[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Search in scripts for "momentum"
Flux Charts - S&D Automation💎 GENERAL OVERVIEW
The MTF Supply & Demand Zones (S&D) Automation is a powerful and versatile tool designed to help traders rigorously test their trading strategies against historical market data. With various advanced settings, traders can fine-tune their strategies, assess performance, and identify key improvements before deploying in live trading environments. This tool offers a wide range of configurable settings, explained within this write-up.
Features of the new S&D Automation:
Step By Step : Configure your strategy step by step, which will allow you to have OR & AND logic in your strategies.
Highly Configurable : Offers multiple parameters for fine-tuning trade entry and exit conditions.
Multi-Timeframe Analysis : Allows traders to analyze multiple timeframes simultaneously for enhanced accuracy.
Provides advanced stop-loss, take-profit, and break-even settings.
Incorporates Supply & Demand Zone conditions, with settings like Sensitivity, Zone Invalidation, Minimum Zone Width & Minimum Zone Length settings for refined strategy execution.
🚩 UNIQUENESS
The S&D Automation stands out from conventional backtesting tools due to its unparalleled flexibility, precision, and advanced trading logic integration. Key factors that make it unique include:
✅ Comprehensive Strategy Customization – Unlike traditional backtesters that offer basic entry and exit conditions, S&D Automation provides a highly detailed parameter set, allowing traders to fine-tune their strategies with precision.
✅ Multi-Timeframe Supply & Demand Zones – This is the first-ever tool that allows traders to backtest Supply & Demand zones on multiple timeframes.
✅ Customizable Take-Profit Conditions – Offers various methods to set take-profit exits, including using core features from Supply & Demand Zones, and fixed exits like ATR, % change or price change, enabling traders to tailor their exit strategies to specific market behaviors.
✅ Customizable Stop-Loss Conditions – Provides several ways to set up stop losses, including using concepts from Supply & Demand Zones and trailing stops or fixed exits like ATR, % change or price change, allowing for dynamic risk management tailored to individual strategies.
✅ Integration of External Indicators – Allows the inclusion of other indicators or data sources from TradingView for creating strategy conditions, enabling traders to enhance their strategies with additional insights and data points.
By integrating these advanced features, S&D Automation ensures that traders can rigorously test and optimize their strategies with great accuracy and efficiency.
📌 HOW DOES IT WORK ?
The first setting you will want to set it the pyramiding setting. This setting controls the number of simultaneous trades in the same direction allowed in the strategy. For example, if you set it to 1, only one trade can be active in any time, and the second trade will not be entered unless the first one is exited. If it is set to 2, the script will handle both of them at the same time. Note that you should enter the same value to this pyramiding setting, and the pyramiding setting in the "Properties" tab of the script for this to work.
You can enable and set a backtesting window that will limit the entries to between the start date & end date.
Then, you can enter your desired settings for Supply & Demand Zones. You can also enable and set up to 3 timeframes, which you can use later on when customizing your strategies enter / exit conditions.
Entry Conditions
From the "Long Conditions" or the "Short Conditions" groups, you can set your position entry conditions. For settings like "initial capital" or "order size", you can open the "Properties" tab, where these are handled.
The S&D Automation can use the following conditions for entry conditions :
1. Demand Zone
Detection: Triggered when a Demand Zone forms or is detected
Retest: Triggered when price retests a Demand Zone. A retest is confirmed when a candle enters a Demand Zone and closes outside of it.
2nd Retest: Triggered when price retests a Demand Zone for the second time. A retest is confirmed when a candle enters a Demand Zone and closes outside of it.
3rd Retest: Triggered when price retests a Demand Zone for the third time. A retest is confirmed when a candle enters a Demand Zone and closes outside of it.
Retracement: Triggered when price touches a Demand Zone
Break: Triggered when a Demand Zone is invalidated by candle close or wick, depending on the user's input.
2. Supply Zone
Detection: Triggered when a Supply Zone forms or is detected
Retest: Triggered when price retests a Supply Zone. A retest is confirmed when a candle enters a Supply Zone and closes outside of it.
2nd Retest: Triggered when price retests a Supply Zone for the second time. A retest is confirmed when a candle enters a Supply Zone and closes outside of it.
3rd Retest: Triggered when price retests a Supply Zone for the third time. A retest is confirmed when a candle enters a Supply Zone and closes outside of it.
Retracement: Triggered when price touches a Supply Zone
Break: Triggered when a Supply Zone is invalidated by candle close or wick, depending on the user's input.
3. Any Zone
Detection: Triggered when any Supply or Demand Zone forms or is detected
Retest: Triggered when price retests any Supply or Demand Zone. A retest is confirmed when a candle enters any Supply or Demand Zone and closes outside of it.
2nd Retest: Triggered when price retests any Supply or Demand Zone for the second time. A retest is confirmed when a candle enters any Supply or Demand Zone and closes outside of it.
3rd Retest: Triggered when price retests any Supply or Demand Zone for the third time. A retest is confirmed when a candle enters any Supply or Demand Zone and closes outside of it.
Retracement: Triggered when price touches any Supply or Demand Zone
Break: Triggered when any Supply or Demand Zone is invalidated by candle close or wick, depending on the user's input.
🕒 TIMEFRAME CONDITIONS
The S&D Automation supports Multi-Timeframe (MTF) features, just like the Supply & Demand indicator. When setting an entry condition, you can also choose the timeframe.
To set up MTF conditions, navigate to the 'Timeframes' section in the settings, select your desired timeframes, and enable them. You can choose up to three timeframes.
Once you've selected your timeframes, you can use them in your strategy. When setting long and short entry/exit conditions, you can choose from Timeframe 1, Timeframe 2, or Timeframe 3.
External Conditions
Users can use external indicators on the chart to set entry conditions.
The second dropdown in the external condition settings allows you to choose a conditional operator to compare external outputs. Available options include:
Less Than or Equal To: <=
Less Than: <
Equal To: =
Greater Than: >
Greater Than or Equal To: >=
The position entry conditions work like this ;
Each side has 5 S&D Zone conditions and 1 Source condition. Each condition can be enabled or disabled using the checkbox on the left side of them.
The next selection is the alert type, which you can select between "Detection", "Retest", "Retracement" or "Break".
You can select which timeframe this condition should work on from Timeframe 1, 2, or 3. If you select "Any Timeframe", the condition will work for all timeframes.
Lastly select the step of this condition from 1 to 6.
The Source Condition
The last condition on each side is a source condition that is different from the others. Using this condition, you can create your own logic using other indicators' outputs on your chart. For example, suppose that you have an EMA indicator in your chart. You can have the source condition to something like "EMA > high".
The Step System
Each condition has a step number, and conditions are in topological order based on them.
The conditions are executed step by step. This means the condition with step 2 cannot be executed before the condition with step 1 is executed.
Conditions with the same step numbers have "OR" logic. This means that if you have 2 conditions with step 3, the condition with step 4 can trigger after only one of the step 3 conditions is executed.
➕ OTHER ENTRY FEATURES
The S&D Automation allows traders to choose when to execute trades and when not to execute trades.
1. Only Take Trades
This setting lets users specify the time period when their strategy can open or execute trades.
2. Don't Take Trades
This setting lets users specify time periods when their strategy can't open or execute trades.
↩️ EXIT CONDITIONS
1. Exit on Opposite Signal
When enabled, a long position will close when short entry conditions are met, and a short position will close when long entry conditions are met.
2. Exit on Session End
When enabled, positions will be closed at the end of the trading session.
📈 TAKE PROFIT CONDITIONS
There are several methods available for setting take profit exits and conditions.
1. Entry Condition TP
Users can use entry conditions as triggers for take-profit exits. This setting can be found under the long and short exit conditions.
2. Fixed TP
Users can set a fixed TP for exits. This setting can be found under the long and short exit conditions. Users can choose between the following:
Price: This method triggers a TP exit when price reaches a specified level. For example, if you set the Price TP to 10 and buy NASDAQ:TSLA at $190, the trade will automatically exit when the price reaches $200 ($190 + $10).
Ticks: This method triggers a TP exit when price moves a specified number of ticks.
Percentage (%): This method triggers a TP exit when price moves a specified percentage.
ATR: This method triggers a TP exit based on a specified multiple of the Average True Range (ATR).
📉 STOP LOSS CONDITIONS
There are several methods available for setting stop-loss exits and conditions.
