The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Cerca negli script per "profit"
Channels Strategy [JoseMetal]============
ENGLISH
============
- Description:
This strategy is based on Bollinger Bands / Keltner Channel price "rebounds" (the idea of price bouncing from one band to another).
The strategy has several customizable options, which allows you to refine the strategy for your asset and timeframe.
You can customize settings for ALL indicators, Bollinger Bands (period and standard deviation), Keltner Channel (period and ATR multiplier) and ATR (period).
- AVAILABLE INDICATORS:
You can pick Bollinger Bands or Keltner Channels for the strategy, the chosen indicator will be plotted as well.
- CUSTOM CONDITIONS TO ENTER A POSITION:
1. Price breaks the band (low below lower band for LONG or high above higher band for SHORT).
2. Same as 1 but THEN (next candle) price closes INSIDE the bands.
3. Price breaks the band AND CLOSES OUT of the band (lower band for LONG and higher band for SHORT).
4. Same as 3 but THEN (next candle) price closes INSIDE the bands.
- STOP LOSS OPTIONS:
1. Previous wick (low of previous candle if LONG and high or previous candle if SHORT).
2. Extended band, you can customize settings for a second indicator with larger values to use it as STOP LOSS, for example, Bollinger Bands with 2 standard deviations to open positions and 3 for STOP LOSS.
3. ATR: you can pick average true ratio from a source (like closing price) with a multiplier to calculate STOP LOSS.
- TAKE PROFIT OPTIONS:
1. Opposite band (top band for LONGs, bottom band for SHORTs).
2. Moving average: Bollinger Bands simple moving average or Keltner Channel exponential moving average .
3. ATR: you can pick average true ratio from a source (like closing price) with a multiplier to calculate TAKE PROFIT.
- OTHER OPTIONS:
You can pick to trade only LONGs, only SHORTs, both or none (just indicator).
You can enable DYNAMIC TAKE PROFIT, which updates TAKE PROFIT on each candle, for example, if you pick "opposite band" as TAKE PROFIT, it'll update the TAKE PROFIT based on that, on every single new candle.
- Visual:
Bands shown will depend on the chosen indicator and it's settings.
ATR is only printed if used as STOP LOSS and/or TAKE PROFIT.
- Recommendations:
Recommended on DAILY timeframe , it works better with Keltner Channels rather than Bollinger Bands .
- Customization:
As you can see, almost everything is customizable, for colors and plotting styles check the "Style" tab.
Enjoy!
============
ESPAÑOL
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- Descripción:
Esta estrategia se basa en los "rebotes" de precios en las Bandas de Bollinger / Canal de Keltner (la idea de que el precio rebote de una banda a otra).
La estrategia tiene varias opciones personalizables, lo que le permite refinar la estrategia para su activo y temporalidad favoritas.
Puedes personalizar la configuración de TODOS los indicadores, Bandas de Bollinger (periodo y desviación estándar), Canal de Keltner (periodo y multiplicador ATR) y ATR (periodo).
- INDICADORES DISPONIBLES:
Puedes elegir las Bandas de Bollinger o los Canales de Keltner para la estrategia, el indicador elegido será mostrado en pantalla.
- CONDICIONES PERSONALIZADAS PARA ENTRAR EN UNA POSICIÓN:
1. El precio rompe la banda (mínimo por debajo de la banda inferior para LONG o máximo por encima de la banda superior para SHORT).
2. Lo mismo que en el punto 1 pero ADEMÁS (en la siguiente vela) el precio cierra DENTRO de las bandas.
3. El precio rompe la banda Y CIERRA FUERA de la banda (banda inferior para LONG y banda superior para SHORT).
4. Igual que el 3 pero ADEMÁS (siguiente vela) el precio cierra DENTRO de las bandas.
- OPCIONES DE STOP LOSS:
1. Mecha anterior (mínimo de la vela anterior si es LONGy máximo de la vela anterior si es SHORT).
2. Banda extendida, puedes personalizar la configuración de un segundo indicador con valores más extensos para utilizarlo como STOP LOSS, por ejemplo, Bandas de Bollinger con 2 desviaciones estándar para abrir posiciones y 3 para STOP LOSS.
3. ATR: puedes elegir el average true ratio de una fuente (como el precio de cierre) con un multiplicador para calcular el STOP LOSS.
- OPCIONES DE TAKE PROFIT:
1. Banda opuesta (banda superior para LONGs, banda inferior para SHORTs).
2. Media móvil: media móvil simple de las Bandas de Bollinger o media móvil exponencial del Canal de Keltner .
3. ATR: se puede escoger el average true ratio de una fuente (como el precio de cierre) con un multiplicador para calcular el TAKE PROFIT.
- OTRAS OPCIONES:
Puedes elegir operar sólo con LONGs, sólo con SHORTs, ambos o ninguno (sólo el indicador).
Puedes activar el TAKE PROFIT DINÁMICO, que actualiza el TAKE PROFIT en cada vela, por ejemplo, si eliges "banda opuesta" como TAKE PROFIT, actualizará el TAKE PROFIT basado en eso, en cada nueva vela.
- Visual:
Las bandas mostradas dependerán del indicador elegido y de su configuración.
El ATR sólo se muestra si se utiliza como STOP LOSS y/o TAKE PROFIT.
- Recomendaciones:
Recomendada para temporalidad de DIARIO, funciona mejor con los Canales de Keltner que con las Bandas de Bollinger .
- Personalización:
Como puedes ver, casi todo es personalizable, para los colores y estilos de dibujo comprueba la pestaña "Estilo".
¡Que lo disfrutes!
PIVOT STRATEGY [INDIAN MARKET TIMING]
A Back-tested Profitable Strategy for Free!!
A PIVOT INTRADAY STRATEGY for 5 minute Time-Frame , that also explains the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above ema1 ,indicated by pivot highest line in green color .
2) Price crosses below ema1 ,indicated by pivot lowest line in red color .
3) Candle high crosses above pivot highest , is the Long condition .
4) Candle low crosses below pivot lowest , is the Short condition .
5) Maximum Risk per trade for the intraday trade can be changed .
6) Default_qty_size is set to 60 contracts , which can be changed under settings → properties → order size .
7) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
Leftbars —————> Length of pivot highs and lows
Rightbars —————> Length of pivot highs and lows
Price Cross Ema —————> Added condition
ATR LONG —————> ATR stoploss trail for Long positions
ATR SHORT —————> ATR stoploss trail for Short positions
RISK —————> Maximum Risk per trade for the day
The strategy was back-tested on RELIANCE ,the input values and the results are mentioned under "BACKTEST RESULTS" below .
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 60 contracts , which can be changed under settings
↓
properties
↓
order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 25 .
The Indian Markets open at 9:15am and closes at 3:30pm .
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm, at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 103 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
NSE:RELIANCE
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 128 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better back-test results.
The strategy applied to NIFTY ( 5 min Time-Frame and contract size 60 ) gives us 60% profitability y , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.45 ,net Profit of 21,500Rs profit .
