Inizia

Volatilità

3c Ultimate reversal strategy With scanner and backtester v2This might just be the ultimate strategy to identify reversals. This strategy includes a scanner, a backtester and ability to connect it with you 3 commas bot(See adviced settings below) Strategy: -Signals reversal that happened in the last bar. This signal DO NOT repaint. -Identifies potential reversal that might happen in the current bar but can also not happen depending upon the timeframe closing price. -The strategy combines the Moving Average Trend Changer, SuperTrend (ATR price detection) and ADX. -It reduces the number of false signals in sideways market conditons and give more reliable trade signals. -The signal does not repaint and can be used in any market condition. It determines the trend with high precision. Take profit: -Set 2 separate TP conditions. -You can take profit using percentage, ATR, or RR(Risk Reward), aswell as using Trailing Take Profit. - Use sell signal from the strategy(I often find way better results using that) Stoploss: -You can use either ATR, Percentage or sell signal from the strategy (For now to let the strategy itself decide when to TP or SL, just set these parameters really high.) Scanner: -Identifies coins that are currently in the sell zone -Identifies coins that are currently in the buy zone -Screener explores up to 20 pairs in current graph's time frame. -Optimize the strategy to your liking and use the built in backtester to see if it is a viable strategy. 3commas settings: -For now you can only use simple bots. -Create LONG and SHORT bots for the coins you like to trade and set up alerts(You can send long and short signal from the same alert) -Set TP to 50% the strategy will handle buys and exits based on your inputs. -Set safety orders to 0. I might add DCA to the strategy if testing proves that to be a good solution. -When you have made the bots input the bot ID and token adress in the settings of the strategy. -When creating the alert use this webhook :https://3commas.io/trade_signal/trading_view -In the message field you use {{strategy.order.alert_message}} as the placeholder. In the future this signal might make it to the 3commas marketplace. You can then subscribe to that signal where I have cherrypicked coins based on thorough backtesting and optimization.
Strategia Pine Script®
di Kveie
10
Mean Reverse Grid Algorithm - The Quant ScienceMean Reverse Grid Algorithm - The Quant Science™  is a dynamic grid algorithm that follows the trend and run a mean reverting strategy on average percentage yield variation. DESCRIPTION Trades on different price levels of the grid, following the trend. The grid consists of 10 levels, 5 higher and 5 lower. The grids together create a channel, this channel represents the total percentage change where the algorithm works. The channel also represents the average change yields of the asset, identified during analysis with the "Yield Trend Indicator". The algorithm can be set long or short. 1. Long algorithm:  opens long positions with 20% of the capital every time the price crossunder a lower grid, for a maximum total of 5 simultaneous trades. Trades are closed each time the price crossover a higher grid. 2. Short algorithm:  opens short positions with 20% of the capital every time the price crossover a higher grid, for a maximum total of 5 simultaneous trades. Trades are closed each time the price crossunder a lower grid. USER INTERFACE SETTING The user configures the percentage value of each grid from the user interface. AUTO TRADING COMPLIANT With the user interface, the trader can easily set up this algorithm for automatic trading. Automating it is very simple, activate the alert functions and enter the links generated by your broker. BACKTESTING INCLUDED With the user interface, the trader can adjust the backtesting period of the strategy before putting it live. You can analyze large periods such as years or months or focus on short-term periods. NO LIMIT TIMEFRAME This algorithm can be used on all timeframes and is ideal for lower timeframes. GENERAL FEATURES Multi-strategy:  the algorithm can apply either the long strategy or the short strategy. Built-in alerts:  the algorithm contains alerts that can be customized from the user interface. Integrated grid:  the grid indicator is included. Backtesting included:  automatic backtesting of the strategy is generated based on the values set. Auto-trading compliant:  functions for auto trading are included. ABOUT BACKTESTING Backtesting refers to the period 1 August 2022 - today, ticker: ETH/USDT, timeframe 1H. Initial capital:  $1000.00 Commission per trade:  0.03%
Strategia Pine Script®
di thequantscience
5
Swing Trend StrategyThis script is a trend following system which uses a long term Moving Average to spot the trend in combination with the Average True Range to filter out Fakeouts, limiting the overall drawdown. Default Settings and Calculation: - The trend is detected using the Exponential Moving Average on 200 periods. - The Average True Range is calculated on 10 periods. - The Market is considered in an Uptrend when the price closes above the EMA + ATR. - The Market is considered in a Downtrend when the price closes below the EMA - ATR. - The strategy will open a LONG position when the market is in an Uptrend. - The strategy will close its LONG positions when the price closes below the EMA. - The strategy will open a SHORT position when the market is in a Downtrend. - The strategy will close its SHORT positions when the price closes above the EMA. This script is best suited for the 4h timeframe, and shows good results on BTC and ETH especially. The options allow to modify the type of moving average to use, the period of the moving average, the ATR multiplier to add as well as the possibility to open short trades or not.