1. Entry Condition SL
Users can use entry conditions as triggers for stop-loss exits. This setting can be found under the long and short exit conditions.
2. Fixed SL
Users can set a fixed SL for exits. This setting can be found under the long and short exit conditions. Users can choose between the following:
Price: This method triggers a SL exit when price reaches a specified level. For example, if you set the Price SL to 10 and buy NASDAQ:TSLA at $200, the trade will automatically exit when the price reaches $190 ($200 - $10).
Ticks: This method triggers a SL exit when price moves a specified number of ticks.
Percentage (%): This method triggers a SL exit when price moves a specified percentage.
ATR: This method triggers a SL exit based on a specified multiple of the Average True Range (ATR).
3. Trailing Stop
An explanation & example for the trailing stop feature is present on the write-up within the next section.
Exit conditions have the same logic of constructing conditions like the entry ones. You can construct a Take-Profit Condition & a Stop-Loss Condition. Note that the Take-Profit condition will only work if the position is in profit, regardless of if it's triggered or not. The same applies for the Stop-Loss condition, meaning that it will only work if the position is in loss.
You can also set a Fixed TP & Fixed SL based on the price movement after the position is entered. You have options like "Price", "Ticks", "%", or "Average True Range". For example, you can set a Fixed TP like "5%", and the position will be entered once it moves 5% up in a long position.
Trailing Stop
For the Fixed SL, you also have a "Trailing" stop option, for which you can set its activation level as well. The Trailing stop activation level and its value are expressed in ticks. Check this scenario for an example :
We have a ticker with a tick value of $1. Our Trailing Stop is set to 10 ticks, and the activation level is set to 30 ticks.
We buy 1 contract when the price is $100.
When the price becomes $110, we are in $10 (10 ticks) profit and the trailing stop is now activated.
The current price our stop's on is $110 - $30 (30 ticks), which is the level of $80.
The trailing stop will only move if the price moves up the highest high the price has been after we entered the position.
Let's suppose that price moves up $40 right after our trailing stop is activated. The price will now be $150, and our trailing stop will sit on $150 - $30 (30 ticks) = $120.
If the price is down the $120 level, our stop loss will be triggered.
There is also a "Hard SL" option designed for a backup stop-loss when trailing stops are enabled. You can enable & set this option and if the price goes down before our trailing stop even activates, the position will be exited.
You can also move stop-loss to the break-even (entry price of the position) after a certain profit is achieved using the last setting of the exit conditions. Note that for this to work, you must have a Fixed SL set-up.
➕ OTHER EXIT FEATURES
1. Move Stop Loss to Breakeven
This setting allows the strategy to automatically move the SL to Breakeven (BE) when the position is in profit by a certain amount. Users can choose between the following:
Price: This method moves the SL to BE when price reaches a specified level.
Ticks: This method moves the SL to BE when price moves a specified number of ticks.
Percentage (%): This method moves the SL to BE when price moves a specified percentage.
ATR: This method moves the SL to BE when price moves a specified multiple of the Average True Range (ATR).
Example Entry Scenario
To give an example , check this scenario; out conditions are :
LONG CONDITIONS
Demand Zone Detection, Step 1
Supply Zone Retest, Step 2
Demand Zone Break, Step 2
open > close, Step 3
First, the strategy needs to detect a Demand Zone Detection in order to start working.
After it's detected, now it's looking for either a Supply Zone Retest, or a Demand Zone Break to proceed to the next step, the reason for this is that they both have the same step number.
After one of them is detected, the strategy will consistently check candlesticks for the condition open > close. If a bullish candlestick occurs, a long position will be entered.
⏰ ALERTS
This indicator uses TradingView's strategy alert system. All entries and exits will be sent as an alert if configured. It's possible to further customize these alerts to your liking. For more information check TradingView's strategy alert customization page : www.tradingview.com
⚙️ SETTINGS
1. Backtesting Settings
Pyramiding: Controls the number of simultaneous trades allowed in the strategy. This setting must have the same value that is entered on the script's properties tab on the settings pane.
Enable Custom Backtesting Period: Restricts backtesting to a specific date range.
Start & End Time Configuration: Define precise start and end dates for historical analysis.
2. General Configuration
Detection Method: There are two detection methods you can choose from for identifying Supply & Demand Zones. Both methods aim to identify key areas where price is likely to react, but they do so using different approaches. Traders can choose the method that aligns with their trading style and time horizon.
Sensitivity: The Sensitivity setting allows traders to adjust how aggressively the script identifies supply and demand zones when using the Momentum Detection Method. This setting directly impacts the threshold for detecting zones when using the momentum detection method.
Zone Invalidation: The Zone Invalidation setting determines how supply and demand zones are invalidated.
Wick -> A zone is invalidated if a candle’s wick goes below a demand zone or above a supply zone.
Close -> A zone is invalidated if a candle closes below a demand zone or above a supply zone.
Zone Visibility Range: The Zone Visibility Range setting controls how far from the current price supply and demand zones are displayed on the chart. It helps traders focus on relevant zones while avoiding clutter from distant or less impactful areas.
Minimum Zone Width: The Minimum Zone Width setting defines the smallest size a supply or demand zone must have to be displayed on the chart. It uses the Average True Range (ATR) as a reference to ensure zones are proportionate to current market volatility.
Minimum Zone Length: The Minimum Zone Length setting determines the minimum number of bars a supply or demand zone must span to be displayed on the chart. This setting helps filter out short-lived or insignificant zones, ensuring only meaningful areas of supply or demand are highlighted.
3. Multi-Timeframe Analysis
Enable Up to Three Timeframes: Select and analyze trades across multiple timeframes.
4. Entry Conditions for Long & Short Trades
Multiple Conditions (1-6): Configure up to six independent conditions per trade direction.
Condition Types: Options include Detection, Retest, 2nd Retest, 3rd Retest, Retracement, and Break.
Timeframe Specification: Choose between "Any Timeframe", "Timeframe 1", "Timeframe 2", or "Timeframe 3".
Trade Execution Filters: Restrict trades within specific trading sessions.
5. Exit Conditions for Long & Short Trades
Exit on Opposite Signal: Automatically exit trades upon opposite trade conditions.
Exit on Session End: Closes all positions at the end of the trading session.
Multiple Take-Profit (TP) and Stop-Loss (SL) Configurations:
TP/SL based on % move, ATR, Ticks, or Fixed Price.
Hard SL option for additional risk control.
Move SL to BE (Break Even) after a certain profit threshold.
Simple Time-Based Strategy(Price Action Hypothesis)Core Theory: Trend Continuation Pattern Recognition**
1. **Price Action Hypothesis**
The strategy is built on the assumption that consecutive price movements (3-bar patterns) indicate momentum continuation:
- *Long Pattern*: Three consecutive higher closes combined with ascending highs
- *Short Pattern*: Three consecutive lower closes combined with descending lows
This reflects a belief that sustained directional price movement creates self-reinforcing trends that can be captured through simple pattern recognition.
2. **Time-Based Risk Management**
Implements a dynamic exit mechanism:
- *Training Phase*: 5-bar holding period (quick turnover)
- *Testing Phase*: 10-bar holding period (extended exposure)
This dual timeframe approach suggests the hypothesis that market conditions may require different holding durations in different market eras.
3. **Adaptive Market Hypothesis**
The structure incorporates two distinct phases:
- *Training Period (11 years)*: Pattern recognition without stop losses
- *Testing Period*: Pattern recognition with stop losses
This assumes markets may change character over time, requiring different risk parameters in different epochs.
4. **Asymmetric Risk Control**
Implements stop-losses only in the testing phase:
- Fixed 500-pip (point) stop distance
- Activated post-training period
This reflects a belief that historical patterns might need different risk constraints than real-time trading.
5. **Dual-Path Validation**
The split between training/testing phases suggests:
- Pattern validity should first be confirmed without protective stops
- Real-world implementation requires added risk constraints
6. **Market Efficiency Paradox**
The simultaneous use of both long/short entries assumes:
- Markets exhibit persistent inefficiencies
- These inefficiencies manifest differently in bullish/bearish conditions
- A symmetric approach can capture opportunities in both directions
7. **Behavioral Finance Elements**
The 3-bar pattern recognition potentially exploits:
- Herd mentality in trend formation
- Delayed reaction to price momentum
- Cognitive bias in trend confirmation
8. **Quantitative Time Segmentation**
The annual-based period division (training vs testing) implies:
- Market cycles operate on multi-year timeframes
- Strategy robustness requires validation across different market regimes
- Parameter sensitivity needs temporal validation
This strategy combines elements of technical pattern recognition, temporal adaptability, and phased risk management to create a systematic approach to trend exploitation. The theoretical framework suggests markets exhibit persistent but evolving patterns that can be systematically captured through rule-based execution.
