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Cari dalam skrip untuk "Volatility"

Jeges JigsThis is a combination of all my old indicators, with an added feature for trend lines (inspiration for this came from Wedge Maker script thanks to veryfid, I hope he doesn't mind). This script looks for a period with increased volatility , as measured by ATR ( Average True Range ), then it looks for a high or a low in that area. When price is above EMA (400 is default, can be changed), it looks for the highs and adds multiples of ATR to the high. Default values for multipliers are 3,9 and 27, meaning that the script will show 3xATR level above the high, 9xATR above the high and 27xATR above the high. When price is below EMA it looks for the lows and subtracts multiples of ATR from the low.The script will show 3xATR level below the low, 9xATR below the low and 27xATR below the low. Multipliers values can be changed as well, making it a versatile tool that shows potential levels of suppport/resistance based on the volatility . Possible use cases: Breakout trading, when price crosses a certain level, it may show potential profit targets for trades opened at a breakout. Stoploss helper. Many traders use ATR for their stoplosses, 1 ATR below the swing low for long trades and 1 ATR above the swing high for short trades are common values used by many traders. In this case, the Lookback value comes handy, if we want to look maybe at a more recent value for swing high/low point. It highlights ATR peaks, it also displays Bollinger bands of SMA400 (or Ema), breakouts for upper/lower bands. Another thing you get is Parabolic SAR and Zigzag based on SAR.
Penunjuk Pine Script®
oleh Troptrap
8
[KL] Mean Reversion (ATR) StrategyThis strategy will enter into a position when price volatility is relative high, betting that price will subsequently trend in a favourable direction. Hypothesis : During periods of high price volatility, ATR will divert from its moving average by at least +/- one standard deviation. Eventually, ATR will revert back to the mean. However, just knowing the magnitude of increase/decrease of ATR does not give a trend signal, so we need to introduce a model in this script to predict whether the next bars will be up/down. Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping or if the drift value is positive. Entry Conditions : Long position is entered when: (a) ATR has diverted from mean by one standard deviation, and (b) trend is predicted to move in our favor. Exit Condition : When trailing stop loss is hit. Results from backtesting against VOO (1H timeframe): - approx 46% win rate over 491 trades, on average holding for 20 hours per trade - price at the beginning of backtest (Jan. 2015) was $187.52, giving holding period return of ~120% had we not sold in between ("HPR of HODL'ing") - this strategy gained ~159%, exceeding ~120% HPR of HODL'ing
Strategi Pine Script®
oleh DojiEmoji
2
MACD-RSI With @LuckyNickVAMACD & RSi Confluence. Great for those who are looking for RSI & macd signals. Highlights volatility & structure points for entering & exiting the market. You have to understand market volatility to understand this concept. So please research more on those subjects before using. But The RSI is the relative strength index it helps you understand the increase in interest in price great for trend trading along with the momentum based indicator. Macd Developed by Gerald Appel, the Moving Average Convergence-Divergence, or MACD, is an oscillator that measures price momentum. The indicator also measures the strength, direction and duration of a trend. Forex traders can use the MACD to confirm an entry price or exit point.
Penunjuk Pine Script®
oleh Nickafella
5
HYE Trend Hunter [Strategy]*** Stratejinin Türkçe ve İngilizce açıklaması aşağıya eklenmiştir. HYE Trend Hunter In this strategy, two of the most basic data (price and volume) necessary for detecting trends as early as possible and entering the trade on time are used. In this context, the approaches of some classical and new generation indicators using price and volume have been taken into account. The strategy is prepared to generate buy signals only. The following steps were followed to generate the buy and exit signals. 1-) First of all, the two most basic data of the strategy, “slow leading line” and “fast leading line” need to be calculated. For this, we use the formula of the “senkou span A” line of the indicator known as the Ichimoku Cloud. We also need to calculate lines known as tenkan sen and kijun sen in ichimoku because they are used in the calculation of this formula. The high and low values of the candles are taken into account when calculating the Tenkansen, Kijunsen and Senkou Span A lines in the Ichimoku cloud. In this strategy, the highest and lowest values of the periodic VWAP are taken into account when calculating the "slow leading line" and "fast leading line". (The periodic vwap formula was coded and made available by @neolao on tradingviev). Also, in the ichimoku cloud, while the Senkou Span A line is plotted 26 periods into the future, we consider the values of the fast and slow leading lines in the last candle in this strategy. ORIGINAL ICHIMOKU SPAN A FORMULA Tenkansen = (Highest high of the last 9 candles + Lowest low of the last 9 candles) / 2 Kijunsen = (Highest high of the last 26 candles + Lowest low of the last 26 candles) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 HYE TREND HUNTER SPAN A FORMULA* Tenkansen = (Highest VWAP of the last 9 candles + Lowest VWAP of the last 9 candles) / 2 Kijunsen = (Highest VWAP of the last 26 candles + Lowest VWAP of the last 26 candles) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 * We use the original ichimoku values 9 and 26 for the slow line, and 5 and 13 for the fast line. These settings can be changed from the strategy settings. 2-) At this stage, we have 2 lines that we obtained by using the formula of the ichimoku cloud, one of the most classical trend indicators, and by including the volume-weighted average price. a-) Fast Leading Line (5-13) b-) Slow Leading Line (9-26) For the calculation we will do soon, we get a new value by taking the average of these two lines. Using this value, which is the average of the fast and slow leading lines, we plot the Bollinger Bands indicator, which is known as one of the most classic volatility indicators of technical analysis. Thus, we are trying to understand whether there is a volatility change in the market, which may mean the presence of a trend start. We will use this data in the calculation of buy-sell signals. In the classical Bollinger Bands calculation, the standard deviation is calculated by applying a multiplier at the rate determined by the user (2 is used in the original settings) to the moving average calculated with the “closing price”, and this value is added or subtracted from the moving average and upper band and lower band lines are drawn. In the HYE Trend Hunter Strategy, instead of the moving average calculated with the closing price in the Bollinger Band calculation, we consider the average of the fast and slow leading lines calculated in the 1st step and draw the Bollinger upper and lower bands accordingly. We use the values of 2 and 20 as the standard deviation and period, as in the original settings. These settings can also be changed from the strategy settings. 