Strategia Pine Script®
di Inkedlau
2
Trade HourThis script is just finds the best hour to buy and sell hour in a day by checking chart movements in past For example if the red line is on the 0.63 on BTC/USDT chart it mean the start of 12AM hour on a day is the best hour to buy (all based on It's just for 1 hour time-frame but you can test it on other charts. IMPORTANT: You can change time Zone in strategy settings.to get the real hours as your location timezone IMPORTANT: Its for now just for BTC/USDT but you can optimize and test for other charts... IMPORTANT: A green and red background color calculated for show the user the best places of buy and sell (green : positive signal, red: negative signals) settings : timezone : We choice a time frame for our indicator as our geo location source : A source to calculate rate of change for it Time Period : Time period of ROC indicator About Calculations: 1- We first get a plot that just showing the present hour as a zigzag plot 2- So we use an indicator ( Rate of change ) to calculate chart movements as positive and negative numbers. I tested ROC is the best indicator but you can test close-open or real indicator or etc as indicator. 3 - for observe effects of all previous data we should indicator_cum that just a full sum of indicator values. 4- now we need to split this effects to hours and find out which hour is the best place to buy and which is the best for sell. Ok we should just calculate multiple of hour*indicator and get complete sum of it so: 5- we will divide this number to indicator_cum : (indicator_mul_hour_cum) / indicator_cum 6- Now we have the best hour to buy! and for best sell we should just reverse the ROC indicator and recalculate the best hour for it! 7- A green and red background color calculated for show the user the best places of buy and sell that dynamically changing with observing green and red plots(green : positive signal, red: negative signals) when green plot on 15 so each day on hour 15 the background of strategy indicator will change to 15 and if its go upper after some days and reached to 16 the background green color will move to 16 dynamically.
Strategia Pine Script®
di mablue
1
Bollinger Bands and RSI Short Selling (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus provide the best time for buying and selling it. The relative strength index ( RSI ) is a momentum indicator used in technical analysis . RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition. The short order is placed on assets that present strong momentum when it's more likely that it is about to decrease further. The rule strategy places and closes the order when the following conditions are met: ENTRY The closing price is greater than the upper standard deviation of the Bollinger Bands The RSI is less than 70 EXIT The trade is closed in profit when the RSI is less than 70 Upper standard deviation of the Bollinger Band is greater than the the closing price. This strategy comes with a stop loss and a take profit, and as you can see by the results, it is well suited for a bear market. This trade works very well with ETH (1h timeframe), AVA (4h timeframe), and SOL (3h timeframe) and is backtested from the 1 December 2021 to capture how this strategy would perform in a bear market. To make the results more realistic, the strategy assumes each order to trade 30% of the available capital. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange.
Strategia Pine Script®
di Coinrule
1
LudovicaLudovica is a trend following strategy that works on intraday timeframes (15 minutes). The stop loss is decided based on the last price movement, take profits are projected through a Fibonacci extension. Two different extensions are calculated, based on a filter that affects the last price movement it is chosen which one to use for take profits. Money management is fixed fractional: regardless of the distance between entry point and stop loss, the risk on capital for each trade is decided by the user in the strategy inputs. Take profits from 1 to 4 plan to exit with 15% of the initial size, TPs from 5 to 8 plan to exit with 10% of initial size. There is a trailing stop system to reduce the drawdown of the strategy (note that stop loss moves as the trade develops). Take profits are limit orders, stops (loss or trailing) occur at candlestick close (set alerts on the strategy). Optimized strategies selectable from input panel: -ETHUSDTPERP 15 min -CRVUSDTPERP 15 min v1 -CRVUSDTPERP 15 min v2 -SNXUSDTPERP 15 min Other pairs in development and soon available. This strategy is in beta stage.
