Swing Trader-Pro V2The strategy- what is it?
This indicator is designed from a theory created by myself in order to distinguish a correction from an impulse. This comes down to the ability to compare "x" range of candles to "y" range of candles and highlight key differences to then correctly portray that the most recent move in price will be (or is) a correction.
Following this theory, we all understand that corrections don't go with the trend right? So this means at some point, there is a high probability of a rejection somewhere in this most recent move, that will ultimately push price higher or lower as it continues back with the trend. Therefore, through extensive quantitative research and back-testing, we are able to highlight areas of high-probability rejections within these supposed corrections.
How does it work?
Firstly, we need to establish a high and low point (using pivots ) that help us decide what the state is of the recent move between the high and low (we call this "point A" and "point B"). So we can only consider whether the recent move in price was an impulse or a correction until the move from "point B" to "point C" is made. But before that, once we have identified "Point A" and "point B", we use 2 (supposedly) strong levels which help integrate a box onscreen and thus, indicate this area of high liquidity. This box will continue to adjust according to the change of pivots (if price keeps creating HH's & HL's or LH's & LL's depending on market trend). But if we establish a strong high and low and price stays within this range, then the box will remain in place.
The default color of the box is red; the only time the color of the box will change is when:
- Price retraces from the high/low back to the box (price has to touch the box)
AND
-If any of our confirmations indicate a successful correction based on our theory.
So the box color varies:
- Red = very weak (or) no entry = no confirmations were made
- Yellow = weak entry = some but not all confirmations were made
- Green = strong entry = all confirmations have indicated that the move from "point B" to "point C" (remember that "point C" is where the box is) is a correction when compared with the move from "point A" to "point B"
These confirmations are all validated on the same candle during live candle activity (not when the candle has closed on the box). As this happens, the confirmations will determine the state of entry quality as soon as price touches the box.
In this time, we will see a new orange label highlighting what indicators have confirmed a successful correction and what haven't.
The label shows the different confirmation indicators in which we have provided different names (as this is the secret we intend to keep). So we have:
- "CC"
- "B1/B2"
- "B3"
Usually, we will see either an "OK" or "NOT OK" next to each confirmation indicator. This just tells us whether they have confirmed or not. Please note that this "point C" label does not stay permanently, regardless of the state of entry quality. The label will in fact stay on the screen until the next box has been generated, which is usually a few candles after the entry has been triggered.
Entries, SL's and TP's
This indicator shows the user an area of high-probability rejection. So in terms of specifying a precise entry, you're completely free to enter on the following:
- the moment price touches the box (depending on what color it is of course)
- the other end of the box (if you would like to catch a "sniper entry")
- or if price pierces the entire box and is still green, you can wait to see if price comes back through the box (which indicates a false breakout).
As for Stop-losses, i would recommend:
- Long entries: set your SL at the recent low (this should be "point A")
- Short entries: set your SL to the recent high (this should be "point A" as well, because if you're switching from the "long entry" setting to the "short entry" setting, the indicator labels flip around and are the opposite of what they are for long entries).
For Take profits, this is entirely up to the user. Because some entries will allow you to have great RR ratios depending on how you manage the active trades. Some recommendations below:
- Set TP to "point B" pivot
- Use trailing stop function or something similar if available
- Add other indicators such as the RSI and close when price reaches key levels
- When price shows signs of exhaustion or early stages of reversal then just close
Additional information and recommendations
- This works on any time frame and on any financial market, whether you prefer Forex, stocks, crypto, commodities , etc.
- In regards to trade direction, you can change in the settings to look for either long or short positions in the market. I would recommend using it in favor of the overall trend of the markets because you will find a lot better entries. Although, this does work against the trend at times as well. Additionally, this tool also works in consolidating markets which is beneficial.
- After becoming used to the script, i would say to apply it twice to your screen and have one looking for Long entries and the other looking for Short entries.
- As the user, you have the ability to remove the labels in the parameter settings (because it does look quite messy onscreen, especially if you have both long and short entries on at the same time). I would only personally show the labels when price hits the current box to see what confirmations have been identified.
- I will also provide the best parameters to use. You will only need one set of parameters for each long and short setting, as these parameters are universal for any time frame and any financial market.
FIRST UPDATE
After extensive back testing using our first version, we found that in fact, there are some great opportunities being wasted as the entry box stays red. This is due to some series of market structure that don't always fit our theory of continuations within the market. We found that although our theory is accurate, the amount of times the market fits this is more rare than times when price follows sequences. When we look for sequences in the market instead of specifying differences between impulses and corrections, we actually see areas of serious repetitiveness, thanks to how our indicator initially generates. Not how it confirms. So, understanding this new theory through one component of our previous indicator, we are still able to keep boxes at the same area yet accurately confirm more profitable entries external to our full previous strategy.
Moving towards the practical side of things:
-Make sure "add extra confirmation" parameter is selected, as this will allow the indicator to search for more valid entries rather than just our normal confirmations. (this is a tick box).
- Default parameters are already set for both C1 and C2
In a simple sense, this update is added to find more confirmations to turn more red boxes into green boxes based on other theories outside of our original one. How we do this exactly is part of the mystery.
SECOND UPDATE
- Fibonacci based moving average: using elements of the Fibonacci sequence and its relevance to being a hot-spot in price activity, we have integrated this into a moving average which is stronger than your usual MA. Here, you will notice it showing stronger signs of rejecting price, especially when trending. Hence, this is extremely useful to implement into your strategy as part of the trend identification. When price is consolidating, depending on how volatile or close-in the waves are during these periods, the FMA is similar to your typical MA, so therefore not so good. But the overall intention of this is to enhance your conclusion to whether price is trending and whether price is bullish or bearish.
- This is now a strategy, not just an indicator: So now we can choose from a huge variety of parameters in accordance to what ones work best with what pair, or time frame. The typical parameters to change would be the entry points, stop losses and take profits. We have also added in a "SL to entry" option. ALL PARAMETERS ARE FIBONACCI LEVELS AS THIS MAKES IT UNIVERSAL TO ANY PAIR/ TIME FRAME.
- Move the entry boxes : So this is very useful for certain pairs and mainly to help the user understand key sequences on a quantitative level. Sometimes we can notice that pairs spike higher than the typical entry (0.618) so we have allowed flexibility to the point where you can alter the box appearance to either the 0.618 level (default), 0.786 and the 0.9 level.
- Back-testing: Now the user can back-test the strategy and see the performance within any financial market you add this to! Please note that according to the strategy, once a trade is placed, it wont enter any more trades when the current one is still active. I have requested to change this, but it is out of our development team's reach. However, this doesn't discredit what the system can help you achieve, as you will still be able to find profitable parameters within the financial markets.
Strategy default properties
Backtest start: this date is when you would like to start the backtest, however, the indicator will go as far as the data can be read
Backtest end: choose your date to end the back test.
Trade session: choose the trading session you want this strategy to work on.
Filter by session: you can filter the backtested results depending on whether you want the strategy to take trades within the chosen trading session.
Filter by Fibonacci moving average: select this if you would like for the back tested results to consider whether the valid trade setups are in accordance to what the FMA displays (Bullish or Bearish). This is deselected.
Fibonacci Moving Average Timeframe: here you can select what timeframe you would like the FMA to work on, default is the “same as chart” button/ option.
TraderDirection: choose whether you would like LONG or SHORT entries for the indicator to find.
Max risk per trade: choose the risk setting per trade, i would suggest lowering this to 1% ((MODERATOR) This is the default setting!)
EntryFib: choose between the options as to where you would like the strategy to enter positions, the default is the 0.618 zone which is the closest side of the box to price. You will also see that when you choose to change this, the boxes on your screen will move accordingly. A very helpful function!
StopFib: choose your Stop Loss based on the same Fibonacci level as what you choose for your entry, remember that the higher the fib level, the higher (or safer) your Stop Loss is from price spiking. It all comes down to preference.
TakeProfitFib: choose your Take Profit based on the same Fibonacci level as what you choose for your entry, remember that the lower the fib level, the higher your Take Profit is again, It all comes down to preference.
BreakevenFib: the default setting is on “disabled” however when you select a certain Fibonacci level, once price reaches there during the active trade, your Stop Loss will be set to entry, this function is designed to stop volatile price fluctuations rendering your in-profit trade result to hitting your Stop Loss and losing when it closes out.
Cerca negli script per "stop loss"
TradePro's Trading Idea Cipher Divergence EMA Pb StrategyHere I present you on of Trade Pro's Trading Idea: Cipher B+ Divergence EMA Pullback Strategy.
Optimized the crypto pairBTC/USDT in the 30 minute chart.
There is the possibility to switch between short and long positions.
You can choose between 2 different take profit/stop loss types: The Lowest Low/ Highest High Stop Loss/ Take Profit and the ATR Take Profit/ Stop Loss.
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How does the strategy work?
ENTRY
Long
The price must be above the 200 EMA .
The price needs to make a pullback into the 50 EMA .
Right after that, the Cipher B indicator must give a buy signal, it must be below the zero line and the Money Flow cloud must be green.
Short
Contrary to the premise of long positions.
EXIT
Lowest Low/ Highest High Exit
The Lowest Low (long) / highest high (short) serves as the stop loss. The TP is formed on the basis of a factor.
(Long for example: *Lowest Low* multiplied by *Profitfactor* = TP).
ATR Exit
The value of ATR at the time of buying is multiplied by the value entered in "Profit factor ATR" and "Stop factor ATR". As soon as the price reaches this value, it is closed.
Important
The script must be optimized for each coin or currency pair. However, only the values for the profit factor, the stop loss and Lowest Low / Highest High are relevant.
Also, by changing the Chanel Length and the Chanel Average, you can create strong profit changes.
The results of the strategy are without commissions and leverage.
If you have any questions or feedback, please let me know in the comments.
If you need more information about the strategy and want to know exactly how to apply it, check out my profile. There I have created a tutorial for the function of the script.
SIDD-Master-Moving-AverageSIDD-Master-Moving-Average is based on RSI average calculation Moving average plotted on chart.
This Moving Average is giving 2 signals Bullish and Bearish .
Whenever Bullish signals is coming price is doing crossover with moving average on upside and this indicate price will go up from current market price.
Whenever Bearish signals is coming price is doing cross-under with moving average on downside and this indicate price will go down from current market price.
Moving average color is changing based on upside movement or downside movement , for upside its green and for downside its orange color.
This indicator i have created with stop loss line means any price close below cross line for bullish position then that trade should be closed and take the stop loss. similarly for Bearish trade and candle close above stop loss line means trade should be closed and take the stop loss.
Stop loss i have taken care with ATR and Super trend you can see the settings.
I have defined setting for general use of indicator if any modification on setting then result may vary.
Its multi time frame moving average. And I have given time frame for indicator as well so if any trending move need to capture then that setting need to be increased with respect to chart time frame else keep it same.
I have added commission and slippages as well in indicator.
Ping me or DM me to subscribe this indicator.
I have given all my indicator details below link (Signature URL). You can check indicators and call me on given number or email me on given email to access the scripts and indicators. Telegram link is also given you can ping me there.
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Disclaimer : Past performance of the indicator is not giving guarantee for future performance as well, it may change as per market condition.
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888 BOT #backtest█ 888 BOT #backtest
This is an Expert Advisor 'EA' or Automated trading script for ‘longs’ and ‘shorts’, which uses only a Take Profit or, in the worst case, a Stop Loss to close the trade.
It's a much improved version of the previous ‘Repanocha’. It doesn`t use 'Trailing Stop' or 'security()' functions (although using a security function doesn`t mean that the script repaints) and all signals are confirmed, therefore the script doesn`t repaint in alert mode and is accurate in backtest mode.
Apart from the previous indicators, some more and other functions have been added for Stop-Loss, re-entry and leverage.
It uses 8 indicators, (many of you already know what they are, but in case there is someone new), these are the following:
1. Jurik Moving Average
It's a moving average created by Mark Jurik for professionals which eliminates the 'lag' or delay of the signal. It's better than other moving averages like EMA, DEMA, AMA or T3.
There are two ways to decrease noise using JMA. Increasing the 'LENGTH' parameter will cause JMA to move more slowly and therefore reduce noise at the expense of adding 'lag'
The 'JMA LENGTH', 'PHASE' and 'POWER' parameters offer a way to select the optimal balance between 'lag' and over boost.