3-) At this stage, we have fast and slow leading lines trying to understand the trend direction using VWAP, and Bollinger lower and upper bands calculated by the average of these lines. In this step, we will use another tool that will help us understand whether the invested market (forex, crypto, stocks) is gaining momentum in volume. The Time Segmented Volume indicator was created by the Worden Brothers Inc. and coded by @liw0 and @vitelot on tradingview. The TSV indicator segments the price and volume of an investment instrument according to certain time periods and makes calculations on comparing these price and volume data to reveal the buying and selling periods. To trade in the buy direction on the HYE Trend Hunter Strategy, we look for the TSV indicator to be above 0 and above its exponential moving average value. TSV period and exponential moving average period settings (13 and 7) can also be changed in the strategy settings. BUY SIGNAL 1-) Fast Leading Line value should be higher than the Fast Leading Line value in the previous candle. 2-) Slow Leading Line value should be higher than the Slow Leading Line value in the previous candle. 3-) Candle Closing value must be higher than the Upper Bollinger Band. 4-) TSV value must be greater than 0. 5-) TSV value must be greater than TSVEMA value. EXIT SIGNAL 1-) Fast Leading Line value should be lower than the Fast Leading Line value in the previous candle. 2-) Slow Leading Line value should be lower than the Slow Leading Line value in the previous candle. TIPS AND WARNINGS 1-) The standard settings of the strategy work better in higher timeframes (4-hour, daily, etc.). For lower timeframes, you should change the strategy settings and find the best value for yourself. 2-) All lines (fast and slow leading lines and Bollinger bands) except TSV are displayed on the strategy. For a simpler view, you can hide these lines in the strategy settings. 3-) You can see the color changes of the fast and slow leading lines as well as you can specify a single color for these lines in the strategy settings. 4-) It is an strategy for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this strategy. _______________________________________________ HYE Trend Avcısı Bu stratejide, trendlerin olabildiğince erken tespit edilebilmesi ve zamanında işleme girilebilmesi için gerekli olan en temel iki veriden (fiyat ve hacim) yararlanılmaktadır. Bu kapsamda, fiyat ve hacim kullanan bazı klasik ve yeni nesil indikatörlerin yaklaşımları dikkate alınmıştır. Strateji yalnızca alış yönlü sinyaller üretecek şekilde hazırlanmıştır. Alış ve çıkış sinyallerinin üretilmesi için aşağıdaki adımlar izlenmiştir. 1-) Öncelikle, stratejinin en temel iki verisi olan “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplamasının yapılması gerekiyor. Bunun için de Ichimoku Bulutu olarak bilinen indikatörün “senkou span A” çizgisinin formülünü kullanıyoruz. Bu formülün hesaplamasında kullanılmaları nedeniyle ichimoku’da tenkan sen ve kijun sen olarak bilinen çizgileri de hesaplamamız gerekiyor. Ichimoku bulutunda Tenkansen, Kijunsen ve Senkou Span A çizgileri hesaplanırken mumların yüksek ve düşük değerleri dikkate alınıyor. Bu stratejide ise “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplanırken periyodik VWAP’ın en yüksek ve en düşük değerleri dikkate alınıyor. (Periyodik vwap formülü, tradingviev’de @neolao tarafından kodlanmış ve kullanıma açılmış). Ayrıca, ichimoku bulutunda Senkou Span A çizgisi geleceğe yönelik çizilirken (26 mum ileriye dönük) biz bu stratejide öncü çizgilerin son mumdaki değerlerini dikkate alıyoruz. ORJİNAL ICHIMOKU SPAN A FORMÜLÜ Tenkansen = (Son 9 mumun en yüksek değeri + Son 9 mumun en düşük değeri) / 2 Kijunsen = (Son 26 mumun en yüksek değeri + Son 26 mumun en düşük değeri) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 HYE TREND HUNTER SPAN A FORMÜLÜ* Tenkansen = (Son 9 mumun en yüksek VWAP değeri + Son 9 mumun en düşük VWAP değeri) / 2 Kijunsen = (Son 26 mumun en yüksek VWAP değeri + Son 26 mumun en düşük VWAP değeri) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 * Yavaş çizgi için orijinal ichimoku değerleri olan 9 ve 26’yı kullanırken, hızlı çizgi için 5 ve 13’ü kullanıyoruz. Bu ayarlar, strateji ayarlarından değiştirilebiliyor. 2-) Bu aşamada, elimizde en klasik trend indikatörlerinden birisi olan ichimoku bulutunun formülünden faydalanarak, işin içinde hacim ağırlıklı ortalama fiyatı da sokmak suretiyle elde ettiğimiz 2 çizgimiz var. a-) Hızlı Öncü Çizgi (5-13) b-) Yavaş Öncü Çizgi (9-26) Birazdan yapacağımız hesaplama için bu iki çizginin de ortalamasını alarak yeni bir değer elde ediyoruz. Hızlı ve yavaş öncü çizgilerin ortalaması olan bu değeri kullanarak, teknik analizin en klasik volatilite indikatörlerinden birisi olarak bilinen Bollinger Bantları indikatörünü çizdiriyoruz. Böylelikle piyasada bir trend başlangıcının varlığı anlamına gelebilecek volatilite değişikliği var mı yok mu anlamaya çalışıyoruz. Bu veriyi al-sat sinyallerinin hesaplamasında kullanacağız. Klasik Bollinger Bantları hesaplamasında, “kapanış fiyatıyla” hesaplanan hareketli ortalamaya, kullanıcı olarak belirlenen oranda (orijinal ayarlarında 2 kullanılır) bir çarpan uygulanarak standart sapma hesaplanıyor ve bu değer hareketli ortalamaya eklenip çıkartılarak üst bant ve alt bant çizgileri çiziliyor. HYE Trend Avcısı stratejisinde, Bollinger Bandı hesaplamasında kapanış fiyatıyla hesaplanan hareketli ortalama yerine, 1. adımda hesapladığımız hızlı ve yavaş öncü çizgilerin ortalamasını dikkate alıyoruz ve buna göre bollinger üst ve alt bantlarını çizdiriyoruz. Standart sapma ve periyot olarak yine orijinal ayarlarında olduğu gibi 2 ve 20 değerlerini kullanıyoruz. Bu ayarlar da strateji ayarlarından değiştirilebiliyor. 3-) Bu aşamada, elimizde VWAP kullanarak trend yönünü anlamaya çalışan hızlı ve yavaş öncü çizgilerimiz ile bu çizgilerin ortalaması ile hesaplanan bollinger alt ve üst bantlarımız var. Bu adımda, yatırım yapılan piyasanın (forex, kripto, hisse senedi) hacimsel olarak ivme kazanıp kazanmadığını anlamamıza yarayacak bir araç daha kullanacağız. Time Segmented Volume indikatörü, Worden Kardeşler şirketi tarafından oluşturulmuş ve tradingview’de @liw0 ve @vitelot tarafından kodlanarak kullanıma açılmış. TSV indikatörü, bir yatırım aracının fiyatını ve hacmini belirli zaman aralıklarına göre bölümlere ayırarak, bu fiyat ve hacim verilerini, alış ve satış dönemlerini ortaya çıkarmak için karşılaştırmak üzerine hesaplamalar yapar. HYE Trend Avcısı stratejisinde alış yönünde işlem yapmak için, TSV indikatörünün 0’ın üzerinde olmasını ve kendi üstel hareketli ortalama değerinin üzerinde olmasını arıyoruz. TSV periyodu ve üstel hareketli ortalama periyodu ayarları da (13 ve 7) strateji ayarlarından değiştirilebiliyor. ALIŞ SİNYALİ 1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden yüksek olmalı. 2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden yüksek olmalı. 3-) Kapanış Değeri, Üst Bollinger Bandı değerinden yüksek olmalı. 4-) TSV değeri 0’dan büyük olmalı. 5-) TSV değeri TSVEMA değerinden büyük olmalı. ÇIKIŞ SİNYALİ 1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden düşük olmalı. 2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden düşük olmalı. İPUÇLARI VE UYARILAR 1-) Stratejinin standart ayarları, yüksek zaman dilimlerinde (4 saatlik, günlük vs.) daha iyi çalışıyor. Düşük zaman dilimleri için strateji ayarlarını değiştirmeli ve kendiniz için en iyi değeri bulmalısınız. 2-) Stratejide tüm çizgiler (hızlı ve yavaş öncü çizgiler ile bollinger bantları) -TSV dışında- açık olarak gelmektedir. Daha sade bir görüntü için bu çizgilerin görünürlüğünü strateji ayarlarından gizleyebilirsiniz. 3-) Hızlı ve yavaş öncü çizgilerin renk değişimlerini görebileceğiniz gibi bu çizgiler için tek bir renk olarak da strateji ayarlarında belirleme yapabilirsiniz. 4-) Eğitim ve deneysel amaçlı bir stratejidir. Yatırım tavsiyesi olarak değerlendirilemez. Bu stratejiyi kullanarak gerçek piyasa işlem açarken dikkatli olmalı ve kendi risk değerlendirmenizi yapmalısınız.
