MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. 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: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 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 between 30 min and 4 hours and chart (optimal performance observed on 45 min 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
Moving Averages
Dual Chain StrategyDual Chain Strategy - Technical Overview
How It Works:
The Dual Chain Strategy is a unique approach to trading that utilizes Exponential Moving Averages (EMAs) across different timeframes, creating two distinct "chains" of trading signals. These chains can work independently or together, capturing both long-term trends and short-term price movements.
Chain 1 (Longer-Term Focus):
Entry Signal: The entry signal for Chain 1 is generated when the closing price crosses above the EMA calculated on a weekly timeframe. This suggests the start of a bullish trend and prompts a long position.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Exit Signal: The exit signal is triggered when the closing price crosses below the EMA on a daily timeframe, indicating a potential bearish reversal.
exitLongChain1 = enableChain1 and ta.crossunder(src1, exitEMA1)
Parameters: Chain 1's EMA length is set to 10 periods by default, with the flexibility for user adjustment to match various trading scenarios.
Chain 2 (Shorter-Term Focus):
Entry Signal: Chain 2 generates an entry signal when the closing price crosses above the EMA on a 12-hour timeframe. This setup is designed to capture quicker, shorter-term movements.
bullishChain2 = enableChain2 and ta.crossover(src2, entryEMA2)
Exit Signal: The exit signal occurs when the closing price falls below the EMA on a 9-hour timeframe, indicating the end of the shorter-term trend.
exitLongChain2 = enableChain2 and ta.crossunder(src2, exitEMA2)
Parameters: Chain 2's EMA length is set to 9 periods by default, and can be customized to better align with specific market conditions or trading strategies.
Key Features:
Dual EMA Chains: The strategy's originality shines through its dual-chain configuration, allowing traders to monitor and react to both long-term and short-term market trends. This approach is particularly powerful as it combines the strengths of trend-following with the agility of momentum trading.
Timeframe Flexibility: Users can modify the timeframes for both chains, ensuring the strategy can be tailored to different market conditions and individual trading styles. This flexibility makes it versatile for various assets and trading environments.
Independent Trade Logic: Each chain operates independently, with its own set of entry and exit rules. This allows for simultaneous or separate execution of trades based on the signals from either or both chains, providing a robust trading system that can handle different market phases.
Backtesting Period: The strategy includes a configurable backtesting period, enabling thorough performance assessment over a historical range. This feature is crucial for understanding how the strategy would have performed under different market conditions.
time_cond = time >= startDate and time <= finishDate
What It Does:
The Dual Chain Strategy offers traders a distinctive trading tool that merges two separate EMA-based systems into one cohesive framework. By integrating both long-term and short-term perspectives, the strategy enhances the ability to adapt to changing market conditions. The originality of this script lies in its innovative dual-chain design, providing traders with a unique edge by allowing them to capitalize on both significant trends and smaller, faster price movements.
Whether you aim to capture extended market trends or take advantage of more immediate price action, the Dual Chain Strategy provides a comprehensive solution with a high degree of customization and strategic depth. Its flexibility and originality make it a valuable tool for traders seeking to refine their approach to market analysis and execution.
How to Use the Dual Chain Strategy
Step 1: Access the Strategy
Add the Script: Start by adding the Dual Chain Strategy to your TradingView chart. You can do this by searching for the script by name or using the link provided.
Select the Asset: Apply the strategy to your preferred trading pair or asset, such as #BTCUSD, to see how it performs.
Step 2: Configure the Settings
Enable/Disable Chains:
The strategy is designed with two independent chains. You can choose to enable or disable each chain depending on your trading style and the market conditions.
enableChain1 = input.bool(true, title='Enable Chain 1')
enableChain2 = input.bool(true, title='Enable Chain 2')
By default, both chains are enabled. If you prefer to focus only on longer-term trends, you might disable Chain 2, or vice versa if you prefer shorter-term trades.
Set EMA Lengths:
Adjust the EMA lengths for each chain to match your trading preferences.
Chain 1: The default EMA length is 10 periods. This chain uses a weekly timeframe for entry signals and a daily timeframe for exits.
len1 = input.int(10, minval=1, title='Length Chain 1 EMA', group="Chain 1")
Chain 2: The default EMA length is 9 periods. This chain uses a 12-hour timeframe for entries and a 9-hour timeframe for exits.
len2 = input.int(9, minval=1, title='Length Chain 2 EMA', group="Chain 2")
Customize Timeframes:
You can customize the timeframes used for entry and exit signals for both chains.
Chain 1:
Entry Timeframe: Weekly
Exit Timeframe: Daily
tf1_entry = input.timeframe("W", title='Chain 1 Entry Timeframe', group="Chain 1")
tf1_exit = input.timeframe("D", title='Chain 1 Exit Timeframe', group="Chain 1")
Chain 2:
Entry Timeframe: 12 Hours
Exit Timeframe: 9 Hours
tf2_entry = input.timeframe("720", title='Chain 2 Entry Timeframe (12H)', group="Chain 2")
tf2_exit = input.timeframe("540", title='Chain 2 Exit Timeframe (9H)', group="Chain 2")
Set the Backtesting Period:
Define the period over which you want to backtest the strategy. This allows you to see how the strategy would have performed historically.
startDate = input.time(timestamp('2015-07-27'), title="StartDate")
finishDate = input.time(timestamp('2026-01-01'), title="FinishDate")
Step 3: Analyze the Signals
Understand the Entry and Exit Signals:
Buy Signals: When the price crosses above the entry EMA, the strategy generates a buy signal.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Sell Signals: When the price crosses below the exit EMA, the strategy generates a sell signal.
bearishChain2 = enableChain2 and ta.crossunder(src2, entryEMA2)
Review the Visual Indicators:
The strategy plots buy and sell signals on the chart with labels for easy identification:
BUY C1/C2 for buy signals from Chain 1 and Chain 2.