Sharpe Ratio : 0.311
Sortino Ratio : 0.727
The graph has a Linear Curve with consistent profits .
The INPUTS are as follows,
1) Leftbars ————————> 3
2) Rightbars ————————> 5
3) Price Cross Ema ——————> 150
4) ATR LONG ————————> 2.7
5) ATR SHORT ———————> 2.9
6) RISK —————————> 2500
7) Default qty size ——————> 60
NSE:RELIANCE
Save it to favorites.
Apply it to your charts Now !!
↓
FOLLOW US FOR MORE !
Thank me later ;)
Short Swing Bearish MACD Cross (By Coinrule)This strategy is oriented towards shorting during downside moves, whilst ensuring the asset is trading in a higher timeframe downtrend, and exiting after further downside.
This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to hodl this cash, or use it to reinvest when the market reaches attractive buying levels. Alternatively, you can use this when trading contracts on futures markets where there is no need to already own the underlying asset prior to shorting it.
ENTRY
This script utilises the MACD indicator accompanied by the Exponential Moving Average (EMA) 450 to enter trades. The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 11-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9.
The EMA 450 is used as additional confirmation to prevent the script from shorting when price is above this long-term moving average. Once price is above the EMA 450 the script will not open any shorts - preventing the rule from attempting to short uptrends. Due to this, this strategy is ideal for setting and forgetting.
The script will enter trades based on two conditions:
1) When the MACD signals a bearish cross. This occurs when the EMA 11 crosses below the EMA 26 within the MACD signalling the start of a potential downtrend.
2) Price has closed below the EMA 450. Price closing below this long-term EMA signals that the asset is in a sustained downtrend. Price breaking above this could indicate a bullish strength in which shorting would not be profitable.
EXIT
This script utilises a set take-profit and stop-loss from the entry of the trade. The take profit is set at 8% and the stop loss of 4%, providing a risk reward ratio of 2. This indicates the script will be profitable if it has a win ratio greater than 33%.
Take-Profit Exit: -8% price decrease from entry price.
OR
Stop-Loss Exit: +4% price increase from entry price.
Based on backtesting results across a selection of assets, the 45-minute and 1-hour timeframes are the best for this strategy.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
The backtesting data was recorded from December 1st 2021, just as the market was beginning its downtrend. We therefore recommend analysing the market conditions prior to utilising this strategy as it operates best on weak coins during downtrends and bearish conditions, however the EMA 450 condition should mitigate entries during bullish market conditions.
Scalping Dips On Trend (by Coinrule)Coinrule's Community is an excellent source of inspiration for our trading strategies.
In these months of Bull Market, our traders opted mostly on buy-the-dips strategies, which resulted in great returns recently. But there has been an element that turned out to be the cause for deep division among the Community.
Is it advisable or not to use a stop-loss during a Bull Market?
This strategy comes with a large stop-loss to offer a safer alternative for those that are not used to trade with a downside protection.
Entry
The strategy buys only when the price is above the Moving Average 50 , making it less risky to buy the dip, which is set to 2%.
The preferred time frame is 1-hour.
The stop-loss is set to be quite loose to increase the chances of closing the trade in profit, yet protecting from unexpected larger drawdowns that could undermine the allocation's liquidity.
Exit
Stop loss: 10%
Take Profit: 3%
In times of Bull Market, such a trading system has a very high percentage of trades closed in profit (ranging between 70% to 80%), which makes it still overall profitable to have a stop-loss three times larger than the take profit.
Pro tip: use a larger stop-loss only when you expect to close in profit most of the trades!
The strategy assumes each order to trade 30% of the available capital and opens a trade at a time. A trading fee of 0.1% is taken into account.
Pinescript v4 - The Holy Grail (Trailing Stop)After studying several other scripts, I believe I have found the Holy Grail! (Or perhaps I've just found a bug with Tradingview's Pinescript v4 language) Anyhow, I'm publishing this script in the hope that someone smarter than myself could shed some light on the fact that adding a trailing stop to any strategy seems to make it miraculously...no that's an understatement...incredulously, stupendously, mind-bendingly profitable. I'm talking about INSANE profit factors, higher than 200x, with drawdowns of <10%. Sounds too good to be true? Maybe it is...or you could hook it up to your LIVE broker, and pray it doesn't explode. This is an upgraded version of my original Pin Bar Strategy.
Recommended Chart Settings:
Asset Class: Forex
Time Frame: H1
Long Entry Conditions:
a) Exponential Moving Average Fan up trend
b) Presence of a Bullish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Short Entry Conditions:
a) Exponential Moving Average down trend
b) Presence of a Bearish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Exit Conditions:
a) Trailing stop is hit
b) Moving Averages cross-back (optional)
c) It's the weekend
Default Robot Settings:
Equity Risk (%): 3 //how much account balance to risk per trade
Stop Loss (x*ATR, Float): 0.5 //stoploss = x * ATR, you can change x
Stop Loss Trail Points (Pips): 1 //the magic sauce, not sure how this works
Stop Loss Trail Offset (Pips): 1 //the magic sauce, not sure how this works
Slow SMA (Period): 50 //slow moving average period
Medium EMA (Period): 18 //medium exponential moving average period
Fast EMA (Period): 6 //fast exponential moving average period
ATR (Period): 14 // average true range period
Cancel Entry After X Bars (Period): 3 //cancel the order after x bars not triggered, you can change x
Backtest Results (2019 to 2020, H1, Default Settings):
AUDUSD - 1604% profit, 239.6 profit factor, 4.9% drawdown (INSANE)
NZDUSD - 1688.7% profit, 100.3 profit factor, 2.5% drawdown
GBPUSD - 1168.8% profit, 98.7 profit factor, 0% drawdown
USDJPY - 900.7% profit, 93.7 profit factor, 4.9% drawdown
USDCAD - 819% profit, 31.7 profit factor, 8.1% drawdown
EURUSD - 685.6% profit, 26.8 profit factor, 5.9% drawdown
USDCHF - 1008% profit, 18.7 profit factor, 8.6% drawdown
GBPJPY - 1173.4% profit, 16.1 profit factor, 7.9% drawdown
EURAUD - 613.3% profit, 14.4 profit factor, 9.8% drawdown
AUDJPY - 1619% profit, 11.26 profit factor, 9.1% drawdown
EURJPY - 897.2% profit, 6 profit factor, 13.8% drawdown
EURGBP - 608.9% profit, 5.3 profit factor, 9.8% drawdown (NOT TOO SHABBY)
As you can clearly see above, this forex robot is projected by the Tradingview backtester to be INSANELY profitable for all common forex pairs. So what was the difference between this strategy and my previous strategies? Check my code and look for "trail_points" and "trail_offset"; you can even look them up in the PineScript v4 documentation. They specify a trailing stop as the exit condition, which automatically closes the trade if price reverses against you.
I however suspect that the backtester is not properly calculating intra-bar price movement, and is using a simplified model. With this simplfied approach, the trailing stop code becomes some sort of "holy grail" generator, making every trade entered profitable.
