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Bollinger Pair TradeNYSE:MA-1.6*NYSE:V Revision: 1 Author: @ozdemirtrading Revision 2 Considerations : - Simplify and clean up plotting Disclaimer: This strategy is currently working on the 5M chart. Change the length input to accommodate your needs. For the backtesting of more than 3 months, you may need to upgrade your membership. Description: The general idea of the strategy is very straightforward: it takes positions according to the lower and upper Bollinger bands. But I am mainly using this strategy for pair trading stocks. Do not forget that you will get better results if you trade with cointegrated pairs. Bollinger band: Moving average & standard deviation are calculated based on 20 bars on the 1H chart (approx 240 bars on a 5m chart). X-day moving averages (20 days as default) are also used in the background in some of the exit strategy choices. You can define position entry levels as the multipliers of standard deviation (for exp: mult2 as 2 * standard deviation). There are 4 choices for the exit strategy: SMA: Exit when touches simple moving average (SMA) SKP: Skip SMA and do not stop if moving towards 20D SMA, and exit if it touches the other side of the band SKPXDSMA: Skip SMA if moving towards 20D SMA, and exit if it touches 20D SMA NoExit: Exit if it touches the upper & lower band only. Options: - Strategy hard stop: if trade loss reaches a point defined as a percent of the initial capital. Stop taking new positions. (not recommended for pair trade) - Loss per trade: close position if the loss is at a defined level but keeps watching for new positions. - Enable expected profit for trade (expected profit is calculated as the distance to SMA) (recommended for pair trade) - Enable VIX threshold for the following options: (recommended for volatile periods) - Stop trading if VIX for the previous day closes above the threshold - Reverse active trade direction if VIX for the previous day is above the threshold - Take reverse positions (assuming the Bollinger band is going to expand) for all trades Backtesting: Close positions after a defined interval: mark this if you want the close the final trade for backtesting purposes. Unmark it to get live signals. Use custom interval: Backtest specific time periods. Other Options: - Use EMA: use an exponential moving average for the calculations instead of simple moving average - Not against XDSMA: do not take a position against 20D SMA (if X is selected as 20) (recommended for pairs with a clear trend) - Not in XDSMA 1 DEV: do not take a position in 20D SMA 1*standart deviation band (recommended if you need to decrease # of trades and increase profit for trade) - Not in XDSMA 2 DEV: do not take a position in 20D SMA 2*standart deviation band Session management: - Not in session: Session start and end times can be defined here. If you do not want to trade in certain time intervals, mark that session.(helps to reduce slippage and get more realistic backtest results)
Estratégia Pine Script®
por ozdemirtrading
Magic BOXThe Magic BOX strategy is designed to work with cryptocurrency and Forex. Working timeframe from 1 minute to 1 hour. The strategy is based on the formation of a trade zone. Probably everyone has already noticed that every day there is a period of time that sets a certain corridor for further price movement in order to get out of it up or down. In the Magic BOX strategy, you yourself set the period that gives the best result using only 2 parameters - "Start hour" and "Final hour". Every day, the algorithm generates a zone at a selected time and then opens deals to break through the upper or lower level of the resulting trading zone. In addition, the settings have the ability to show additional entries - these are the moments of price rollback to the middle of the zone, as well as repeated breakouts of levels after the completion of the previous transaction. ------------------------------------- 💹 SETUP SETUP: ------------------------------------- To configure, you should change the values ​​"Start hour" and "Final hour" - the hour of the beginning and the hour of the end of the formation of the trading zone. By default, the parameters are 20 hours and 7 hours (the time corresponds to the time zone of the exchange!). To enable additional re-breakout signals, use - "Additional deals (repeat in the zone)" To enable additional signals for position averaging use - "Additional deals (averaging position)" ------------------------------------- 🟢 TAKE SETUP: ------------------------------------- The strategy has 3 types of take: BOX, FIX and DAY_CLOSE BOX - take as a percentage of the width of the formed zone. FIX - take as a percentage of the asset price. DAY_CLOSE - select the hour at the beginning of which we close the position forcibly. ------------------------------------- ⛔️ STOP SETUP: ------------------------------------- The strategy has 3 types of stop line: BOX, FIX and DAY_CLOSE BOX - stop as a percentage of the width of the formed zone. FIX - stop as a percentage of the asset price. DAY_CLOSE - select the hour at the beginning of which we close the position forcibly. ------------------------------------- 💡 OTHER USEFUL FEATURES ------------------------------------- ✅ The screen has a compact display of a table with strategy settings and current level values. For the convenience of saving your settings, use the standard PrintScreen function. ✅ 👉 In the strategy settings, each field has hints, to do this, hover over the ⓘ sign ------------------------------------- Magic BOX strategy is closed! You can get test access to it for 48 hours. 👉 In order to gain access or ask questions, write to me in private messages or at the contacts indicated in my signature. ------------------------------------- ------------------------------------- Magic BOX strategy is closed! You can get test access to it for 48 hours. 👉 In order to gain access or ask questions, write to me in private messages or at the contacts indicated in my signature. ------------------------------------- ======================================================================================================== Стратегия Magic BOX предназначена для работы с криптовалютой и Форексом. Рабочий таймфрейм от 1 минуты до 1 часа. В основе стратегии лежит формирование зоны проторговки. Наверное уже каждый заметил, что каждый день есть период времени, который задаёт некий коридор для дальнейшего движения цены с целью выйти из него вверх или вниз. В стратегии Magic BOX Вы сами задаёте тот период, который даёт наилучший результат с помощью всего 2-х параметров - "Start hour" и "Final hour". Каждый день алгоритм формирует зону в выбранное время и далее открывает сделки на пробой верхнего или нижнего уровня полученной зоны проторговки. Кроме этого в настройках есть возможность показать дополнительные входы - это моменты отката цены к середине зоны, а также повторные пробития уровней, после завершения предыдущей сделки. ------------------------------------- 💹 НАСТРОЙКА СЕТАПА: ------------------------------------- Для настройки следует изменять значения "Start hour" и "Final hour" - час начала и час окончания формирования зоны проторговки. По умолчанию стоят параметры 20 часов и 7 часов (время соответствует времени часовой зоны биржи!). Для включения дополнительных сигналов повторных пробоев используйте - "Additional deals (repeat in the zone)" Для включения дополнительных сигналов на усреднение позиции используйте - "Additional deals (averaging position)" ------------------------------------- 🟢 НАСТРОЙКА ТЕЙКОВ: ------------------------------------- Стратегия имеет 3 типа тейка: BOX, FIX и DAY_CLOSE BOX - тейк в процентах от ширины сформированной зоны. FIX - тейк в процентах от цены актива. DAY_CLOSE - выбираем час, в начале которого принудительно закрываем позицию. ------------------------------------- ⛔️ НАСТРОЙКА СТОПА: ------------------------------------- Стратегия имеет 3 типа стоп-линии: BOX, FIX и DAY_CLOSE BOX - стоп в процентах от ширины сформированной зоны. FIX - стоп в процентах от цены актива. DAY_CLOSE - выбираем час, в начале которого принудительно закрываем позицию. ------------------------------------- 💡 ПРОЧИЕ ПОЛЕЗНЫЕ ФУНКЦИИ ------------------------------------- ✅ На экране есть компактное отображение таблицы с настройками стратегии и текущими значениями уровней. Для удобства сохранения своих настроек - воспользуйтесь стандартной функцией PrintScreen. ✅ 👉 В настройках стратегии у каждого поля есть подсказки, для этого наведите курсор на знак ⓘ ------------------------------------- Стратегия Magic BOX является закрытой! Вы можете получить к ней тестовый доступ на 48 часов. 👉 Для того, чтобы получить доступ или задать вопросы пишите мне в личные сообщения или по контактам, указанным в моей подписи. -------------------------------------
Estratégia Pine Script®
por Shuttle_Club
5
Price change scalping short and long strategyPrice change scalping Short and Long strategy uses a rate of change momentum oscillator to calculate the percent change in price between a period of time. Rate of change calculation takes the current price and compares it to a price of "n" periods while the period of time can be defined by a user. The calculated rate of change value is then compared to the upper threshold and the lower threshold values to determine if a position should be opened. If the threshold is crossed and filtering conditions are met a strategy position will be triggered. Entry, take profit, and stop loss prices are calculated and displayed on the chart as well as positions directions. Once the entry price is crossed, a long or short position is created and once the take profit price is crossed, the stop loss price will begin