Strategi Pine Script®
oleh HYE0619
3
HYE Trend Hunter [Indicator]*** İndikatörün Türkçe ve İngilizce açıklaması aşağıya eklenmiştir. HYE Trend Hunter In this indicator, two of the most basic data (price and volume) necessary for detecting trends as early as possible and entering the trade on time are used. In this context, the approaches of some classical and new generation indicators using price and volume have been taken into account. The indicator is prepared to generate buy signals only. The following steps were followed to generate the buy and exit signals. 1-) First of all, the two most basic data of the indicator, “slow leading line” and “fast leading line” need to be calculated. For this, we use the formula of the “senkou span A” line of the indicator known as the Ichimoku Cloud. We also need to calculate lines known as tenkan sen and kijun sen in ichimoku because they are used in the calculation of this formula. The high and low values of the candles are taken into account when calculating the Tenkansen, Kijunsen and Senkou Span A lines in the Ichimoku cloud. In this indicator, the highest and lowest values of the periodic VWAP are taken into account when calculating the "slow leading line" and "fast leading line". (The periodic vwap formula was coded and made available by @neolao on tradingviev). Also, in the ichimoku cloud, while the Senkou Span A line is plotted 26 periods into the future, we consider the values of the fast and slow leading lines in the last candle in this indicator. ORIGINAL ICHIMOKU SPAN A FORMULA Tenkansen = (Highest high of the last 9 candles + Lowest low of the last 9 candles) / 2 Kijunsen = (Highest high of the last 26 candles + Lowest low of the last 26 candles) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 HYE TREND HUNTER SPAN A FORMULA* Tenkansen = (Highest VWAP of the last 9 candles + Lowest VWAP of the last 9 candles) / 2 Kijunsen = (Highest VWAP of the last 26 candles + Lowest VWAP of the last 26 candles) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 * We use the original ichimoku values 9 and 26 for the slow line, and 5 and 13 for the fast line. These settings can be changed from the indicator settings. 2-) At this stage, we have 2 lines that we obtained by using the formula of the ichimoku cloud, one of the most classical trend indicators, and by including the volume-weighted average price. a-) Fast Leading Line (5-13) b-) Slow Leading Line (9-26) For the calculation we will do soon, we get a new value by taking the average of these two lines. Using this value, which is the average of the fast and slow leading lines, we plot the Bollinger Bands indicator, which is known as one of the most classic volatility indicators of technical analysis. Thus, we are trying to understand whether there is a volatility change in the market, which may mean the presence of a trend start. We will use this data in the calculation of buy-sell signals. In the classical Bollinger Bands calculation, the standard deviation is calculated by applying a multiplier at the rate determined by the user (2 is used in the original settings) to the moving average calculated with the “closing price”, and this value is added or subtracted from the moving average and upper band and lower band lines are drawn. In the HYE Trend Hunter indicator, instead of the moving average calculated with the closing price in the Bollinger Band calculation, we consider the average of the fast and slow leading lines calculated in the 1st step and draw the Bollinger upper and lower bands accordingly. We use the values of 2 and 20 as the standard deviation and period, as in the original settings. These settings can also be changed from the indicator settings. 3-) At this stage, we have fast and slow leading lines trying to understand the trend direction using VWAP, and Bollinger lower and upper bands calculated by the average of these lines. In this step, we will use another tool that will help us understand whether the invested market (forex, crypto, stocks) is gaining momentum in volume. The Time Segmented Volume indicator was created by the Worden Brothers Inc. and coded by @liw0 and @vitelot on tradingview. The TSV indicator segments the price and volume of an investment instrument according to certain time periods and makes calculations on comparing these price and volume data to reveal the buying and selling periods. To trade in the buy direction on the HYE Trend Hunter indicator, we look for the TSV indicator to be above 0 and above its exponential moving average value. TSV period and exponential moving average period settings (13 and 7) can also be changed in the indicator settings. BUY SIGNAL 1-) Fast Leading Line value should be higher than the Fast Leading Line value in the previous candle. 2-) Slow Leading Line value should be higher than the Slow Leading Line value in the previous candle. 3-) Candle Closing value must be higher than the Upper Bollinger Band. 4-) TSV value must be greater than 0. 5-) TSV value must be greater than TSVEMA value. EXIT SIGNAL 1-) Fast Leading Line value should be lower than the Fast Leading Line value in the previous candle. 2-) Slow Leading Line value should be lower than the Slow Leading Line value in the previous candle. TIPS AND WARNINGS 1-) The standard settings of the indicator work better in higher timeframes (4-hour, daily, etc.). For lower timeframes, you should change the indicator settings and find the best value for yourself. 2-) All lines (fast and slow leading lines and Bollinger bands) except TSV are displayed on the indicator. For a simpler view, you can hide these lines in the indicator settings. 3-) You can see the color changes of the fast and slow leading lines as well as you can specify a single color for these lines in the Indicator settings. 4-) Alarms have been added for Buy and Exit. When setting up the alarm, you should set it to be triggered at "every bar close". Otherwise it may repaint. There is no repaint after the candle closes. 5-) It is an indicator for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this indicator. _______________________________________________ HYE Trend Avcısı Bu indikatörde, trendlerin olabildiğince erken tespit edilebilmesi ve zamanında işleme girilebilmesi için gerekli olan en temel iki veriden (fiyat ve hacim) yararlanılmaktadır. Bu kapsamda, fiyat ve hacim kullanan bazı klasik ve yeni nesil indikatörlerin yaklaşımları dikkate alınmıştır. İndikatör yalnızca alış yönlü sinyaller üretecek şekilde hazırlanmıştır. Alış ve çıkış sinyallerinin üretilmesi için aşağıdaki adımlar izlenmiştir. 