Strategia Pine Script®
di cryptokillerlab
Strategy Myth-Busting #1 - UT Bot+STC+Hull [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously. Our first one is an automated version of the " The ULTIMATE Scalping Trading Strategy for 2022 " strategy from " My Trading Journey " who claims to have achieved not only profits but a 98.3% win rate. As you can see from the backtest results below, I was unable to substantiate anything close to that that claim on the same symbol (NVDA), timeframe (5m) with identical instrument settings that " My Trading Journey " was demonstrating with. Strategy Busted. If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me. This strategy uses a combination of 3 open-source public indicators: UT Bot Alerts by QuantNomad STC Indicator - A Better MACD By shayankm Basic Hull Ma Pack tinkered by InSilico Trading Rules: 5 min candles Long New Buy Signal from UT Bot Alerts Strategy STC is green and below 25 and rising Hull Suite is green Short New Sell Signal from UT Bot Alerts Strategy STC is red and above 75 and falling Hull Suite is red
Strategia Pine Script®
di myncrypto
9
[MT Trader] Backtest template w/ Supertrend Strategy---EN: In this strategy template you will find some functions already pre-programmed to be used in your strategies to speed up the programming process, among them we can highlight the default stop loss and take profit functions, which will help to set easily and quickly, defining the price range in which we want to prevent large losses or protect our profits from unexpected market movements. 🔴 Stop Loss: Among the functions of the stop loss are the 4 most known, first we have the fixed percentage range (%) and price ($), when the price reaches this fixed price will limit the losses of the operation avoiding larger losses, then we have the average true range (ATR), a moving average of true range and X period that can give us good reference points to place our stop loss, finally the last point higher or lower is the most used by traders to place their stop loss. In addition, the price range between the entry and stop loss can be converted into a trailing stop loss. 🟢 Take Profit: We have 3 options for take profit, just like stop loss, the fixed range of percentage(%) and price($), are available, in addition to this we have the 1:# ratio option, which multiplies by X number the range between the entry and stop loss to use it as take profit, perfect for strategies that use ATR or last high/low point for their strategy. 📈 Heikin Ashi Entrys: The heikin ashi entries are trades that are calculated based on heikin ashi candles but their price is executed in Japanese candles, thus avoiding the false results that occur in heikin candlestick charts, making that in certain cases better results are obtained in the strategies that are executed with this option compared to Japanese candlesticks. 📊 Dashboard: A more visual and organized way to see the results and data needed for our strategy. Feel free to use this template to program your own strategies, if you find bugs or want to request a new feature let me know in the comments or through my telegram @hvert_mt __________________________________________________________________________________________________________________________________________________ ---ES: En esta plantilla de estrategia podrás encontrar algunas funciones ya pre-programadas para ser usadas en tus estrategias para acelerar procesos de programación, entre ellas podemos destacar las funciones por defecto de stop loss y take profit, que ayudaran a establecer de manera fácil y rápida, definiendo los rango de precio en los que queremos prevenirnos de perdidas grandes o proteger nuestras ganancias de movimientos inesperados del mercado. 🔴 Stop Loss: Entre las funciones del stop loss están las 4 más conocidas, en primer lugar tenemos el rango de porcentaje fijo(%) y el precio($), cuando el precio alcance este precio fijo se limitaran las perdidas de la operación evitando perdidas mas grandes, después tenemos el promedio de rango verdadero(ATR), una media móvil del rango verdadero y X periodo que nos puede dar buenos puntos de referencia para colocar nuestro stop loss, por ultimo el ultimo punto mas alto o mas bajo es de los mas usados por los traders para colocar su stop loss. Adicional a esto, el rango de precio entre la entrada y el stop loss se puede convertir en un trailing stop loss. 🟢 Take Profit: Tenemos 3 opciones para take profit, al igual que en el stop loss, el rango fijo de porcentaje(%) y precio($) se encuentran disponibles, adicional a esto tenemos la opción de ratio 1:#, que multiplica por X numero el rango entre la entrada y el stop loss para usarlo como take profit, perfecto para estrategias que usen ATR o ultimo punto alto/bajo. 📈 Entradas Heikin Ashi: Las entradas Heikin Ashi son trades que son calculados en base a las velas Aeikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas. 📊 Panel de Control: Una manera mas visual y organizada de ver los resultados y datos necesarios de nuestra estrategia. Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mi Telegram: @hvert_mt