SELL C1/C2 for sell signals from Chain 1 and Chain 2.
This visual aid helps you quickly understand when and why trades are being executed.
Step 4: Optimize the Strategy
Backtest Results:
Review the strategy’s performance over the backtesting period. Look at key metrics like net profit, drawdown, and trade statistics to evaluate its effectiveness.
Adjust the EMA lengths, timeframes, and other settings to see how changes affect the strategy’s performance.
Customize for Live Trading:
Once satisfied with the backtest results, you can apply the strategy settings to live trading. Remember to continuously monitor and adjust as needed based on market conditions.
Step 5: Implement Risk Management
Use Realistic Position Sizing:
Keep your risk exposure per trade within a comfortable range, typically between 1-2% of your trading capital.
Set Alerts:
Set up alerts for buy and sell signals, so you don’t miss trading opportunities.
Paper Trade First:
Consider running the strategy in a paper trading account to understand its behavior in real market conditions before committing real capital.
This dual-layered approach offers a distinct advantage: it enables the strategy to adapt to varying market conditions by capturing both broad trends and immediate price action without one chain's activity impacting the other's decision-making process. The independence of these chains in executing transactions adds a level of sophistication and flexibility that is rarely seen in more conventional trading systems, making the Dual Chain Strategy not just unique, but a powerful tool for traders seeking to navigate complex market environments.
Quatro SMA Strategy [4h]Hello, I would like to present to you The "Quatro SMA" strategy
Strategy is based on four simple moving averages of different lengths and monitoring trading volume. The key idea is to identify strong market trends by comparing short-term moving averages with the long-term SMA. The strategy generates buy signals when all short-term SMAs are above the SMA(200) and the volume confirms the strength of the move. Similarly, sell signals are generated when all short-term SMAs are below the SMA(200), and the volume is sufficiently high.
The strategy manages risk by applying a stop loss and three different Take Profit levels (TP1, TP2, TP3), with varying percentages of the position closed at each level.
Each Take Profit level is triggered at a specific percentage gain, with the position being closed gradually depending on the achieved targets. The percentage of the position closed at each TP level is also defined by the user.
Indicators and Parameters:
Simple Moving Averages (SMA):
The script utilizes four simple moving averages with different lengths (4, 16, 32, 200). The first three SMAs (SMA1, SMA2, SMA3) are used to determine the trend direction, while the fourth SMA (with a length of 200) serves as a support/resistance line.
Volume:
The script monitors trading volume and checks if the current volume exceeds 2.5 times the average volume of the last 40 candles. High volume is considered as confirmation of trend strength.
Entry Conditions:
- Long Position: Triggered when SMA1 > SMA2 > SMA3, the closing price is above SMA(200), and the volume condition is met.
- Short Position: Triggered when SMA1 < SMA2 < SMA3, the closing price is below SMA(200), and the volume condition is met.
Exit Conditions:
- Long Position: Closed when SMA1 < SMA2 < SMA3 and the closing price is above SMA(200).
- Short Position: Closed when SMA1 > SMA2 > SMA3 and the closing price is below SMA(200).
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Kyrie Crossover ( @zaytradellc )Unlocking Market Dynamics: Kyrie Crossover Script by @zaytradellc
personalized trading success with the "Kyrie Crossover" script, meticulously crafted by @zaytrade. This innovative Pine Script, tailored to the birthdays of Kyrie and the script creator, combines the power of technical analysis with a touch of personalization to revolutionize your trading experience.
**Exponential Moving Average (EMA) Crossover Strategy:**
At the heart of the "Kyrie Crossover" script lies a sophisticated EMA crossover strategy. By utilizing a 10-period EMA and a 323-period EMA (symbolizing long term price action ), the strategy effectively captures market trends with precision and insight.
- **Short-Term EMA (10-period):** This EMA reacts swiftly to recent price changes, offering heightened sensitivity to short-term fluctuations. It excels in identifying immediate shifts in market sentiment, making it invaluable for pinpointing short-lived trends and potential reversal points.
- **Long-Term EMA (323-period):** In contrast, the long-term EMA provides a broader perspective by smoothing out short-term noise and focusing on longer-term trend direction. Its extended length filters out market noise effectively, providing a clear representation of the underlying trend's momentum and sustainability.
**Directional Movement Index (DMI) Metrics:**
The "Kyrie Crossover" script goes beyond traditional indicators by incorporating DMI metrics across multiple timeframes. By assessing trend strength and direction, traders gain valuable insights into market dynamics, allowing for informed decision-making.
**Simple Instructions to Profit:**
1. **Identify EMA Crossovers:** Look for instances where the short-term EMA (10-period) crosses above the long-term EMA (323-period) for a bullish signal, indicating a potential buying opportunity. Conversely, a crossover where the short-term EMA crosses below the long-term EMA signals a bearish trend and a potential selling opportunity.