Tick Marubozu StrategyStrategy Concept:
This strategy identifies Marubozu candles on a tick chart (customizable pip size) with high volume to signal strong market momentum.
Bearish Marubozu → Strong selling pressure → Enter a SELL trade
Bullish Marubozu → Strong buying pressure → Enter a BUY trade
Entry Conditions:
Marubozu Definition:
Open price ≈ High for a bearish Marubozu (minimal wick at the top).
Open price ≈ Low for a bullish Marubozu (minimal wick at the bottom).
Customizable body size (in pips).
High Volume Confirmation:
The volume of the Marubozu candle must be above the moving average of volume (e.g., 20-period SMA).
Trade Direction:
Bearish Marubozu with High Volume → SELL
Bullish Marubozu with High Volume → BUY
Exit Conditions:
Time-Based Expiry: Since it's for binary options, the trade duration is pre-defined (e.g., 1-minute expiry).
Reversal Candle: If a strong opposite Marubozu appears, it may indicate a trend shift.
Consecutive Bearish Candle Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bearish Candle Strategy" is a momentum-based strategy designed to identify potential reversals after a sustained bearish move. It enters a long position when a specific number of consecutive bearish candles occur and exits when the price shows strength by exceeding the previous bar's high. This strategy is optimized for use on various timeframes and instruments.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price has been lower than the previous close for at least `Lookback` consecutive bars. This indicates a sustained bearish move, suggesting a potential reversal.
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Lookback: The number of consecutive bearish bars required to trigger a Buy Signal. Default is 3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for markets with frequent momentum shifts.
It performs best in volatile conditions where price movements are significant.
Backtesting results should be analysed to optimize the `Lookback` parameter for specific instruments.
KAMA Cloud STIndicator:
Description:
The KAMA Cloud indicator is a sophisticated trading tool designed to provide traders with insights into market trends and their intensity. This indicator is built on the Kaufman Adaptive Moving Average (KAMA), which dynamically adjusts its sensitivity to filter out market noise and respond to significant price movements. The KAMA Cloud leverages multiple KAMAs to gauge trend direction and strength, offering a visual representation that is easy to interpret.
How It Works:
The KAMA Cloud uses twenty different KAMA calculations, each set to a distinct lookback period ranging from 5 to 100. These KAMAs are calculated using the average of the open, high, low, and close prices (OHLC4), ensuring a balanced view of price action. The relative positioning of these KAMAs helps determine the direction of the market trend and its momentum.
By measuring the cumulative relative distance between these KAMAs, the indicator effectively assesses the overall trend strength, akin to how the Average True Range (ATR) measures market volatility. This cumulative measure helps in identifying the trend’s robustness and potential sustainability.
The visualization component of the KAMA Cloud is particularly insightful. It plots a 'cloud' formed between the base KAMA (set at a 100-period lookback) and an adjusted KAMA that incorporates the cumulative relative distance scaled up. This cloud changes color based on the trend direction — green for upward trends and red for downward trends, providing a clear, visual representation of market conditions.
How the Strategy Works:
The KAMA Cloud ST strategy employs multiple KAMA calculations with varying lengths to capture the nuances of market trends. It measures the relative distances between these KAMAs to determine the trend's direction and strength, much like the original indicator. The strategy enhances decision-making by plotting a 'cloud' formed between the base KAMA (set to a 100-period lookback) and an adjusted KAMA that scales according to the cumulative relative distance of all KAMAs.
Key Components of the Strategy:
Multiple KAMA Layers: The strategy calculates KAMAs for periods ranging from 5 to 100 to analyze short to long-term market trends.
Dynamic Cloud: The cloud visually represents the trend’s strength and direction, updating in real-time as the market evolves.
Signal Generation: Trade signals are generated based on the orientation of the cloud relative to a smoothed version of the upper KAMA boundary. Long positions are initiated when the market trend is upward, and the current cloud value is above its smoothed average. Conversely, positions are closed when the trend reverses, indicated by the cloud falling below the smoothed average.
Suggested Usage:
Market: Stocks, not cryptocurrency
Timeframe: 1 Hour
Indicator:
Systematic Risk Aggregation ModelThe “Systematic Risk Aggregation Model” is a quantitative trading strategy implemented in Pine Script™ designed to assess and visualize market risk by aggregating multiple financial risk factors. This model uses a multi-dimensional scoring approach to quantify systemic risk, incorporating volatility, drawdowns, put/call ratios, tail risk, volume spikes, and the Sharpe ratio. It derives a composite risk score, which is dynamically smoothed and plotted alongside adaptive Bollinger Bands to identify trading opportunities. The strategy’s theoretical framework aligns with modern portfolio theory and risk management literature (Markowitz, 1952; Taleb, 2007).
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Key Components of the Model
1. Volatility as a Risk Proxy
The model calculates the standard deviation of the closing price over a specified period (volatility_length) to quantify market uncertainty. Volatility is normalized to a score between 0 and 100, using its historical minimum and maximum values.
Reference: Volatility has long been regarded as a critical measure of financial risk and uncertainty in capital markets (Hull, 2008).
2. Drawdown Assessment
The drawdown metric captures the relative distance of the current price from the highest price over the specified period (drawdown_length). This is converted into a normalized score to reflect the magnitude of recent losses.
Reference: Drawdown is a key metric in risk management, often used to measure potential downside risk in portfolios (Maginn et al., 2007).
3. Put/Call Ratio as a Sentiment Indicator
The strategy integrates the put/call ratio, sourced from an external symbol, to assess market sentiment. High values often indicate bearish sentiment, while low values suggest bullish sentiment (Whaley, 2000). The score is normalized similarly to other metrics.
4. Tail Risk via Modified Z-Score
Tail risk is approximated using the modified Z-score, which measures the deviation of the closing price from its moving average relative to its standard deviation. This approach captures extreme price movements and potential “black swan” events.
Reference: Taleb (2007) discusses the importance of considering tail risks in financial systems.
5. Volume Spikes as a Proxy for Market Activity
A volume spike is defined as the ratio of current volume to its moving average. This ratio is normalized into a score, reflecting unusual trading activity, which may signal market turning points.
Reference: Volume analysis is a foundational tool in technical analysis and is often linked to price momentum (Murphy, 1999).
6. Sharpe Ratio for Risk-Adjusted Returns
The Sharpe ratio measures the risk-adjusted return of the asset, using the mean log return divided by its standard deviation over the same period. This ratio is transformed into a score, reflecting the attractiveness of returns relative to risk.
Reference: Sharpe (1966) introduced the Sharpe ratio as a standard measure of portfolio performance.
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Composite Risk Score
The composite risk score is calculated as a weighted average of the individual risk factors:
• Volatility: 30%
• Drawdown: 20%
• Put/Call Ratio: 20%
• Tail Risk (Z-Score): 15%
• Volume Spike: 10%
• Sharpe Ratio: 5%
This aggregation captures the multi-dimensional nature of systemic risk and provides a unified measure of market conditions.
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Dynamic Bands with Bollinger Bands
The composite risk score is smoothed using a moving average and bounded by Bollinger Bands (basis ± 2 standard deviations). These bands provide dynamic thresholds for identifying overbought and oversold market conditions:
• Upper Band: Signals overbought conditions, where risk is elevated.
• Lower Band: Indicates oversold conditions, where risk subsides.
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Trading Strategy
The strategy operates on the following rules:
1. Entry Condition: Enter a long position when the risk score crosses above the upper Bollinger Band, indicating elevated market activity.
2. Exit Condition: Close the long position when the risk score drops below the lower Bollinger Band, signaling a reduction in risk.
These conditions are consistent with momentum-based strategies and adaptive risk control.
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Conclusion
This script exemplifies a systematic approach to risk aggregation, leveraging multiple dimensions of financial risk to create a robust trading strategy. By incorporating well-established risk metrics and sentiment indicators, the model offers a comprehensive view of market dynamics. Its adaptive framework makes it versatile for various market conditions, aligning with contemporary advancements in quantitative finance.
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References
1. Hull, J. C. (2008). Options, Futures, and Other Derivatives. Pearson Education.
2. Maginn, J. L., Tuttle, D. L., McLeavey, D. W., & Pinto, J. E. (2007). Managing Investment Portfolios: A Dynamic Process. Wiley.
3. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91.
4. Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
5. Sharpe, W. F. (1966). Mutual Fund Performance. The Journal of Business, 39(1), 119–138.
6. Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House.
7. Whaley, R. E. (2000). The Investor Fear Gauge. The Journal of Portfolio Management, 26(3), 12–17.
FON60DK by leventsahThe strategy generates buy and sell signals using the Tillson T3 and TOTT (Twin Optimized Trend Tracker) indicators. Additionally, the Williams %R indicator is used to filter the signals. Below is an explanation of the main components of the code:
1. Input Parameters:
Tillson T3 and TOTT parameters: Separate parameters are defined for both buy (AL) and sell (SAT) conditions. These parameters control the sensitivity and behavior of the indicators.
Williams %R period: The period for the Williams %R indicator is set to determine overbought and oversold levels.
2. Tillson T3 Calculation:
The Tillson T3 indicator is a smoothed moving average that uses an exponential moving average (EMA) with additional smoothing. The formula calculates a weighted average of multiple EMAs to produce a smoother line.
The t3 function computes the Tillson T3 value based on the close price and the input parameters.
3. TOTT Calculation (Twin Optimized Trend Tracker):
The TOTT indicator is a trend-following tool that adjusts its sensitivity based on market conditions. It uses a combination of price action and a volatility coefficient to determine trend direction.
The Var_Func function calculates the TOTT value, which is then used to derive the OTT (Optimized Trend Tracker) levels for both buy and sell conditions.
4. Williams %R Calculation:
Williams %R is a momentum oscillator that measures overbought and oversold levels. It is calculated using the highest high and lowest low over a specified period.
5. Buy and Sell Conditions:
Buy Condition: A buy signal is generated when the Tillson T3 value crosses above the TOTT upper band (OTTup) and the Williams %R is above -20 (indicating an oversold condition).
Sell Condition: A sell signal is generated when the Tillson T3 value crosses below the TOTT lower band (OTTdnS) and the Williams %R is above -70 (used to close long positions).
6. Strategy Execution:
The strategy.entry function is used to open a long position when the buy condition is met.
The strategy.close function is used to close the long position when the sell condition is met.
7. Visualization:
The bars on the chart are colored green when a long position is open.
The Tillson T3, TOTT upper band (OTTup), and TOTT lower band (OTTdn) are plotted on the chart for both buy and sell conditions.
8. Plots:
The Tillson T3 values for buy and sell conditions are plotted in blue.
The TOTT upper and lower bands are plotted in green and red, respectively, for both buy and sell conditions.
Summary:
This strategy combines trend-following indicators (Tillson T3 and TOTT) with a momentum oscillator (Williams %R) to generate buy and sell signals. The use of separate parameters for buy and sell conditions allows for fine-tuning the strategy based on market behavior. The visual elements, such as colored bars and plotted indicators, help traders quickly identify signals and trends on the chart.
DCA Buy v1Key Features
1. Selective Entry Filters
Trend Filter
Enabled through "Enable Trend Filter?" using the "EMA Length" setting to ensure entries align with prevailing trends.
Momentum Filter
Configured using "Enable Momentum Filter?" combined with "RSI Length" and "RSI Source" to detect oversold conditions.
Bollinger Filter
Activated via "Enable Bollinger Filter?" along with "BB Length" and "BB Multiplier" to focus entries on deeper price dips below Bollinger Bands.
2. DCA Configuration
Base Order Settings
Choose between a percentage ("Base Order % of Equity/Initial Capital") or fixed value ("Base Order Value ($)").
Safety Order Settings
Fine-tune "Initial Deviation (%)" and "Price Deviation Multiplier" to control the spacing of safety orders.
Use "Volume Scaling Factor (Qty)" to scale the size of each subsequent safety order.
Customize the "First Safety Order Type" as either value-based or a multiplier of the base order using "1st Safety Order Value ($)" or "1st Safety Order Multiplier (Qty)".
Set the maximum number of safety orders through "Max Safety Orders".
3. Profit and Risk Management
Take Profit Settings
"Take Profit (%)" triggers a sell when a specific profit percentage above the average entry is reached.
Use "Trailing Take Profit (%)" to lock in profits while capturing additional upside if prices continue to rise.
Stop Loss Settings
Configure "Stop Loss (%)" to prevent excessive drawdowns by closing all positions when prices drop below a defined percentage.
4. Time Control & Visualization
Time Filters
Define trading windows with "Start Time" and "End Time".
Use "Cooldown (Seconds)" to avoid frequent entries during rapid price movements.
Visualization
Enable "Show Average Entry Price", "Show Take Profit Level", and "Show Stop Loss Level" to plot key levels on the chart for better monitoring.
5. Performance Metrics
Built-in performance tracking includes:
Net Profit (%): Measures overall profitability.
Win Rate (%): Displays the ratio of winning trades.
Max Drawdown (%): Tracks the largest equity decline.
Trading Days: Calculates the duration of active trades.
Profit/Day (%): Evaluates daily returns.
The performance table also shows average cycle duration and utilization of available capital.
EMA Crossover with RSI and DistanceEMA Crossover with RSI and Distance Strategy
This strategy combines Exponential Moving Averages (EMA) with Relative Strength Index (RSI) and distance-based conditions to generate buy, sell, and neutral signals. It is designed to help traders identify entry and exit points based on multiple technical indicators.
Key Components:
Exponential Moving Averages (EMA):
The strategy uses four EMAs: EMA 5, EMA 13, EMA 40, and EMA 55.
A buy signal (long) is triggered when EMA 5 crosses above EMA 13 and EMA 40 crosses above EMA 55.
A sell signal (short) is generated when EMA 55 crosses above EMA 40.
The distance between EMAs (5 and 13) is also important. If the current distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, a neutral condition is triggered, preventing a signal even if all other conditions are met.
Relative Strength Index (RSI):
The 14-period RSI is used to determine market strength and direction.
The strategy requires RSI to be above 50 and greater than the average RSI (over the past 14 periods) for a buy signal.
If the RSI is above 60, a green signal is given, indicating a strong bullish condition, even if the EMA conditions are not fully met.
If the RSI is below 40, a red signal is given, indicating a strong bearish condition, regardless of the EMA crossover.
Distance Conditions:
The strategy calculates the distance between EMA 5 and EMA 13 on each candle and compares it to the average distance of the last 5 candles.
If the current distance between EMA 5 and EMA 13 is lower than the average of the last 5 candles, a neutral signal is triggered. This helps avoid entering a trade when the market is losing momentum.
Additionally, if the distance between EMA 40 and EMA 13 is greater than the previous distance, the previous signal is kept intact, ensuring that the trend is still strong enough for the signal to remain valid.
Signal Persistence:
Once a buy (green) or sell (red) signal is triggered, it remains intact as long as the price is closing above EMA 5 for long trades or below EMA 55 for short trades.
If the price moves below EMA 5 for long trades or above EMA 55 for short trades, the signal is recalculated based on the most recent conditions.
Signal Display:
Green Signals: Represent a strong buy signal and are shown below the candle when the RSI is above 60.
Red Signals: Represent a strong sell signal and are shown above the candle when the RSI is below 40.
Neutral Signals: Displayed when the conditions for entry are not met, specifically when the EMA distance condition is violated.
Long and Short Signals: Additional signals are shown based on the EMA crossovers and RSI conditions. These signals are plotted below the candle for long positions and above the candle for short positions.
Trade Logic:
Long Entry: Enter a long trade when EMA 5 crosses above EMA 13, EMA 40 crosses above EMA 55, and the RSI is above 50 and greater than the average RSI. Additionally, the current distance between EMA 5 and EMA 13 should be larger than the average distance of the last 5 candles.
Short Entry: Enter a short trade when EMA 55 crosses above EMA 40 and the RSI is below 40.
Neutral Condition: If the distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, the strategy will not trigger a signal, even if other conditions are met.
IU 4 Bar UP StrategyIU 4 Bar UP Strategy
The IU 4 Bar UP Strategy is a trend-following strategy designed to identify and execute long trades during strong bullish momentum, combined with confirmation from the SuperTrend indicator. This strategy is suitable for traders aiming to capitalize on sustained upward market movements.
Features :
1. SuperTrend Confirmation: Incorporates the SuperTrend indicator as a dynamic support/resistance line to filter trades in the direction of the trend.