Strategia Pine Script®
di VertMT
7
Squeeze Momentum Strategy [LazyBear] Buy Sell TP SL Alerts-Modified version of Squeeze Momentum Indicator by @LazyBear. -Converted to version 5, -Taken inspiration from @KivancOzbilgic for its buy sell calculations, -Used @Bunghole strategy template with Take Profit, Stop Loss and Enable/Disable Toggles -Added Custom Date Backtesting Module ------------------------------------------------------------------------------------------------------------------------ All credit goes to above Problem with original version: The original Squeeze Momentum Strategy did not have buy sell signals and there was alot of confusion as to when to enter and exit. There was no proper strategy that would allow backtesting on which further analysis could be carried out. There are 3 aspects this strategy: 1 ) Strategy Logic (easily toggleable from the dropdown menu from strategy settings) - LazyBear (I have made this simple by using Kivanc technique of Momentums Moving Average Crossover, BUY when MA cross above signal line, SELL when crossdown signal line) - Zero Crossover Line (BUY signal when crossover zero line, and SELL crossdown zero line) 2) Long Short TP and SL - In strategies there is usually only 1 SL and 1 TP, and it is assumed that if a 2% SL giving a good profit %, then it would be best for both long and short. However this is not the case for many. Many markets/pairs, go down with much more speed then they go up with. Hence once we have a profitable backtesting setting, then we should start optimizing Long and Short SL's seperately. Once that is done, we should start optimizing for Long and Short TP's separately, starting with Longs first in both cases. 3) Enable and Disable Toggles of Long and Short Trades - Many markets dont allow short trades, or are not suitable for short trades. In this case it would be much more feasible to disable "Short" Trading and see results of Long Only as a built in graphic view of backtestor provides a more easy to understand data feed as compared to the performance summary in which you have to review long and short profitability separately. 4) Custom Data Backtesting - One of most crucial aspects while optimizing for backtesting is to check a strategies performance on uptrends, downtrend and sideways markets seperately as to understand the weak points of strategy. - Once you enable custom date backtesting, you will see lines on the chart which can be dragged left right based on where you want to start and end the backtesting from and to. Note: - Not a financial advise - Open to feedback, questions, improvements, errors etc. - More info on how the squeeze momentum works visit LazyBear indicator link: Happy Trading! Cheers M Tahreem Alam @mtahreemalam
Strategia Pine Script®
di mtahreemalam
11
Smoothed Heikin Ashi Trend on Chart - TraderHalai BACKTESTSmoothed Heikin Ashi Trend on chart - Backtest This is a backtest of the Smoothed Heikin Ashi Trend indicator, which computes the reverse candle close price required to flip a Heikin Ashi trend from red to green and vice versa. The original indicator can be found in the scripts section of my profile. This particular back test uses this indicator with a Trend following paradigm with a percentage-based stop loss. 

Note, that backtesting performance is not always indicative of future performance, but it does provide some basis for further development and walk-forward / live testing.

Testing was performed on Bitcoin , as this is a primary target market for me to use this kind of strategy. Sample Backtesting results as of 10th June 2022: Backtesting parameters:
 Position size: 10% of equity
 Long stop: 1% below entry
 Short stop: 1% above entry Repainting: Off
 Smoothing: SMA Period: 10
 8 Hour: Number of Trades: 1046

 Gross Return: 249.27 % CAGR Return: 14.04 % 
Max Drawdown: 7.9 % Win percentage: 28.01 % 
Profit Factor (Expectancy): 2.019 
 Average Loss: 0.33 % 
 Average Win: 1.69 %
 Average Time for Loss: 1 day
 Average Time for Win: 5.33 days 

 1 Day:

 Number of Trades: 429

 Gross Return: 458.4 % CAGR Return: 15.76 %
 Max Drawdown: 6.37 % 
Profit Factor (Expectancy): 2.804 
Average Loss: 0.8 % 
 Average Win: 7.2 % Average Time for Loss: 3 days
 Average Time for Win: 16 days


 5 Day: Number of Trades: 69

 Gross Return: 1614.9 % CAGR Return: 26.7 %
 Max Drawdown: 5.7 % 
Profit Factor (Expectancy): 10.451 
Average Loss: 3.64 % 
Average Win: 81.17 %
 Average Time for Loss: 15 days
 Average Time for Win: 85 days Analysis: The strategy is typical amongst trend following strategies with a less regular win rate, but where profits are more significant than losses. Most of the losses are in sideways, low volatility markets. This strategy performs better on higher timeframes, where it shows a positive expectancy of the strategy.

 The average win was positively impacted by Bitcoin’s earlier smaller market cap, as the percentage wins earlier were higher.