1-) Öncelikle, indikatörün en temel iki verisi olan “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplamasının yapılması gerekiyor. Bunun için de Ichimoku Bulutu olarak bilinen indikatörün “senkou span A” çizgisinin formülünü kullanıyoruz. Bu formülün hesaplamasında kullanılmaları nedeniyle ichimoku’da tenkan sen ve kijun sen olarak bilinen çizgileri de hesaplamamız gerekiyor. Ichimoku bulutunda Tenkansen, Kijunsen ve Senkou Span A çizgileri hesaplanırken mumların yüksek ve düşük değerleri dikkate alınıyor. Bu indikatörde ise “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplanırken periyodik VWAP’ın en yüksek ve en düşük değerleri dikkate alınıyor. (Periyodik vwap formülü, tradingviev’de @neolao tarafından kodlanmış ve kullanıma açılmış). Ayrıca, ichimoku bulutunda Senkou Span A çizgisi geleceğe yönelik çizilirken (26 mum ileriye dönük) biz bu indikatörde öncü çizgilerin son mumdaki değerlerini dikkate alıyoruz. ORJİNAL ICHIMOKU SPAN A FORMÜLÜ Tenkansen = (Son 9 mumun en yüksek değeri + Son 9 mumun en düşük değeri) / 2 Kijunsen = (Son 26 mumun en yüksek değeri + Son 26 mumun en düşük değeri) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 HYE TREND HUNTER SPAN A FORMÜLÜ* Tenkansen = (Son 9 mumun en yüksek VWAP değeri + Son 9 mumun en düşük VWAP değeri) / 2 Kijunsen = (Son 26 mumun en yüksek VWAP değeri + Son 26 mumun en düşük VWAP değeri) / 2 Senkou Span A = Tenkansen + Kijunsen / 2 * Yavaş çizgi için orijinal ichimoku değerleri olan 9 ve 26’yı kullanırken, hızlı çizgi için 5 ve 13’ü kullanıyoruz. Bu ayarlar, indikatör ayarlarından değiştirilebiliyor. 2-) Bu aşamada, elimizde en klasik trend indikatörlerinden birisi olan ichimoku bulutunun formülünden faydalanarak, işin içinde hacim ağırlıklı ortalama fiyatı da sokmak suretiyle elde ettiğimiz 2 çizgimiz var. a-) Hızlı Öncü Çizgi (5-13) b-) Yavaş Öncü Çizgi (9-26) Birazdan yapacağımız hesaplama için bu iki çizginin de ortalamasını alarak yeni bir değer elde ediyoruz. Hızlı ve yavaş öncü çizgilerin ortalaması olan bu değeri kullanarak, teknik analizin en klasik volatilite indikatörlerinden birisi olarak bilinen Bollinger Bantları indikatörünü çizdiriyoruz. Böylelikle piyasada bir trend başlangıcının varlığı anlamına gelebilecek volatilite değişikliği var mı yok mu anlamaya çalışıyoruz. Bu veriyi al-sat sinyallerinin hesaplamasında kullanacağız. Klasik Bollinger Bantları hesaplamasında, “kapanış fiyatıyla” hesaplanan hareketli ortalamaya, kullanıcı olarak belirlenen oranda (orijinal ayarlarında 2 kullanılır) bir çarpan uygulanarak standart sapma hesaplanıyor ve bu değer hareketli ortalamaya eklenip çıkartılarak üst bant ve alt bant çizgileri çiziliyor. HYE Trend Avcısı indikatöründe, Bollinger Bandı hesaplamasında kapanış fiyatıyla hesaplanan hareketli ortalama yerine, 1. adımda hesapladığımız hızlı ve yavaş öncü çizgilerin ortalamasını dikkate alıyoruz ve buna göre bollinger üst ve alt bantlarını çizdiriyoruz. Standart sapma ve periyot olarak yine orijinal ayarlarında olduğu gibi 2 ve 20 değerlerini kullanıyoruz. Bu ayarlar da indikatör ayarlarından değiştirilebiliyor. 3-) Bu aşamada, elimizde VWAP kullanarak trend yönünü anlamaya çalışan hızlı ve yavaş öncü çizgilerimiz ile bu çizgilerin ortalaması ile hesaplanan bollinger alt ve üst bantlarımız var. Bu adımda, yatırım yapılan piyasanın (forex, kripto, hisse senedi) hacimsel olarak ivme kazanıp kazanmadığını anlamamıza yarayacak bir araç daha kullanacağız. Time Segmented Volume indikatörü, Worden Kardeşler şirketi tarafından oluşturulmuş ve tradingview’de @liw0 ve @vitelot tarafından kodlanarak kullanıma açılmış. TSV indikatörü, bir yatırım aracının fiyatını ve hacmini belirli zaman aralıklarına göre bölümlere ayırarak, bu fiyat ve hacim verilerini, alış ve satış dönemlerini ortaya çıkarmak için karşılaştırmak üzerine hesaplamalar yapar. HYE Trend Avcısı indikatöründe alış yönünde işlem yapmak için, TSV indikatörünün 0’ın üzerinde olmasını ve kendi üstel hareketli ortalama değerinin üzerinde olmasını arıyoruz. TSV periyodu ve üstel hareketli ortalama periyodu ayarları da (13 ve 7) indikatör ayarlarından değiştirilebiliyor. ALIŞ SİNYALİ 1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden yüksek olmalı. 2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden yüksek olmalı. 3-) Kapanış Değeri, Üst Bollinger Bandı değerinden yüksek olmalı. 4-) TSV değeri 0’dan büyük olmalı. 5-) TSV değeri TSVEMA değerinden büyük olmalı. ÇIKIŞ SİNYALİ 1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden düşük olmalı. 2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden düşük olmalı. İPUÇLARI VE UYARILAR 1-) İndikatörün standart ayarları, yüksek zaman dilimlerinde (4 saatlik, günlük vs.) daha iyi çalışıyor. Düşük zaman dilimleri için indikatör ayarlarını değiştirmeli ve kendiniz için en iyi değeri bulmalısınız. 2-) İndikatörde tüm çizgiler (hızlı ve yavaş öncü çizgiler ile bollinger bantları) -TSV dışında- açık olarak gelmektedir. Daha sade bir görüntü için bu çizgilerin görünürlüğünü indikatör ayarlarından gizleyebilirsiniz. 3-) Hızlı ve yavaş öncü çizgilerin renk değişimlerini görebileceğiniz gibi bu çizgiler için tek bir renk olarak da İndikatör ayarlarında belirleme yapabilirsiniz. 4-) Alış ve Çıkış için alarmlar eklenmiştir. Alarm kurulumu yaparken “Her çubuk kapanışında” tetiklenecek şekilde ayarlama yapmalısınız. Aksi takdirde repaint yapabilir. Mum kapanışından sonra repaint söz konusu değildir. 5-) Eğitim ve deneysel amaçlı bir indikatördür. Yatırım tavsiyesi olarak değerlendirilemez. Bu indikatörü kullanarak gerçek piyasa işlem açarken dikkatli olmalı ve kendi risk değerlendirmenizi yapmalısınız.
Penunjuk Pine Script®
oleh HYE0619
Scalping Screener - 15minSCALPING SCREENER - 15 mins (Indicator Tool) TIME FRAME to use - 15 mins DURATION OF TRADE - Using this indicator, Trade must be taken only during market hours and must be closed before market close (must not be carried forrward for next day). SCALPING - This is a scalping strategy that is intended to make small profits in intraday trading ENTRY CONCEPT - - There must be 2 bulish candles and the 2nd candle's high should be greater than first candle's high. - And If the latest candle high breaks high of the 2nd candle (prev candle), BUY signal is generated. - Additional filters are added to reduce non-performaing trades. - visa versa for SHORT signal EXIT CONCEPT - - 2nd candles low is the stop loss. - Difference between 2nd candle high and 2nd candle low is target. - The script will indicate when to BUY / SHORT and when to EXIT the trade. INSTRUMENTS TO TRADE - - High volatility instruments are best to be traded - Nifty 50 stocks have been added to this indicator for the sake of screener. User can change these stocks with high volatility ones - There is a limitation to add upto 40 scripts. SCREENER FUNCTION - - Right side of the chart has screener section which shows the list of stocks that qualify as per the BUY / SELL signal NOTE - The purpose of the scipt is for self learning / improvement and analysis. Trading is a risky business and a trader must take any trade at their own RISK. The author shall not be held responsible for Losses / Profits
Penunjuk Pine Script®
oleh Atma_Sakshatkar
8
DEMA/EMA & VOL (Short strategy)Hello, I am trying to build a short momentum strategy that is based off of the DEMA crossing under the EMA, but because many momentum strategies send too many signals, I have also implemented a volatility condition based on the average true range percentage (ATRP). Essentially, as momentum moves downwards + volatility (ATRP) moves upwards, it shorts the security. However, I am having an issue with exiting trades. I think this would be a great strategy if I could simply get the strategy to exit the trades. Does anyone mind looking through the source code and tell me what I might be doing wrong? In return, I would hope that this strategy could be useful to you in same way! Thank you for looking!