Green: Bullish, Red: Bearish.
2. Range filter
Created by Donovan Wall, its function is to filter or eliminate noise and to better determine the price trend in the short term.
First, a uniform average price range 'SAMPLING PERIOD' is calculated for the filter base and multiplied by a specific quantity 'RANGE MULTIPLIER'.
The filter is then calculated by adjusting price movements that do not exceed the specified range.
Finally, the target ranges are plotted to show the prices that will trigger the filter movement.
Green: Bullish, Red: Bearish.
3. Average Directional Index (ADX Classic) and (ADX Masanakamura)
It's an indicator designed by Welles Wilder to measure the strength and direction of the market trend. The price movement is strong when the ADX has a positive slope and is above a certain minimum level 'ADX THRESHOLD' and for a given period 'ADX LENGTH'.
The green color of the bars indicates that the trend is bullish and that the ADX is above the level established by the threshold.
The red color of the bars indicates that the trend is down and that the ADX is above the threshold level.
The orange color of the bars indicates that the price is not strong and will surely lateralize.
You can choose between the classic option and the one created by a certain 'Masanakamura'. The main difference between the two is that in the first it uses RMA () and in the second SMA () in its calculation.
4. Parabolic SAR
This indicator, also created by Welles Wilder, places points that help define a trend. The Parabolic SAR can follow the price above or below, the peculiarity that it offers is that when the price touches the indicator, it jumps to the other side of the price (if the Parabolic SAR was below the price it jumps up and vice versa) to a distance predetermined by the indicator. At this time the indicator continues to follow the price, reducing the distance with each candle until it is finally touched again by the price and the process starts again. This procedure explains the name of the indicator: the Parabolic SAR follows the price generating a characteristic parabolic shape, when the price touches it, stops and turns (SAR is the acronym for 'stop and reverse'), giving rise to a new cycle. When the points are below the price, the trend is up, while the points above the price indicate a downward trend.
5. RSI with Volume
This indicator was created by LazyBear from the popular RSI.
The RSI is an oscillator-type indicator used in technical analysis and also created by Welles Wilder that shows the strength of the price by comparing individual movements up or down in successive closing prices.
LazyBear added a volume parameter that makes it more accurate to the market movement.
A good way to use RSI is by considering the 50 'RSI CENTER LINE' centerline. When the oscillator is above, the trend is bullish and when it is below, the trend is bearish.
6. Moving Average Convergence Divergence (MACD) and (MAC-Z)
It was created by Gerald Appel. Subsequently, the histogram was added to anticipate the crossing of MA. Broadly speaking, we can say that the MACD is an oscillator consisting of two moving averages that rotate around the zero line. The MACD line is the difference between a short moving average 'MACD FAST MA LENGTH' and a long moving average 'MACD SLOW MA LENGTH'. It's an indicator that allows us to have a reference on the trend of the asset on which it is operating, thus generating market entry and exit signals.
We can talk about a bull market when the MACD histogram is above the zero line, along with the signal line, while we are talking about a bear market when the MACD histogram is below the zero line.
There is the option of using the MAC-Z indicator created by LazyBear, which according to its author is more effective, by using the parameter VWAP (volume weighted average price) 'Z-VWAP LENGTH' together with a standard deviation 'STDEV LENGTH' in its calculation.
7. Volume Condition
Volume indicates the number of participants in this war between bulls and bears, the more volume the more likely the price will move in favor of the trend. A low trading volume indicates a lower number of participants and interest in the instrument in question. Low volumes may reveal weakness behind a price movement.
With this condition, those signals whose volume is less than the volume SMA for a period 'SMA VOLUME LENGTH' multiplied by a factor 'VOLUME FACTOR' are filtered. In addition, it determines the leverage used, the more volume, the more participants, the more probability that the price will move in our favor, that is, we can use more leverage. The leverage in this script is determined by how many times the volume is above the SMA line.
The maximum leverage is 8.
8. Bollinger Bands
This indicator was created by John Bollinger and consists of three bands that are drawn superimposed on the price evolution graph.
The central band is a moving average, normally a simple moving average calculated with 20 periods is used. ('BB LENGTH' Number of periods of the moving average)
The upper band is calculated by adding the value of the simple moving average X times the standard deviation of the moving average. ('BB MULTIPLIER' Number of times the standard deviation of the moving average)
The lower band is calculated by subtracting the simple moving average X times the standard deviation of the moving average.
the band between the upper and lower bands contains, statistically, almost 90% of the possible price variations, which means that any movement of the price outside the bands has special relevance.
In practical terms, Bollinger bands behave as if they were an elastic band so that, if the price touches them, it has a high probability of bouncing.
Sometimes, after the entry order is filled, the price is returned to the opposite side. If price touch the Bollinger band in the same previous conditions, another order is filled in the same direction of the position to improve the average entry price, (% MINIMUM BETTER PRICE ': Minimum price for the re-entry to be executed and that is better than the price of the previous position in a given %) in this way we give the trade a chance that the Take Profit is executed before. The downside is that the position is doubled in size. 'ACTIVATE DIVIDE TP': Divide the size of the TP in half. More probability of the trade closing but less profit.
█ STOP LOSS and RISK MANAGEMENT.
A good risk management is what can make your equity go up or be liquidated.
The % risk is the percentage of our capital that we are willing to lose by operation. This is recommended to be between 1-5%.
% Risk: (% Stop Loss x % Equity per trade x Leverage) / 100
First the strategy is calculated with Stop Loss, then the risk per operation is determined and from there, the amount per operation is calculated and not vice versa.
In this script you can use a normal Stop Loss or one according to the ATR. Also activate the option to trigger it earlier if the risk percentage is reached. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': The Stop Loss is only activated if the closing of the previous bar is in the loss limit condition. It's useful to prevent the SL from triggering when they do a ‘pump’ to sweep Stops and then return the price to the previous state.
█ BACKTEST
The objective of the Backtest is to evaluate the effectiveness of our strategy. A good Backtest is determined by some parameters such as:
- RECOVERY FACTOR: It consists of dividing the 'net profit' by the 'drawdown’. An excellent trading system has a recovery factor of 10 or more; that is, it generates 10 times more net profit than drawdown.
- PROFIT FACTOR: The ‘Profit Factor’ is another popular measure of system performance. It's as simple as dividing what win trades earn by what loser trades lose. If the strategy is profitable then by definition the 'Profit Factor' is going to be greater than 1. Strategies that are not profitable produce profit factors less than one. A good system has a profit factor of 2 or more. The good thing about the ‘Profit Factor’ is that it tells us what we are going to earn for each dollar we lose. A profit factor of 2.5 tells us that for every dollar we lose operating we will earn 2.5.
- SHARPE: (Return system - Return without risk) / Deviation of returns.
When the variations of gains and losses are very high, the deviation is very high and that leads to a very poor ‘Sharpe’ ratio. If the operations are very close to the average (little deviation) the result is a fairly high 'Sharpe' ratio. If a strategy has a 'Sharpe' ratio greater than 1 it is a good strategy. If it has a 'Sharpe' ratio greater than 2, it is excellent. If it has a ‘Sharpe’ ratio less than 1 then we don't know if it is good or bad, we have to look at other parameters.
- MATHEMATICAL EXPECTATION: (% winning trades X average profit) + (% losing trades X average loss).
To earn money with a Trading system, it is not necessary to win all the operations, what is really important is the final result of the operation. A Trading system has to have positive mathematical expectation as is the case with this script: ME = (0.87 x 30.74$) - (0.13 x 56.16$) = (26.74 - 7.30) = 19.44$ > 0
The game of roulette, for example, has negative mathematical expectation for the player, it can have positive winning streaks, but in the long term, if you continue playing you will end up losing, and casinos know this very well.
PARAMETERS
'BACKTEST DAYS': Number of days back of historical data for the calculation of the Backtest.
'ENTRY TYPE': For '% EQUITY' if you have $ 10,000 of capital and select 7.5%, for example, your entry would be $ 750 without leverage. If you select CONTRACTS for the 'BTCUSDT' pair, for example, it would be the amount in 'Bitcoins' and if you select 'CASH' it would be the amount in $ dollars.
'QUANTITY (LEVERAGE 1X)': The amount for an entry with X1 leverage according to the previous section.
'MAXIMUM LEVERAGE': It's the maximum allowed multiplier of the quantity entered in the previous section according to the volume condition.
The settings are for Bitcoin at Binance Futures (BTC: USDTPERP) in 30 minutes.
For other pairs and other timeframes, the settings have to be adjusted again. And within a month, the settings will be different because we all know the market and the trend are changing.
█ 888 BOT (SPANISH)
Este es un Expert Advisor 'EA' o script de trading automatizado para ‘longs’ y ‘shorts’, el cual, utiliza solo un Take Profit o, en el peor de los casos, un Stop Loss para cerrar el trade.
Es una versión muy mejorada del anterior ‘Repanocha’. No utiliza ‘Trailing Stop’, ni funciones ‘security()’ (aunque usar una función security no significa que el script repinte) y todas las señales son confirmadas, por consiguiente, el script no repinta en modo alertas y es preciso en en el modo backtest.
Aparte de los anteriores indicadores se han añadido algunos más y otras funciones para Stop-Loss, de re-entrada y apalancamiento.
Utiliza 8 indicadores, (muchos ya sabéis sobradamente lo que son, pero por si hay alguien nuevo), son los siguientes:
1. Jurik Moving Average
Es una media móvil creada por Mark Jurik para profesionales la cual elimina el ‘lag’ o retardo de la señal. Es mejor que otras medias móviles como la EMA, DEMA, AMA o T3.
Hay dos formas de disminuir el ruido utilizando JMA. El aumento del parámetro 'LENGTH' hará que JMA se mueva más lentamente y, por lo tanto, reducirá el ruido a expensas de añadir ‘lag’
Los parámetros 'JMA LENGTH', 'PHASE' y 'POWER' ofrecen una forma de seleccionar el equilibrio óptimo entre ‘lag’ y sobre impulso.
Verde : Alcista, Rojo: Bajista.
2. Range filter
Creado por Donovan Wall, su función es la de filtrar o eliminar el ruido y poder determinar mejor la tendencia del precio a corto plazo.
Primero, se calcula un rango de precio promedio uniforme 'SAMPLING PERIOD' para la base del filtro y se multiplica por una cantidad específica 'RANGE MULTIPLIER'.
A continuación, el filtro se calcula ajustando los movimientos de precios que no exceden el rango especificado.
Por último, los rangos objetivo se trazan para mostrar los precios que activarán el movimiento del filtro.
Verde : Alcista, Rojo: Bajista.
3. Average Directional Index (ADX Classic) y (ADX Masanakamura)
Es un indicador diseñado por Welles Wilder para medir la fuerza y dirección de la tendencia del mercado. El movimiento del precio tiene fuerza cuando el ADX tiene pendiente positiva y está por encima de cierto nivel mínimo 'ADX THRESHOLD' y para un periodo dado 'ADX LENGTH'.
El color verde de las barras indica que la tendencia es alcista y que el ADX está por encima del nivel establecido por el threshold.
El color Rojo de las barras indica que la tendencia es bajista y que el ADX está por encima del nivel de threshold.
El color naranja de las barras indica que el precio no tiene fuerza y seguramente lateralizará.
Se puede elegir entre la opción clásica y la creada por un tal 'Masanakamura'. La diferencia principal entre los dos es que en el primero utiliza RMA() y en el segundo SMA() en su cálculo.
4. Parabolic SAR
Este indicador, creado también por Welles Wilder, coloca puntos que ayudan a definir una tendencia. El Parabolic SAR puede seguir al precio por encima o por debajo, la particularidad que ofrece es que cuando el precio toca al indicador, este salta al otro lado del precio (si el Parabolic SAR estaba por debajo del precio salta arriba y viceversa) a una distancia predeterminada por el indicador. En este momento el indicador vuelve a seguir al precio, reduciendo la distancia con cada vela hasta que finalmente es tocado otra vez por el precio y se vuelve a iniciar el proceso. Este procedimiento explica el nombre del indicador: el Parabolic SAR va siguiendo al precio generando una característica forma parabólica, cuando el precio lo toca, se para y da la vuelta (SAR son las siglas en inglés de ‘stop and reverse’), dando lugar a un nuevo ciclo. Cuando los puntos están por debajo del precio, la tendencia es alcista, mientras que los puntos por encima del precio indica una tendencia bajista.