Risk Warning:
This is a forex trading strategy that involves high risk of equity loss, and backtest performance will not equal future results. You agree to use this script at your own risk.
Hint:
To get more realistic results, and *maybe* overcome the intrabar simulation error, change the settings to: "Stop Loss Trail Points (pips)": 100
I am not sure if this eradicates the bug, but the entries and exits look more proper, and the profit factors are more believable.
Low volatility Buy w/ TP & SL (Coinrule)The compression of volatility usually leads to expansion. When the breakout comes, it can ignite strong trends. One way to catch a coin trading in an accumulation area is to spot three moving averages with values close to each other. The strategy uses a combination of Moving Averages to spot the best time to buy a coin before its breakout.
Buy Condition
The MA200 is greater than the MA100
The MA50 is greater than the MA100
According to backtesting results, the 1-hour time frame is the best to run this strategy.
Sell Condition
Take Profit: the price increases 8% from the entry price
Stop Loss: the price drops 4% from the entry price
The strategy has a profitability of 40-60% (depending on the market conditions). Having a ratio of two between Take profit and Stop Loss helps keeping the strategy profitable in the long term.
Relative Normalized VolatilityThere are plenty of indicators that aim to measure the volatility (degree of variation) in the price of an instrument, the most well known being the average true range and the rolling standard deviation. Volatility indicators form the key components of most bands and trailing stops indicators, but can also be used to normalize oscillators, they are therefore extremely versatile.
Today proposed indicator aim to compare the estimated volatility of two instruments in order to provide various informations to the user, especially about risk and profitability.
CALCULATION
The relative normalized volatility (RNV) indicator is the ratio between the moving average of the absolute normalized price changes value of two securities, that is:
SMA(|Δ(a)/σ(a)|)
―――――――――――
SMA(|Δ(b)/σ(b)|)
Where a and b are two different securities (note that notation "Δ(x)" refer to the 1st difference of x, and the "||" notation is used to indicate absolute value, for example "|x|" means absolute value of x) .
INTERPRETATION
The indicator aim tell us which security is more volatile between a and b , with a value of the indicator greater than 1 indicating that a is on average more volatile than b over the last length period, while a value lower than 1 indicating that the security b is more on average volatile than a .
The indicator use the current symbol as a , while the second security b must be defined in the setting window (by default the S&P500). Risk and profitability are closely related to volatility, as larger price variations could potentially mean larger losses (but also larger gains), therefore a value of the indicator greater than 1 can indicate that it could be more risked (and profitable) to trade security a .
RNV using AMD (top) volatility against Intel (bottom) volatility.
RNV using EURUSD (top) volatility against USDJPY (bottom) volatility.
Larger values of length will make the indicator fluctuate less often around 1. You can also plot the logarithm of the ratio instead in order to have the indicator centered around 0, it will also help make values originally below 1 have more importance in the scale.
POSSIBLE ERRORS
If you compare different types of markets the indicator might return NaN values, this is because one market might be closed, for example if you compare AMD against BTCUSD with the indicator you will get NaN values. If you really need to compare two markets then increase your time frame, else use an histogram or area plot in order to have a cleaner plot.
CONCLUSION
An original indicator comparing the volatility between two securities has been presented. The choice of posting a volatility indicator has been made by my twitter followers, so if you want to decide which type of indicator i should do next make sure to check my twitter to see if there are polls available (i should do one after every posted indicator).
Multi Stoch + VWAP Heatmap + Histogram + ScalpingThis indicator was developed by referencing various indicators from many contributors. I apologize that I cannot identify all the original authors due to the numerous sources referenced. Thank you to everyone who contributed to the trading community.
Important Notice: Please use this indicator with sufficient caution and proper risk management. I do not assume any responsibility for any losses incurred from using this indicator. Trade at your own risk.
Alternative version:
Acknowledgment & Disclaimer:
This indicator incorporates ideas and concepts from numerous community indicators. I sincerely apologize for not being able to properly credit all the original creators due to the extensive references used. My heartfelt gratitude goes out to all the talented developers in the trading community.
Risk Warning: Please exercise extreme caution when using this indicator. All trading involves substantial risk of loss, and I accept no liability for any financial losses that may result from the use of this indicator. Always implement proper risk management and trade responsibly.
Multi Stoch + VWAP Heatmap + Histogram + Scalping Usage Guide
🔧 Basic Settings
Parameter Settings (Recommended for XAU/USD)
Fast Stoch Length: 5 # Ultra-short term trend
Medium Stoch Length: 14 # Short term trend
Slow Stoch Length: 21 # Medium term trend
%K Smoothing: 2 # High sensitivity setting
%D Smoothing: 2 # High sensitivity setting
Overbought Level: 75 # Sell zone
Oversold Level: 25 # Buy zone
📈 Reading the Chart
1. Histogram (Background Bar Chart)
Green tones: Strong uptrend
Red tones: Strong downtrend
Gray: Trendless/neutral
2. Line Display
Blue lines: Ultra-short term Stochastic (K1/D1)
Orange lines: Short term Stochastic (K2/D2)
Purple lines: Medium term Stochastic (K3/D3)
Yellow line: VWAP (normalized)
3. Horizontal Lines
Upper line (75): Sell zone
Center line (50): Neutral line
Lower line (25): Buy zone
🎯 Signal Types and Meanings
Scalping Signals (● marks)
Green ● (bottom): 📈 Scalp buy entry
RSI(7) < 25 + K1 < 30 combination
VWAP bounce targeting
Red ● (top): 📉 Scalp sell entry
RSI(7) > 75 + K1 > 70 combination
VWAP rejection targeting
Main Trend Signals
▲ (large, green): 💪 Strong buy signal - Multiple conditions aligned
▼ (large, red): 💪 Strong sell signal - Multiple conditions aligned
△ (medium, green): 📈 Normal buy signal
▽ (medium, orange): 📉 Normal sell signal
Warning/Reversal Signals
▼ (pink): ⚠️ Sell warning - Trend reversal caution
△ (teal): ⚠️ Buy warning - Trend reversal caution
Cross Signals (● marks, positioned up/down)
Green ● (bottom): Histogram crosses above VWAP
Red ● (top): Histogram crosses below VWAP
🚀 Practical Usage
Scalping Strategy (1-5 minute charts recommended)
Entry: Enter on green ● or red ● signals
Take Profit: At opposite zone or next ● signal
Stop Loss: Around 10-15 pips (for gold)
Time Session: London-NY overlap optimal
Swing Trading Strategy (15min-1hour charts)
Entry: Strong ▲▼ signals
Take Profit: Opposite warning signals (▼△)
Stop Loss: VWAP reverse break or 30-50 pips
Day Trading Strategy (5-15 minute charts)
Trend Confirmation: Histogram color
Entry: △▽ signals
Take Profit: Opposite zone reached
Stop Loss: 20-30 pips
⚡ XAU/USD Specific Usage
Session-Based Strategy
Tokyo Session (9-15 JST): Wait and see, small scalps
London Session (16-24 JST): Main trading
NY Session (22-6 JST): Most active, all signals valid
Major News Events
Pre-announcement: Reduce positions
Post-announcement: Trend following with ● signals
🔍 Filter Functions
ATR Filter
Small price movements filtered as noise
Signals only on significant price moves
Time Filter
Strong signals only during high volatility sessions
Weaker signals during low volatility periods
Consecutive Signal Prevention
Duplicate signals within 2 bars filtered out
Prevents noise trading
⚙️ Settings Customization
For Aggressive Trading
Signal Cooldown: 1 # More frequent signals
ATR Length: 5 # More sensitive filter
For Conservative Trading
Signal Cooldown: 5 # Relaxed signals
ATR Length: 20 # Stricter filter
Overbought: 80 # More extreme levels
Oversold: 20
📱 Recommended Alert Settings
Strong Buy/Sell Signal: Priority ★★★
Scalping Buy/Sell Signal: Priority ★★☆
Reverse Warning: Priority ★★★ (for position management)
⚠️ Important Notes
Scalping requires quick decision-making
Multiple timeframe confirmation recommended
Exercise caution during major news events
Risk management is top priority
This indicator is a versatile multi-functional tool suitable for short to medium-term trading strategies!