Strategi Pine Script®
oleh Qorbanjf
Monte Carlo Range Forecast [DW]This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation. Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results. These types of algorithms have a number of applications in numerous fields of study including physics, engineering, behavioral sciences, climate forecasting, computer graphics, gaming AI, mathematics, and finance. Although the applications vary, there is a typical process behind the majority of Monte Carlo methods: -> First, a distribution of possible inputs is defined. -> Next, values are generated randomly from the distribution. -> The values are then fed through some form of deterministic algorithm. -> And lastly, the results are aggregated over some number of iterations. In this study, the Monte Carlo process used generates a distribution of aggregate pseudorandom linear price returns summed over a user defined period, then plots standard deviations of the outcomes from the mean outcome generate forecast regions. The pseudorandom process used in this script relies on a modified Wichmann-Hill pseudorandom number generator (PRNG) algorithm. Wichmann-Hill is a hybrid generator that uses three linear congruential generators (LCGs) with different prime moduli. Each LCG within the generator produces an independent, uniformly distributed number between 0 and 1. The three generated values are then summed and modulo 1 is taken to deliver the final uniformly distributed output. Because of its long cycle length, Wichmann-Hill is a fantastic generator to use on TV since it's extremely unlikely that you'll ever see a cycle repeat. The resulting pseudorandom output from this generator has a minimum repetition cycle length of 6,953,607,871,644. Fun fact: Wichmann-Hill is a widely used PRNG in various software applications. For example, Excel 2003 and later uses this algorithm in its RAND function, and it was the default generator in Python up to v2.2. The generation algorithm in this script takes the Wichmann-Hill algorithm, and uses a multi-stage transformation process to generate the results. First, a parent seed is selected. This can either be a fixed value, or a dynamic value. The dynamic parent value is produced by taking advantage of Pine's timenow variable behavior. It produces a variable parent seed by using a frozen ratio of timenow/time. Because timenow always reflects the current real time when frozen and the time variable reflects the chart's beginning time when frozen, the ratio of these values produces a new number every time the cache updates. After a parent seed is selected, its value is then fed through a uniformly distributed seed array generator, which generates multiple arrays of pseudorandom "children" seeds. The seeds produced in this step are then fed through the main generators to produce arrays of pseudorandom simulated outcomes, and a pseudorandom series to compare with the real series. The main generators within this script are designed to (at least somewhat) model the stochastic nature of financial time series data. The first step in this process is to transform the uniform outputs of the Wichmann-Hill into outputs that are normally distributed. In this script, the transformation is done using an estimate of the normal distribution quantile function. Quantile functions, otherwise known as percent-point or inverse cumulative distribution functions, specify the value of a random variable such that the probability of the variable being within the value's boundary equals the input probability. The quantile equation for a normal probability distribution is μ + σ(√2)erf^-1(2(p - 0.5)) where μ is the mean of the distribution, σ is the standard deviation, erf^-1 is the inverse Gauss error function, and p is the probability. Because erf^-1() does not have a simple, closed form interpretation, it must be approximated. To keep things lightweight in this approximation, I used a truncated Maclaurin Series expansion for this function with precomputed coefficients and rolled out operations to avoid nested looping. This method provides a decent approximation of the error function without completely breaking floating point limits or sucking up runtime memory. Note that there are plenty of more robust techniques to approximate this function, but their memory needs very. I chose this method specifically because of runtime favorability. To generate a pseudorandom approximately normally distributed variable, the uniformly distributed variable from the Wichmann-Hill algorithm is used as the input probability for the quantile estimator. Now from here, we get a pretty decent output that could be used itself in the simulation process. Many Monte Carlo simulations and random price generators utilize a normal variable. However, if you compare the outputs of this normal variable with the actual returns of the real time series, you'll find that the variability in shocks (random changes) doesn't quite behave like it does in real data. This is because most real financial time series data is more complex. Its distribution may be approximately normal at times, but the variability of its distribution changes over time due to various underlying factors. In light of this, I believe that returns behave more like a convoluted product distribution rather than just a raw normal. So the next step to get our procedurally generated returns to more closely emulate the behavior of real returns is to introduce more complexity into our model. Through experimentation, I've found that a return series more closely emulating real returns can be generated in a three step process: -> First, generate multiple independent, normally distributed variables simultaneously. -> Next, apply pseudorandom weighting to each variable ranging from -1 to 1, or some limits within those bounds. This modulates each series to provide more variability in the shocks by producing product distributions. -> Lastly, add the results together to generate the final pseudorandom output with a convoluted distribution. This adds variable amounts of constructive and destructive interference to produce a more "natural" looking output. In this script, I use three independent normally distributed variables multiplied by uniform product distributed variables. The first variable is generated by multiplying a normal variable by one uniformly distributed variable. This produces a bit more tailedness (kurtosis) than a normal distribution, but nothing too extreme. The second variable is generated by multiplying a normal variable by two uniformly distributed variables. This produces moderately greater tails in the distribution. The third variable is generated by multiplying a normal variable by three uniformly distributed variables. This produces a distribution with heavier tails. For additional control of the output distributions, the uniform product distributions are given optional limits. These limits control the boundaries for the absolute value of the uniform product variables, which affects the tails. In other words, they limit the weighting applied to the normally distributed variables in this transformation. All three sets are then multiplied by user defined amplitude factors to adjust presence, then added together to produce our final pseudorandom return series with a convoluted product distribution. Once we have the