5. RSI with Volume
Este indicador lo creo un tal LazyBear de TV a partir del popular RSI.
El RSI es un indicador tipo oscilador utilizado en análisis técnico y creado también por Welles Wilder que muestra la fuerza del precio mediante la comparación de los movimientos individuales al alza o a la baja de los sucesivos precios de cierre.
LazyBear le añadió un parámetro de volumen que lo hace más preciso al movimiento del mercado.
Una buena forma de usar el RSI es teniendo en cuenta la línea central de 50 'RSI CENTER LINE'. Cuando el oscilador está por encima, la tendencia es alcista y cuando está por debajo la tendencia es bajista.
6. Moving Average Convergence Divergence (MACD) y (MAC-Z)
Fue creado por Gerald Appel. Posteriormente se añadió el histograma para anticipar el cruce de medias. A grandes rasgos podemos decir que el MACD es un oscilador consistente en dos medias móviles que van girando en torno a la línea de cero. La línea del MACD no es más que la diferencia entre una media móvil corta 'MACD FAST MA LENGTH' y una media móvil larga 'MACD SLOW MA LENGTH'. Es un indicador que nos permite tener una referencia sobre la tendencia del activo sobre el cual se está operando, generando de este modo señales de entrada y salida del mercado.
Podemos hablar de mercado alcista cuando el histograma del MACD se sitúe por encima de la línea cero, junto con la línea de señal, mientras que hablaremos de mercado bajista cuando el histograma MACD se situará por debajo de la línea cero.
Está la opción de utilizar el indicador MAC-Z creado por LazyBear que según su autor es más eficaz, por utilizar el parámetro VWAP (precio medio ponderado por volumen) 'Z-VWAP LENGTH' junto con una desviación standard 'STDEV LENGTH' en su cálculo.
7. Volume Condition
El volumen indica el número de participantes en esta guerra entre toros y osos, cuanto más volumen más probabilidad de que se mueva el precio a favor de la tendencia. Un volumen bajo de negociación indica un menor número de participantes e interés por el instrumento en cuestión. Los bajos volúmenes pueden revelar debilidad detrás de un movimiento de precios.
Con esta condición se filtran aquellas señales cuyo volumen es inferior a la SMA de volumen para un periodo 'SMA VOLUME LENGTH' multiplicado por un factor 'VOLUME FACTOR'. Además, determina el apalancamiento utilizado, a más volumen, más participantes, más probabilidad de que se mueva el precio a nuestro favor, es decir, podemos utilizar más apalancamiento. El apalancamiento en este script lo determina las veces que está el volumen por encima de la línea de la SMA.
El apalancamiento máximo es de 8.
8. Bollinger Bands
Este indicador fue creado por John Bollinger y consiste en tres bandas que se dibujan superpuestas al gráfico de evolución del precio.
La banda central es una media móvil, normalmente se emplea una media móvil simple calculada con 20 períodos. ('BB LENGTH' Número de periodos de la media móvil)
La banda superior se calcula sumando al valor de la media móvil simple X veces la desviación típica de la media móvil. ('BB MULTIPLIER' Número de veces la desviación típica de la media móvil)
La banda inferior de calcula restando a la media móvil simple X veces la desviación típica de la media móvil.
la franja comprendida entre las bandas superior e inferior contiene, estadísticamente, casi un 90% de las posibles variaciones del precio, lo que significa que cualquier movimiento del precio fuera de las bandas tiene especial relevancia.
En términos prácticos, las bandas de Bollinger se comporta como si de una banda elástica se tratara de manera que, si el precio las toca, éste tiene mucha probabilidad de rebotar.
En ocasiones, después de rellenarse la orden de entrada, el precio se devuelve hacia el lado contrario. Si toca la banda de Bollinger se rellena otra orden en la misma dirección de la posición para mejorar el precio medio de entrada, (% MINIMUM BETTER PRICE': Precio mínimo para que se ejecute la re-entrada y que sea mejor que el precio de la posición anterior en un % dado) de esta manera damos una oportunidad al trade de que el Take Profit se ejecute antes. La desventaja es que se dobla el tamaño de la posición. 'ACTIVATE DIVIDE TP': Divide el tamaño del TP a la mitad. Más probabilidad de que se cierre el trade pero menos ganancias.
█ STOP LOSS y RISK MANAGEMENT.
Una buena gestión de las pérdidas o gestión del riesgo es lo que puede hacer que tu cuenta suba o se liquide en poco tiempo.
El % de riesgo es el porcentaje de nuestro capital que estamos dispuestos a perder por operación. Este se aconseja que debe estar comprendido entre un 1-5%.
% Risk = (% Stop Loss x % Equity per trade x Leverage) / 100
Primero se calcula la estrategia con Stop Loss, después se determina el riesgo por operación y a partir de ahí se calcula el monto por operación y no al revés.
En este script puedes usar un Stop Loss normal o uno según el ATR. También activar la opción de que salte antes si se alcanza el porcentaje de riesgo. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': Solamente se activa el Stop Loss si el cierre de la barra anterior se encuentra en la condición de límite de pérdidas. Es útil para evitar que se dispare el SL cuando hacen un ‘pump’ para barrer Stops y luego se devuelve el precio a la normalidad.
█ BACKTEST
El objetivo del Backtest es evaluar la eficacia de nuestra estrategia. Un buen Backtest lo determinan algunos parámetros como son:
- RECOVERY FACTOR: Consiste en dividir el ‘beneficio neto’ entre el ‘drawdown’. Un excelente sistema de trading tiene un recovery factor de 10 o más; es decir, genera 10 veces más beneficio neto que drawdown.
- PROFIT FACTOR: El ‘Profit Factor’ es otra medida popular del rendimiento de un sistema. Es algo tan simple como dividir lo que ganan las operaciones con ganancias entre lo que pierden las operaciones con pérdidas. Si la estrategia es rentable entonces por definición el ‘Profit Factor’ va a ser mayor que 1. Las estrategias que no son rentables producen factores de beneficio menores que uno. Un buen sistema tiene un profit factor de 2 o más. Lo bueno del ‘Profit Factor’ es que nos dice lo que vamos a ganar por cada dolar que perdemos. Un profit factor de 2.5 nos dice que por cada dolar que perdamos operando vamos a ganar 2.5.
- SHARPE: (Retorno sistema – Retorno sin riesgo) / Desviación de los retornos.
Cuando las variaciones de ganancias y pérdidas son muy altas, la desviación es muy elevada y eso conlleva un ratio de ‘Sharpe’ muy pobre. Si las operaciones están muy cerca de la media (poca desviación) el resultado es un ratio de ‘Sharpe’ bastante elevado. Si una estrategia tiene un ratio de ‘Sharpe’ mayor que 1 es una buena estrategia. Si tiene un ratio de ‘Sharpe’ mayor que 2, es excelente. Si tiene un ratio de ‘Sharpe’ menor que 1 entonces no sabemos si es buena o mala, hay que mirar otros parámetros.
- MATHEMATICAL EXPECTATION:(% operaciones ganadoras X ganancia media) + (% operaciones perdedoras X pérdida media).
Para ganar dinero con un sistema de Trading, no es necesario ganar todas las operaciones, lo verdaderamente importante es el resultado final de la operativa. Un sistema de Trading tiene que tener esperanza matemática positiva como es el caso de este script.
El juego de la ruleta, por ejemplo, tiene esperanza matemática negativa para el jugador, puede tener rachas positivas de ganancias, pero a la larga, si se sigue jugando se acabará perdiendo, y esto los casinos lo saben muy bien.
PARAMETROS
'BACKTEST DAYS': Número de días atrás de datos históricos para el calculo del Backtest.
'ENTRY TYPE': Para % EQUITY si tienes 10000$ de capital y seleccionas 7.5% tu entrada sería de 750$ sin apalancamiento. Si seleccionas CONTRACTS para el par BTCUSDT sería la cantidad en Bitcoins y si seleccionas CASH sería la cantidad en dólares.
'QUANTITY (LEVERAGE 1X)': La cantidad para una entrada con apalancamiento X! según el apartado anterior.
'MAXIMUM LEVERAGE': Es el máximo multiplicador permitido de la cantidad introducida en el apartado anterior según la condición de volumen.
Los settings son para Bitcoin en Binance Futures (BTC:USDTPERP) en 30 minutos.
Para otro pares y otras temporalidades se tienen que ajustar las opciones de nuevo. Además para dentro de un mes, los ajustes serán otros distintos ya que el mercado y la tendencia es cambiante.
MACKAVELLI Algorithmic StrategyI had a hard time finding a strategy that would work in different time-frames and multiple different currency pairs. This is what I ended up with after countless hours of research and testing. I designed this strategy for auto-algorithmic trading and it uses three different indicators for Long/Short positions and a 4th indicator for exiting positions.
1) A green-light indicator that tells you whether or not you can go long/short.
2) A confirmation indicator that executes the long/short positions.
3) A chop indicator that measures the distance between the two MA's. When they're too close a trade will not be executed, as this usually indicates a chop zone.
4) A third MA is used as an exit indicator.
5) Finally, a loop function is designed to prevent repeat signals. Once a signal is produced on bar close it cannot happen again until that trade is closed or a new position is opened.
Be advised, you need to adjust the settings for each currency pair and time-frame. Once you do that, back-test it and count the last 100 trades to determine accurately your wins/losses. Long entries are the top of the previous bar, shorts are the bottom of the previous bar. This is a more accurate way of counting wins/losses. Tradingview back-test's are not accurate because of where they estimate your long/short entries are, it's very misleading.
Right now I have it setup for 2hr USDCAD with a back-test of 58% win rate on the last 100 trades.
The chop indicator is set to 0.04, I suggest starting there. 0.03 is the lowest I would go. You can go all the way up to 0.1 and higher if needed. You'll start missing big trades though.
The EMA for green-light signal is set to 10, a lower number will give you more entries but less accurate results, bigger number will give less entries with more accuracy but with missed opportunities. 10 is a good starting point.
This strategy is also designed so you can use tight stop losses to prevent large losses. This is because the strategy typically catches trends on the way up/down, minimizing risk for reversal.
I use Heikin Ashi candles for a smoother chart to work with. I have not tested this strategy with normal candles.
DEMO this strategy before using it live and make sure you back-test and tune it before you start. This is written in PINE V3 SO IT WILL NOT REPAINT.
QZ Trend (Crypto Edition) v1.1a: Donchian, EMA, ATR, Liquidity/FThe "QZ Trend (Crypto Edition)" is a rules-based trend-following breakout strategy for crypto spot or perpetual contracts, focusing on following trends, prioritizing risk control, seeking small losses and big wins, and trading only when advantageous.
Key mechanisms include:
- Market filters: Screen favorable conditions via ADX (trend strength), dollar volume (liquidity), funding fee windows, session/weekend restrictions, and spot-long-only settings.
- Signals & entries: Based on price position relative to EMA and EMA trends, combined with breaking Donchian channel extremes (with ATR ratio confirmation), plus single-position rules and post-exit cooldowns.
- Position sizing: Calculate positions by fixed risk percentage; initial stop-loss is ATR-based, complying with exchange min/max lot requirements.
- Exits & risk management: Include initial stop-loss, trailing stop (tightens only), break-even rule (stop moves to entry when target floating profit is hit), time-based exit, and post-exit cooldowns.
- Pyramiding: Add positions only when profitable with favorable momentum, requiring ATR-based spacing; add size is a fraction of the base position, with layers sharing stop logic but having unique order IDs.
Charts display EMA, Donchian channels, current stop lines, and highlight low ADX, avoidable funding windows, and low-liquidity periods.
Recommend starting with 4H or 1D timeframes, with typical parameters varying by cycle. Liquidity settings differ by token; perpetuals should enable funding window filters, while spot requires "long-only" and matching fees. The strategy performs well in trends with quick stop-losses but faces whipsaws in ranges (filters mitigate but don’t eliminate noise). Share your symbol and timeframe for tailored parameters.
Imbalance RSI Divergence Strategy# Imbalance RSI Divergence Strategy - User Guide
## What is This Strategy?
This strategy identifies **imbalance** zones in the market and combines them with **RSI divergence** to generate trading signals. It aims to capitalize on price gaps left by institutional investors and large volume movements.
### Main Settings
- **RSI Period (14)**: Period used for RSI calculation. Lower values = more sensitive, higher values = more stable signals.