 Overall the strategy shows potential for further development and may be suitable for walk-forward testing and out of sample analysis to be considered for a demo trading account. Note in an actual trading setup, you may wish to use this with volatility filters, combined with support resistance zones for a better setup. As always, this post/indicator/strategy is not financial advice, and please do your due diligence before trading this live. Original indicator links: On chart version - Oscillator version - Update - 27/06/2022 Unfortunately, It appears that the original script had been taken down due to auto-moderation because of concerns with no slippage / commission. I have since adjusted the backtest, and re-uploaded to include the following to address these concerns, and show that I am genuinely trying to give back to the community and not mislead anyone: 1) Include commission of 0.1% - to match Binance's maker fees prior to moving to a fee-less model. 2) Include slippage of 10 ticks (This is a realistic slippage figure from searching online for most crypto exchanges) 3) Adjust account balance to 10,000 - since most of us are not millionaires. The rest of the backtesting parameters are comparable to previous results: Backtesting parameters:
 Initial capital: 10000 dollars Position size: 10% of equity
 Long stop: 2% below entry
 Short stop: 2% above entry Repainting: Off
 Smoothing: SMA Period: 10
 Slippage: 10 ticks Commission: 0.1% This script still remains to shows viability / profitablity on higher term timeframes (with slightly higher drawdown), and I have included the backtest report below to document my findings: 8 Hour: Number of Trades: 1082

 Gross Return: 233.02% CAGR Return: 14.04 % 
Max Drawdown: 7.9 % Win percentage: 25.6% 
Profit Factor (Expectancy): 1.627 Average Loss: 0.46 % 
 Average Win: 2.18 %
 Average Time for Loss: 1.33 day
 Average Time for Win: 7.33 days Once again, please do your own research and due dillegence before trading this live. This post is for education and information purposes only, and should not be taken as financial advice.
Strategia Pine Script®
di TraderHalai
4
STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT [Loxx]STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones BT is the backtest strategy for "STD-Filterd, R-squared Adaptive T3 w/ Dynamic Zones " seen below: Included: This backtest uses a special implementation of ATR and ATR smoothing called "True Range Double" which is a range calculation that accounts for volatility skew. You can set the backtest to 1-2 take profits with stop-loss Signals can't exit on the same candle as the entry, this is coded in a way for 1-candle delay post entry This should be coupled with the INDICATOR version linked above for the alerts and signals. Strategies won't paint the signal "L" or "S" until the entry actually happens, but indicators allow this, which is repainting on current candle, but this is an FYI if you want to get serious with Pinescript algorithmic botting You can restrict the backtest by dates It is advised that you understand what Heikin-Ashi candles do to strategies, the default settings for this backtest is NON Heikin-Ashi candles but you have the ability to change that in the source selection This is a mathematically heavy, heavy-lifting strategy with multi-layered adaptivity. Make sure you do your own research so you understand what is happening here. This can be used as its own trading system without any other oscillators, moving average baselines, or volatility/momentum confirmation indicators. What is the T3 moving average? Better Moving Averages Tim Tillson November 1, 1998 Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years. Introduction "Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done." This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced. "Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator. Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus. We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes: It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values. It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits. The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade! Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how: Two Interesting Moving Averages We will examine two benchmark moving averages based on Linear Regression analysis. In both cases, a Linear Regression line of length n is fitted to price data. I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data. We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA . Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present. However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line. These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot. A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2. Filter Techniques Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag. There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by: L' = L(time series) + L(time series - L(time series)) That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to: 2L-L(L) This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994). In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator. We will use these two techniques to construct our better moving average, after we explore the first one a little more closely. Fixing Overshoot An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2. Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once. This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible. The solution to the overshoot problem is to recall what we are doing with twicing: DEMA (n) = EMA (n) + EMA (time series - EMA (n)) The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block: EMA (n) + EMA (time series - EMA (n))*.7; This is algebraically the same as: EMA (n)*1.7-EMA( EMA (n))*.7; I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is: GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v, Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data: T3(n) = GD ( GD ( GD (n))) In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves. What is R-squared Adaptive? One tool available in forecasting the trendiness of the breakout is the coefficient of determination ( R-squared ), a statistical measurement. The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average . R-squared is used here to derive a T3 factor used to modify price before passing price through a six-pole non-linear Kalman filter. What are Dynamic Zones? As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl" Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator. One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem. Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system. An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader. To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition: Find V such that: For dynamic zone buy: P{X <= V}=P1 For dynamic zone sell: P{X >= V}=P2 where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone. The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory. Calculating the Dynamic Zones The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone. For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone. In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone. Included: Bar coloring Signals Alerts Loxx's Expanded Source Types
Strategia Pine Script®
di loxx
1
3C QFL Mean reversalWhat is QFL trading strategy? QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders. What is Base level or Support Level? Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction. In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier. QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes. The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading. Experiment with parameters to find your trading setup. Beware how large your total leveraged position is and how far can market go before you get liquidated! Do that with the help of futures liquidation calculators you can find online! Included: An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage. A graphic interface, so levels are clearly visible and back-test analyzing made easier. Long & Short direction of the strategy. Table display a summary of past trades Vertical colored lines appear when the new maximum deviation from the original price has been reached All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
Strategia Pine Script®
di Kveie
95
Strategy Oil Z ScoreObjective is to find forward looking indicators to find good entries into major index's. In similar vein to my Combo Z Score script I have implemented one looking at oil and oil volatility. Interestingly the script out performs WITHOUT applying the EMA in longer timeframes but under performs in shorter timeframes, for example 2007 vs 2019. Likely due to the bullish nature of the past decade (by and large). You have some options on the underlying included Oil vs OVX (Best), MOVE vs OVX and VIX vs OVX. Oil vs OVX out performs Combo Z Script. Favours Spy over QQQ or derivations (SPXL etc).