final, more "natural" looking pseudorandom series, the values are recursively summed over the forecast period to generate a simulated result. This process of generation, weighting, addition, and summation is repeated over the user defined number of simulations with different seeds generated from the parent to produce our array of initial simulated outcomes. After the initial simulation array is generated, the max, min, mean and standard deviation of this array are calculated, and the values are stored in holding arrays on each iteration to be called upon later. Reference difference series and price values are also stored in holding arrays to be used in our comparison plots. In this script, I use a linear model with simple returns rather than compounding log returns to generate the output. The reason for this is that in generating outputs this way, we're able to run our simulations recursively from the beginning of the chart, then apply scaling and anchoring post-process. This allows a greater conservation of runtime memory than the alternative, making it more suitable for doing longer forecasts with heavier amounts of simulations in TV's runtime environment. From our starting time, the previous bar's price, volatility, and optional drift (expected return) are factored into our holding arrays to generate the final forecast parameters. After these parameters are computed, the range forecast is produced. The basis value for the ranges is the mean outcome of the simulations that were run. Then, quarter standard deviations of the simulated outcomes are added to and subtracted from the basis up to 3σ to generate the forecast ranges. All of these values are plotted and colorized based on their theoretical probability density. The most likely areas are the warmest colors, and least likely areas are the coolest colors. An information panel is also displayed at the starting time which shows the starting time and price, forecast type, parent seed value, simulations run, forecast bars, total drift, mean, standard deviation, max outcome, min outcome, and bars remaining. The interesting thing about simulated outcomes is that although the probability distribution of each simulation is not normal, the distribution of different outcomes converges to a normal one with enough steps. In light of this, the probability density of outcomes is highest near the initial value + total drift, and decreases the further away from this point you go. This makes logical sense since the central path is the easiest one to travel. Given the ever changing state of markets, I find this tool to be best suited for shorter term forecasts. However, if the movements of price are expected to remain relatively stable, longer term forecasts may be equally as valid. There are many possible ways for users to apply this tool to their analysis setups. For example, the forecast ranges may be used as a guide to help users set risk targets. Or, the generated levels could be used in conjunction with other indicators for meaningful confluence signals. More advanced users could even extrapolate the functions used within this script for various purposes, such as generating pseudorandom data to test systems on, perform integration and approximations, etc. These are just a few examples of potential uses of this script. How you choose to use it to benefit your trading, analysis, and coding is entirely up to you. If nothing else, I think this is a pretty neat script simply for the novelty of it. ---------- How To Use: When you first add the script to your chart, you will be prompted to confirm the starting date and time, number of bars to forecast, number of simulations to run, and whether to include drift assumption. You will also be prompted to confirm the forecast type. There are two types to choose from: -> End Result - This uses the values from the end of the simulation throughout the forecast interval. -> Developing - This uses the values that develop from bar to bar, providing a real-time outlook. You can always update these settings after confirmation as well. Once these inputs are confirmed, the script will boot up and automatically generate the forecast in a separate pane. Note that if there is no bar of data at the time you wish to start the forecast, the script will automatically detect use the next available bar after the specified start time. From here, you can now control the rest of the settings. The "Seeding Settings" section controls the initial seed value used to generate the children that produce the simulations. In this section, you can control whether the seed is a fixed value, or a dynamic one. Since selecting the dynamic parent option will change the seed value every time you change the settings or refresh your chart, there is a "Regenerate" input built into the script. This input is a dummy input that isn't connected to any of the calculations. The purpose of this input is to force an update of the dynamic parent without affecting the generator or forecast settings. Note that because we're running a limited number of simulations, different parent seeds will typically yield slightly different forecast ranges. When using a small number of simulations, you will likely see a higher amount of variance between differently seeded results because smaller numbers of sampled simulations yield a heavier bias. The more simulations you run, the smaller this variance will become since the outcomes become more convergent toward the same distribution, so the differences between differently seeded forecasts will become more marginal. When using a dynamic parent, pay attention to the dispersion of ranges. When you find a set of ranges that is dispersed how you like with your configuration, set your fixed parent value to the parent seed that shows in the info panel. This will allow you to replicate that dispersion behavior again in the future. An important thing to note when settings alerts on the plotted levels, or using them as components for signals in other scripts, is to decide on a fixed value for your parent seed to avoid minor repainting due to seed changes. When the parent seed is fixed, no repainting occurs. The "Amplitude Settings" section controls the amplitude coefficients for the three differently tailed generators. These amplitude factors will change the difference series output for each simulation by controlling how aggressively each series moves. When "Adjust Amplitude Coefficients" is disabled, all three coefficients are set to 1. Note that if you expect volatility to significantly diverge from its historical values over the forecast interval, try experimenting with these factors to match your anticipation. The "Weighting Settings" section controls the weighting boundaries for the three generators. These weighting limits affect how tailed the distributions in each generator are, which in turn affects the final series outputs. The maximum absolute value range for the weights is . When "Limit Generator Weights" is disabled, this is the range that is automatically used. The last set of inputs is the "Display Settings", where you can control the visual outputs. From here, you can select to display either "Forecast" or "Difference Comparison" via the "Output Display Type" dropdown tab. "Forecast" is the type displayed by default. This plots the end result or developing forecast ranges. There is an option with this display type to show the developing extremes of the simulations. This