2. **Confirm with DMI Metrics:** Validate EMA crossovers by checking DMI metrics across different timeframes (5 minutes, 15 minutes, 30 minutes, and 1 hour). Pay attention to color-coded indicators, with green indicating a bullish trend, red indicating a bearish trend, and white indicating no clear trend.
3. **Manage Risk:** Implement proper risk management techniques, such as setting stop-loss orders and position sizing based on your risk tolerance and trading objectives.
4. **Stay Informed:** Regularly monitor market conditions and adjust your trading strategy accordingly based on new signals and emerging trends.
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. 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: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 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 2h 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
WODIsMA Strategy 3 MA Crossover & Bull-Bear Trend ConfirmationWODIsMA Strategy is a versatile trading strategy designed to leverage the strength of moving averages and volatility indicators to provide clear trading signals for both long and short positions. This strategy is suitable for traders looking for a systematic approach to trading with adjustable parameters to fit various market conditions and personal trading styles.
Key Features
Customizable Moving Averages:
The strategy allows users to select different types of moving averages (SMA, EMA, SMMA, WMA, VWMA) for short-term, mid-term, long-term, and bull-bear trend identification.
Each moving average can be customized with different lengths, sources (e.g., close, high, low), timeframes, and colors.
Position Management:
Users can specify the percentage of capital to use per trade and the percentage to close per partial exit.
The strategy supports both long and short positions with the ability to enable or disable each direction.
Volatility Filter:
Incorporates a volatility filter to ensure trades are only taken when market volatility is above a user-defined threshold, enhancing the strategy's effectiveness in dynamic market conditions.
Bull-Bear Trend Line:
Option to enable a bull-bear trend line that helps identify the overall market trend. Trades are taken based on the relationship between the long-term moving average and the bull-bear trend line.
Partial Exits and Full Close Logic:
The strategy includes logic for partial exits based on the crossing of mid-term and long-term moving averages.
Ensures that positions are fully closed when adverse conditions are detected, such as the price crossing below the bull-bear trend line.
Stop Loss Management:
Implements user-defined stop loss levels to manage risk effectively. The stop loss is dynamically adjusted based on the entry price and user input.
Detailed Description
Moving Average Calculation: The strategy calculates up to six different moving averages, each with customizable parameters. These moving averages help identify the short-term, mid-term, long-term trends, and overall market direction.
Trading Signals:
Long Signal: A long position is opened when the short-term moving average is above the long-term moving average, and the mid-term moving average crosses above the long-term moving average.
Short Signal: A short position is opened when the short-term moving average is below the long-term moving average, and the mid-term moving average crosses below the long-term moving average.
Volatility Condition: The strategy includes a volatility filter that activates trades only when volatility exceeds a specified threshold, ensuring trades are made in favorable market conditions.
Bull-Bear Trend Confirmation: When enabled, trades are filtered based on the relationship between the long-term moving average and the bull-bear trend line, adding another layer of confirmation.
Stop Loss and Exits:
The strategy manages risk by placing stop loss orders based on user-defined percentages.
Positions are partially or fully closed based on the crossing of moving averages and the relationship with the bull-bear trend line.
Originality and Usefulness
This strategy is original as it combines multiple moving averages and volatility indicators in a structured manner to provide reliable trading signals. Its versatility allows traders to adjust the parameters to match their trading preferences and market conditions. The inclusion of a volatility filter and bull-bear trend line adds significant value by reducing false signals and ensuring trades are taken in the direction of the overall market trend. The detailed descriptions and customizable settings make this strategy accessible and understandable for traders, even those unfamiliar with the underlying Pine Script code.
By providing clear entry, exit, and risk management rules, the WODIsMA Strategy enhances the trader's ability to navigate different market environments, making it a valuable addition to the TradingView community scripts.
Chandelier Exit Strategy with 200 EMA FilterStrategy Name and Purpose
Chandelier Exit Strategy with 200EMA Filter
This strategy uses the Chandelier Exit indicator in combination with a 200-period Exponential Moving Average (EMA) to generate trend-based trading signals. The main purpose of this strategy is to help traders identify high-probability entry points by leveraging the Chandelier Exit for stop loss levels and the EMA for trend confirmation. This strategy aims to provide clear rules for entries and exits, improving overall trading discipline and performance.
Originality and Usefulness
This script integrates two powerful indicators to create a cohesive and effective trading strategy:
Chandelier Exit : This indicator is based on the Average True Range (ATR) and identifies potential stop loss levels. The Chandelier Exit helps manage risk by setting stop loss levels at a distance from the highest high or lowest low over a specified period, multiplied by the ATR. This ensures that the stop loss adapts to market volatility.
200-period Exponential Moving Average (EMA) : The EMA acts as a trend filter. By ensuring trades are only taken in the direction of the overall trend, the strategy improves the probability of success. For long entries, the close price must be above the 200 EMA, indicating a bullish trend. For short entries, the close price must be below the 200 EMA, indicating a bearish trend.
Combining these indicators adds layers of confirmation and risk management, enhancing the strategy's effectiveness. The Chandelier Exit provides dynamic stop loss levels based on market volatility, while the EMA ensures trades align with the prevailing trend.
Entry Conditions
Long Entry
A buy signal is generated by the Chandelier Exit.
The close price is above the 200 EMA, indicating a strong bullish trend.
Short Entry
A sell signal is generated by the Chandelier Exit.