to trail behind the price action using the close of the previous bar. Once the trailing stop price is crossed, the position is closed. If the entry price is not crossed and the price action crosses the stop level, the trade setup is cancelled. The strategy is enhanced by DCA algorithm which allows to average entry price with safety orders. The script also allows to use Martingale coefficient to increase averaging power Advantages of this script: Strategy has high net profit of 293% at backtests Backtests show high accuracy around 71% High frequency and low duration of trades Can be used with short-term timeframes ranging from 5 to 60 minutes Strategy is sustainable to market slumps due to DCA implementation Can be used for short and long positions (can be adjusted to long only, short only or both) Can be applied to any market and quote currency Easy to configure user interface settings Built in detailed statistic menu How to use? 1. Apply the strategy to a trading pair your are interested in using 5 to 60 minutes timeframe chart 2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage 3. Set up a TradingView alert to trigger when strategy conditions are met 4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms 5. Update settings once market conditions are changed using backtests on a monthly period
Estratégia Pine Script®
por Skyrexio
1
Ichimoku Cloud and Bollinger Bands (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future. The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals. The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in. The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line. The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up. The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down. 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 providing the best time for buying and selling it. This strategy combines the Ichimoku Cloud with Bollinger Bands to better enter trades. Long orders are placed when these basic signals are triggered. Long Position: Tenkan-Sen is above the Kijun-Sen Chikou-Span is above the close of 26 bars ago Close is above the Kumo Cloud The closing price is greater than the upper standard deviation of the Bollinger Bands Short Position: Tenkan-Sen is below the Kijun-Sen Chikou-Span is below the close of 26 bars ago Close is below the Kumo Cloud The upper standard deviation of the Bollinger Band is greater than the closing price The script is backtested from 1 January 2022 and provides good returns. The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance. This script also works well on BTC 30m/1h, ETH 2h, MATIC 2h/30m, AVAX 1h/2h, SOL 45m timeframes
Estratégia Pine Script®
por Coinrule
Consolidation Breakout [Indian Market Timing]OK let's get started , A Day Trading (Intraday) Consolidation Breakout Indication Strategy that explains time condition for Indian Markets . The commission is also included in the strategy . The basic idea is , 1) Price crosses above upper band , indicated by a color change (green) is the Long condition . 2) Price crosses below lower band , indicated by a color change (red) is the Short condition . 3) ATR is used for trailing after entry // ═══════════════════════════════// // ————————> TIME CONDITION <————————— // // ═══════════════════════════════// The Indian Markets open at 9:15am and closes at 3:30pm. The time_condition specifies the time at which Entries should happen . "Close All" function closes all the trades at 2:57pm. All open trades get closed at 2:57pm , because some brokers dont allow you to place fresh intraday orders after 3pm. NSE:NIFTY1! // ═══════════════════════════════════════════════ // // ————————> BACKTEST RESULTS ( 114 CLOSED TRADES )<————————— // // ═══════════════════════════════════════════════ // LENGTH , MULT (factor) and ATR can be changed for better backtest results. The strategy applied to NIFTY (3 min Time-Frame and contract size 5) gives us 60% profitability , as shown below It was tested for a period a 8 months with a Profit Factor of 2.2 , avg Trade of 6000Rs profit and Sharpe Ratio : 0.67 The graph has a Linear Curve with consistent profits. NSE:NIFTY1! Save it favorites. Apply it to your charts Now !! Thank me later ;)
Estratégia Pine Script®
por The_Algo_Engineer
3
QG-Trend Pullback StrategyI wanted to test the pullback strategy shown by TradePro and 5 minute scalping channels on the YT. So here it is, worked on USDCHF pair best and not so much on other forex pairs on 15 min or 5 min charts as shown in strategy. Entry rules for Long: Price above EMA200 or G channel as trend filter Donchian trend ribbon in retracement or red in color Wavetrend cross below a threshold level below zeroline. Opposite rules for Shorts. The SL and TP based on the ATR multiplier and a TP as RR ratio to SL. Attaching the equity curve on USDCHF 15 min chart where it worked best.