🎓 Trading Examples
Scalping Example
Wait for green ● at oversold level (below 30)
Enter long position immediately
Target: 50 level or red ● signal
Stop: Below recent swing low
Day Trading Example
Histogram turns green (bullish trend)
Wait for △ buy signal near support
Target: Overbought level (75)
Exit: Warning signal ▼ appears
Risk Management Rules
Never risk more than 2% per trade
Use proper position sizing
Set stops before entry
Take partial profits at key levels
This comprehensive guide will help you maximize the potential of this advanced multi-timeframe indicator!
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
TrendZonesTrendZones
This is an indicator which I use, have tested, tweaked and added features to for use in my trend following investing system. I got the idea for it when for some reason I was looking for a dynamic reference to measure the height of a channel or something. In search of this I made MA’s of the high and low borders of a Donchian channel which turned out to be two near parallel and stunningly smooth curves. This visual was so appealing that I immediately tried to turn it into a replacement for the KeltCOG which I previously used in my system. First I created a curve in the middle of the upper and lower curves, which I called COG (Center Of Gravity). Then I decided to enter only one lookback and let the script create a Donchian channel with half the lookback and use this to create the curves with an MA of whole lookback. For this reason the minimum lookback is set to 14, enough room for the Donchian Channel of 7 periods. This Donchian ChanneI has a special way of calculating the borders, involving a 5 period Median value. Thanks to this these borders are really a resistance and support level, which won’t change at a whim, e.g. when a ‘dead cat bounce’ occurs. I prevented the Donchian channel to show itself between the curves and only pop out from behind these. These pop outs now function as “strong trend zones”. I gave it colors (blue:-strong up, green: moderate up, orange: moderate down, red: strong down, near COG: gray, curves horizontal: gray) and it looked very appealing. I tested it in different time frames. In some weekend, when I was bored, I observed for a few hours the minute chart of bitcoin. It turned out that you can reliably tell that an uptrend ends when the candles go under the COG beginning a downtrend. Uptrend starts again once the candles go above COG. As Trends on minute charts only last around half an hour, this entertainment made the potential of this indicator very clear to me in just one afternoon.
Risk Management, Safe Level and Logical Stops.
In the inputs are settings for “Risk Tolerance”, and to activate “Show Logical Stop Level” (activated in example chart) and “Show Safe Level”. As a rule of thump a trade should not expose the invested capital to a risk of losing more than 2 percent. I divided my investment capital in ten equal parts which are allocated to ten different stocks or other instruments or kept liquid. This means that when a position is closed by triggering a Stop with a loss of 20 percent, the invested capital suffers only 2 percent (20% x 10% = 2%). This is why the value for “Risk Tolerance” has a default of 20. Because I put my Stops on the lower curve, a “Safe Level” can be calculated such that when you buy for a price below or at this level, the stop will protect the position sufficiently. Because I only buy when the instrument is in uptrend, the buying price should be between COG and Safe Level. Although I never do that, putting the stop at other curves is feasible and when you want to widen the stop (I never lower my stops btw) in a downtrend situation, even 1 ATR below the “Low Border”. I call these “Logical Stop Levels”, marked with dark green circles on the lower curve when safe buying by placing the Stoploss on this curve is possible, gray circles on the other curves, on the Upper Curve navy when price enters very profitable level. In a downtrend situation maroon circles appear.
Target lines
When I open a position I always set a Stoploss and a Target, for this purpose two types of Target values can be set and corresponding Target lines activated. These lines are drawn above the “High Border” at the set distance. If one expects some price to be used, differences will occur.
Other Features
Support Zone, this is 1 ATR below the “Low Border”, the maroon circles of the “Logal Stops” are placed on this “Support level”.
Stop distance and Channel Width. (activated in example chart) These are reported in a two cell table in the right lower corner of the main panel. I created this because I want to be able to check the volatility, whether the channel shows a situation in which safe buying in most levels of the channel is possible or what risk you take when you buy now and set the Stop at the nearest logical level (which is not always the “Lower curve”). This feature comes in handy for creating a setup I propose in the “Day Trading Fantasy” below.
Some General and User Settings. I never activate this, perhaps you will.
Use Of TrendZones In My System.
Create a list of stocks in uptrend. I define ‘stock in uptrend’ as in uptrend zone in all three monthly, weekly and daily charts, all three should at the same time be in uptrend. The advantage of TrendZones is that you can immediately see in which zone the candle moves.
Opening a position in a stock from the above list. I do this only when in both the daily and weekly the green dot on the lower curve indicates a buying opportunity. This is usually not the case in most of the items of the list, this feature thus provides a good timing for opening a position. Sometimes you need to wait a few weeks for this to happen.
Setting a target over a position. For this I use the Target percent line of the weekly chart with the default value of 10.
Updating the Stoploss and Target values. Every week or two weeks I set these to the new values of the “Lower Curve” and the Target line of the weekly. Attention: never shift down Stops, only up or let them stay the same when the curve moves down. I never use Stop levels on other curves.
I Check the charts whenever I like to do this. Close the position when the uptrend obviously shifts down. Otherwise I let the profits run until the Target triggers which closes the position with some profit.
For selecting stocks an checking charts for volume events, I also use a subpanel indicator called “TZanalyser”, which borrows the visual of my “Fibonacci Zone Oscillator”, is based on TrendZones and includes code from my REVE indicators. I intend to publish that as well.
Day Trading Fantasy.
Day trading is an attempt to earn a dime by opening a position in the morning and close it during the day again with a profit (or a loss). Before the market closes, you close all day trading positions.