The close price is below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions: The position is closed when a sell signal is generated by the Chandelier Exit.
For short positions: The position is closed when a buy signal is generated by the Chandelier Exit.
Risk Management
Account Size: 1,000,00 yen
Commission and Slippage: 17 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
Stop Loss: For long trades, the stop loss is placed slightly below the candle that generated the buy signal. For short trades, the stop loss is placed slightly above the candle that generated the sell signal. The stop loss levels are dynamically adjusted based on the ATR.
Settings Options
ATR Period: Set the period for calculating the ATR to determine the Chandelier Exit levels.
ATR Multiplier: Set the multiplier for ATR to define the distance of stop loss levels from the highest high or lowest low.
Use Close Price for Extremums: Choose whether to use the close price for calculating the extremums.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show Buy/Sell Labels: Choose whether to display buy and sell labels on the chart for visual confirmation.
Highlight State: Choose whether to highlight the bullish or bearish state on the chart.
Sufficient Sample Size
The strategy has been backtested with a sufficient sample size to evaluate its performance accurately. This ensures that the strategy's results are statistically significant and reliable.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the Chandelier Exit indicator. Special thanks to the original contributors for their work on the Chandelier Exit concept.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
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MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
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(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
Strategy SEMA SDI WebhookPurpose of the Code:
The strategy utilizes Exponential Moving Averages (EMA) and Smoothed Directional Indicators (SDI) to generate buy and sell signals. It includes features like leverage, take profit, stop loss, and trailing stops. The strategy is intended for backtesting and automating trades based on the specified indicators and conditions.
Key Components and Functionalities:
1.Strategy Settings:
Overlay: The strategy will overlay on the price chart.
Slippage: Set to 1.
Commission Value: Set to 0.035.
Default Quantity Type: Percent of equity.
Default Quantity Value: 50% of equity.
Initial Capital: Set to 1000 units.
Calculation on Order Fills: Enabled.
Process Orders on Close: Enabled.
2.Date and Time Filters:
Inputs for enabling/disabling start and end dates.
Filters to execute strategy only within specified date range.
3.Leverage and Quantity:
Leverage: Adjustable leverage input (default 3).
USD Percentage: Adjustable percentage of equity to use for trades (default 50%).
Initial Capital: Calculated based on leverage and percentage of equity.
4.Take Profit, Stop Loss, and Trailing Stop:
Inputs for enabling/disabling take profit, stop loss, and trailing stop.
Adjustable parameters for take profit percentage (default 25%), stop loss percentage (default 4.8%), and trailing stop percentage (default 1.9%).
Calculations for take profit, stop loss, trailing price, and maximum profit tracking.
5.EMA Calculations:
Fast and slow EMAs.
Smoothed versions of the fast and slow EMAs.
6.SDI Calculations:
Directional movement calculation for positive and negative directional indicators.
Difference between the positive and negative directional indicators, smoothed.
7.Buy/Sell Conditions:
Long (Buy) Condition: Positive DI is greater than negative DI, and fast EMA is greater than slow EMA.
Short (Sell) Condition: Negative DI is greater than positive DI, and fast EMA is less than slow EMA.
8.Strategy Execution:
If buy conditions are met, close any short positions and enter a long position.
If sell conditions are met, close any long positions and enter a short position.
Exit conditions for long and short positions based on take profit, stop loss, and trailing stop levels.
Close all positions if outside the specified date range.
Usage:
This strategy is used to automate trading based on the specified conditions involving EMAs and SDI. It allows backtesting to evaluate performance based on historical data. The strategy includes risk management through take profit, stop loss, and trailing stops to protect gains and limit losses. Traders can customize the parameters to fit their specific trading preferences and risk tolerance. Differently, it can perform leverage analysis and use it as a template.
By using this strategy, traders can systematically execute trades based on technical indicators, helping to remove emotional bias and improve consistency in trading decisions.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Smoothed Heiken Ashi Strategy Long OnlyThis is a trend-following approach that uses a modified version of Heiken Ashi candles with additional smoothing. Here are the key components and features:
1. Heiken Ashi Modification: The strategy starts by calculating Heiken Ashi candles, which are known for better trend visualization. However, it modifies the traditional Heiken Ashi by using Exponential Moving Averages (EMAs) of the open, high, low, and close prices.
2. Double Smoothing: The strategy applies two layers of smoothing. First, it uses EMAs to calculate the Heiken Ashi values. Then, it applies another EMA to the Heiken Ashi open and close prices. This double smoothing aims to reduce noise and provide clearer trend signals.
3. Long-Only Approach: As the name suggests, this strategy only takes long positions. It doesn't short the market during downtrends but instead exits existing long positions when the sell signal is triggered.
4. Entry and Exit Conditions:
- Entry (Buy): When the smoothed Heiken Ashi candle color changes from red to green (indicating a potential start of an uptrend).
- Exit (Sell): When the smoothed Heiken Ashi candle color changes from green to red (indicating a potential end of an uptrend).
5. Position Sizing: The strategy uses a percentage of equity for position sizing, defaulting to 100% of available equity per trade. This should be tailored to each persons unique approach. Responsible trading would use less than 5% for each trade. The starting capital used is a responsible and conservative $1000, reflecting the average trader.