- **ATR Period (10)**: Period for volatility measurement using Average True Range.
- **ATR Stop Loss Multiplier (2.0)**: How many ATR units to use for stop loss calculation.
- **Risk:Reward Ratio (4.0)**: Risk-reward ratio. 2.0 = 2 units of reward for 1 unit of risk.
- **Use RSI Divergence Filter (true)**: Enables/disables the RSI divergence filter.
### Imbalance Filters
- **Minimum Imbalance Size (ATR) (0.3)**: Minimum imbalance size in ATR units to filter out small imbalances.
- **Enable Lookback Limit (false)**: Activates historical lookback limitations.
- **Maximum Lookback Bars (300)**: Maximum number of bars to look back.
### Visual Settings
- **Show Imbalance Size**: Displays imbalance size in ATR units.
- **Show RSI Divergence Lines**: Shows/hides divergence lines.
- **Divergence Line Colors**: Colors for bullish/bearish divergence lines.
### Volatility-Based Adjustments
- **Low volatility markets**:
- Minimum Imbalance Size: 0.2-0.4 ATR
- ATR Stop Loss Multiplier: 1.5-2.0
- **High volatility markets**:
- Minimum Imbalance Size: 0.5-1.0 ATR
- ATR Stop Loss Multiplier: 2.5-3.5
### Risk Tolerance
- **Conservative approach**:
- Risk:Reward Ratio: 2.0-3.0
- RSI Divergence Filter: Enabled
- Minimum Imbalance Size: Higher (0.5+ ATR)
- **Aggressive approach**:
- Risk:Reward Ratio: 4.0-6.0
- Minimum Imbalance Size: Lower (0.2-0.3 ATR)
###Market Conditions
- **Trending markets**: Higher RSI Period (21-28)
- **Sideways markets**: Lower RSI Period (10-14)
- **Volatile markets**: Higher ATR Multiplier
## Recommended Testing Procedure
1. **Start with default settings** and backtest on 3-6 months of historical data
2. **Adjust RSI Period** to see which value produces better results
3. **Optimize ATR Multiplier** for stop loss levels
4. **Test different Risk:Reward ratios** comparatively
5. **Fine-tune Minimum Imbalance Size** to improve signal quality
## Important Considerations
- **False positive signals**: Imbalances may be less reliable during low volatility periods
- **Market openings**: First hours often produce more imbalances but can be riskier
- **News events**: Consider disabling strategy during major news releases
- **Backtesting**: Test across different market conditions (trending, sideways, volatile)
## Recommended Settings for Beginners
**Safe settings for new users:**
- RSI Period: 14
- ATR Period: 14
- ATR Stop Loss Multiplier: 2.5
- Risk:Reward Ratio: 3.0
- Minimum Imbalance Size: 0.5 ATR
- RSI Divergence Filter: Enabled
## Advanced Tips
### Signal Quality Improvement
- **Combine with market structure**: Look for imbalances near key support/resistance levels
- **Volume confirmation**: Higher volume during imbalance formation increases reliability
- **Multiple timeframe analysis**: Confirm signals on higher timeframes
### Risk Management
- **Position sizing**: Never risk more than 1-2% of account per trade
- **Maximum drawdown**: Set overall stop loss for the strategy
- **Market hours**: Consider avoiding low liquidity periods
### Performance Monitoring
- **Win rate**: Track percentage of profitable trades
- **Average R:R**: Monitor actual risk-reward achieved vs. target
- **Maximum consecutive losses**: Set alerts for strategy review
This strategy works best when combined with proper risk management and market analysis. Always backtest thoroughly before using real money and adjust parameters based on your specific market and trading style.
Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Engulfing & Pin Bar Breakout StrategyOverview
This strategy automates a classic, powerful trading methodology based on identifying key candlestick reversal patterns and trading the subsequent price breakout. It is designed to be a complete, "set-and-go" system with built-in risk and position size management.
The core logic operates on the 1-Hour timeframe, scanning for four distinct high-probability reversal signals: two bullish and two bearish. An entry is only triggered when the market confirms the signal by breaking a key price level, aiming to capture momentum following a potential shift in market sentiment.
The Strategy Logic
The system is composed of two distinct modules: Bullish (Long) and Bearish (Short).
🐂 Bullish (Long) Setup
The script initiates a long trade based on the following strict criteria:
Signal: Identifies either a Hammer or a Bullish Engulfing pattern. These patterns often indicate that sellers are losing control and buyers are stepping in.
Confirmation: Waits for the very next candle after the signal.
Entry Trigger: A long position is automatically opened as soon as the price breaks above the high of the signal candle.
Stop Loss: Immediately set just below the low of the signal candle.
Take Profit: A fixed target is placed at a 1:5 Risk/Reward Ratio.
🐻 Bearish (Short) Setup
The script initiates a short trade based on the following strict criteria:
Signal: Identifies either a Shooting Star or a Bearish Engulfing pattern. These patterns suggest buying pressure is fading and sellers are taking over.
Confirmation: Waits for the very next candle after the signal.
Entry Trigger: A short position is automatically opened as soon as the price breaks below the low of the signal candle.
Stop Loss: Immediately set just above the high of the signal candle.
Take Profit: A fixed target is placed at a 1:4 Risk/Reward Ratio.
Key Feature: Automated Risk Management
This strategy is designed for disciplined trading. You do not need to calculate position sizes manually.
Fixed Risk: The script automatically calculates the correct position size to risk exactly 2% of your total account equity on every single trade.
Dynamic Sizing: The position size will adjust based on the distance between your entry price and your stop loss for each specific setup, ensuring a consistent risk profile.
How To Use
Apply the script to your chosen chart (e.g., BTC/USD).
Crucially, set your chart's timeframe to 1-Hour (H1). The strategy is specifically calibrated for this interval.
Navigate to the "Strategy Tester" tab below your chart to view backtest results, including net profit, win rate, and individual trades.
Disclaimer: This script is provided for educational and informational purposes only. It is not financial advice. All trading involves substantial risk, and past performance is not indicative of future results. Please use this tool responsibly and at your own risk.
Keltner Channel Based Grid Strategy # KC Grid Strategy - Keltner Channel Based Grid Trading System
## Strategy Overview
KC Grid Strategy is an innovative grid trading system that combines the power of Keltner Channels with dynamic position sizing to create a mean-reversion trading approach. This strategy automatically adjusts position sizes based on price deviation from the Keltner Channel center line, implementing a systematic grid-based approach that capitalizes on market volatility and price oscillations.
## Core Principles
### Keltner Channel Foundation
The strategy builds upon the Keltner Channel indicator, which consists of:
- **Center Line**: Moving average (EMA or SMA) of the price
- **Upper Band**: Center line + (ATR/TR/Range × Multiplier)
- **Lower Band**: Center line - (ATR/TR/Range × Multiplier)
### Grid Trading Logic
The strategy implements a sophisticated grid system where:
1. **Position Direction**: Inversely correlated to price position within the channel
- When price is above center line → Short positions
- When price is below center line → Long positions
2. **Position Size**: Proportional to distance from center line
- Greater deviation = Larger position size
3. **Grid Activation**: Positions are adjusted only when the difference exceeds a predefined grid threshold
### Mathematical Foundation
The core calculation uses the KC Rate formula:
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
This creates a mean-reversion system where positions increase as price moves further from the mean, expecting eventual return to equilibrium.
## Parameter Guide
### Time Range Settings
- **Start Date**: Beginning of strategy execution period
- **End Date**: End of strategy execution period
### Core Parameters
1. **Number of Grids (NumGrid)**: Default 12
- Controls grid sensitivity and position adjustment frequency
- Higher values = More frequent but smaller adjustments
- Lower values = Less frequent but larger adjustments
2. **Length**: Default 10
- Period for moving average and volatility calculations
- Shorter periods = More responsive to recent price action
- Longer periods = Smoother, less noisy signals
3. **Grid Coefficient (kcRateMult)**: Default 1.33
- Multiplier for channel width calculation
- Higher values = Wider channels, less frequent trades
- Lower values = Narrower channels, more frequent trades
4. **Source**: Default Close
- Price source for calculations (Close, Open, High, Low, etc.)
- Close price typically provides most reliable signals
5. **Use Exponential MA**: Default True
- True = Uses EMA (more responsive to recent prices)
- False = Uses SMA (equal weight to all periods)
6. **Bands Style**: Default "Average True Range"
- **Average True Range**: Smoothed volatility measure (recommended)
- **True Range**: Current bar's volatility only
- **Range**: Simple high-low difference
## How to Use
### Setup Instructions
1. **Apply to Chart**: Add the strategy to your desired timeframe and instrument
2. **Configure Parameters**: Adjust settings based on market characteristics:
- Volatile markets: Increase Grid Coefficient, reduce Number of Grids
- Stable markets: Decrease Grid Coefficient, increase Number of Grids
3. **Set Time Range**: Define your backtesting or live trading period
4. **Monitor Performance**: Watch strategy performance metrics and adjust as needed
### Optimal Market Conditions
- **Range-bound markets**: Strategy performs best in sideways trending markets
- **High volatility**: Benefits from frequent price oscillations around the mean
- **Liquid instruments**: Ensures efficient order execution and minimal slippage
### Position Management
The strategy automatically:
- Calculates optimal position sizes based on account equity
- Adjusts positions incrementally as price moves through grid levels
- Maintains risk control through maximum position limits
- Executes trades only during specified time periods
## Risk Warnings
### ⚠️ Important Risk Considerations
1. **Trending Market Risk**:
- Strategy may underperform or generate losses in strong trending markets
- Mean-reversion assumption may fail during sustained directional moves
- Consider market regime analysis before deployment
2. **Leverage and Position Size Risk**:
- Strategy uses pyramiding (up to 20 positions)
- Large positions may accumulate during extended moves
- Monitor account equity and margin requirements closely
3. **Volatility Risk**:
- Sudden volatility spikes may trigger multiple rapid position adjustments
- Consider volatility filters during high-impact news events
- Backtest across different volatility regimes
4. **Execution Risk**:
- Strategy calculates on every tick (calc_on_every_tick = true)
- May generate frequent orders in volatile conditions
- Ensure adequate execution infrastructure and consider transaction costs
5. **Parameter Sensitivity**:
- Performance highly dependent on parameter optimization
- Over-optimization may lead to curve-fitting
- Regular parameter review and adjustment may be necessary
## Suitable Scenarios
### Ideal Market Conditions
- **Sideways/Range-bound markets**: Primary use case
- **Mean-reverting instruments**: Forex pairs, some commodities
- **Stable volatility environments**: Consistent ATR patterns
- **Liquid markets**: Major currency pairs, popular stocks/indices
## Important Notes
### Strategy Limitations
1. **No Stop Loss**: Strategy relies on mean reversion without traditional stop losses
2. **Capital Requirements**: Requires sufficient capital for grid-based position sizing
3. **Market Regime Dependency**: Performance varies significantly across different market conditions
## Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly test the strategy and understand its mechanics before risking real capital. The author assumes no responsibility for trading losses incurred through the use of this strategy.
