Percent Range indicator, available on the TradingView platform.
This strategy aims to identify potential overbought and oversold conditions in the market, providing clear buy and sell signals for entry and exit.
The strategy utilizes the Williams %R indicator, which measures the momentum of the market by comparing the current close price with the highest high and lowest low over a specified period. When the Williams %R crosses above the oversold level, a buy signal is generated, indicating a potential upward price movement. Conversely, when the indicator crosses below the overbought level, a sell signal is generated, suggesting a possible downward price movement.
Position management is straightforward with this strategy. Upon receiving a buy signal, a long position is initiated, and the position is closed when a sell signal is generated. This strategy allows traders to capture potential price reversals and take advantage of short-term market movements.
To manage risk, it is recommended to adjust the position size based on the available capital. In this strategy, the position size is set to 10% of the initial capital, ensuring proper risk allocation and capital preservation.
It is important to note that the Williams %R Strategy should be used in conjunction with other technical analysis tools and risk management techniques. Backtesting and paper trading can help evaluate the strategy's performance and fine-tune the parameters before deploying it with real funds.
Remember, trading involves risks, and past performance is not indicative of future results. It is always advised to do thorough research, seek professional advice, and carefully consider your financial goals and risk tolerance before making any investment decisions.
HK Percentile Interpolation One
This script is designed to execute a trading strategy based on Heikin Ashi candlesticks, moving averages, and percentile levels.
Please note that you should keep your original chart in normal candlestick mode and not switch it to Heikin Ashi mode. The script itself calculates Heikin Ashi values from regular candlesticks. If your chart is already in Heikin Ashi mode, the script would be calculating Heikin Ashi values based on Heikin Ashi values, which would produce incorrect results.
The strategy begins trading from a start date that you can specify by modifying the `startDate` parameter. The format of the date is "YYYY MM DD". So, for example, to start the strategy from January 1, 2022, you would set `startDate = timestamp("2022 01 01")`.
The script uses Heikin Ashi candlesticks, which are plotted in the chart. This approach can be useful for spotting trends and reversals more easily than with regular candlestick charts. This is particularly useful when backtesting in TradingView's "Rewind" mode, as you can see how the Heikin Ashi candles behaved at each step of the strategy.
Buy and sell signals are generated based on two factors:
1. The crossing over or under of the Heikin Ashi close price and the 75th percentile price level.
2. The Heikin Ashi close price being above certain moving averages.
You have the flexibility to adjust several parameters in the script, including:
1. The stop loss and trailing stop percentages (`stopLossPercentage` and `trailStopPercentage`). These parameters allow the strategy to exit trades if the price moves against you by a certain percentage.
2. The lookback period (`lookback`) used to calculate percentile levels. This determines the range of past bars used in the percentile calculation.
3. The lengths of the two moving averages (`yellowLine_length` and `purplLine_length`). These determine how sensitive the moving averages are to recent price changes.
4. The minimum holding period (`holdPeriod`). This sets the minimum number of bars that a trade must be kept open before it can be closed.
Please adjust these parameters according to your trading preferences and risk tolerance. Happy trading!
BB and KC StrategyThis script is designed as a TradingView strategy that uses Bollinger Bands (BB) and Keltner Channels (KC) as the primary indicators for generating trade signals. It aims to catch potential market trends by comparing the movements of these two popular volatility measures.
Key aspects of this strategy:
1. **Bollinger Bands and Keltner Channels:** Both are volatility-based indicators. The Bollinger Bands consist of a middle band (simple moving average) and two outer bands calculated based on standard deviation, which adjusts itself to market conditions. Keltner Channels are a set of bands placed above and below an exponential moving average of the price. The distance between the bands is calculated based on the Average True Range (ATR), a measure of price volatility.
2. **Entry Signals:** The strategy enters a long position when the upper KC line crosses above the upper BB line and the volume is above its moving average. Conversely, it enters a short position when the lower KC line crosses below the lower BB line and the volume is above its moving average.
3. **Exit Signals:** The strategy exits a position under two conditions. First, if the trade has been open for a certain number of bars defined by the user (default 20 bars). Second, a stop loss and trailing stop are in place to limit potential losses and lock in profits as the price moves favorably. The stop loss is set at a percentage of the entry price (default 1.5% for long and -1.5% for short), and the trailing stop is also a percentage of the entry price (default 2%).
4. **Trade Quantity:** The script allows specifying the investment amount for each trade, set to a default of 1000 currency units.
Remember, this is a strategy script, which means it is used for backtesting and not for real-time signals or live trading. It is also recommended that it is used as a tool to aid your trading, not as a standalone system. As with any strategy, it should be tested over different market conditions and used in conjunction with other aspects of technical and fundamental analysis to ensure robustness and effectiveness.