2. 4 Consecutive Bullish Bars: Detects a series of 4 bullish candles as a signal for strong upward momentum, ensuring robust trade setups.
3. Dynamic Alerts: Sends alerts for trade entries and exits to keep traders informed.
4. Visual Enhancements:
- Plots the SuperTrend indicator on the chart.
- Changes the background color while a trade is active for easy visualization.
Inputs :
- SuperTrend ATR Period: The period used to calculate the Average True Range (ATR) for the SuperTrend indicator.
- SuperTrend ATR Factor: The multiplier for the ATR in the SuperTrend calculation.
Entry Conditions :
A long entry is triggered when:
1. The last 4 consecutive candles are bullish (closing prices are higher than opening prices).
2. The current price is above the SuperTrend line.
3. The strategy is not already in a position.
4. The bar is confirmed (not a partially formed bar).
When all these conditions are met, the strategy enters a long position and provides an alert:
"Long Entry triggered"
Exit Conditions :
The strategy exits the long position when:
1. The closing price drops below the SuperTrend line.
2. An alert is generated: "Close the long Trade"
Visualization :
- The SuperTrend line is plotted, dynamically colored:
- Green when the trend is bullish.
- Red when the trend is bearish.
- The background color turns semi-transparent green while a trade is active, indicating a long position.
Do use proper risk management while using this strategy.
Refined SMA/EMA Crossover with Ichimoku and 200 SMA FilterYour **Refined SMA/EMA Crossover with Ichimoku and 200 SMA Filter** strategy is a multi-faceted technical trading strategy that combines several key technical indicators to refine entry and exit points for trades. Here's a breakdown of the components and how they work together:
### 1. **SMA/EMA Crossover**
- **Simple Moving Average (SMA) & Exponential Moving Average (EMA) Crossover**:
- The core idea behind the crossover strategy is to use the relationship between two moving averages to generate buy or sell signals.
- **SMA** (Simple Moving Average) gives an average of past prices over a set period.
- **EMA** (Exponential Moving Average) places more weight on recent prices, making it more responsive to price movements.
- A **bullish crossover** occurs when a shorter period moving average (such as a 50-period EMA) crosses above a longer period moving average (such as a 200-period SMA), signaling a potential buy.
- A **bearish crossover** occurs when a shorter period moving average crosses below the longer period moving average, signaling a potential sell.
### 2. **Ichimoku Cloud**
- The **Ichimoku Cloud** is a versatile indicator that provides insight into trend direction, support and resistance levels, and momentum.
- **Cloud (Kumo)**: The space between the Senkou Span A and Senkou Span B lines. It helps identify whether the market is in an uptrend, downtrend, or consolidation.
- **Tenkan-sen** (Conversion Line) and **Kijun-sen** (Base Line): These lines are used for additional confirmation of trend direction.
- **Chikou Span**: A lagging line that is used to confirm the trend.
- The general trading rules based on the Ichimoku Cloud are:
- **Bullish Signal**: When the price is above the cloud and the Tenkan-sen crosses above the Kijun-sen.
- **Bearish Signal**: When the price is below the cloud and the Tenkan-sen crosses below the Kijun-sen.
### 3. **200 SMA Filter**
- The **200 SMA Filter** serves as a long-term trend filter.
- When the price is **above the 200 SMA**, it signals a long-term bullish trend, and you only look for buying opportunities.
- When the price is **below the 200 SMA**, it signals a long-term bearish trend, and you only look for selling opportunities.
- This filter helps to avoid counter-trend trades, aligning your positions with the broader market trend.
### **How the Strategy Works Together**
- **Trade Setup (Long Position)**
1. The **200 SMA Filter** must confirm an **uptrend** by ensuring that the price is above the 200 SMA.
2. A **bullish crossover** (e.g., the 50 EMA crossing above the 200 SMA) occurs.
3. **Ichimoku Cloud** confirms a bullish trend, with the price above the cloud and the Tenkan-sen crossing above the Kijun-sen.
4. You enter a **long trade** with this confluence of signals.
- **Trade Setup (Short Position)**
1. The **200 SMA Filter** must confirm a **downtrend** by ensuring the price is below the 200 SMA.
2. A **bearish crossover** (e.g., the 50 EMA crossing below the 200 SMA) occurs.
3. **Ichimoku Cloud** confirms a bearish trend, with the price below the cloud and the Tenkan-sen crossing below the Kijun-sen.
4. You enter a **short trade** with this confluence of signals.
### **Exit Strategy**
- Exits can be determined based on any of the following:
- **SMA/EMA crossover reversal**: Exit when the shorter-term moving average crosses back below the longer-term moving average for a long position or crosses above for a short position.
- **Ichimoku Cloud reversal**: If the price breaks through the cloud or the Tenkan-sen and Kijun-sen lines cross in the opposite direction.
- **Profit target or stop loss**: Setting predefined profit targets or using a trailing stop to lock in profits as the trade moves in your favor.
Summary of the Strategy
This strategy is designed to identify strong trends and avoid false signals by combining:
SMA/EMA crossovers for immediate market direction signals.
Ichimoku Cloud for confirming the strength and trend direction.
A 200
SMA filter to ensure trades align with the long-term trend.
By using these multiple indicators together, the strategy aims to refine entry and exit points, minimize risk, and increase the likelihood of successful trades.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
ROBO STB GainCraft strategyPure Price Action Candlestick Strategy by ROBO STB
Overview
This strategy is built entirely on the principles of price action and candlestick analysis, designed for traders who prefer raw market data over traditional indicators. By focusing solely on candlestick patterns and their context within recent price movements, the strategy identifies high-probability entry and exit points in liquid markets.
Entry signals are generated based on these patterns appearing at significant market locations, such as after consolidations, pullbacks, or at key support/resistance levels.
Price Action Integration:
Instead of relying on oscillators or moving averages, the script leverages the inherent market structure provided by candlesticks to interpret potential trend reversals or continuations.
This approach provides a clearer view of market sentiment.
No External Indicators:
This script avoids the use of traditional indicators like RSI, MACD, or Bollinger Bands, offering a clean, uncluttered chart.
Risk Management (Optional):
Fixed-percentage risk management options can also be enabled, ensuring trades remain within acceptable risk parameters.
How the Strategy Works
Entry Conditions:
Buy Entry: A bullish candlestick pattern (e.g., bullish engulfing) forms after a period of consolidation or pullback, indicating potential upward momentum.
Sell Entry: A bearish candlestick pattern (e.g., bearish engulfing) suggests a downturn is likely.
Exit Conditions:
Exits are triggered by the appearance of reversal candlestick patterns or through predefined SL/TP levels.
The strategy adapts to varying market conditions by analyzing candlestick structures dynamically.
Ideal Use Cases
Short-Term Trading: Designed for day traders and scalpers targeting quick moves on shorter timeframes.
Highly Liquid Markets: Performs best in markets with high liquidity, such as Nifty, Bank Nifty, or major forex pairs, where candlestick patterns provide reliable signals.
30-Minute Timeframe: For optimal results, the strategy is recommended for use on a 30-minute timeframe.
Transparency and Realism
Backtesting Parameters:
The default backtesting settings simulate realistic trading conditions, including commissions and slippage, ensuring that results are not misleading.
Trade sizes are calibrated to risk sustainable amounts (.05% maximum equity per trade).
Dataset Selection:
This strategy has been tested on diverse datasets to produce a statistically significant number of trades, ensuring robust performance evaluation.
Why This Strategy is Unique
This script stands apart by offering a refined approach to price action trading. Unlike generic indicator mashups, it provides traders with an actionable, candlestick-focused methodology tailored for volatile, high-liquidity markets.
The strategy is both simple to understand and powerful in execution, making it an excellent tool for traders who want to develop their skills in raw price action analysis while maintaining strict risk management.
Key Features
Candlestick-Based Entry and Exit Signals:
1. Risk Management:
- Risk-to-Reward Ratio (RTR):
Set a customizable risk-to-reward ratio to calculate target prices based on stop-loss levels.
Default: 3:1
order size added -100
2. Opening Range Identification
- Opening Range High and Low:
The script detects the high and low of the first trading session using Pine Script's session functions.
These levels are plotted as visual guides on the chart:
- High: Lime-colored circles.
- Low: Red-colored circles.
3. Trade Entry Logic
- Long Entry:
A long trade is triggered when the price closes above the opening range high.