Estratégia Pine Script®
por QuantG
3C Reversal Filter v1In essence, this strategy is a heavily smoothed range filter. This strategy includes a backtester and ability to connect it with your 3 commas bot(See adviced settings below) The calculation steps below gives an example on how signals are made: 1. Calculating the price movement using ATR, % change, standard deviation etc.. 2. Obtaining the smoothed price using SMA. 3. Obtaining the absolute value of the bar-to-bar change. 4. Applying EMA, twice, to the values in step 3. 5. Obtaining the slow trailing line by multiplying the result of step 4 by 1.618. Think of it as a heavily smoothed price range If the 1.618 value looks familiar, that’s because it’s used in Fibonacci sequences. You can of course experiment with other values. I’ve seen good results with both 2.618 and 4.236 What does the strategy do? 1. Determine Trend Detection 2. Detect Short-Term Momentum 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.
Estratégia Pine Script®
por Kveie
4
Rob Booker - ADX Breakout updated to pinescript V5Rob Booker - ADX Breakout. The strategy remains unchanged but the code has been updated to pinescript V5. This enables compatibility with all new Tradingview features. Additonally, indicators have been made more easily visible, default cash settings as well as input descriptions have been added. Rob Booker - ADX Breakout: (Directly taken from the official Tradingview V1 version of the script) Definition Rob Booker’s Average Directional Index (ADX) Breakout is a trend strength indicator that affirms the belief that trading in the direction of a trend and continuing to follow its pull is more profitable for traders, while simultaneously reducing risk. History ADX was traditionally used and developed to determine a price’s trend strength. It is commonly known as a tool from the arsenal of Rob Booker, experienced entrepreneur and currency trader. Calculations Calculations for the ADX Breakout indicator are based on a moving average of price range expansion over a specific period of time. By default, the setting rests at 14 bars, this however is not mandatory, as other periods are routinely used for analysis as well. Takeaways The ADX line is used to measure and determine the strength of a trend, and so the direction of this line and its interpretation are crucial in a trader’s analysis. As the ADX line rises, a trend increases in strength and price moves in the trend’s direction. Similarly, if the ADX line is falling, a trend decreases in strength and price then enters a period of consolidation, or retracement. Traditionally, the ADX is plotted on the chart as a single line that consists of values that range from 0-100. The line is non-directional, meaning that it always measures trend strength regardless of the position of a price’s trend (up or down). Essentially, ADX quantifies trend strength by presenting in both uptrends and downtrends of the line. What to look for The values associated with the ADX line help traders determine the most profitable trades and where risk lies in the current trend. It is important to know how to quantify trend strength and distinguish between the varying values in order to understand the differences in trending vs. non-trending conditions. Let’s take a look at ADX values and what they mean for trend strength. ADX Value: 0-25: Signifies an absent of weak trend 25-50: Signifies a strong trend 50-75: Signifies a very strong trend 75-100: Signifies an extremely strong trend To delve into this a bit further, let’s assess the meaning of ADX if it is valued below 25. If the ADX line remains below 25 for more than 30 or so bars, price then enters range conditions, making price patterns more distinguishable and visible to traders. Price will move up and down between resistance and support in order to determine selling and buying interest and may then eventually break out into a trend or pattern. The way in which ADX peaks, ebs, and flows is also a signifier of its overall pattern and trend momentum. The line can clearly indicate to the trader when trend strength is