option is enabled by default. There's also an option with this display type to show one of the simulated price series from the set alongside actual prices. This allows you to visually compare simulated prices alongside the real prices. "Difference Comparison" allows you to visually compare a synthetic difference series from the set alongside the actual difference series. This display method is primarily useful for visually tuning the amplitude and weighting settings of the generators. There are also info panel settings on the bottom, which allow you to control size, colors, and date format for the panel. It's all pretty simple to use once you get the hang of it. So play around with the settings and see what kinds of forecasts you can generate! ---------- ADDITIONAL NOTES & DISCLAIMERS Although I've done a number of things within this script to keep runtime demands as low as possible, the fact remains that this script is fairly computationally heavy. Because of this, you may get random timeouts when using this script. This could be due to either random drops in available runtime on the server, using too many simulations, or running the simulations over too many bars. If it's just a random drop in runtime on the server, hide and unhide the script, re-add it to the chart, or simply refresh the page. If the timeout persists after trying this, then you'll need to adjust your settings to a less demanding configuration. Please note that no specific claims are being made in regards to this script's predictive accuracy. It must be understood that this model is based on randomized price generation with assumed constant drift and dispersion from historical data before the starting point. Models like these not consider the real world factors that may influence price movement (economic changes, seasonality, macro-trends, instrument hype, etc.), nor the changes in sample distribution that may occur. In light of this, it's perfectly possible for price data to exceed even the most extreme simulated outcomes. The future is uncertain, and becomes increasingly uncertain with each passing point in time. Predictive models of any type can vary significantly in performance at any point in time, and nobody can guarantee any specific type of future performance. When using forecasts in making decisions, DO NOT treat them as any form of guarantee that values will fall within the predicted range. When basing your trading decisions on any trading methodology or utility, predictive or not, you do so at your own risk. No guarantee is being issued regarding the accuracy of this forecast model. Forecasting is very far from an exact science, and the results from any forecast are designed to be interpreted as potential outcomes rather than anything concrete. With that being said, when applied prudently and treated as "general case scenarios", forecast models like these may very well be potentially beneficial tools to have in the arsenal.
Penunjuk Pine Script®
oleh DonovanWall
79
Statistical and Financial MetricsGood morning traders! This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market) By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle Here are the metrics you can have by storing data from a variable period of candles (by default 51): ✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE) ✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER) ✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close ✓ Covariance of the two datasets (in BLUE) ✓ Correlation coefficient of the two datasets (in AQUA) ✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same). WHAT IS BETA (β)? The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds. We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk). The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio. Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset. So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld. In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f) where: r_i = expected yeld of the asset r_f = risk free interest rate β = beta r_m = yeld of market portfolio I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
Penunjuk Pine Script®
oleh Drun30
2
Power Bar [racer8]Introduction: 🌟 The Power Bar indicator is a powerful volatility indicator that can detect power bars 💪. A power bar is just a really big price bar that forms after a price base. A price base is chart pattern consisting of many low volatility price bars (bars that have small ranges). To detect such powerful bars, the PB indicator uses the following formula: PB = ( Absolute value of current close - previous close ) / ( Previous price range over n periods ) Looking at the formula, you can see that PB compares the current change in closing price to the n-period base pattern's range. Strong PB values are typically greater than a value of 1. If n periods = 10, the indicator will look back 11 periods. The 11 periods includes the 10-period base plus the current price bar. 10 periods is the default setting for the indicator. After the calculation, PB is then plotted as a histogram. Along with the histogram, a horizontal dashed line is also plotted. PB's other setting controls the dashed line's level. This level is preset at a default value of 1. The dashed line is just a way to filter out weak PB values, and to generate signals. A signal is generated when the PB histogram is above the dashed line. Objective: 🤔 This indicator shall prove very useful to you if your main objective is to trade only the best chart pattern in the market...and the base pattern is one of the best, if not the best chart pattern that exists today. This indicator is a mechanical way of detecting the chart pattern. Enjoy! 🥳
Penunjuk Pine Script®
oleh racer8
3
Comprehensive BandsComprehensive Bands is an unabashed mashup combining Bollinger Bands, STARC Bands, and Keltner Channels. STARC Bands are modified Keltner Channels whichdo a better job than the Bollinger Bands when it comes to showing where the top and bottom ranges of natural volatility exist. The pale white exterior cloud is your STARC Band fill. The white line is the STARC basis line. Next closest to the center we have the Bollinger Bands in yellow without a basis line (because BB basis lines aren't that great). Bollinger Bands will help to highlight when volatility breakouts are about to happen. Keltner Channels are based on an exponential moving average represented by the purple basis line in the center usually accompanied by a pair of channel lines above and below, in this case represented as a blue fill. Every component of this indicator can represent support and resistance on the go. You can use this as a trading system. The method in this case would be similar to the Bollinger Band trading method. The Bollinger Band method involves waiting for price to hit a support or resistance line where it then prints a reversal candle, and to trade in the direction of that reversal. This indicator can improve the Bollinger Band trading method by providing a better idea of when a trend has reached a reversal point through the use of superior maximum/minimum representations and superior basis lines. All this while configured in a visual representation that's light on noise. I'd suggest using this indicator in conjunction with an oscillator you feel comfortable with such as the MacD or RSI. Happy hunting. Shoutout to LazyBear. Note: I'm aware that this does not contain Donchian channels and have no regrets.