- Entry condition: Crossover of the price above the opening range high.
-Short Entry:
A short trade is triggered when the price closes below the opening range low.
- Entry condition: Crossunder of the price below the opening range low.
Both entries are conditional on the absence of an existing position.
4. Stop Loss and Take Profit
- Long Position:
- Stop Loss: Previous candle's low.
- Take Profit: Calculated based on the RTR.
- **Short Position:**
- **Stop Loss:** Previous candle's high.
- **Take Profit:** Calculated based on the RTR.
The strategy plots these levels for visual reference:
- Stop Loss: Red dashed lines.
- Take Profit: Green dashed lines.
5. Visual Enhancements
-Trade Level Highlighting:
The script dynamically shades the areas between the entry price and SL/TP levels:
- Red shading for the stop-loss region.
- Green shading for the take-profit region.
How to Use:
1.Input Configuration:
Adjust the Risk-to-Reward ratio, max trades per day, and session end time to suit your trading preferences.
2.Visual Cues:
Use the opening range high/low lines and shading to identify potential breakout opportunities.
3.Execution:
The strategy will automatically enter and exit trades based on the conditions. Review the plotted SL and TP levels to monitor the risk-reward setup.
Important Notes:
- This strategy is designed for intraday trading and works best in markets with high volatility during the opening session.
- Backtest the strategy on your preferred market and timeframe to ensure compatibility.
- Proper risk management and position sizing are essential when using this strategy in live markets.
Please let me know if you have any doubts.
DemaRSI StrategyThis is a repost to a old script that cant be updated anymore, the request was made on Feb, 27, 2016.
Here's a engaging description for the tradingview script:
**DemaRSI Strategy: A Proven Trading System**
Join thousands of traders who have already experienced the power of this highly effective strategy. The DemaRSI system combines two powerful indicators - DEMA (Double Exponential Moving Average) and RSI (Relative Strength Index) - to generate profitable trades with minimal risk.
**Key Features:**
* **Trend-Following**: Our algorithm identifies strong trends using a combination of DEMA and RSI, allowing you to ride the waves of market momentum.
* **Risk Management**: The system includes built-in stop-loss and take-profit levels, ensuring that your gains are protected and losses are minimized.
* **Session-Based Trading**: Trade during specific sessions only (e.g., London or New York) for even more targeted results.
* **Customizable Settings**: Adjust the length of moving averages, RSI periods, and other parameters to suit your trading style.
**What You'll Get:**
* A comprehensive strategy that can be used with any broker or platform
* Easy-to-use interface with customizable settings
* Real-time performance metrics and backtesting capabilities
**Start Trading Like a Pro Today!**
This script is designed for intermediate to advanced traders who want to take their trading game to the next level. With its robust risk management features, this strategy can help you achieve consistent profits in various market conditions.
**Disclaimer:** This script is not intended as investment advice and should be used at your own discretion. Trading carries inherent risks, and losses are possible.
~Llama3
MicuRobert EMA Cross StrategyThis is a repost of a old strategy that cant be updated anymore, it was a request for a user made in Oct, 6, 2015
Here's a possible engaging description for the tradingview script:
**MicuRobert EMA Cross V2: A Powerful Trading Strategy**
Join the ranks of successful traders with this advanced strategy, designed to help you profit from market trends. The MicuRobert EMA Cross V2 combines two essential indicators - Exponential Moving Average (EMA) and Divergence EMA (DEMA) - to generate buy and sell signals.
**Key Features:**
* **Trading Session Filter**: Only trade during your preferred session, ensuring you're in sync with market conditions.
* **Trailing Stop**: Automatically adjust stop-loss levels to lock in profits or limit losses.
* **Customizable Trade Size**: Set the size of each trade based on your risk tolerance and trading goals.
**How it Works:**
The script uses two EMAs (5-period and 34-period) to identify trends. When the shorter EMA crosses above the longer one, a buy signal is generated. Conversely, when the shorter EMA falls below the longer one, a sell signal is triggered. The strategy also incorporates divergence analysis between price action and the EMAs.
**Visual Aids:**
* **EMA Plots**: Visualize the two EMAs on your chart to gauge market momentum.
* **Buy/Sell Signals**: See when buy or sell signals are generated, along with their corresponding entry prices.
* **Trailing Stop Lines**: Monitor stop-loss levels as they adjust based on price action.
**Get Started:**
Download this script and start trading like a pro! With its robust features and customizable settings, the MicuRobert EMA Cross V2 is an excellent addition to any trader's arsenal.
~Llama3
Liquidity + Engulfment StrategyThis strategy identifies potential trading opportunities by combining bullish and bearish engulfing candle patterns with liquidity seal-off points. The logic is based on the concept of engulfing candles, which signal a shift in market sentiment, and liquidity lines, which represent local price extremes (highs and lows) that can indicate potential reversal or continuation points.
Key Features:
Mode Selection
The strategy allows for three modes: "Both", "Bullish Only", and "Bearish Only". Users can choose whether to trade both directions, only bullish setups, or only bearish setups.
Time Range
Users can define a specific time range for when the strategy is active, enabling tailored analysis and trade execution over a desired period.
Engulfing Candles
Bullish Engulfing: A candle that closes above the high of the previous bearish candle, signaling potential upward momentum.
Bearish Engulfing: A candle that closes below the low of the previous bullish candle, indicating a potential downtrend.
Liquidity Seal-Off Points
The strategy detects local highs and local lows within a specified lookback period, which can serve as critical support and resistance points.
A bullish signal is triggered when the price touches a lower liquidity point (local low), and a bearish signal is triggered at a higher liquidity point (local high).
Signal Confirmation
Signals are only triggered when both an engulfing candle and the price action at a liquidity seal-off point align. This helps filter out weaker signals.
Consecutive signals are prevented by locking the trade direction after an initial signal and waiting for the liquidity line to be broken before re-triggering a signal.
Entry and Exit Conditions
The strategy can enter both long (bullish) or short (bearish) positions based on the mode and signals.
Exit is based on opposing signals or reaching predefined stop-loss and take-profit levels.
Alerts
The strategy supports alert conditions to notify users when bullish engulfing after a lower liquidity touch or bearish engulfing after an upper liquidity touch is detected.
MultiLayer Awesome Oscillator Saucer Strategy [Skyrexio]Overview
MultiLayer Awesome Oscillator Saucer Strategy leverages the combination of Awesome Oscillator (AO), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Awesome Oscillator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Awesome Oscillator shall create the "Saucer" long signal (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created "Saucer signal".
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one "Saucer" signal another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's go through all concepts used in this strategy to understand how they works together. Let's start from the easies one, the EMA. Let's briefly explain what is EMA. The Exponential Moving Average (EMA) is a type of moving average that gives more weight to recent prices, making it more responsive to current price changes compared to the Simple Moving Average (SMA). It is commonly used in technical analysis to identify trends and generate buy or sell signals. It can be calculated with the following steps:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy uses EMA an initial long term trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
Let's go to the next, short-term trend filter which consists of Alligator and Fractals. Let's briefly explain what do these indicators means. The Williams Alligator, developed by Bill Williams, is a technical indicator designed to spot trends and potential market reversals. It uses three smoothed moving averages, referred to as the jaw, teeth, and lips:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When these lines diverge and are properly aligned, the "alligator" is considered "awake," signaling a strong trend. Conversely, when the lines overlap or intertwine, the "alligator" is "asleep," indicating a range-bound or sideways market. This indicator assists traders in identifying when to act on or avoid trades.
The Williams Fractals, another tool introduced by Bill Williams, are used to pinpoint potential reversal points on a price chart. A fractal forms when there are at least five consecutive bars, with the middle bar displaying the highest high (for an up fractal) or the lowest low (for a down fractal), relative to the two bars on either side.
Key Points:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often combine fractals with other indicators to confirm trends or reversals, improving the accuracy of trading decisions.
How we use their combination in this strategy? Let’s consider an uptrend example. A breakout above an up fractal can be interpreted as a bullish signal, indicating a high likelihood that an uptrend is beginning. Here's the reasoning: an up fractal represents a potential shift in market behavior. When the fractal forms, it reflects a pullback caused by traders selling, creating a temporary high. However, if the price manages to return to that fractal’s high and break through it, it suggests the market has "changed its mind" and a bullish trend is likely emerging.
The moment of the breakout marks the potential transition to an uptrend. It’s crucial to note that this breakout must occur above the Alligator's teeth line. If it happens below, the breakout isn’t valid, and the downtrend may still persist. The same logic applies inversely for down fractals in a downtrend scenario.