Strategia Pine Script®
di jroche1973
ATR + MTF Candles + HullMa + DIThis is a strategy based on a youtube video by TradeIQ: www.youtube.com I've reverse engineered the 1 minute Easy Scalping Sys 3.0 indicator (since it is not open source). The default trading rules are set to the recommendations of TradeIQ but can be adjusted to find maximum performance. This script uses 4 timeframes to color the bars, stop-loss ATR bands to find the stop-loss, Divergence Indicator to find an entry and Hull MA for trend analysis. Special credits go to: @mohamed982 for making Hull MA @veryfid for making ATR Stop Loss Finder @BeikabuOyaji for making ADX and DI
Strategia Pine Script®
di PietervdWerk
9
Inverse MACD + DMI Scalping with Volatility Stop (By Coinrule)This script is focused on shorting during downtrends and utilises two strength based indicators to provide confluence that the start of a short-term downtrend has occurred - catching the opportunity as soon as possible. This script can work well on coins you are planning to hodl for long-term and works especially well whilst using an automated bot that can execute your trades for you. It allows you to hedge your investment by allocating a % of your coins to trade with, whilst not risking your entire holding. This mitigates unrealised losses from hodling as it provides additional cash from the profits made. You can then choose to hodl this cash, or use it to reinvest when the market reaches attractive buying levels. Alternatively, you can use this when trading contracts on futures markets where there is no need to already own the underlying asset prior to shorting it. ENTRY The trading system uses the Momentum Average Convergence Divergence (MACD) indicator and the Directional Movement Index (DMI) indicator to confirm when the best time is for selling. Combining these two indicators prevents trading during uptrends and reduces the likelihood of getting stuck in a market with low volatility. The MACD is a trend following momentum indicator and provides identification of short-term trend direction. In this variation it utilises the 12-period as the fast and 26-period as the slow length EMAs, with signal smoothing set at 9. The DMI indicates what way price is trending and compares prior lows and highs with two lines drawn between each - the positive directional movement line (+DI) and the negative directional movement line (-DI). The trend can be interpreted by comparing the two lines and what line is greater. When the negative DMI is greater than the positive DMI, there are more chances that the asset is trading in a sustained downtrend, and vice versa. The system will enter trades when two conditions are met: 1) The MACD histogram turns bearish. 2) When the negative DMI is greater than the positive DMI. EXIT The strategy comes with a fixed take profit combined with a volatility stop, which acts as a trailing stop to adapt to the trend's strength. Depending on your long-term confidence in the asset, you can edit the fixed take profit to be more conservative or aggressive. The position is closed when: Take-Profit Exit: +8% price decrease from entry price. OR Stop-Loss Exit: Price crosses above the volatility stop. In general, this approach suits medium to long term strategies. The backtesting for this strategy begins on 1 April 2022 to 18 July 2022 in order to demonstrate its results in a bear market. Back testing it further from the beginning of 2022 onwards further also produces good returns. Pairs that produce very strong results include SOLUSDT on the 45m timeframe, MATICUSDT on the 2h timeframe, and AVAUSDT on the 1h timeframe. Generally, the back testing suggests that it works best on the 45m/1h timeframe across most pairs. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Strategia Pine Script®
di Coinrule
1