This strategy aims to provide a smooth, trend-following approach that may be particularly useful in markets with clear, sustained trends. However, it may lag in choppy or ranging markets due to its heavy smoothing. As with any strategy, it's important to thoroughly backtest and forward test before using it with real capital, and to consider using it in conjunction with other analysis tools and risk management techniques.
This has been created mainly to provide data to judge what time frame is most profitable for any single asset, as the volatility of each asset is different. This can bee seen using it on AUXUSD, which has a higher profitable result on the daily time frame, whereas other currencies need a higher or lower time frame. The user can toggle between each time frame and watch for the higher profit results within the strategy tester window.
Other smoothed Heiken Ashi indicators also do not provide buy and sell signals, and only show the change in color to dictate a change in trend. By adding buy and sell signals after the close of the candle in which the candle changes color, alerts can be programmed, which helps this be a more hands off protocol to experiment with. Other smoothed Heiken Ashi indicators do not allow for alarms to be set.
This is a unique HODL strategy which helps identify a change in trend, without the noise of day to day volatility. By switching to a line chart, it removes the candles altogether to avoid even more noise. The goal is to HODL a coin while the color is bullish in an uptrend, but once the indicator gives a sell signal, to sell the holdings back to a stable coin and let the chart ride down. Once the chart gives the next buy signal, use that same capital to buy back into the asset. In essence this removes potential losses, and helps buy back in cheaper, gaining more quantitity fo the asset, and therefore reducing your average initial buy in price.
Most HODL strategies ride the price up, miss selling at the top, then riding the price back down in anticipation that it will go back up to sell. This strategy will not hit the absolute tops, but it will greatly reduce potential losses.
FVG Positioning Average with 200EMA Auto Trading [Pakun]Description
Strategy Name and Purpose
FVG Positioning Average with 200EMA Auto Trading
This strategy uses Fair Value Gaps (FVG) combined with a 200-period Exponential Moving Average (EMA) and Average True Range (ATR) to generate trend-based trading signals. It is designed to help traders identify high-probability entry points by leveraging the gaps between fair value prices and current market prices.
Originality and Usefulness
This script combines multiple indicators to create a cohesive trading strategy that is greater than the sum of its parts. While FVG is a powerful tool on its own, combining it with the EMA and ATR adds layers of confirmation and risk management, enhancing its effectiveness. Here’s how the components work together:
Fair Value Gap (FVG): Identifies gaps in the market where price action has not fully filled, indicating potential reversal or continuation points.
200-period Exponential Moving Average (EMA): Acts as a trend filter to ensure trades are taken in the direction of the overall trend, improving the probability of success.
Average True Range (ATR): Used to filter out insignificant gaps and set dynamic stop-loss levels based on market volatility, enhancing risk management.
Entry Conditions
Long Entry
The close price crosses above the downtrend FVG.
The close price, FVG up average, and down average are all above the 200 EMA, indicating a strong bullish trend.
Short Entry
The close price crosses below the uptrend FVG.
The close price, FVG up average, and down average are all below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions, the stop loss is set at the recent low, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
For short positions, the stop loss is set at the recent high, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
Risk Management
Account Size: 1,000,000 yen
Commission and Slippage: 2 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
The stop loss is based on the recent low or recent high, ensuring trades are exited when the market moves against the position.
Settings Options
FVG Lookback: Set the lookback period for calculating FVGs.
Lookback Type: Choose the type of lookback (Bar Count or FVG Count).
ATR Multiplier: Set the multiplier for ATR to filter significant gaps.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show FVGs on Chart: Choose whether to display FVGs on the chart for visual confirmation.
Bullish/Bearish Color: Set the color for bullish and bearish FVGs to distinguish them easily.
Show Gradient Areas: Choose whether to display gradient areas to highlight the zones of interest.
Sufficient Sample Size
The strategy has been backtested with 113 trades, providing a sufficient sample size to evaluate its performance.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the FVG Positioning Average Strategy indicator. Thanks to for their contribution.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
MA MACD BB BackTesterOverview:
This Pine Script™ code provides a comprehensive backtesting tool that combines Moving Average (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands (BB). It is designed to help traders analyze market trends and make informed trading decisions by testing various strategies over historical data.
Key Features:
1. Customizable Indicators:
Moving Average (MA): Smooths out price data for clearer trend direction.
MACD: Measures trend momentum through MACD Line, Signal Line, and Histogram.
Bollinger Bands (BB): Identifies overbought or oversold conditions with upper and lower bands.
2. Flexible Trading Direction: Choose between long or short positions to adapt to different market conditions.
3. Risk Management: Efficiently allocate your capital with customizable position sizes.
4. Signal Generation:
Buy Signals: Triggered by crossovers for MACD, MA, and BB.
Sell Signals: Triggered by crossunders for MACD, MA, and BB.
5. Automated Trading: Automatically enter and exit trades based on signal conditions and strategy parameters.
How It Works:
1. Indicator Selection: Select your preferred indicator (MA, MACD, BB) and trading direction (Long/Short).
2. Risk Management Configuration: Set the percentage of capital to allocate per position to manage risk effectively.
3.Signal Detection: The algorithm identifies and plots buy/sell signals directly on the chart based on the chosen indicator.
4. Trade Execution: The strategy automatically enters and exits trades based on signal conditions and configured strategy parameters.
Use Cases:
- Backtesting: Evaluate the effectiveness of trading strategies using historical data to understand potential performance.
- Strategy Development: Customize and expand the strategy to incorporate additional indicators or conditions to fit specific trading styles.