---
# KC网格策略 - 基于肯特纳通道的网格交易系统
## 策略概述
KC网格策略是一个创新的网格交易系统，它将肯特纳通道的力量与动态仓位调整相结合，创建了一个均值回归交易方法。该策略根据价格偏离肯特纳通道中心线的程度自动调整仓位大小，实施系统化的网格方法，利用市场波动和价格振荡获利。
## 核心原理
### 肯特纳通道基础
该策略建立在肯特纳通道指标之上，包含：
- **中心线**: 价格的移动平均线（EMA或SMA）
- **上轨**: 中心线 + (ATR/TR/Range × 乘数)
- **下轨**: 中心线 - (ATR/TR/Range × 乘数)
### 网格交易逻辑
该策略实施复杂的网格系统：
1. **仓位方向**: 与价格在通道中的位置呈反向关系
- 当价格高于中心线时 → 空头仓位
- 当价格低于中心线时 → 多头仓位
2. **仓位大小**: 与距离中心线的距离成正比
- 偏离越大 = 仓位越大
3. **网格激活**: 只有当差异超过预定义的网格阈值时才调整仓位
### 数学基础
核心计算使用KC比率公式：
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
这创建了一个均值回归系统，当价格偏离均值越远时仓位越大，期望最终回归均衡。
## 参数说明
### 时间范围设置
- **开始日期**: 策略执行期间的开始时间
- **结束日期**: 策略执行期间的结束时间
### 核心参数
1. **网格数量 (NumGrid)**: 默认12
- 控制网格敏感度和仓位调整频率
- 较高值 = 更频繁但较小的调整
- 较低值 = 较少频繁但较大的调整
2. **长度**: 默认10
- 移动平均线和波动率计算的周期
- 较短周期 = 对近期价格行为更敏感
- 较长周期 = 更平滑，噪音更少的信号
3. **网格系数 (kcRateMult)**: 默认1.33
- 通道宽度计算的乘数
- 较高值 = 更宽的通道，较少频繁的交易
- 较低值 = 更窄的通道，更频繁的交易
4. **数据源**: 默认收盘价
- 计算的价格来源（收盘价、开盘价、最高价、最低价等）
- 收盘价通常提供最可靠的信号
5. **使用指数移动平均**: 默认True
- True = 使用EMA（对近期价格更敏感）
- False = 使用SMA（对所有周期等权重）
6. **通道样式**: 默认"平均真实范围"
- **平均真实范围**: 平滑的波动率测量（推荐）
- **真实范围**: 仅当前K线的波动率
- **范围**: 简单的高低价差
## 使用方法
### 设置说明
1. **应用到图表**: 将策略添加到您所需的时间框架和交易品种
2. **配置参数**: 根据市场特征调整设置：
- 波动市场：增加网格系数，减少网格数量
- 稳定市场：减少网格系数，增加网格数量
3. **设置时间范围**: 定义您的回测或实盘交易期间
4. **监控表现**: 观察策略表现指标并根据需要调整
### 最佳市场条件
- **区间震荡市场**: 策略在横盘趋势市场中表现最佳
- **高波动性**: 受益于围绕均值的频繁价格振荡
- **流动性强的品种**: 确保高效的订单执行和最小滑点
### 仓位管理
策略自动：
- 根据账户权益计算最优仓位大小
- 随着价格在网格水平移动逐步调整仓位
- 通过最大仓位限制维持风险控制
- 仅在指定时间段内执行交易
## 风险警示
### ⚠️ 重要风险考虑
1. **趋势市场风险**:
- 策略在强趋势市场中可能表现不佳或产生损失
- 在持续方向性移动期间均值回归假设可能失效
- 部署前考虑市场制度分析
2. **杠杆和仓位大小风险**:
- 策略使用金字塔加仓（最多20个仓位）
- 在延长移动期间可能积累大仓位
- 密切监控账户权益和保证金要求
3. **波动性风险**:
- 突然的波动性激增可能触发多次快速仓位调整
- 在高影响新闻事件期间考虑波动性过滤器
- 在不同波动性制度下进行回测
4. **执行风险**:
- 策略在每个tick上计算（calc_on_every_tick = true）
- 在波动条件下可能产生频繁订单
- 确保充足的执行基础设施并考虑交易成本
5. **参数敏感性**:
- 表现高度依赖于参数优化
- 过度优化可能导致曲线拟合
- 可能需要定期参数审查和调整
## 适用场景
### 理想市场条件
- **横盘/区间震荡市场**: 主要用例
- **均值回归品种**: 外汇对，某些商品
- **稳定波动性环境**: 一致的ATR模式
- **流动性市场**: 主要货币对，热门股票/指数
## 注意事项
### 策略限制
1. **无止损**: 策略依赖均值回归而无传统止损
2. **资金要求**: 需要充足资金进行基于网格的仓位调整
3. **市场制度依赖性**: 在不同市场条件下表现差异显著
## 免责声明
该策略仅供教育和研究目的。过往表现不保证未来结果。交易涉及重大损失风险，并非适合所有投资者。用户应在投入真实资金前彻底测试策略并理解其机制。作者对使用此策略产生的交易损失不承担任何责任。
---
**Strategy Version**: Pine Script v6
**Author**: Signal2Trade
**Last Updated**: 2025-8-9
**License**: Open Source (Mozilla Public License 2.0)
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
Strategy Chameleon [theUltimator5]Have you ever looked at an indicator and wondered to yourself "Is this indicator actually profitable?" Well now you can test it out for yourself with the Strategy Chameleon!
Strategy Chameleon is a versatile, signal-agnostic trading strategy designed to adapt to any external indicator or trading system. Like a chameleon changes colors to match its environment, this strategy adapts to match any buy/sell signals you provide, making it the ultimate backtesting and automation tool for traders who want to test multiple strategies without rewriting code.
🎯 Key Features
1) Connects ANY external indicator's buy/sell signals
Works with RSI, MACD, moving averages, custom indicators, or any Pine Script output
Simply connect your indicator's signal output to the strategy inputs
2) Multiple Stop Loss Types:
Percentage-based stops
ATR (Average True Range) dynamic stops
Fixed point stops
3) Advanced Trailing Stop System:
Percentage trailing
ATR-based trailing
Fixed point trailing
4) Flexible Take Profit Options:
Risk:Reward ratio targeting
Percentage-based profits
ATR-based profits
Fixed point profits
5) Trading Direction Control
Long Only - Bull market strategies
Short Only - Bear market strategies
Both - Full market strategies
6) Time-Based Filtering
Optional trading session restrictions
Customize active trading hours
Perfect for day trading strategies
📈 How It Works
Signal Detection: The strategy monitors your connected buy/sell signals
Entry Logic: Executes trades when signals trigger during valid time periods
Risk Management: Automatically applies your chosen stop loss and take profit levels
Trailing System: Dynamically adjusts stops to lock in profits
Performance Tracking: Real-time statistics table showing win rate and performance
⚙️ Setup Instructions
0) Add indicator you want to test, then add the Strategy to your chart
Connect Your Signals:
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Go to strategy settings → Signal Sources
1) Set "Buy Signal Source" to your indicator's buy output
2) Set "Sell Signal Source" to your indicator's sell output
3) Choose table position - This simply changes the table location on the screen
4) Set trading direction preference - Buy only? Sell only? Both directions?
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5) Set your preferred stop loss type and level
You can set the stop loss to be either percentage based or ATR and fully configurable.
6) Enable trailing stops if desired
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7) Configure take profit settings
8) Toggle time filter to only consider specific time windows or trading sessions.
🚀 Use Cases
Test various indicators to determine feasibility and/or profitability.
Compare different signal sources quickly
Validate trading ideas with consistent risk management
Portfolio Management
Apply uniform risk management across different strategies
Standardize stop loss and take profit rules
Monitor performance consistently
Automation Ready
Built-in alert conditions for automated trading
Compatible with trading bots and webhooks
Easy integration with external systems
⚠️ Important Notes
This strategy requires external signals to function
Default settings use 10% of equity per trade
Pyramiding is disabled (one position at a time)
Strategy calculates on bar close, not every tick
🔗 Integration Examples
Works perfectly with:
RSI strategies (connect RSI > 70 for sells, RSI < 30 for buys)
Moving average crossovers
MACD signal line crosses
Bollinger Band strategies
Custom oscillators and indicators
Multi-timeframe strategies
📋 Default Settings
Position Size: 10% of equity
Stop Loss: 2% percentage-based
Trailing Stop: 1.5% percentage-based (enabled)
Take Profit: Disabled (optional)
Trade Direction: Both long and short
Time Filter: Disabled
Momentum Long + Short Strategy (BTC 3H)Momentum Long + Short Strategy (BTC 3H)
🔍 How It Works, Step by Step
Detect the Trend (📈/📉)
Calculate two moving averages (100-period and 500-period), either EMA or SMA.
For longs, we require MA100 > MA500 (uptrend).
For shorts, we block entries if MA100 exceeds MA500 by more than a set percentage (to avoid fading a powerful uptrend).
Apply Momentum Filters (⚡️)
RSI Filter: Measures recent strength—only allow longs when RSI crosses above its smoothed average, and shorts when RSI dips below the oversold threshold.
ADX Filter: Gauges trend strength—ensures we only enter when a meaningful trend exists (optional).
ATR Filter: Confirms volatility—avoids choppy, low-volatility conditions by requiring ATR to exceed its smoothed value (optional).
Confirm Entry Conditions (✅)
Long Entry:
Price is above both MAs
Trend alignment & optional filters pass ✅
Short Entry:
Price is below both MAs and below the lower Bollinger Band
RSI is sufficiently oversold
Trend-blocker & ATR filter pass ✅
Position Sizing & Risk (💰)
Each trade uses 100 % of account equity by default.
One pyramid addition allowed, so you can scale in if the move continues.
Commission and slippage assumptions built in for realistic backtests.
Stops & Exits (🛑)
Long Stop-Loss: e.g. 3 % below entry.
Long Auto-Exit: If price falls back under the 500-period MA.
Short Stop-Loss: e.g. 3 % above entry.
Short Take-Profit: e.g. 4 % below entry.
🎨 Why It’s Powerful & Customizable
Modular Filters: Turn on/off RSI, ADX, ATR filters to suit different market regimes.
Adjustable Thresholds: Fine-tune stop-loss %, take-profit %, RSI lengths, MA gaps and more.
Multi-Timeframe Potential: Although coded for 3 h BTC, you can adapt it to stocks, forex or other cryptos—just recalibrate!
Backtest Fine-Tuned: Default settings were optimized via backtesting on historical BTC data—but they’re not guarantees of future performance.
⚠️ Warning & Disclaimer
This strategy is for educational purposes only and designed for a toy fund. Crypto markets are highly volatile—you can lose 100 % of your capital. It is not a predictive “holy grail” but a rules-based framework using past data. The parameters have been fine-tuned on historical data and are not valid for future trades without fresh calibration. Always practice with paper-trading first, use proper risk management, and do your own research before risking real money. 🚨🔒
Good luck exploring and experimenting! 🚀📊
Fusion Sniper X [ Crypto Strategy]📌 Fusion Sniper X — Description for TradingView
Overview:
Fusion Sniper X is a purpose-built algorithmic trading strategy designed for cryptocurrency markets, especially effective on the 1-hour chart. It combines advanced trend analysis, momentum filtering, volatility confirmation, and dynamic trade management to deliver a fast-reacting, high-precision trading system. This script is not a basic mashup of indicators, but a fully integrated strategy with logical synergy between components, internal equity management, and visual trade analytics via a customizable dashboard.
🔍 How It Works
🔸 Trend Detection – McGinley Dynamic + Gradient Slope
McGinley Dynamic is used as the baseline to reflect adaptive price action more responsively than standard moving averages.
A custom gradient filter, calculated using the slope of the McGinley line normalized by ATR, determines if the market is trending up or down.
trendUp when slope > 0
trendDown when slope < 0
🔸 Momentum Confirmation – ZLEMA-Smoothed CCI
CCI (Commodity Channel Index) is used to detect momentum strength and direction.
It is further smoothed with ZLEMA (Zero Lag EMA) to reduce noise while keeping lag minimal.
Entry is confirmed when:
CCI > 0 (Bullish momentum)
CCI < 0 (Bearish momentum)
🔸 Volume Confirmation – Relative Volume Spike Filter
Uses a 20-period EMA of volume to calculate the expected average.
Trades are only triggered if real-time volume exceeds this average by a user-defined multiplier (default: 1.5x), filtering out low-conviction signals.
🔸 Trap Detection – Wick-to-Body Reversal Filter
Filters out potential trap candles using wick-to-body ratio and body size compared to ATR.
Avoids entering on manipulative price spikes where:
Long traps show large lower wicks.
Short traps show large upper wicks.
🔸 Entry Conditions
A trade is only allowed when:
Within selected date range
Cooldown between trades is respected
Daily drawdown guard is not triggered
All of the following align:
Trend direction (McGinley slope)
Momentum confirmation (CCI ZLEMA)
Volume spike active
No trap candle detected
🎯 Trade Management Logic
✅ Take Profit (TP1/TP2 System)
TP1: 50% of the position is closed at a predefined % gain (default 2%).
TP2: Remaining 100% is closed at a higher profit level (default 4%).
🛑 Stop Loss
A fixed 2% stop loss is enforced per position using strategy.exit(..., stop=...) logic.
Stop loss is active for both TP2 and primary entries and updates the dashboard if triggered.
❄️ Cooldown & Equity Protection
A user-defined cooldown period (in bars) prevents overtrading.
A daily equity loss guard blocks new trades if portfolio drawdown exceeds a % threshold (default: 2.5%).