TASC 2022.08 Trading The Fear Index█ OVERVIEW TASC's August 2022 edition of Traders' Tips includes an article by Markos Katsanos titled "Trading The Fear Index". This script implements a trading strategy called the “daily long/short trading system for ​volatility ETFs” presented in this article. █ CONCEPTS This long-term strategy aims to capitalize on stock market volatility by using exchange-traded funds (ETFs or ETNs) linked to the VIX index. The strategy rules (see below) are based on a combination of the movement of the ​Cboe VIX index, the readings of the stochastic oscillator applied to the SPY ​ETF relative to the ​​VIX, and a custom indicator presented in the article and called the correlation trend . Thus, they are not based on the price movement of the traded ​ETF itself, but rather on the movement of the ​VIX and of the S&P 500 index. This allows the strategy to capture most of the spikes in ​volatility while profiting from the long-term time decay of the traded ETFs. █ STRATEGY RULES Long rules Rising ​volatility: The ​VIX should rise by more than 50% in the last 6 days. Trend: The correlation trend of the ​VIX should be 0.8 or higher and also higher than yesterday's value. ​VIX-​SPY relative position: The 25-day and 10-day ​VIX ​stochastics should be above the 25-day and 10-day ​SPY ​stochastics respectively. In addition, the 10-day ​stochastic of the ​VIX should be above its yesterday's value. Long positions are closed if the 10-day ​stochastic of the ​SPY rises above the 10-day ​​stochastic of the ​VIX or falls below the yesterday's value. Short rules Declining ​volatility: The ​VIX should drop over 20% in the last 6 days and should be down during the last 3 days. ​VIX threshold: The ​VIX should spend less than 35% of time below 15. ​VIX-​SPY relative position: The 10-day ​VIX ​stochastic should be below the 10-day ​SPY ​stochastic. In addition, the 10-day ​SPY ​stochastic should be higher than the yesterday's value. Long positions are closed if the first two Long rules are triggered (Rising ​volatility and Trend). The script allows you to display the readings of the indicators used in the strategy rules in the form of oscillator time series (as in the preview chart) and/or in the form of a table.
Strategia Pine Script®
di PineCodersTASC
Market First - Relative Strength/Weakness (the ZenBot strategy)This market-first trading strategy gives BUY, SHORT, and CLOSE signals based on volume, trend, and relative strength or weakness to the market (SPY by default, can be customized). This indicator is useful for signaling day-trade entries and exits for tickers that are strong (or weak) against the market. Stocks that are showing relative strength (or weakness) to the market, are trending, and have decent movement generate a buy (or short) signal. When the trend runs out, a CLOSE signal is fired. Potential profit (based on ATR) and actual profit is calculated, predicting the type of move expected Unique 'stay in trade' logic helps prevent unnecessary CLOSE signals if a trend is likely to continue A colored plot indicates the strength of the current trend and turns orange/red when the strength is weakened. Crypto traders can uncheck 'Trade during market hours' for 24-hour trading, and should change the comparison ticker from SPY to BTCUSD or something similar for their market. Enjoy! KEY CONCEPTS The three- and five-minute timeframes are used to establish and verify trend ( ADX /DI with custom logic) Entries and exits are based on Parabolic SAR and confirmed on multiple timeframes, trend, and relative volume Relative strength /weakness to the market compares ticker to SPY Chop is avoided at all costs. I've experimented with choppiness indicator below 38, but found that the ADX DI+/- readings work even better. Trend is established using ADX DI+/- readings over 20, confirmed by EMA 5/13 crossover and EMA5 slope Signals will fire only if the average volume for the current 5-min bar is above normal Only tickers with a five-bar / 13 period ATR of 1% the ticker's price generate signal. Only longs above daily-anchored VWAP , shorts below daily-anchored VWAP Signals fire on bar close to prevent repainting / look-ahead bias Indicator labels and alerts generated SIGNALS BUY: up-trending tickers showing relative strength are bought on the three-minute PSAR SELL: when the close price falls below the 1, 3, and 5-minute PSAR, or the ADX DI- falls below 20 SHORT: down-trending tickers with relative weakness are shorted on the three-minute PSAR COVER: when the close price moves above the 1, 3, and 5-minute PSAR, or the ADX DI- falls below 20 ALERTS Alerts are generated on BUY, SELL, SHORT, and COVER signals, as well as optional LOST RELATIVE STRENGTH and LOST RELATIVE WEAKNESS INPUTS Use relative strength /weakness comparison with the market : trigger trades based on the ticker's strength or weakness to the selected comparison ticker (usually SPY for equities or BTCUSD for crypto) [* ]Comparison Ticker for relative strength /weakness : Ticker to compare against for relative strength /weakness Trade during market