ADDONS That Affect Strategy:
1. Indicator Parameters:
Adjustments to the settings of MACD (e.g., fast length, slow length), MA (e.g., length), and BB (e.g., length, multiplier) will directly impact the detection of signals and the strategy's performance.
2. Trading Direction:
Changing the trading direction (Long/Short) will alter the entry and exit conditions based on the detected signals.
3. Risk Management Settings:
Modifying the position size percentage affects capital allocation and overall risk exposure per trade.
ADDONS That Do Not Affect Strategy:
1. Visual Customizations:
Changes to the color, shape, and style of the plotted lines and signals do not impact the core functionality of the strategy but enhance visual clarity.
2. Text and Labels:
Modifying text labels for the signals (such as renaming "Buy MACD" to "MACD Buy Signal") is purely cosmetic and does not influence the strategy’s logic or outcomes.
Notes:
- Customization: The indicator is highly customizable to fit various trading styles and market conditions.
- Risk Management: Adjust position sizes and risk parameters according to your risk tolerance and account size.
- Optimization: Regularly backtest and optimize parameters to adapt to changing market dynamics for better performance.
Getting Started:
-Add the script to your chart.
-Adjust the input parameters to suit your analysis preferences.
-Observe the marked buy and sell signals on your chart to make informed trading decisions.
Uptrick:Intensity IndexPurpose:
The "Uptrick: Intensity Index" strategy is designed to provide traders with insights into the trend intensity of security by combining multiple moving averages and their relative positions. This versatile tool can be used effectively by both short-term and long-term traders to identify potential buy and sell signals based on specific conditions.
Explanation:
Input Parameters and Customization:
Moving Averages Lengths:
Adjust MA1, MA2, and MA3 lengths to change the calculation periods for the moving averages.
Trend Intensity Index SMA Length:
Adjust the length of the SMA applied to the TII.
Plot Colors:
Change the colors of the TII and TII MA plots for better visualization.
Background Colors and Transparency:
Set different colors for positive and negative TII MA values.
Control the transparency of the background color.
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MA1 (Length 10): Short-term moving average, useful for capturing short-term market trends.
MA2 (Length 20): Medium-term moving average, providing a balanced view of market trends.
MA3 (Length 50): Long-term moving average, offering insights into long-term market trends.
The script calculates the relative positions of the closing price to each moving average (rel1, rel2, rel3) to determine how far the current price deviates from each average.
Trend Intensity Index (TII):
The TII is calculated as the average of the relative positions (rel1, rel2, rel3), multiplied by 100 to convert it into a percentage. This index reflects the overall intensity of the trend, considering short-term, medium-term, and long-term perspectives.
The TII is plotted in blue, providing a visual representation of trend intensity.
SMA of TII:
An additional SMA is applied to the TII (matii) to smooth out fluctuations and provide a clearer long-term trend signal.
The SMA of TII is plotted in orange, offering a reference for long-term trend analysis.
Determining Potential Price Movements:
For Short-Term Traders:
When the blue TII line crosses above the orange SMA of TII line, it indicates a potential buy signal.
When the blue TII line crosses below the orange SMA of TII line, it indicates a potential sell signal.
For Long-Term Traders:
When the orange SMA of TII line crosses above the highlighted 0 line, it indicates a potential buy signal.
When the orange SMA of TII line crosses below the highlighted 0 line, it indicates a potential sell signal.
Plotting and Visualization:
The TII and its SMA are plotted with distinct colors for easy identification.
A horizontal line at 0 is plotted in gray to serve as a reference point for long-term trend signals.
The background color changes based on the value of the SMA of TII (matii):
Green background for matii values above 0, indicating bullish conditions.
Red background for matii values below 0, indicating bearish conditions.
Utility and Potential Usage:
The "Uptrick: Intensity Index" indicator is a powerful tool for both short-term and long-term traders, offering clear buy and sell signals based on the crossover of the TII and its SMA, as well as the position of the SMA relative to the zero line.
By consolidating multiple moving averages and their relative positions into a single indicator, traders can gain comprehensive insights into market trends and intensity.
The ability to adjust all inputs and toggle visibility options enhances the flexibility and utility of the indicator, making it suitable for various trading styles and market conditions.
Through its versatile design and advanced features, the "Uptrick: Intensity Index" indicator equips traders with actionable insights into trend intensity and potential price movements. By integrating this robust tool into their trading strategies, traders can navigate the markets with greater precision and confidence, thereby enhancing their trading outcomes.
WHAT SETTINGS TO HAVE FOR THE MOVING AVERAGE:
Short-term traders (day traders) might prefer a shorter SMA length (e.g., 5-20 periods) as they are looking for quick signals and react to price changes more rapidly.
Medium-term traders (swing traders) might opt for a medium SMA length (e.g., 20-50 periods) which can filter out some noise and provide a clearer signal on the trend.
Long-term traders (position traders) might choose a longer SMA length (e.g., 50-200 periods) to get a broader view of the market trend and avoid reacting to short-term fluctuations.
Versatile Moving Average StrategyVersatile Moving Average Strategy (VMAS)
Overview:
The Versatile Moving Average Strategy (VMAS) is designed to provide traders with a flexible approach to trend-following, utilizing multiple types of moving averages. This strategy allows for customization in choosing the moving average type and length, catering to various market conditions and trading styles.