📊 Real-Time Dashboard (On-Chart Table)
Fusion Sniper X features a futuristic, color-coded dashboard with theme controls, showing:
Current position and entry price
Real-time profit/loss (%)
TP1, TP2, and SL status
Trend and momentum direction
Volume spike state and trap candle alerts
Trade statistics: total, win/loss, drawdown
Symbol and timeframe display
Themes include: Neon, Cyber, Monochrome, and Dark Techno.
📈 Visuals
McGinley baseline is plotted in orange for trend bias.
Bar colors reflect active positions (green for long, red for short).
Stop loss line plotted in red when active.
Background shading highlights active volume spikes.
✅ Why It’s Not Just a Mashup
Fusion Sniper X is an original system architecture built on:
Custom logic (gradient-based trend slope, wick trap rejection)
Synergistic indicator stacking (ZLEMA-smoothed momentum, ATR-based slope)
Position and equity tracking (not just signal-based plotting)
Intelligent risk control with take-profits, stop losses, cooldown, and max loss rules
An interactive dashboard that enhances usability and transparency
Every component has a distinct role in the system, and none are used as-is from public sources without modification or integration logic. The design follows a cohesive and rule-based structure for algorithmic execution.
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It does not constitute financial advice. Trading cryptocurrencies involves substantial risk, and past performance is not indicative of future results. Always backtest and forward-test before using on a live account. Use at your own risk.
📅 Backtest Range & Market Conditions Note
The performance results displayed for Fusion Sniper X are based on a focused backtest period from December 1, 2024 to May 10, 2025. This range was chosen intentionally due to the dynamic and volatile nature of cryptocurrency markets, where structural and behavioral shifts can occur rapidly. By evaluating over a shorter, recent time window, the strategy is tuned to current market mechanics and avoids misleading results that could come from outdated market regimes. This ensures more realistic, forward-aligned performance — particularly important for high-frequency systems operating on the 1-hour timeframe.
Praetor Sentinel V11.2 NOLOOSE BETA📈 Praetor Sentinel V11.2 – "NOLOOSE BETA"
Algorithmic Trading Strategy for Trend Markets with Adaptive Risk Management
Praetor Sentinel V11.2 is an advanced algorithmic trading strategy for TradingView, specifically designed to operate in strong trend conditions. It combines multiple technical systems—including dynamic trend filters, multi-layer EMA structures, ADX-based volatility control, and adaptive trailing stops—into a powerful and automated trading framework.
🔧 Core Features
Multi-EMA Trend Detection: Two EMA pairs (short/long) to identify and confirm directional trends.
XO-EMA Breakout Logic: Fast EMA crossover to detect breakout opportunities.
ADX Trend Filter: Trades only during strong market trends (above custom ADX threshold).
HTF Filter: Optional higher timeframe trend confirmation (e.g. Daily 50 EMA).
VWAP Validation: Ensures entries aren't taken against the volumetric average.
RSI Filter: Adds a momentum filter (e.g. RSI > 50 for long trades).
🎯 Entry Signals
The strategy uses two entry types:
Breakout Entries: Based on XO-EMA cross and multi-EMA trend alignment.
Pullback Entries: Configurable via various methods such as EMA21 reentry, RSI reversal, engulfing candles, or VWAP reclaim.
All entries can be delayed via confirmation candle logic, requiring a bullish or bearish follow-up bar.
🛡️ Risk Management & Exit Logic
Dynamic ATR Trailing Stop: Adjusts stop distance according to market volatility with optional swing high/low protection.
Break-Even Logic: Locks in trades at breakeven once a defined profit is reached.
Hard Stop-Loss: Caps potential loss per trade with a fixed % (e.g. 1%).
Safe Mode ("NOLOOSE"): Exits early if price moves too far against the position — ideal for automated bots that must avoid drawdowns.
🤖 Automation & Alerts
This strategy is fully automatable with services like 3Commas using built-in alert messages for entries and exits.
All parameters are fully configurable to adapt to different assets, timeframes, and trading styles.
⚙️ Additional Features
Configurable leverage & position sizing
Time-based trading window
Built-in Anchored VWAP
Modular design for easy extension
📌 Summary
Praetor Sentinel V11.2 is a professional-grade tool for trend traders who want rule-based entry/exit logic, adaptive stop systems, and robust protection features. When paired with automation tools, it offers a reliable, low-maintenance setup that emphasizes safety, structure, and scalability.
🛠 How to Use Praetor Sentinel V11.2 – NOLOOSE BETA
🔍 1. Basic Configuration (Required)
Setting Description
Enable Long Trades Enables long (buy) positions.
Enable Short Trades Enables short (sell) positions.
Leverage Used for position sizing calculations.
Position Size % Defines % of capital to be used per trade.
⏰ 2. Time Filter (Optional)
Restricts trading to a defined time range.
Setting Description
Start Date Start date for strategy to be active.
End Date End date for strategy to stop.
Time Zone Time zone for above settings.
📊 3. Trend Setup (Essential for Entry Signals)
Setting Description
MA Type Type of moving average: EMA or SMA.
EMA1/2 Short & Long Two EMA-based systems to determine trend.
Fast/Slow EMA (XO) Used for crossover breakout detection.
HTF Filter Uses higher timeframe trend for additional confirmation.
RSI Filter Confirms entries only if momentum (RSI) supports it.
ADX Threshold Ensures trades only occur during strong trends.
🎯 4. Entry Logic
Setting Description
Pullback Entry Type Enables optional entry setups:
"Off"
"EMA21"
"RSI"
"Engulfing"
"VWAP"
| Use Confirmation Candle | Entry is delayed until a confirmation bar appears. |
| VWAP Confirmation | Trade only if price is above/below the VWAP (based on direction). |
Note: You can combine breakout + pullback signals. Only one has to trigger.
🧯 5. Risk Control & Exit Settings
Setting Description
Trailing Stop Mode
"Standard": Classic trailing stop
"Dynamic ATR": Adjusts to current volatility
"Dynamic ATR + Swing": Adds swing high/low buffer
| Enable Break-Even | Moves SL to breakeven once a target % gain is reached. |
| Enable Hard Stop-Loss | Fixed stop-loss (e.g. 1%) to cap trade risk. |
| Enable Safe Mode | Exits trade early if price moves against it beyond defined % (e.g. 0.3%). |
🔔 6. Alerts & Bot Automation
Setting Description
Entry Long/Short Msg Text message sent via alert when a position opens.
Exit Long/Short Msg Alert message for stop-loss/exit logic.
How to automate with 3Commas:
Load the strategy on your chart.
Manually create alerts using "Create Alert" in TradingView.
Use the built-in alert_message values for bot integration.
✅ Recommended Settings (Example for BTC/ETH on 1H)
Long & Short: ✅ Enabled
Leverage: 2.0
Timeframe: 1H
Pullback Entry: "EMA21"
MA Type: EMA
HTF Filter: Enabled (Daily EMA50)
RSI Filter: Enabled
VWAP Filter: Enabled
Break-Even: On at 0.5%
Hard SL: 1.0%
Safe Mode: On at -0.3%
Trailing Stop: "Dynamic ATR + Swing"
📘 Pro Tips for Testing & Customization
Use the Strategy Tester in TradingView to analyze performance over different assets.
Experiment with timeframes and entry modes.
Ideal for trending assets like BTC, ETH, SOL, etc.
You can expand it with take-profit logic, fixed TPs, indicator exits, etc.
Dskyz (DAFE) MAtrix with ATR-Powered Precision Dskyz (DAFE) MAtrix with ATR-Powered Precision
This cutting‐edge futures trading strategy built to thrive in rapidly changing market conditions. Developed for high-frequency futures trading on instruments such as the CME Mini MNQ, this strategy leverages a matrix of sophisticated moving averages combined with ATR-based filters to pinpoint high-probability entries and exits. Its unique combination of adaptable technical indicators and multi-timeframe trend filtering sets it apart from standard strategies, providing enhanced precision and dynamic responsiveness.
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Core Functional Components
1. Advanced Moving Averages
A distinguishing feature of the DAFE strategy is its robust, multi-choice moving averages (MAs). Clients can choose from a wide array of MAs—each with specific strengths—in order to fine-tune their trading signals. The code includes user-defined functions for the following MAs:
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Hull Moving Average (HMA):
The hma(src, len) function calculates the HMA by using weighted moving averages (WMAs) to reduce lag considerably while smoothing price data. This function computes an intermediate WMA of half the specified length, then a full-length WMA, and finally applies a further WMA over the square root of the length. This design allows for rapid adaptation to price changes without the typical delays of traditional moving averages.
Triple Exponential Moving Average (TEMA):
Implemented via tema(src, len), TEMA uses three consecutive exponential moving averages (EMAs) to effectively cancel out lag and capture price momentum. The final formula—3 * (ema1 - ema2) + ema3—produces a highly responsive indicator that filters out short-term noise.
Double Exponential Moving Average (DEMA):
Through the dema(src, len) function, DEMA calculates an EMA and then a second EMA on top of it. Its simplified formula of 2 * ema1 - ema2 provides a smoother curve than a single EMA while maintaining enhanced responsiveness.
Volume Weighted Moving Average (VWMA):
With vwma(src, len), this MA accounts for trading volume by weighting the price, thereby offering a more contextual picture of market activity. This is crucial when volume spikes indicate significant moves.
Zero Lag EMA (ZLEMA):
The zlema(src, len) function applies a correction to reduce the inherent lag found in EMAs. By subtracting a calculated lag (based on half the moving average window), ZLEMA is exceptionally attuned to recent price movements.
Arnaud Legoux Moving Average (ALMA):
The alma(src, len, offset, sigma) function introduces ALMA—a type of moving average designed to be less affected by outliers. With parameters for offset and sigma, it allows customization of the degree to which the MA reacts to market noise.
Kaufman Adaptive Moving Average (KAMA):
The custom kama(src, len) function is noteworthy for its adaptive nature. It computes an efficiency ratio by comparing price change against volatility, then dynamically adjusts its smoothing constant. This results in an MA that quickly responds during trending periods while remaining smoothed during consolidation.
Each of these functions—integrated into the strategy—is selectable by the trader (via the fastMAType and slowMAType inputs). This flexibility permits the tailored application of the MA most suited to current market dynamics and individual risk management preferences.
2. ATR-Based Filters and Risk Controls
ATR Calculation and Volatility Filter:
The strategy computes the Average True Range (ATR) over a user-defined period (atrPeriod). ATR is then used to derive both:
Volatility Assessment: Expressed as a ratio of ATR to closing price, ensuring that trades are taken only when volatility remains within a safe, predefined threshold (volatilityThreshold).
ATR-Based Entry Filters: Implemented as atrFilterLong and atrFilterShort, these conditions ensure that for long entries the price is sufficiently above the slow MA and vice versa for shorts. This acts as an additional confirmation filter.
Dynamic Exit Management:
The exit logic employs a dual approach:
Fixed Stop and Profit Target: Stops and targets are set at multiples of ATR (fixedStopMultiplier and profitTargetATRMult), helping manage risk in volatile markets.
Trailing Stop Adjustments: A trailing stop is calculated using the ATR multiplied by a user-defined offset (trailOffset), which captures additional profits as the trade moves favorably while protecting against reversals.
3. Multi-Timeframe Trend Filtering
The strategy enhances its signal reliability by leveraging a secondary, higher timeframe analysis:
15-Minute Trend Analysis:
By retrieving 15-minute moving averages (fastMA15m and slowMA15m) via request.security, the strategy determines the broader market trend. This secondary filter (enabled or disabled through useTrendFilter) ensures that entries are aligned with the prevailing market direction, thereby reducing the incidence of false signals.
4. Signal and Execution Logic
Combined MA Alignment:
The entry conditions are based primarily on the alignment of the fast and slow MAs. A long condition is triggered when the current price is above both MAs and the fast MA is above the slow MA—complemented by the ATR filter and volume conditions. The reverse applies for a short condition.
Volume and Time Window Validation:
Trades are permitted only if the current volume exceeds a minimum (minVolume) and the current hour falls within the predefined trading window (tradingStartHour to tradingEndHour). An additional volume spike check (comparing current volume to a moving average of past volumes) further filters for optimal market conditions.