So, if last up fractal breakout was higher, than Alligator's teeth and it happened after last down fractal breakdown below teeth, algorithm considered current trend as an uptrend. During this uptrend long trades can be opened if signal was flashed. If during the uptrend price breaks down the down fractal below teeth line, strategy considered that uptrend is finished with the high probability and strategy closes all current long trades. This combination is used as a short term trend filter increasing the probability of opening profitable long trades in addition to EMA filter, described above.
Now let's talk about Awesome Oscillator's "Sauser" signals. Briefly explain what is the Awesome Oscillator. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
Now we know what is AO, but what is the "Saucer" signal? This concept was introduced by Bill Williams, let's briefly explain it and how it's used by this strategy. Initially, this type of signal is a combination of the following AO bars: we need 3 bars in a row, the first one shall be higher than the second, the third bar also shall be higher, than second. All three bars shall be above the zero line of AO. The price bar, which corresponds to third "saucer's" bar is our signal bar. Strategy places buy stop order one tick above the price bar which corresponds to signal bar.
After that we can have the following scenarios.
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower low. If current AO bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AO bar become decreasing. In the second case buy order cancelled and strategy wait for the next "Saucer" signal.
If long trades has been opened strategy use all the next signals until number of trades doesn't exceed 5. All trades are closed when the trend changes to downtrend according to combination of Alligator and Fractals described above.
Why we use "Saucer" signals? If AO above the zero line there is a high probability that price now is in uptrend if we take into account our two trend filters. When we see the decreasing bars on AO and it's above zero it's likely can be considered as a pullback on the uptrend. When we see the stop of AO decreasing and the first increasing bar has been printed there is a high probability that this local pull back is finished and strategy open long trade in the likely direction of a main trend.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next saucer signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.10%
Maximum Single Profit: +22.80%
Net Profit: +2838.58 USDT (+28.39%)
Total Trades: 107 (42.99% win rate)
Profit Factor: 3.364
Maximum Accumulated Loss: 373.43 USDT (-2.98%)
Average Profit per Trade: 26.53 USDT (+2.40%)
Average Trade Duration: 78 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Ichimoku + RSI + MACD Strategy1. Relative Strength Index (RSI)
Overview:
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions in a market.
How to Use with Ichimoku:
Long Entry: Look for RSI to be above 30 (indicating it is not oversold) when the price is above the Ichimoku Cloud.
Short Entry: Look for RSI to be below 70 (indicating it is not overbought) when the price is below the Ichimoku Cloud.
2. Moving Average Convergence Divergence (MACD)
Overview:
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. It consists of the MACD line, signal line, and histogram.
How to Use with Ichimoku:
Long Entry: Enter a long position when the MACD line crosses above the signal line while the price is above the Ichimoku Cloud.
Short Entry: Enter a short position when the MACD line crosses below the signal line while the price is below the Ichimoku Cloud.
Combined Strategy Example
Here’s a brief outline of how to structure a trading strategy using Ichimoku, RSI, and MACD:
Long Entry Conditions:
Price is above the Ichimoku Cloud.
RSI is above 30.
MACD line crosses above the signal line.
Short Entry Conditions:
Price is below the Ichimoku Cloud.
RSI is below 70.
MACD line crosses below the signal line.
Exit Conditions:
Exit long when MACD line crosses below the signal line.
Exit short when MACD line crosses above the signal line.
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
RVI Crossover Strategy[Kopottaja]Overview of the RVI Crossover Strategy
Strategy Name: RVI Crossover Strategy
Purpose: The RVI Crossover Strategy is based on the crossover signals between the Relative Vigor Index (RVI) and its moving average signal line. This strategy aims to identify potential buy and sell signals by evaluating the market’s directional trend.
Key Indicator Features
Relative Vigor Index (RVI): This indicator measures the momentum of price changes over a specified period and helps identify the market’s current trend. The RVI is based on the idea that prices generally close higher than they open in an uptrend (and lower in a downtrend). The RVI helps provide an indication of the strength and direction of a trend.
Signal Line: A moving average (e.g., SMA) is applied to the RVI values, creating a "signal line." When the RVI crosses above or below this line, it signals a potential trading opportunity.
Calculations and Settings
Calculating the RVI: The RVI is calculated by comparing the difference between the close and open prices to the difference between high and low prices. This provides information about the direction and momentum of price movement:
RVI= Sum(SWMA(high−low))Sum(SWMA(close−open))
where SWMA is a smoothed weighted moving average over a specified period.
Signal Line Calculation: The RVI value is smoothed by applying a simple moving average (SMA) to create the signal line. This signal line helps filter crossover signals for improved accuracy.
Buy and Sell Conditions: Buy and sell conditions are identified based on crossovers between the RVI and its signal line.
Buy Signal: A buy condition is triggered when the RVI crosses above the signal line, provided that the "Bearish" condition (trend confirmation) is met.
Sell Signal: A sell condition occurs when the RVI crosses below the signal line, alongside the "Bullish" trend confirmation.
Volume-Weighted Moving Averages (VWMA): VWMA indicators are used to assess price-volume relationships over different timeframes:
Fast VWMA: A short-period volume-weighted moving average.
Slow VWMA: A longer-period volume-weighted moving average. These values are used to strengthen the buy and sell conditions by confirming trend directions (Bullish or Bearish).
Disclaimer: This is an educational and informational tool. Past performance is not indicative of future results. Always backtest before using in live markets
Shark Zone Day Machine V17### **Strategy Overview: Shark Zone Day Machine V14**
The "Shark Zone Day Machine V14" is a daily breakout trading strategy designed for traders who wish to capitalize on intraday price movements based on key levels from the previous day. The strategy operates on a daily timeframe, allowing traders to execute precise entries and manage their trades effectively. It includes both long and short trading capabilities, with user-friendly inputs for customization.
### **Key Features:**
1. **Daily Breakout Logic**:
- **Long Position**: The strategy opens a long position when the price breaks above the previous day's high, indicating potential upward momentum.
- **Short Position**: The strategy opens a short position when the price drops below the previous day's low, signaling possible downward pressure.
2. **Stop Loss Management**:
- The strategy uses a fixed stop loss of 50 points, which is set at the previous day's low for long trades and 50 points above the entry for short trades.
3. **Spread Adjustment**:
- Includes an adjustable spread input to account for bid-ask differences, ensuring entries and exits are accurately calculated.
4. **Activation Controls**:
- Traders can easily enable or disable long and short trading strategies independently using input toggles.
5. **Custom Alert Integration**:
- The strategy includes alert messages configured to work seamlessly with Pine Connector. These alerts can be set up to automatically send trade signals to MT4, enabling a fully automated trading experience.
### **Automated Trading Setup via Pine Connector to MT4**
To implement this strategy for automated trading between TradingView and MT4 using Pine Connector, follow these steps:
1. **Apply the Script on TradingView**:
- Load the "Shark Zone Day Machine V14" script onto your TradingView chart and adjust the input parameters as needed, including activation toggles, spread, and stop loss settings.
2. **Set Up Alerts on TradingView**:
- Click on the `Alerts` button in TradingView.
- Under "Condition," select the strategy and choose "Any alert() function call."
- For each alert, use the predefined messages:
- **Long Entry Alert**: `"BUY_SIGNAL_7683370025173"`
- **Long Exit Alert**: `"BUY_EXIT_SIGNAL_7683370025173"`
- **Short Entry Alert**: `"SELL_SIGNAL_7683370025173"`
- **Short Exit Alert**: `"SELL_EXIT_SIGNAL_7683370025173"`
- Ensure the alert actions are set to "Notify on app" and "Show pop-up" for immediate feedback.
3. **Configure Pine Connector**:
- Pine Connector should be installed and set up on your MT4 platform. Ensure the Pine Connector ID matches the alert messages from the TradingView script.
- Configure your MT4 EA to recognize these signals and execute trades accordingly. For example, a `"BUY_SIGNAL_7683370025173"` alert from TradingView will instruct MT4 to place a buy order.
4. **Test the Setup**:
- It’s essential to test the automation in a demo account first. Monitor how trades are opened and closed on MT4 when alerts are triggered from TradingView.
- Adjust the parameters on TradingView if needed for optimal performance and minimal slippage.
### **Benefits of Automated Trading with This Strategy**:
- **Consistency**: Eliminates the potential for human error by executing trades precisely as per the strategy’s logic.