In my fantasy the “Logical Stop Level” is repurposed for use as entry point and the ATR-based Target line is used to provide a target setting in an intraday chart, like e.g. 15 minute. To do this the “Safe Level” should be limited to between Channel width and COG. This can be done by showing “Safe Level” and “Channel Width” and then set “Risk Tolerance” to around the shown Channel Width. In this setting you can then wait for the green circle to show up for entering your trade and protect it with the stop.
I don’t know if this works fine or if it’s better than other day trade systems, because I don’t do day trading.
Take care and have fun.
Money Risk Management with Trade Tracking
Overview
The Money Risk Management with Trade Tracking indicator is a powerful tool designed for traders on TradingView to simplify trade simulation and risk management. Unlike the TradingView Strategy Tester, which can be complex for beginners, this indicator provides an intuitive, beginner-friendly interface to evaluate trading strategies in a realistic manner, mirroring real-world trading conditions.
Built on the foundation of open-source contributions from LuxAlgo and TCP, this indicator integrates external indicator signals, overlays take-profit (TP) and stop-loss (SL) levels, and provides detailed money management analytics. It empowers traders to visualize potential profits, losses, and risk-reward ratios, making it easier to understand the financial outcomes of their strategies.
Key Features
Signal Integration: Seamlessly integrates with external long and short signals from other indicators, allowing traders to overlay TP/SL levels based on their preferred strategies.
Realistic Trade Simulation: Simulates trades as they would occur in real-world scenarios, accounting for initial capital, risk percentage, leverage, and compounding effects.
Money Management Dashboard: Displays critical metrics such as current capital, unrealized P&L, risk amount, potential profit, risk-reward ratio, and trade status in a customizable, beginner-friendly table.
TP/SL Visualization: Plots TP and SL levels on the chart with customizable styles (solid, dashed, dotted) and colors, along with optional labels for clarity.
Performance Tracking: Tracks total trades, win/loss counts, win rate, and profit factor, providing a clear overview of strategy performance.
Liquidation Risk Alerts: Warns traders if stop-loss levels risk liquidation based on leverage settings, enhancing risk awareness.
Benefits for Traders
Beginner-Friendly: Simplifies the complexities of the TradingView Strategy Tester, offering an intuitive interface for new traders to simulate and evaluate trades without confusion.
Real-World Insights: Helps traders understand the actual profit or loss potential of their strategies by factoring in capital, risk, and leverage, bridging the gap between theoretical backtesting and real-world execution.
Enhanced Decision-Making: Provides clear, real-time analytics on risk-reward ratios, unrealized P&L, and trade performance, enabling informed trading decisions.
Customizable and Flexible: Allows customization of TP/SL settings, table positions, colors, and sizes, catering to individual trader preferences.
Risk Management Focus: Encourages disciplined trading by highlighting risk amounts, potential profits, and liquidation risks, fostering better financial planning.
Why This Indicator Stands Out
Many traders struggle to translate backtested strategy results into real-world outcomes due to the abstract nature of percentage-based profitability metrics. This indicator addresses that challenge by providing a practical, user-friendly tool that simulates trades with real-world parameters like capital, leverage, and compounding. Its open-source nature ensures accessibility, while its integration with other indicators makes it versatile for various trading styles.
How to Use
Add to TradingView: Copy the Pine Script code into TradingView’s Pine Editor and add it to your chart.
Configure Inputs: Set your initial capital, risk percentage, leverage, and TP/SL values in the indicator settings. Select external long/short signal sources if integrating with other indicators.
Monitor Dashboards: Use the Money Management and Target Dashboard tables to track trade performance and risk metrics in real time.
Analyze Results: Review win rates, profit factors, and P&L to refine your trading strategy.
Credits
This indicator builds upon the open-source contributions of LuxAlgo and TCP , whose efforts in sharing their code have made this tool possible. Their dedication to the trading community is deeply appreciated.
Dual MACD Strategy [Js.k]Strategy Overview
The Dual MACD Strategy leverages two MACD indicators with different parameters to generate buy and sell signals. By combining the trend-following properties of MACD with specific entry/exit criteria, this strategy aims to capture significant price movements while effectively managing risk.
Entry and Exit Conditions
Long Entry: A buy signal is triggered when:
The histogram of MACD1 crosses above zero.
The histogram of MACD2 is positive and rising.
Short Entry: A sell signal is triggered when:
The histogram of MACD1 crosses below zero.
The histogram of MACD2 is negative and declining.
Risk Management
Stop Loss and Take Profit:
Stop Loss is set at 1% below the entry price for long positions and 1% above the entry price for short positions.
Take Profit is set at 1.5% above the entry price for long positions and 1.5% below the entry price for short positions.
Position Sizing: Each trade risks a maximum of 10% of account equity, keeping potential losses manageable and in line with standard trading practices.
Backtesting Results
The strategy is tested on BTCUSDT with a time frame of 1 hour, resulting in 200+ trades.
The initial capital for backtesting is set to $10,000, with a realistic commission of 0.04% and a slippage of 2 ticks.
Conclusion
This strategy is inspired by Dreadblitz's Double MACD Buy and Sell, as well as some YouTube videos. My purpose in redeveloping them into this strategy is to validate the practicality of the Double MACD. After multiple modifications, this is the final version. I believe its profitability is limited and may lead to losses; please do not use this strategy for live trading.
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
Canuck Trading IndicatorOverview
The Canuck Trading Indicator is a versatile, overlay-based technical analysis tool designed to assist traders in identifying potential trading opportunities across various timeframes and market conditions. By combining multiple technical indicators—such as RSI, Bollinger Bands, EMAs, VWAP, MACD, Stochastic RSI, ADX, HMA, and candlestick patterns—the indicator provides clear visual signals for bullish and bearish entries, breakouts, long-term trends, and options strategies like cash-secured puts, straddles/strangles, iron condors, and short squeezes. It also incorporates 20-day and 200-day SMAs to detect Golden/Death Crosses and price positioning relative to these moving averages. A dynamic table displays key metrics, and customizable alerts help traders stay informed of market conditions.
Key Features
Multi-Timeframe Adaptability: Automatically adjusts parameters (e.g., ATR multiplier, ADX period, HMA length) based on the chart's timeframe (minute, hourly, daily, weekly, monthly) for optimal performance.
Comprehensive Signal Generation: Identifies short-term entries, breakouts, long-term bullish trends, and options strategies using a combination of momentum, trend, volatility, and candlestick patterns.
Candlestick Pattern Detection: Recognizes bullish/bearish engulfing, hammer, shooting star, doji, and strong candles for precise entry/exit signals.
Moving Average Analysis: Plots 20-day and 200-day SMAs, detects Golden/Death Crosses, and evaluates price position relative to these averages.
Dynamic Table: Displays real-time metrics, including zone status (bullish, bearish, neutral), RSI, MACD, Stochastic RSI, short/long-term trends, candlestick patterns, ADX, ROC, VWAP slope, and MA positioning.
Customizable Alerts: Over 20 alert conditions for entries, exits, overbought/oversold warnings, and MA crosses, with actionable messages including ticker, price, and suggested strategies.