Comprehensive Order Execution:
The strategy utilizes flexible order execution functions that allow pyramiding (up to 10 positions), ensuring that it can scale into positions as favorable conditions persist. The use of both market entries and automated exits (with profit targets, stop-losses, and trailing stops) ensures that risk is managed at every step.
5. Integrated Dashboard and Metrics
For transparency and real-time analysis, the strategy includes:
On-Chart Visualizations:
Both fast and slow MAs are plotted on the chart, making it easy to see the market’s technical foundation.
Dynamic Metrics Dashboard:
A built-in table displays crucial performance statistics—including current profit/loss, equity, ATR (both raw and as a percentage), and the percentage gap between the moving averages. These metrics offer immediate insight into the health and performance of the strategy.
Input Parameters: Detailed Breakdown
Every input is meticulously designed to offer granular control:
Fast & Slow Lengths:
Determine the window size for the fast and slow moving averages. Smaller values yield more sensitivity, while larger values provide a smoother, delayed response.
Fast/Slow MA Types:
Choose the type of moving average for fast and slow signals. The versatility—from basic SMA and EMA to more complex ones like HMA, TEMA, ZLEMA, ALMA, and KAMA—allows customization to fit different market scenarios.
ATR Parameters:
atrPeriod and atrMultiplier shape the volatility assessment, directly affecting entry filters and risk management through stop-loss and profit target levels.
Trend and Volume Filters:
Inputs such as useTrendFilter, minVolume, and the volume spike condition help confirm that a trade occurs in active, trending markets rather than during periods of low liquidity or market noise.
Trading Hours:
Restricting trade execution to specific hours (tradingStartHour and tradingEndHour) helps avoid illiquid or choppy markets outside of prime trading sessions.
Exit Strategies:
Parameters like trailOffset, profitTargetATRMult, and fixedStopMultiplier provide multiple layers of risk management and profit protection by tailoring how exits are generated relative to current market conditions.
Pyramiding and Fixed Trade Quantity:
The strategy supports multiple entries within a trend (up to 10 positions) and sets a predefined trade quantity (fixedQuantity) to maintain consistent exposure and risk per trade.
Dashboard Controls:
The resetDashboard input allows for on-the-fly resetting of performance metrics, keeping the strategy’s performance dashboard accurate and up-to-date.
Why This Strategy is Truly Exceptional
Multi-Faceted Adaptability:
The ability to switch seamlessly between various moving average types—each suited to particular market conditions—enables the strategy to adapt dynamically. This is a testament to the high level of coding sophistication and market insight infused within the system.
Robust Risk Management:
The integration of ATR-based stops, profit targets, and trailing stops ensures that every trade is executed with well-defined risk parameters. The system is designed to mitigate unexpected market swings while optimizing profit capture.
Comprehensive Market Filtering:
By combining moving average crossovers with volume analysis, volatility thresholds, and multi-timeframe trend filters, the strategy only enters trades under the most favorable conditions. This multi-layered filtering reduces noise and enhances signal quality.
-Final Thoughts-
The Dskyz Adaptive Futures Elite (DAFE) MAtrix with ATR-Powered Precision strategy is not just another trading algorithm—it is a multi-dimensional, fully customizable system built on advanced technical principles and sophisticated risk management techniques. Every function and input parameter has been carefully engineered to provide traders with a system that is both powerful and transparent.
For clients seeking a state-of-the-art trading solution that adapts dynamically to market conditions while maintaining strict discipline in risk management, this strategy truly stands in a class of its own.
****Please show support if you enjoyed this strategy. I'll have more coming out in the near future!!
-Dskyz
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Heiken Ashi Supertrend ADX - StrategyHeiken Ashi Supertrend ADX Strategy
Overview
This strategy combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement.
Supertrend Filter : Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop : Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters: All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters: Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings: Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
Recommended Timeframes: Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Position Sizing: The strategy uses a percentage of equity approach (default: 3%) for position sizing
Performance Characteristics
When properly optimized, this strategy has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This strategy represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Trend Strategy + Impulse FilterThis is a Trend Strategy + Impulse Filter designed for trading in a dynamic market using both Simple Moving Average (SMA) and MACD indicators for trend and momentum analysis. The strategy includes risk management features like Stop Loss, Take Profit, and Trailing Stop to secure gains and limit losses. Additionally, it uses a Breakout Filter for confirmation, ensuring trades are taken only when the price breaks out from a specified range.
Key Features:
Trend Filter: Enter long when the price is above the SMA and MACD line crosses above the signal line. Enter short when the price is below the SMA and MACD line crosses below the signal line.
Breakout Filter: Only takes trades if the price breaks the previous high (for long) or low (for short) within a defined lookback period.
Risk Management: Set stop-loss and take-profit levels based on ATR for dynamic risk management.
Trailing Stop: Locks profits as the price moves in favor of the trade.
Position Sizing: Trade size is based on a percentage of the current equity.
Customizable Parameters: All indicators and risk management settings are adjustable to fit individual preferences.
This strategy is suitable for traders looking for a comprehensive approach that combines trend-following, momentum, and breakout filtering with solid risk management.
Ukrainian Description:
Це стратегія Trend + Impulse Filter, розроблена для торгівлі на динамічному ринку, використовуючи індикатори Простого ковзаючого середнього (SMA) та MACD для аналізу тренду та імпульсу. Стратегія включає в себе функції управління ризиками, такі як Stop Loss, Take Profit та Trailing Stop, щоб забезпечити прибутки та обмежити збитки. Крім того, вона використовує Breakout Filter для підтвердження, забезпечуючи виконання угод лише тоді, коли ціна пробиває визначений діапазон.
Основні характеристики:
Фільтр тренду: Вхід у лонг, коли ціна вище SMA, і MACD лінія перетинає сигнальну лінію знизу вгору. Вхід у шорт, коли ціна нижча за SMA, і MACD лінія перетинає сигнальну лінію зверху вниз.
Фільтр пробою: Торгові угоди відкриваються лише в разі пробою попереднього максимуму (для лонга) або мінімуму (для шорта) протягом заданого періоду.
Управління ризиками: Стоп-лосс та тейк-профіт визначаються на основі ATR для динамічного управління ризиками.
Trailing Stop: Фіксує прибутки, коли ціна рухається в бік угоди.
Розмір позиції: Розмір угоди залежить від відсотка від поточного балансу.
Налаштовувані параметри: Усі індикатори та налаштування управління ризиками можна відкоригувати відповідно до індивідуальних уподобань.
Ця стратегія підходить для трейдерів, які шукають комплексний підхід, що поєднує слідкування за трендом, імпульсом та фільтрацією пробоїв із надійним управлінням ризиками.
Scalping Strategy Signal v2 by [INFINITYTRADER]Overview
This Pine Script (v6) implements a scalping strategy that uses higher timeframe data (default: 4H) to generate entry and exit signals, originally designed for the 15-minute timeframe with an option for 30-minute charts. The "Scalping Strategy Signal v2 by " integrates moving averages, RSI, volume, ATR, and candlestick patterns to identify trading opportunities. It features adjustable risk management with ATR-based stop-loss, take-profit, and trailing stops, plus dynamic position sizing based on user-set capital. Trades trigger only on the higher timeframe candle close (e.g., 4H) to limit activity within the same period. This closed-source script offers a structured scalping approach, blending multiple entry methods and risk controls for adaptability across market conditions.
What Makes It Unique
Unlike typical scalping scripts relying on single-indicator triggers (e.g., RSI alone or basic MA crossovers), this strategy combines four distinct entry methods—standard MA crossovers, RSI-based momentum shifts, trend-following shorts, and candlestick pattern logic—evaluated on a 4H timeframe for confirmation. This multi-layered design, paired with re-entry logic after losses and a mix of manual, ATR-based, and trailing exits, aims to balance trade frequency and reliability. The higher timeframe filter adds precision not commonly found in simpler scalping tools, while the 30-minute option enhances consistency by reducing noise.
How It Works
Timeframe Logic
Runs on a base timeframe (designed for 15-minute charts, with a 30-minute option) while pulling data from a user-chosen higher timeframe (default: 4H) for signal accuracy.
Limits entries to the close of each 4H candle, ensuring one trade per period to avoid over-trading in volatile conditions.
Indicators and Data
Moving Averages : Employs 21-period and 50-period simple moving averages on the higher timeframe to detect trends and signal entries/exits.
Volume : Requires volume to exceed 70% of its 20-period average on the higher timeframe for momentum confirmation.
RSI : Uses a 14-period RSI for overbought/oversold filtering and a 6-period RSI for precise entry timing.
ATR : Applies a 14-period Average True Range on the higher timeframe to set adaptive stop-loss and take-profit levels.
Candlestick Patterns : Analyzes consecutive green or red 4H bars for trend continuation signals.
Why These Indicators
The blend of moving averages, RSI, volume, ATR, and candlestick patterns forms a robust scalping framework. Moving averages establish trend context, RSI filters momentum and avoids extremes, volume confirms market activity, ATR adjusts risk to volatility, and candlestick patterns enhance entry timing with price action insights. Together, they target small, frequent moves in flat or trending markets, with the 4H filter reducing false signals common in lower-timeframe scalping.
Entry Conditions
Four entry methods are evaluated at the 4H candle close:
Standard Long Entry: Price crosses above the 21-period moving average, volume exceeds 70% of its 20-period average, and the 1H 14-period RSI is below 70—confirms uptrend momentum.
Special Long Entry: The 6-period RSI crosses above 23, price is more than 1.5 times the ATR from the 21-period moving average, and price exceeds its prior close—targets oversold bounces with a stop-loss at the 4H candle’s low.
Short Entries:
- RSI-Based: The 6-period RSI crosses below 68 with volume support—catches overbought pullbacks.
- Trend-Based: Price crosses below the 21-period moving average, volume is above 70% of its average, and the 1H 14-period RSI is above 30—confirms downtrends.
Red/Green Bar Logic: Two consecutive green 4H bars for longs or red 4H bars for shorts—uses candlestick patterns for continuation, with a tight stop-loss from the base timeframe candle.
Re-Entry Logic
Long : After a losing special long, triggers when the 6-period RSI crosses 27 and price crosses the 21-period moving average.
Short : After a losing short, triggers when the 6-period RSI crosses 50 and price crosses below the 21-period moving average.
Purpose: Offers recovery opportunities with stricter conditions.
Exit Conditions
Manual Exits: Longs close if the 21-period MA crosses below the 50-period MA or the 1H 14-period RSI exceeds 68; shorts close if the 21-period MA crosses above the 50-period MA or RSI drops below 25.
ATR-Based TP/SL: Stop-loss is entry price ± ATR × 1.5 (default); take-profit is ± ATR × 4 (default), checked at 4H close.
Trailing Stop: Adjusts ±6x ATR from peak/trough, closing if price retraces within 1x ATR.
Special/Tight SL: Special longs exit if price opens below the 4H candle’s low; 4th method entries use the base timeframe candle’s low/high, checked every bar.
Position Sizing
Bases trade value on user-set capital (default: 100 USDT), dividing by the higher timeframe close price for dynamic sizing.
Visualization
Displays a table at the bottom-right with current/previous signals, TP/SL levels, equity, trading pair, and trade size—color-coded for clarity (green for buy, red for sell).
Inputs
Initial Capital (USDT): Sets trade value (default: 100, min: 1).
ATR Stop-Loss Multiplier: Adjusts SL distance (default: 1.5, min: 1).
ATR Take-Profit Multiplier: Adjusts TP distance (default: 4, min: 1).
Higher Timeframe: Selects analysis timeframe (options: 1m, 5m, 15m, 30m, 1H, 4H, D, W; default: 4H).
Usage Notes
Intended Timeframe: Designed for 15-minute charts with 4H confirmation for precision and frequency; 30-minute charts improve consistency by reducing noise.
Backtesting: Adjust ATR multipliers and capital to match your asset’s volatility and risk tolerance.
Risk Management: Combines manual, ATR, and trailing exits—monitor to avoid overexposure.
Limitations: 4H candle-close dependency may delay entries in fast markets; RSI/volume filters can reduce trades in low-momentum periods.
Backtest Observations
Tested on BTC/USDT (4H higher timeframe, default settings: Initial Capital: 100 USDT, ATR SL: 1.5x, ATR TP: 4x) across market conditions, comparing 15-minute and 30-minute charts:
Bull Market (Jul 2023 - Dec 2023):
15-Minute: 277 long, 219 short; Win Rate: 42.74%; P&L: 108%; Drawdown: 1.99%; Profit Factor: 3.074.