hours only : Take buy/sells during specified hours. Disable this for crypto trading. [* ]Market hours (market time) : Customize market hours - defaults to 9:30 to 16:00 EST [* ]"Only trade very strong trends" : take trades only if an established trend is very strong ( ADX over 40 ) (DEFAULT = ON) "Limit trade direction to VWAP" : Long trades only above VWAP , shorts below (DEFAULT = ON) "Limit trade direction to Market direction" : Long trades only if SPY (or selected comparison ticker) is up, shorts if the market is down. (DEFAULT= ON) "Limit trades based on a ticker's green/red status for the day" : Long trades if the ticker is green for the day, shorts if red. (DEFAULT = ON)
Strategia Pine Script®
di glst0rm
5
5-8-13 EMAs Strategy (Andrew's Trading Channel)============ ENGLISH ============ - Description: This strategy was designed by "Andrew's Trading Channel" (credits to him for the base strategy). A lot of improvements have been added to the strategy, more conditions, trailing stop, custom stop loss and take profit, everything explained below. - CONDITIONS FOR ENTERING A LONG: EMA 5 crossovers EMA 8. - EXIT LONG: EMA 8 crossovers EMA 8 and closing price goes below EMA 13. - CONDITIONS FOR ENTERING SHORT: EMA 8 crossovers EMA 5. - EXIT SHORT: EMA 5 crossovers EMA 8 and closing price goes above EMA 13. - Visual: All EMAs are visible (5, 8 and 13 periods) with different and customizable colors/width. Position start price, take profit, stop loss and trailing stop (if present) are shown automatically. Background color shows green when LONG conditions are met (and of course, position is opened on the next candle), same for SHORT but red. - Usage and recommendations: As this is a coded strategy, you don't even have to check for indicators, just open and close trades as the strategy shows. There're various customizable settings like optional take profit/stop loss, trailing stop (both based on ATR or any of the EMAs), open only LONGs/SHORTs or both, date range... Take profit and stop loss ATR default values have been tested for scalping on 5 min charts, however feel free to check strategy results and increase the winning rate/profit for your favorite asset. - Customization: As usual I like to make as many aspects of my indicators/strategies customizable, indicators, colors etc., feel free to ask if you feel that something that should be configurable is missing or if you have any ideas to optimize the strategy. ============ ESPAÑOL ============ - Descripción: Esta estrategia fue diseñada por "Andrew's Trading Channel" (créditos a él por la estrategia base). Se han añadido muchas mejoras a la estrategia, más condiciones, trailing stop, stop loss y take profit personalizados, todo explicado a continuación. - CONDICIONES PARA ENTRAR EN LONG: Cruce de EMA 5 con EMA 8 ascendente. - SALIR DE LONG: Cruce de EMA 8 con EMA 5 ascendente y el precio de cierre se sitúa por debajo de la EMA 13. - CONDICIONES PARA ENTRAR EN SHORT: Cruce de EMA 8 con EMA 5 ascendente. - SALIR DE SHORT: Cruce de EMA 5 con EMA 8 ascendente y el precio de cierre se sitúa por encima de la EMA 13. - Visual: Todas las EMAs son visibles (5, 8 y 13 períodos) con colores/anchos y personalizables. El precio de inicio de la posición, el take profit, el stop loss y el trailing stop (si están presentes) se muestran automáticamente. El color de fondo es verde cuando se cumplen las condiciones de LONG (y por supuesto, la posición se abre en la siguiente vela), lo mismo para SHORT pero en rojo. - Uso y recomendaciones: Como esta es una estrategia programada, ni siquiera tienes que comprobar los indicadores, sólo abrir y cerrar las operaciones como te muestra la estrategia. Hay varios ajustes personalizables como el take profit/stop loss opcional, el trailing stop (ambos basados en el ATR o en cualquiera de las EMAs), abrir sólo LONGs/SHORTs o ambos, rango de fechas... Los valores por defecto del take profit y el stop loss ATR han sido probados para scalping en gráficos de 5 minutos, sin embargo, siéntase libre de comprobar los resultados de la estrategia y aumentar la tasa de ganancia / beneficio para su activo favorito. - Personalización: Como siempre me gusta hacer personalizables todos los aspectos de mis indicadores/estrategias, indicadores, colores, etc., siéntase libre de preguntar si cree que falta algo que debería ser configurable o si tiene alguna idea para optimizar la estrategia.
Strategia Pine Script®
di JoseMetal
2