- **Speed**: Rapid response to breakout conditions, ensuring you capture opportunities as soon as they arise.
- **Flexibility**: The ability to adjust stop loss, spread, and trading size allows for quick adaptation to different market conditions.
### **Important Notes**:
- Ensure your TradingView account remains active and has real-time data enabled for accurate alerts.
- Verify that Pine Connector and MT4 settings are configured correctly to prevent missed trades or incorrect lot sizes.
- Be mindful of market conditions, as breakout strategies may perform differently during high-volatility periods.
By following this guide, you'll be able to leverage the "Shark Zone Day Machine V14" strategy to its full potential, automating your trades and optimizing your trading efficiency.
Chill in WavesChill in Waves is a distinctive technical indicator that integrates both volume and price action, specifically designed to help traders identify key market trends and optimize entry/exit points. What sets this indicator apart is its ability to normalize data using Z-score techniques, making it highly adaptable and reliable across any timeframe, from short-term intraday trading to long-term position strategies.
Key Features and What Makes it Unique:
1. Volume-Weighted Moving Averages (VWMA): At the core of Chill in Waves are two volume-weighted moving averages (VWMA), which highlight periods of strong price movement influenced by high trading volume. The use of VWMA ensures that market activity during times of increased volume has a greater influence on the signals generated. This provides a more accurate reflection of market sentiment compared to traditional moving averages.
2. Z-Score Normalization: One of the key innovations of Chill in Waves is its Z-score normalization of the difference between the fast and slow VWMAs. This normalization helps to smooth out the noise typically present in raw market data, allowing traders to better identify statistically significant deviations from historical price norms. By using normalized data, traders can confidently apply this indicator across all timeframes without the risk of distortion caused by extreme values or outliers. This is especially beneficial for traders who operate in volatile markets.
3. Versatility Across Timeframes: Unlike many indicators that are calibrated for specific timeframes, Chill in Waves is designed for use on all timeframes, from minute-by-minute charts to daily, weekly, and even monthly charts. The Z-score normalization ensures that signals are consistently reliable, no matter the timeframe you are trading in, providing traders with a flexible tool to adapt to any market conditions.
4. Clear Visual Cues for Buy/Sell Signals: Chill in Waves offers straightforward visual cues by plotting Z-scores with color-coded signals: green for potential bullish trends and red for bearish movements. This makes it easy for traders to quickly assess market conditions at a glance, without the need to interpret complex calculations.
5. Customizable Trailing Stop Feature: To further support effective risk management, Chill in Waves includes a customizable trailing stop feature, allowing traders to lock in profits while minimizing downside risk. The flexibility in adjusting the trailing stop percentage ensures that the indicator can be tailored to fit each trader’s risk tolerance and strategy.
Buy and Sell Logic:
Buy Logic: A long position is triggered when both the fast and slow VWMA Z-scores are trending upward, signaling a statistically significant shift toward bullish price action.
Sell Logic: Positions are closed when the trailing stop condition is met or after a predetermined period, ensuring traders can capture gains while limiting exposure to downside risk.
Customization Options:
VWMA Length: Traders can adjust the lengths of the fast and slow VWMA to better suit specific market conditions or individual asset classes.
Bar Color Customization: For additional visual clarity, you can enable an optional feature that changes the color of price bars based on the Z-score difference, providing further insight into market momentum.
Chill in Waves stands out as a flexible and robust indicator for traders across all timeframes, combining the power of volume-weighted moving averages with normalized data to produce accurate and adaptable buy/sell signals. Whether you're a short-term scalper or a long-term trend follower, this indicator offers you the calm confidence needed to ride the waves of market volatility.
MACD Enhanced Strategy MTF with Stop Loss [LTB]Test strategy for MACD
This strategy, named "MACD Enhanced Strategy MTF with Stop Loss ," is a modified Moving Average Convergence Divergence (MACD) strategy with enhancements such as multi-timeframe (MTF) analysis, custom scoring, and a dynamic stop loss mechanism. Let’s break down how to effectively use it:
Key Elements of the Strategy
MACD Indicator with Modifications:
The strategy uses MACD, a well-known momentum indicator, with customizable parameters:
fastLength, slowLength, and signalLength represent the standard MACD settings.
Instead of relying solely on MACD crossovers, it introduces scoring parameters for histogram direction (histside), indicator direction (indiside), and signal cross (crossscore). This allows for a more nuanced decision-making process when determining buy and sell signals.
Multi-Timeframe Analysis (MTF):
The strategy compares the current timeframe's MACD score with that of a higher timeframe (HTF). It dynamically selects the higher timeframe based on the current timeframe. For example, if the current chart period is 1, it will select 5 as the higher timeframe.
This MTF approach aims to align trades with broader trends, filtering out false signals that could be present when analyzing only a single timeframe.
Scoring System:
A custom scoring system (count() function) is used to evaluate buy and sell signals. This includes calculations based on the direction and momentum of MACD (indi) and the histogram. The score is used to determine the strength of signals.
Positive scores indicate bullish sentiment, while negative scores indicate bearish sentiment.
This scoring mechanism aims to reduce the influence of noise and provide more reliable entries.
Entry Conditions:
Long Condition: When the Result value (a combination of MTF and current MACD analysis) changes and becomes positive, a long entry is triggered.
Short Condition: When the Result changes and becomes negative, a short entry is initiated.
Stop Loss Mechanism:
The countstop() function calculates dynamic stop loss values for both long and short trades. It is based on the Average True Range (ATR) multiplied by a factor (Mult), providing adaptive stop loss levels depending on market volatility.
The stop loss is plotted on the chart to show potential risk levels for open trades, with the line appearing only if shotsl is enabled.
How to Use the Strategy
To properly use the strategy, follow these steps:
Parameter Optimization:
Adjust the input parameters such as fastLength, slowLength, and signalLength to tune the MACD indicator to the specific asset you’re trading. The values provided are typical defaults, but optimizing these values based on backtesting can help improve performance.
Customize the scoring parameters (crossscore, indiside, histside) to balance how much weight you want to put on the direction, histogram, and cross events of the MACD indicator.
Select Appropriate Timeframes:
This strategy employs a multi-timeframe (MTF) approach, so it's important to understand how the higher timeframe (HTF) is selected based on the current timeframe. For instance, if you are trading on a 5-minute chart, the higher timeframe will be 15 minutes, which helps filter out lower timeframe noise.
Ensure you understand the relationship between the timeframe you’re using and the HTF it automatically selects. The strategy’s effectiveness can vary depending on how these timeframes align with the asset’s overall volatility.
Run Backtests:
Always backtest the strategy over historical data to determine its reliability for the asset and timeframes you’re interested in. Note that the MTF approach may require substantial data to capture how different timeframes interact.
Use the backtest results to adjust the scoring parameters or the Stop Loss Factor (Mult) for better risk management.
Stop Loss Usage:
The stop loss is calculated dynamically using ATR, which means that it adjusts with changing volatility. This can be useful to avoid being stopped out too often during periods of increased volatility.
The shotsl parameter can be set to true to visualize the stop loss line on the chart. This helps to monitor the protection level and make better decisions regarding holding or closing a trade manually.
Entry Signals and Trade Execution:
Look for changes in the Result value to determine entry points. For a long position, the Result needs to become positive, and for a short position, it must be negative.
Note that the strategy's entries are more conservative because it waits for the Result to confirm the direction using multiple factors, which helps filter out false breakouts.
Risk Management:
The adaptive stop loss mechanism reduces the risk by basing the stop level on market volatility. However, you must still consider additional risk management practices such as position sizing and profit targets.
Given the scoring mechanism, it might not enter trades frequently, which means using this strategy may result in fewer but potentially more accurate trades. It’s important to be patient and not force trades that don’t align with the calculated results.
Real-Time Monitoring:
Make sure to monitor trades actively. Since the strategy recalculates the score on each bar, real-time changes in the Result value could provide exit opportunities even if the stop loss isn't triggered.
Summary
The "MACD Enhanced Strategy MTF with Stop Loss " is a sophisticated version of the MACD strategy, enhanced with multi-timeframe analysis and adaptive stop loss. Properly using it involves optimizing MACD and scoring parameters, selecting suitable timeframes, and actively managing entries and exits based on a combination of scoring and volatility-based stop losses. Always conduct thorough backtesting before applying it in a live environment to ensure the strategy performs well on the asset you're trading.