Visual Clarity: Uses distinct shapes, colors, and sizes to plot signals (e.g., green triangles for bullish entries, red triangles for bearish entries) and overlays key levels like EMA, VWAP, Bollinger Bands, support/resistance, and HMA.
Options Strategy Signals: Suggests opportunities for selling cash-secured puts, straddles/strangles, iron condors, and capitalizing on short squeezes.
How to Use
Add to Chart: Apply the indicator to any TradingView chart by selecting "Canuck Trading Indicator" from the Pine Script library.
Interpret Signals:
Bullish Signals: Green triangles (short-term entry), lime diamonds (breakout), blue circles (long-term entry).
Bearish Signals: Red triangles (short-term entry), maroon diamonds (breakout).
Options Strategies: Purple squares (cash-secured puts), yellow circles (straddles/strangles), orange crosses (iron condors), white arrows (short squeezes).
Exits: X-cross shapes in corresponding colors indicate exit signals.
Monitor: Gray circles suggest holding cash or monitoring for setups.
Review Table: Check the top-right table for real-time metrics, including zone status, RSI, MACD, trends, and MA positioning.
Set Alerts: Configure alerts for specific signals (e.g., "Short-Term Bullish Entry" or "Golden Cross") to receive notifications via TradingView.
Adjust Inputs: Customize input parameters (e.g., RSI period, EMA length, ATR period) to suit your trading style or market conditions.
Input Parameters
The indicator offers a wide range of customizable inputs to fine-tune its behavior:
RSI Period (default: 14): Length for RSI calculation.
RSI Bullish Low/High (default: 35/70): RSI thresholds for bullish signals.
RSI Bearish High (default: 65): RSI threshold for bearish signals.
EMA Period (default: 15): Main EMA length (15 for day trading, 50 for swing).
Short/Long EMA Length (default: 3/20): For momentum oscillator.
T3 Smoothing Length (default: 5): Smooths momentum signals.
Long-Term EMA/RSI Length (default: 20/15): For long-term trend analysis.
Support/Resistance Lookback (default: 5): Periods for support/resistance levels.
MACD Fast/Slow/Signal (default: 12/26/9): MACD parameters.
Bollinger Bands Period/StdDev (default: 15/2): BB settings.
Stochastic RSI Period/Smoothing (default: 14/3/3): Stochastic RSI settings.
Uptrend/Short-Term/Long-Term Lookback (default: 2/2/5): Candles for trend detection.
ATR Period (default: 14): For volatility and price targets.
VWAP Sensitivity (default: 0.1%): Threshold for VWAP-based signals.
Volume Oscillator Period (default: 14): For volume surge detection.
Pattern Detection Threshold (default: 0.3%): Sensitivity for candlestick patterns.
ROC Period (default: 3): Rate of change for momentum.
VWAP Slope Period (default: 5): For VWAP trend analysis.
TradingView Publishing Compliance
Originality: The Canuck Trading Indicator is an original script, combining multiple technical indicators and custom logic to provide unique trading signals. It does not replicate existing public scripts.
No Guaranteed Profits: This indicator is a tool for technical analysis and does not guarantee profits. Trading involves risks, and users should conduct their own research and risk management.
Clear Instructions: The description and usage guide are detailed and accessible, ensuring users understand how to apply the indicator effectively.
No External Dependencies: The script uses only built-in Pine Script functions (e.g., ta.rsi, ta.ema, ta.vwap) and requires no external libraries or data sources.
Performance: The script is optimized for performance, using efficient calculations and adaptive parameters to minimize lag on various timeframes.
Visual Clarity: Signals are plotted with distinct shapes and colors, and the table provides a concise summary of market conditions, enhancing usability.
Limitations and Risks
Market Conditions: The indicator may generate false signals in choppy or low-liquidity markets. Always confirm signals with additional analysis.
Timeframe Sensitivity: Performance varies by timeframe; test settings on your preferred chart (e.g., 5-minute for day trading, daily for swing trading).
Risk Management: Use stop-losses and position sizing to manage risk, as suggested in alert messages (e.g., "Stop -20%").
Options Trading: Options strategies (e.g., straddles, iron condors) carry unique risks; consult a financial advisor before trading.
Feedback and Support
For questions, suggestions, or bug reports, please leave a comment on the TradingView script page or contact the author via TradingView. Your feedback helps improve the indicator for the community.
Disclaimer
The Canuck Trading Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
SuperTrade ST1 StrategyOverview
The SuperTrade ST1 Strategy is a long-only trend-following strategy that combines a Supertrend indicator with a 200-period EMA filter to isolate high-probability bullish trade setups. It is designed to operate in trending markets, using volatility-based exits with a strict 1:4 Risk-to-Reward (R:R) ratio, meaning that each trade targets a profit 4× the size of its predefined risk.
This strategy is ideal for traders looking to align with medium- to long-term trends, while maintaining disciplined risk control and minimal trade frequency.
How It Works
This strategy leverages three key components:
Supertrend Indicator
A trend-following indicator based on Average True Range (ATR).
Identifies bullish/bearish trend direction by plotting a trailing stop line that moves with price volatility.
200-period Exponential Moving Average (EMA) Filter
Trades are only taken when the price is above the EMA, ensuring participation only during confirmed uptrends.
Helps filter out counter-trend entries during market pullbacks or ranges.
ATR-Based Stop Loss and Take Profit
Each trade uses the ATR to calculate volatility-adjusted exit levels.
Stop Loss: 1× ATR below entry.
Take Profit: 4× ATR above entry (1:4 R:R).
This asymmetry ensures that even with a lower win rate, the strategy can remain profitable.
Entry Conditions
A long trade is triggered when:
Supertrend flips from bearish to bullish (trend reversal).
Price closes above the Supertrend line.
Price is above the 200 EMA (bullish market bias).
Exit Logic
Once a long position is entered:
Stop loss is set 1 ATR below entry.
Take profit is set 4 ATR above entry.
The strategy automatically exits the position on either target.
Backtest Settings
This strategy is configured for realistic backtesting, including:
$10,000 account size
2% equity risk per trade
0.1% commission
1 tick slippage
These settings aim to simulate real-world conditions and avoid overly optimistic results.
How to Use
Apply the script to any timeframe, though higher timeframes (1H, 4H, Daily) often yield more reliable signals.
Works best in clearly trending markets (especially in crypto, stocks, indices).
Can be paired with alerts for live trading or analysis.
Important Notes
This version is long-only by design. No short positions are executed.
Ideal for swing traders or position traders seeking asymmetric returns.
Users can modify the ATR period, Supertrend factor, or EMA filter length based on asset behavior.
Key Financial index**Basic Indicators** (updates may be delayed by a few weeks after dividend distribution):
1. **P/E Ratio**: *Price-to-Earnings*. This ratio shows the price investors are willing to pay for each unit of profit the company generates.
- A P/E below 8 is considered good, meaning the company yields a 12.5% annual profit, which implies a payback period of 8 years.
2. **P/B Ratio**: *Price-to-Book Ratio*. This is used to compare a company's market value with its book value.