Key Features:
- Multiple Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, VWMA, HULL, LSMA, and ALMA to best suit your trading needs.
- Customizable Inputs: Adjust the moving average length, source of price data, and stop-loss source to fine-tune the strategy.
- Target Percent: Set the percentage difference between successive profit targets to manage your risk and rewards effectively.
- Position Management: Enable or disable long and short positions, allowing for versatility in different market conditions.
- Commission and Slippage: The strategy includes realistic commission settings to ensure accurate backtesting results.
Strategy Logic:
1. Moving Average Calculation: The selected moving average is calculated based on user-defined parameters.
2. Entry Conditions:
- A long position is entered when the entry source crosses over the moving average, if long positions are enabled.
- A short position is entered when the entry source crosses under the moving average, if short positions are enabled.
3. Stop-Loss: Positions are closed if the stop-loss source crosses the moving average in the opposite direction.
4. Profit Targets: Multiple profit targets are defined, with each target set at an incremental percentage above (for long positions) or below (for short positions) the entry price.
Default Properties:
- Account Size: $10000
- Commission: 0.01% per trade
- Risk Management: Positions are sized to risk 80% of the equity per trade, because we get very tight stoploss when position is open.
- Sample Size: Backtesting has been conducted to ensure a sufficient sample size of trades, ideally more than 100 trades.
How to Use:
1. Configure Inputs: Set your preferred moving average type, length, and other input parameters.
2. Enable Positions: Choose whether to enable long, short, or both types of positions.
3. Backtest and Analyze: Run backtests with realistic settings and analyze the results to ensure the strategy aligns with your trading goals.
4. Deploy and Monitor: Once satisfied with the backtesting results, deploy the strategy in a live environment and monitor its performance.
This strategy is suitable for traders looking to leverage moving averages in a versatile and customizable manner. Adjust the parameters to match your trading style and market conditions for optimal results.
Note: Ensure the strategy settings used for publication are the same as those described here. Always conduct thorough backtesting before deploying any strategy in a live trading environment.
Entry Fragger - Strategy
For basic instructions please visit my other script "Entry Fragger".
The Signal Logic is explained there.
v1.4:
- Added advanced backtesting with fully customizable entries.
- Fully automated Buy Signals (profitable).
- Adjustable timeframes for signal logic. (requested)
Every setting affects the accuracy and profitability greatly now, based on settings applied.
The strategy performs best on high timeframes with larger capital and no leverage.
Useless for Forex, but absolutely smashes stocks and crypto on mid to high timeframes.
Please read through my other scripts description.
Set values as preferred and try your assets.
It does NOT work on low timeframes and forex!
Hint: BTC 4H, Custom Timeframe 1h, Moon Mode and Show Sell Signals enabled, R2R: 2.
Kaufman Adaptive Moving Average (KAMA) Strategy [TradeDots]"The Kaufman Adaptive Moving Average (KAMA) Strategy" is a trend-following system that leverages the adaptive qualities of the Kaufman Adaptive Moving Average (KAMA). This strategy is distinguished by its ability to adjust dynamically to market volatility, enhancing trading accuracy by minimizing the effects of false and delayed signals often associated with the Simple Moving Average (SMA).
HOW IT WORKS
This strategy is centered around use of the Kaufman Adaptive Moving Average (KAMA) indicator, which refines the principles of the Exponential Moving Average (EMA) with a superior smoothing technique.
KAMA distinguishes itself by its responsiveness to changes in market prices through an "Efficiency Ratio (ER)." This ratio is computed by dividing the recent absolute net price change by the cumulative sum of the absolute price changes over a specified period. The resulting ER value ranges between 0 and 1, where 0 indicates high market noise and 1 reflects stronger market momentum.
Using ER, we could get the smoothing constant (SC) for the moving average derived using the following formula:
fastest = 2/(fastma_length + 1)
slowest = 2/(slowma_length + 1)
SC = math.pow((ER * (fastest-slowest) + slowest), 2)
The KAMA line is then calculated by applying the SC to the difference between the current price and the previous KAMA.
APPLICATION
For entering long positions, this strategy initializes when there is a sequence of 10 consecutive rising KAMA lines. Conversely, a sequence of 10 consecutive falling KAMA lines triggers sell orders for long positions. The same logic applies inversely for short positions.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Golden Cross VWMA & EMA 4h PinescriptlabsThis strategy combines the 50-period Volume-Weighted Moving Average (VWMA) on the current timeframe with a 200-period Simple Moving Average (SMA) on the 4-hour timeframe. This combination of indicators with different characteristics and time horizons aims to identify strong and sustained trends across multiple timeframes.
The VWMA is a variant of the moving average that assigns greater weight to periods of higher volatility, helping to avoid misleading signals. On the other hand, the 4-hour SMA is used as an additional trend filter in a shorter-term horizon. By combining these two indicators, the strategy can leverage the strength of the VWMA to capture the main trend, but only when confirmed by the SMA in the lower timeframe.
Buy signals are generated when the VWMA crosses above the 4-hour SMA, indicating a potential bullish trend aligned in both timeframes. Sell signals occur on a bearish cross, suggesting a possible reversal of the main trend.
The default parameters are a 50-period VWMA and a 200-period 4-hour SMA. It is recommended to adjust these lengths according to the traded instrument and the desired timeframe. It is also crucial to use stop losses and profit targets to properly manage risk.