30-Minute: 257 long, 215 short; Win Rate: 49.58%; P&L: 116.85%; Drawdown: 2.34%; Profit Factor: 3.14.
Notes: Moving average crossovers and green bar patterns suited this bullish phase; 30-minute improved win rate and P&L by filtering weaker signals.
Bear Market (Jan 2022 - Jun 2022):
15-Minute: 262 long, 211 short; Win Rate: 44.4%; P&L: 239.80%; Drawdown: 3.74%; Profit Factor: 3.419.
30-Minute: 250 long, 200 short; Win Rate: 52.22%; P&L: 258.77%; Drawdown: 5.34%; Profit Factor: 3.461.
Notes: Red bar patterns and RSI shorts thrived in the downtrend; 30-minute cut choppy reversals for better consistency.
Flat Market (Jan 2021 - Jun 2021):
15-Minute: 280 long, 208 short; Win Rate: 51.84%; P&L: 340.33%; Drawdown: 9.59%; Profit Factor: 2.924.
30-Minute: 270 long, 209 short; Win Rate: 55.11%; P&L: 315.42%; Drawdown: 7.21%; Profit Factor: 2.598.
Notes: High trade frequency and P&L showed strength in ranges; 30-minute lowered drawdown for better risk control.
Results reflect historical performance on BTC/USDT with default settings—users should test on their assets and timeframes. Past performance does not guarantee future results and is shared only to illustrate the strategy’s behavior.
Why It Works Well in Flat Markets
A "flat market" lacks strong directional trends, with price oscillating around moving averages, as in Jan 2021 - Jun 2021 for BTC/USDT. This strategy excels here because its crossover-based entries trigger frequently in tight ranges. In trending markets, an exit might not be followed by a new entry without a pullback, but flat markets produce multiple crossovers, enabling more trades. ATR-based TP/SL and trailing stops capture these small swings, while RSI and volume filters ensure momentum, driving high P&L and win rates.
Technical Details
Built in Pine Script v6 for TradingView compatibility.
Prevents overlapping trades with long/short checks.
Handles edge cases like zero division and auto-detects the trading pair’s base currency (e.g., BTC from BTCUSDT).
This strategy suits scalpers seeking structured entries and risk management. Test on 15-minute or 30-minute charts to match your style and market conditions.
FlexATRFlexATR: A Dynamic Multi-Timeframe Trading Strategy
Overview: FlexATR is a versatile trading strategy that dynamically adapts its key parameters based on the timeframe being used. It combines technical signals from exponential moving averages (EMAs) and the Relative Strength Index (RSI) with volatility-based risk management via the Average True Range (ATR). This approach helps filter out false signals while adjusting to varying market conditions — whether you’re trading on a daily chart, intraday charts (30m, 60m, or 5m), or even on higher timeframes like the 4-hour or weekly charts.
How It Works:
Multi-Timeframe Parameter Adaptation: FlexATR is designed to automatically adjust its indicator settings depending on the timeframe:
Daily and Weekly: On higher timeframes, the strategy uses longer periods for the fast and slow EMAs and standard periods for RSI and ATR to capture more meaningful trend confirmations while minimizing noise.
Intraday (e.g., 30m, 60m, 5m, 4h): The parameters are converted from “days” into the corresponding number of bars. For instance, on a 30-minute chart, a “day” might equal 48 bars. The preset values for a 30-minute chart have been slightly reduced (e.g., a fast EMA is set at 0.35 days instead of 0.4) to improve reactivity while maintaining robust filtering.
Signal Generation:
Entry Signals: The strategy enters long positions when the fast EMA crosses above the slow EMA and the RSI is above 50, and it enters short positions when the fast EMA crosses below the slow EMA with the RSI below 50. This dual confirmation helps ensure that signals are reliable.
Risk Management: The ATR is used to compute dynamic levels for stop loss and profit target:
Stop Loss: For a long position, the stop loss is placed at Price - (ATR × Stop Loss Multiplier). For a short position, it is at Price + (ATR × Stop Loss Multiplier).
Profit Target: The profit target is similarly set using the ATR multiplied by a designated profit multiplier.
Dynamic Trailing Stop: FlexATR further incorporates a dynamic trailing stop (if enabled) that adjusts according to the ATR. This trailing stop follows favorable price movements at a distance defined by a multiplier, locking in gains as the trend develops. The use of a trailing stop helps protect profits without requiring a fixed exit point.
Capital Allocation: Each trade is sized at 10% of the total equity. This percentage-based position sizing allows the strategy to scale with your account size. While the current setup assumes no leverage (a 1:1 exposure), the inherent design of the strategy means you can adjust the leverage externally if desired, with risk metrics scaling accordingly.
Visual Representation: For clarity and accessibility (especially for those with color vision deficiencies), FlexATR employs a color-blind friendly palette (the Okabe-Ito palette):
EMA Fast: Displayed in blue.
EMA Slow: Displayed in orange.
Stop Loss Levels: Rendered in vermilion.
Profit Target Levels: Shown in a distinct azzurro (light blue).
Benefits and Considerations:
Reliability: By requiring both EMA crossovers and an RSI confirmation, FlexATR filters out a significant amount of market noise, which reduces false signals at the expense of some delayed entries.
Adaptability: The automatic conversion of “day-based” parameters into bar counts for intraday charts means the strategy remains consistent across different timeframes.
Risk Management: Using the ATR for both fixed and trailing stops allows the strategy to adapt to changing market volatility, helping to protect your capital.
Flexibility: The strategy’s inputs are customizable via the input panel, allowing traders to fine-tune the parameters for different assets or market conditions.
Conclusion: FlexATR is designed as a balanced, adaptive strategy that emphasizes reliability and robust risk management across a variety of timeframes. While it may sometimes enter trades slightly later due to its filtering mechanism, its focus on confirming trends helps reduce the likelihood of false signals. This makes it particularly attractive for traders who prioritize a disciplined, multi-timeframe approach to capturing market trends.
Advanced Adaptive Grid Trading StrategyThis strategy employs an advanced grid trading approach that dynamically adapts to market conditions, including trend, volatility, and risk management considerations. The strategy aims to capitalize on price fluctuations in both rising (long) and falling (short) markets, as well as during sideways movements. It combines multiple indicators to determine the trend and automatically adjusts grid parameters for more efficient trading.
How it Works:
Trend Analysis:
Short, long, and super long Moving Averages (MA) to determine the trend direction.
RSI (Relative Strength Index) to identify overbought and oversold levels, and to confirm the trend.
MACD (Moving Average Convergence Divergence) to confirm momentum and trend direction.
Momentum indicator.
The strategy uses a weighted scoring system to assess trend strength (strong bullish, moderate bullish, strong bearish, moderate bearish, sideways).
Grid System:
The grid size (the distance between buy and sell levels) changes dynamically based on market volatility, using the ATR (Average True Range) indicator.
Grid density also adapts to the trend: in a strong trend, the grid is denser in the direction of the trend.
Grid levels are shifted depending on the trend direction (upwards in a bear market, downwards in a bull market).
Trading Logic:
The strategy opens long positions if the trend is bullish and the price reaches one of the lower grid levels.
It opens short positions if the trend is bearish and the price reaches one of the upper grid levels.
In a sideways market, it can open positions in both directions.
Risk Management:
Stop Loss for every position.
Take Profit for every position.
Trailing Stop Loss to protect profits.
Maximum daily loss limit.
Maximum number of positions limit.
Time-based exit (if the position is open for too long).
Risk-based position sizing (optional).
Input Options:
The strategy offers numerous settings that allow users to customize its operation:
Timeframe: The chart's timeframe (e.g., 1 minute, 5 minutes, 1 hour, 4 hours, 1 day, 1 week).
Base Grid Size (%): The base size of the grid, expressed as a percentage.
Max Positions: The maximum number of open positions allowed.
Use Volatility Grid: If enabled, the grid size changes dynamically based on the ATR indicator.
ATR Length: The period of the ATR indicator.
ATR Multiplier: The multiplier for the ATR to fine-tune the grid size.
RSI Length: The period of the RSI indicator.
RSI Overbought: The overbought level for the RSI.
RSI Oversold: The oversold level for the RSI.
Short MA Length: The period of the short moving average.
Long MA Length: The period of the long moving average.
Super Long MA Length: The period of the super long moving average.
MACD Fast Length: The fast period of the MACD.
MACD Slow Length: The slow period of the MACD.
MACD Signal Length: The period of the MACD signal line.
Stop Loss (%): The stop loss level, expressed as a percentage.
Take Profit (%): The take profit level, expressed as a percentage.
Use Trailing Stop: If enabled, the strategy uses a trailing stop loss.
Trailing Stop (%): The trailing stop loss level, expressed as a percentage.
Max Loss Per Day (%): The maximum daily loss, expressed as a percentage.
Time Based Exit: If enabled, the strategy exits the position after a certain amount of time.
Max Holding Period (hours): The maximum holding time in hours.
Use Risk Based Position: If enabled, the strategy calculates position size based on risk.
Risk Per Trade (%): The risk per trade, expressed as a percentage.
Max Leverage: The maximum leverage.
Important Notes:
This strategy does not guarantee profits. Cryptocurrency markets are volatile, and trading involves risk.
The strategy's effectiveness depends on market conditions and settings.
It is recommended to thoroughly backtest the strategy under various market conditions before using it live.
Past performance is not indicative of future results.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Strategy SuperTrend SDI WebhookThis Pine Script™ strategy is designed for automated trading in TradingView. It combines the SuperTrend indicator and Smoothed Directional Indicator (SDI) to generate buy and sell signals, with additional risk management features like stop loss, take profit, and trailing stop. The script also includes settings for leverage trading, equity-based position sizing, and webhook integration.
Key Features
1. Date-based Trade Execution
The strategy is active only between the start and end dates set by the user.
times ensures that trades occur only within this predefined time range.
2. Position Sizing and Leverage
Uses leverage trading to adjust position size dynamically based on initial equity.
The user can set leverage (leverage) and percentage of equity (usdprcnt).
The position size is calculated dynamically (initial_capital) based on account performance.
3. Take Profit, Stop Loss, and Trailing Stop
Take Profit (tp): Defines the target profit percentage.
Stop Loss (sl): Defines the maximum allowable loss per trade.
Trailing Stop (tr): Adjusts dynamically based on trade performance to lock in profits.
4. SuperTrend Indicator
SuperTrend (ta.supertrend) is used to determine the market trend.
If the price is above the SuperTrend line, it indicates an uptrend (bullish).
If the price is below the SuperTrend line, it signals a downtrend (bearish).
Plots visual indicators (green/red lines and circles) to show trend changes.
5. Smoothed Directional Indicator (SDI)
SDI helps to identify trend strength and momentum.
It calculates +DI (bullish strength) and -DI (bearish strength).
If +DI is higher than -DI, the market is considered bullish.
If -DI is higher than +DI, the market is considered bearish.
The background color changes based on the SDI signal.
6. Buy & Sell Conditions
Long Entry (Buy) Conditions:
SDI confirms an uptrend (+DI > -DI).
SuperTrend confirms an uptrend (price crosses above the SuperTrend line).
Short Entry (Sell) Conditions:
SDI confirms a downtrend (+DI < -DI).
SuperTrend confirms a downtrend (price crosses below the SuperTrend line).
Optionally, trades can be filtered using crossovers (occrs option).
7. Trade Execution and Exits
Market entries:
Long (strategy.entry("Long")) when conditions match.
Short (strategy.entry("Short")) when bearish conditions are met.
Trade exits:
Uses predefined take profit, stop loss, and trailing stop levels.
Positions are closed if the strategy is out of the valid time range.
Usage
Automated Trading Strategy:
Can be integrated with webhooks for automated execution on supported trading platforms.
Trend-Following Strategy:
Uses SuperTrend & SDI to identify trend direction and strength.
Risk-Managed Leverage Trading:
Supports position sizing, stop losses, and trailing stops.
Backtesting & Optimization:
Can be used for historical performance analysis before deploying live.
Conclusion
This strategy is suitable for traders who want to automate their trading using SuperTrend and SDI indicators. It incorporates risk management tools like stop loss, take profit, and trailing stop, making it adaptable for leverage trading. Traders can customize settings, conduct backtests, and integrate it with webhooks for real-time trade execution. 🚀
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