strong versus when it is weak. When ADX peaks are pictured as higher, it points towards an increase in trend momentum. If ADX peaks are pictured as lower - you guessed it - it points towards a decrease in trend momentum. A trend of lower ADX peaks could be a warning for traders to watch prices and manage and assess risk before a trade gets out of hand. Similarly, whenever there is a sudden move that seems out of place or a change in trend character that goes against what you’ve seen before, this should be a clear sign to watch prices and assess risk. Summary The ADX Breakout indicator is a trend strength indicator that analyzes price movements relative to trend strength to signal a user when is best for a trade and when is best to manage risk and assess patterns. As long as a trader recognizes strong trends and assesses the risk of each trade properly, they should have no problem using this indicator and utilizing it to work in their favor. In addition, the ADX helps identify trending conditions, but while doing so, also aids traders in finding strong trends to trade. The indicator can even alert traders to specific changes in trend momentum, allowing them to be primed for risk management.
Estratégia Pine Script®
por Powerscooter
14
Buy/Sell Signal Template/Boilerplate Strategy [MyTradingCoder]This script allows the user to connect an external indicator output/plot value to allow for a no-code solution to setup a simple buy/sell signal strategy. For those of you who do not know how to program, do not be intimidated as this is a very easy setup process. Maybe you want to buy when the 'RSI' value drops below '30' and then sell when the 'RSI' value climbs above '70', but you don't want to code it. You can do that with this indicator along with thousands of others found on the free TradingView indicator library. Step #1: Put the strategy on the chart. Step #2: Apply a secondary indicator onto the chart, such as an RSI . Step #3: Open the strategy settings and change the source to the RSI Step #4: Change the 'Signal Settings' to match when you want a buy, or a sell. For example, if you want to get a buy signal when the RSI crosses above 50, and get a sell when it crosses below 50, set the 'buy value' to 50, and the 'buy type' to greater than, then set the 'sell value' to 50 and the 'sell type' to less than. BOOM! It works :)
Estratégia Pine Script®
por JacobMagleby
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
Estratégia Pine Script®
por loxx
1
Smart Money - Oscillator and Volume StrategyOverview This is a no-repaint strategy that is highly optimized for BINANCE:ETHUSDTPERP 30m, normal candles. It is a long/short strategy that is based on CMF, ADX/DMI, Keltner Channels, and other oscillators to identify smart money. The overall idea of the strategy is to effectively capture the beginnings and ends of trends in price action, and go long/short accordingly. To achieve this, potential entry points are identified with various oscillators and these are then filtered using a variety of moving averages and strength/momentum indicators. Short and sell inflections are found when ADX, DMI, and/or CMF oscillate below a specified threshold, and Keltner Channels are also used to indicate potential trades. The indicator will continue to be updated and optimized for current and future market conditions. If purchased, access to the indicator will be available within 24 hours. Backtest Results Parameters: - 2021-01-01 to present (19 months) - 100% equity order size - 0.04% commission fees - No leverage 17,089% net profit through 296 trades with 60.47% of trades being profitable. Profit factor of 2.862, Sharpe Ratio of 1.158 Parameters: - 2021-01-01 to present (19 months) - $1,000 initial capital - $1,000 order size - 0.04% commission fees - No leverage 584% net profit through 296 trades with 60.47% of trades being profitable. Parameters: - 2021-01-01 to present (19 months) - 500% equity order size - 0.04% commission fees - 5x leverage 8,587,557% net profit through 299 trades with 59.87% of trades being profitable.
Estratégia Pine Script®
por mnuryga
20