By combining indicators of different types and timeframes, this strategy aims to provide a more comprehensive view of trend strength.
Español:
Esta estrategia combina la Volume-Weighted Moving Average (VWMA) de 50 períodos en el timeframe actual con una Simple Moving Average (SMA) de 200 períodos en el timeframe de 4 horas. Esta combinación de indicadores de distinta naturaleza y horizontes temporales busca identificar tendencias fuertes y sostenidas en múltiples timeframes.
La VWMA es una variante de la media móvil que asigna mayor ponderación a los períodos de mayor volatilidad, lo que ayuda a evitar señales engañosas. Por otro lado, la SMA de 4 horas se utiliza como un filtro adicional de tendencia en un horizonte de corto plazo. Al combinar estos dos indicadores, la estrategia puede aprovechar la fortaleza de la VWMA para capturar la tendencia principal, pero sólo cuando es confirmada por la SMA en el timeframe menor.
Las señales de compra se generan cuando la VWMA cruza al alza la SMA de 4 horas, indicando una potencial tendencia alcista alineada en ambos horizontes temporales. Las señales de venta ocurren en el cruce bajista, sugiriendo una posible reversión de la tendencia principal.
Los parámetros predeterminados son: VWMA de 50 períodos y SMA de 4 horas de 200 períodos. Se recomienda ajustar estas longitudes según el instrumento operado y el horizonte temporal deseado. También es crucial utilizar stops y objetivos de ganancias para controlar adecuadamente el riesgo.
Al combinar indicadores de diferentes tipos y timeframes, esta estrategia busca brindar una visión más completa de la fuerza de la tendencia.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Moving average strategyNAME : Moving average strategy
SUMMARY
Long when Short MA period > Long MA period
Exit when Short MA period < Long MA period
Long only strategy, but you can modify this script.
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This strategy uses a moving average line.
It buys when the short-term moving average crosses the long-term moving average and sells when the long-term moving average crosses the short-term moving average.
You can use different moving average lines by setting the MA type.
You can use SMA, EMA, DEMA, TEMA, WMA, and VWMA.
You can also adjust the period of the moving average line.
Price Type sets the type of price that will be used for the moving average line. The options are Close price, Open price, High price, Low price, Typical price, and center price.
High MDD and long periods of sideways movement make it difficult to use in practice, even though the returns may seem high.
Hopefully, you can combine it with other indicators to create a good strategy.
Thank you.
Alligator + MA Trend Catcher [TradeDots]The "Alligator + MA Trend Catcher" is a trading strategy that integrates the William Alligator indicator with a Moving Average (MA) to establish robust entry and exit conditions, optimized for capturing trends.
HOW IT WORKS
This strategy combines the traditional William Alligator set up with an additional Moving Average indicator for enhanced trend confirmation, creating a user-friendly backtesting tool for traders who prefer the Alligator method.
The original Alligator strategy can frequently present fluctuations, even in well-established trends, leading to potentially premature exits. To mitigate this, we incorporate a Moving Average as a secondary confirmation measure to ensure the market trend has indeed shifted.
Here’s the operational flow for long orders:
Entry Signal: When the price rises above the Moving Average, it confirms a bullish market state. Enter if Alligator spread in an upward direction. The trade remains active even if the Alligator indicator suggests a trend reversal.
Exit Signal: The position is closed when the price falls below the Moving Average, and the Alligator spreads in the downward direction. This setup helps traders to maintain positions through the entirety of the trend for maximum gain.
APPLICATION
This strategy is tailored for assets with significant, well-defined trends, such as Bitcoin and Ethereum, which are known for their high volatility and substantial price movements.
This strategy offers a low win-rate but high reward configuration, making asset selection critical for long-term profitability. If you choose assets that lack strong price momentum, there's a high chance that this strategy may not be effective.
For traders seeking to maximize gains from large trends without exiting prematurely, this strategy provides an aggressive yet controlled approach to riding out substantial market waves.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Multi Timeframe RSI Buy Sell Strategy [TradeDots]The "Multi Timeframe RSI Buy/Sell Strategy" is a trading strategy that utilizes Relative Strength Index (RSI) indicators from multiple timeframes to provide buy and sell signals.
This strategy allows for extensive customization, supporting up to three distinct RSIs, each configurable with its own timeframe, length, and data source.
HOW DOES IT WORK
This strategy integrates up to three RSIs, each selectable from different timeframes and customizable in terms of length and source. Users have the flexibility to define the number of active RSIs. These selections visualize as plotted lines on the chart, enhancing interpretability.
Users can also manage the moving average of the selected RSI lines. When multiple RSIs are active, the moving average is calculated based on these active lines' average value.
The color intensity of the moving average line changes as it approaches predefined buying or selling thresholds, alerting users to potential signal generation.
A buy or sell signal is generated when all active RSI lines simultaneously cross their respective threshold lines. Concurrently, a label will appear on the chart to signify the order placement.
For those preferring not to display order information or activate the strategy, an "Enable backtest" option is provided in the settings for toggling activation.
APPLICATION
The strategy leverages multiple RSIs to detect extreme market conditions across various timeframes without the need for manual timeframe switching.
This feature is invaluable for identifying divergences across timeframes, such as detecting potential short-term reversals within broader trends, thereby aiding traders in making better trading decisions and potentially avoiding losses.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 60%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TradeDots Stochastic Z-Score
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