- A low P/B (usually below 1): May indicate that the stock is undervalued compared to the company’s net asset value. This can be a good investment opportunity but may also signal financial trouble.
- A high P/B (usually above 3): May suggest the stock is overvalued relative to the company’s net assets. This could reflect high growth expectations or potential overvaluation.
3. **D/E Ratio**: *Debt-to-Equity Ratio* is a financial metric that measures a company’s financial leverage.
D/E Ratio = Total Liabilities / Shareholders' Equity.
It compares the total liabilities of a company to its equity to indicate how much debt is used to finance its assets compared to shareholder investments.
- D/E Ratio below 1: Generally considered safe.
- D/E Ratio between 1 and 2: May be acceptable depending on the industry.
- D/E Ratio above 2: May indicate high financial risk.
4. **CR Ratio**: *Current Ratio*, an important liquidity metric used to assess a company’s ability to pay off short-term liabilities using its short-term assets.
- CR Ratio > 1: Indicates the company has enough current assets to pay off its short-term debts. The higher the ratio, the better the liquidity position.
- CR Ratio < 1: Suggests the company may face difficulties in meeting short-term obligations. This can be a red flag for financial stability.
5. **Profit Margin**: A key financial indicator that measures a company’s profitability relative to its revenue. It shows what percentage of revenue remains after all related costs are deducted.
**General significance of Profit Margin**:
- **Operational Efficiency**: A high profit margin indicates efficient cost management and the ability to generate strong profits from revenue.
- **Industry Comparison**: Comparing a company’s profit margin with its industry peers helps assess its competitive position and relative performance.
**Note**:
- There is no single “good” margin across all industries. Each industry has different cost structures and competition levels, leading to varying average margins.
- When analyzing profit margins, one must consider the industry context, the company’s business model, and market trends.
6. **Growth Expectation ↑**: This refers to the expected profit growth. The percentage figure reflects how much growth the market expects the company to achieve in the next financial report based on the current stock price.
- The lower the expected growth rate (typically below 15%), the safer the current price is considered.
- A high expected growth rate may indicate that the market anticipates a profit breakthrough or that the stock is trading above its intrinsic value relative to actual earnings.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
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Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
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Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
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Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
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Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
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Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
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Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
Supertrend + MACD CrossoverKey Elements of the Template:
Supertrend Settings:
supertrendFactor: Adjustable to control the sensitivity of the Supertrend.
supertrendATRLength: ATR length used for Supertrend calculation.
MACD Settings:
macdFastLength, macdSlowLength, macdSignalSmoothing: These settings allow you to fine-tune the MACD for better results.
Risk Management:
Stop-Loss: The stop-loss is based on the ATR (Average True Range), a volatility-based indicator.
Take-Profit: The take-profit is based on the risk-reward ratio (set to 3x by default).
Both stop-loss and take-profit are dynamic, based on ATR, which adjusts according to market volatility.
Buy and Sell Signals:
Buy Signal: Supertrend is bullish, and MACD line crosses above the Signal line.
Sell Signal: Supertrend is bearish, and MACD line crosses below the Signal line.
Visual Elements:
The Supertrend line is plotted in green (bullish) and red (bearish).
Buy and Sell signals are shown with green and red triangles on the chart.
Next Steps for Optimization:
Backtesting:
Run backtests on BTC in the 5-minute timeframe and adjust parameters (Supertrend factor, MACD settings, risk-reward ratio) to find the optimal configuration for the 60% win ratio.
Fine-Tuning Parameters:
Adjust supertrendFactor and macdFastLength to find more optimal values based on BTC's market behavior.
Tweak the risk-reward ratio to maximize profitability while maintaining a good win ratio.
Evaluate Market Conditions:
The performance of the strategy can vary based on market volatility. It may be helpful to evaluate performance in different market conditions or pair it with a filter like RSI or volume.
Let me know if you'd like further tweaks or explanations!
Sniper Trade Pro (ES 15-Min) - Topstep Optimized🔹 Overview
Sniper Trade Pro is an advanced algorithmic trading strategy designed specifically for E-mini S&P 500 (ES) Futures on the 15-minute timeframe. This strategy is optimized for Topstep 50K evaluations, incorporating strict risk management to comply with their max $1,000 daily loss limit while maintaining a high probability of success.
It uses a multi-confirmation approach, integrating:
✅ Money Flow Divergence (MFD) → To track liquidity imbalances and institutional accumulation/distribution.
✅ Trend Confirmation (EMA + VWAP) → To identify strong trend direction and avoid choppy markets.
✅ ADX Strength Filter → To ensure entries only occur in trending conditions, avoiding weak setups.
✅ Break-Even & Dynamic Stop-Losses → To reduce drawdowns and protect profits dynamically.
This script automatically generates Buy and Sell signals and provides built-in risk management for automated trading execution through TradingView Webhooks.
🔹 How Does This Strategy Work?
📌 1. Trend Confirmation (EMA + VWAP)
The strategy uses:
✔ 9-EMA & 21-EMA: Fast-moving averages to detect short-term momentum.
✔ VWAP (Volume-Weighted Average Price): Ensures trades align with institutional volume flow.
How it works:
Bullish Condition: 9-EMA above 21-EMA AND price above VWAP → Confirms buy trend.
Bearish Condition: 9-EMA below 21-EMA AND price below VWAP → Confirms sell trend.
📌 2. Liquidity & Money Flow Divergence (MFD)
This indicator measures liquidity shifts by tracking momentum changes in price and volume.
✔ MFD Calculation:
Uses Exponential Moving Average (EMA) of Momentum (MOM) to detect changes in buying/selling pressure.
If MFD is above its moving average, it signals liquidity inflows → bullish strength.
If MFD is below its moving average, it signals liquidity outflows → bearish weakness.
Why is this important?
Detects when Smart Money is accumulating or distributing before major moves.
Filters out false breakouts by confirming momentum strength before entry.
📌 3. Trade Entry Triggers (Candlestick Patterns & ADX Filter)
To avoid random entries, the strategy waits for specific candlestick confirmations with ADX trend strength:
✔ Bullish Entry (Buy Signal) → Requires:
Bullish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD above its moving average (Liquidity inflows)
9-EMA > 21-EMA & price above VWAP (Trend confirmation)
✔ Bearish Entry (Sell Signal) → Requires:
Bearish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD below its moving average (Liquidity outflows)
9-EMA < 21-EMA & price below VWAP (Trend confirmation)
📌 4. Risk Management & Profit Protection
This strategy is built with strict risk management to maintain low drawdowns and maximize profits:
✔ Dynamic Position Sizing → Automatically adjusts trade size to risk a fixed $400 per trade.
✔ Adaptive Stop-Losses → Uses ATR-based stop-loss (0.8x ATR) to adapt to market volatility.
✔ Take-Profit Targets → Fixed at 2x ATR for a Risk:Reward ratio of 2:1.
✔ Break-Even Protection → Moves stop-loss to entry once price moves 1x ATR in profit, locking in gains.
✔ Max Daily Loss Limit (-$1,000) → Stops trading if total losses exceed $1,000, complying with Topstep rules.
[3Commas] Turtle StrategyTurtle Strategy
🔷 What it does: This indicator implements a modernized version of the Turtle Trading Strategy, designed for trend-following and automated trading with webhook integration. It identifies breakout opportunities using Donchian channels, providing entry and exit signals.
Channel 1: Detects short-term breakouts using the highest highs and lowest lows over a set period (default 20).
Channel 2: Acts as a confirmation filter by applying an offset to the same period, reducing false signals.
Exit Channel: Functions as a dynamic stop-loss (wait for candle close), adjusting based on market structure (default 10 periods).
Additionally, traders can enable a fixed Take Profit level, ensuring a systematic approach to profit-taking.
🔷 Who is it for:
Trend Traders: Those looking to capture long-term market moves.
Bot Users: Traders seeking to automate entries and exits with bot integration.
Rule-Based Traders: Operators who prefer a structured, systematic trading approach.
🔷 How does it work: The strategy generates buy and sell signals using a dual-channel confirmation system.
Long Entry: A buy signal is generated when the close price crosses above the previous high of Channel 1 and is confirmed by Channel 2.
Short Entry: A sell signal occurs when the close price falls below the previous low of Channel 1, with confirmation from Channel 2.
Exit Management: The Exit Channel acts as a trailing stop, dynamically adjusting to price movements. To exit the trade, wait for a full bar close.
Optional Take Profit (%): Closes trades at a predefined %.
🔷 Why it’s unique:
Modern Adaptation: Updates the classic Turtle Trading Strategy, with the possibility of using a second channel with an offset to filter the signals.
Dynamic Risk Management: Utilizes a trailing Exit Channel to help protect gains as trades move favorably.
Bot Integration: Automates trade execution through direct JSON signal communication with your DCA Bots.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Best suited for trending markets; higher timeframes (e.g., H4, D1) are recommended to minimize noise.
Sideways Markets: In choppy conditions, breakouts may lead to false signals—consider using additional filters.
Backtesting & Demo Testing: It is crucial to thoroughly backtest the strategy and run it on a demo account before risking real capital.
Parameter Adjustments: Ensure that commissions, slippage, and position sizes are set accurately to reflect real trading conditions.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:ETHUSDT (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.
Period Channel 1: 20.
Period Channel 2: 20.
Period Channel 2 Offset: 20.
Period Exit: 10.
Take Profit %: Disable.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +516.87 USDT (+5.17%).
Max Drawdown: -100.28 USDT (-0.95%).
Total Closed Trades: 281.
Percent Profitable: 40.21%.
Profit Factor: 1.704.
Average Trade: +1.84 USDT (+1.80%).
Average # Bars in Trades: 29.
🔷 How to Use It:
🔸 Adjust Settings:
Select your asset and timeframe suited for trend trading.
Adjust the periods for Channel 1, Channel 2, and the Exit Channel to align with the asset’s historical behavior. You can visualize these channels by going to the Style tab and enabling them.
For example, if you set Channel 2 to 40 with an offset of 40, signals will take longer to appear but will aim for a more defined trend.
Experiment with different values, a possible exit configuration is using 20 as well. Compare the results and adjust accordingly.
Enable the Take Profit (%) option if needed.
🔸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 the option to receive long or short signals (Entry | TP | SL), copy and paste 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
Period Channel 1: Period of highs and lows to trigger signals
Period Channel 2: Period of highs and lows to filter signals
Offset: Move Channel 2 to the right x bars to try to filter out the favorable signals.
Period Exit: It is the period of the Donchian channel that is used as trailing for the exits.
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
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: Check Messages: Enable this option to review the messages that will 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.
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.
SuperTrend AI Oscillator StrategySuperTrend AI Oscillator Strategy
Overview
This strategy is a trend-following approach that combines the SuperTrend indicator with oscillator-based filtering.
By identifying market trends while utilizing oscillator-based momentum analysis, it aims to improve entry precision.
Additionally, it incorporates a trailing stop to strengthen risk management while maximizing profits.
This strategy can be applied to various markets, including Forex, Crypto, and Stocks, as well as different timeframes. However, its effectiveness varies depending on market conditions, so thorough testing is required.
Features
1️⃣ Trend Identification Using SuperTrend
The SuperTrend indicator (a volatility-adjusted trend indicator based on ATR) is used to determine trend direction.
A long entry is considered when SuperTrend turns bullish.
A short entry is considered when SuperTrend turns bearish.
The goal is to capture clear trend reversals and avoid unnecessary trades in ranging markets.
2️⃣ Entry Filtering with an Oscillator
The Super Oscillator is used to filter entry signals.
If the oscillator exceeds 50, it strengthens long entries (indicating strong bullish momentum).
If the oscillator drops below 50, it strengthens short entries (indicating strong bearish momentum).
This filter helps reduce trades in uncertain market conditions and improves entry accuracy.
3️⃣ Risk Management with a Trailing Stop
Instead of a fixed stop loss, a SuperTrend-based trailing stop is implemented.
The stop level adjusts automatically based on market volatility.
This allows profits to run while managing downside risk effectively.
4️⃣ Adjustable Risk-Reward Ratio
The default risk-reward ratio is set at 1:2.
Example: A 1% stop loss corresponds to a 2% take profit target.
The ratio can be customized according to the trader’s risk tolerance.
5️⃣ Clear Trade Signals & Visual Support
Green "BUY" labels indicate long entry signals.
Red "SELL" labels indicate short entry signals.
The Super Oscillator is plotted in a separate subwindow to visually assess trend strength.
A real-time trailing stop is displayed to support exit strategies.
These visual aids make it easier to identify entry and exit points.
Trading Parameters & Considerations
Initial Account Balance: Default is $7,000 (adjustable).
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 1,032
Visual Aids for Clarity
This strategy includes clear visual trade signals to enhance decision-making:
Green "BUY" labels for long entries
Red "SELL" labels for short entries
Super Oscillator plotted in a subwindow with a 50 midline
Dynamic trailing stop displayed for real-time trend tracking
These visual aids allow traders to quickly identify trade setups and manage positions with greater confidence.
Summary
The SuperTrend AI Oscillator Strategy is developed based on indicators from Black Cat and LuxAlgo.
By integrating high-precision trend analysis with AI-based oscillator filtering, it provides a strong risk-managed trading approach.
Important Notes
This strategy does not guarantee profits—performance varies based on market conditions.
Past performance does not guarantee future results. Markets are constantly changing.
Always test extensively with backtesting and demo trading before using it in live markets.
Risk management, position sizing, and market conditions should always be considered when trading.
Conclusion
This strategy combines trend analysis with momentum filtering, enhancing risk management in trading.
By following market trends carefully, making precise entries, and using trailing stops, it seeks to reduce risk while maximizing potential profits.
Before using this strategy, be sure to test it thoroughly via backtesting and demo trading, and adjust the settings to match your trading style.