Penunjuk Pine Script®
oleh ChronicMasturTrader
3
SDev Adjusted StochasticDescription : This Stochastic variant will auto-adjust stochastic period based on volatility measured by standard deviation. The idea behind it are in highly volatile market, %K period will be reduced to account for recent price range, while in low volatility market, %K period will be increased to account less of the recent price range. This idea is based on one of medium article written by Sofien Kaabar with slight modification on the adjusting logic implementation. Any ideas to further improve this indicator are welcome :) Disclaimer: I always felt Pinescript is a very fast to type language with excellent visualization capabilities, so I've been using it as code-testing platform prior to actual coding in other platform. Having said that, these study scripts was built only to test/visualize an idea to see its viability and if it can be used to optimize existing strategy. While some of it are useful and most are useless, none of it should be use as main decision maker.
Penunjuk Pine Script®
oleh fareidzulkifli
2
Bollinger Bands %B Compare VixThis imple script converts your chosen chart price and outputs it as a percentage in relation to the Vix percentage. If price (Blue line) is higher than 0.60 and vix (Red Line) is lower than 0. 40 then there is lower volatility and this is good for buying. If price (Blue line) is lower than 0. 40 and vix (Red Line) is higher than 0.60 then there is higher volatility and this is good for selling, exiting and cash only. If you like risk you can enter as soon as the price and vix cross in either direction This is my first script, please give me a lot of critique, I won't cry hahaha :) For greater accuracy, you use these Vix products for their specific stocks/Indicies: Apple - VXAPL Google - VXGOG Amazon - CBOE:VXAZN IBM - CBOE:VXIBM Goldman Sachs - CBOE:VXGS NASDAQ 100 = CBOE:VXN SP100 - CBOE:VXO SP500 (3months) - VIX3M XLE(energy sector) - CBOE:VXXLE EWZ(brazil etf) - VXEWZ EEM( emerging markets etf) - CBOE:VXEEM EFA (MSCI ETF) - CBOE:VXEFA FXI (Cina ETF) - CBOE:VXFXI
Penunjuk Pine Script®
oleh Siziba_Wallace
6
Equity Risk PremiumInspired by the article "2020's Best Performing Hedge Fund Warns Of 'Incredible Move' Around The Election" from ZeroHedge: This script explores the relationship and attempts to find dislocation between equity risk (VIX) and high-yield corporate debt risk (VXHYG, The Cboe VXHYG Index is an estimate of the expected 30-day volatility of the return on iShares' High Yield Grade ETF (HYG). VXHYG is derived by applying the VIX algorithm to options on HYG). The basic logic is (closing price of VIX / closing price of VXHYG) - 1. When equity risk is high and credit risk is low, the value of premium will be high, and vice-versa. “'Equity volatility is almost inescapably high. Is that a good form of insurance? The payoff profiles are nothing like they were back in January. Whereas in credit, we’re almost back to where we were in January. I find today the risk-reward profile of credit to be basically among the worst, relative to other things, I’ve seen in my career,' Weinstein said. 'A VIX at 20 used to be quite a feat. Here we are at 30, and the credit market hasn’t blinked.' As a result of the gaping divergence between the VIX and credit spreads - the two had moved in tandem for years, but in August the two series blew out as the VIX started rising as spreads kept falling - Weinstein has pounced on the trade, betting on vol compression." When equity risk premium is high, the market may be forming a local top. When equity risk premium is low, the market may be forming a local bottom. Make sure to select your current timeframe on the dropdown menu.
Penunjuk Pine Script®
oleh MartinShkreIi
5
Volume DensitySince we don't have tick count per time interval, let's do it this way. Basically "bigger the move bigger the volume" rule applies in most times, making volume alone kinda useless. What is more interesting, is when there was a huge volume within a relatively small range, or vice versa, a huge move without equally increased volume. Without diving into details, bars with low volatility and serious volume are aprox. areas of possible future reversals/pullbacks, while volumeless high volatility moves should not cause any serious stops in price action. This is just a small easy script to highlight this process. "Mathematically speaking, it's just a reciprocal of quotient of awfewefaffwqg..... Nah, not this time. HOW IT WORKS: Volume Density = 1/(range/volume) We take range of a bar (high minus low), divide it by volume of the same bar, in order to neutralize this "bigger-bigger" relationship. Then we memorize this number, take 1 and divide 1 by this number, in order to inverse the result. So now, small bars with big volume will be rated higher than just by using classic volume histogram. I suppose it would be easy to use it along with classic volume histogram, and assess the differences between these 2 histograms. /// Probs some1 has already posted smth like this before idk, but if it aint the case, here it is, for you.
Penunjuk Pine Script®
oleh gorx1
1
CPR_ATR_PIVOTIntroduction What is so special about this variation of CPR is that it combines three indicators together. It has Central Pivot Range to understand market trend and for taking entry; Average True Range Stop line to identify the stop loss for any trade keeping in view volatility of the instrument; and Standard Pivot Points for profit targets. So overall it combines all essential ingredients for trading in a single indicator. While CPR and Pivot values will remain fixed, the ATR period and multiple can be changed. Central Pivot Range: is a useful intraday technical indicator which comprises 3 levels – a Central pivot point (pivot), Top central level (TC), and Bottom central level (BC). These levels are calculated as follows: TC = (Pivot – BC) + Pivot Pivot = (High + Low + Close)/3 BC = (High + Low)/2 The 3 levels are calculated using 3 variables, High, Low, and Close price. When you add CPR levels in a stock’s chart, TC is highest, the pivot is at the center and BC is the lowest level. However, depending on market conditions TC’s value may be lower than BC. The fundamental idea behind this indicator is that the particular day’s trading range captures everything about the market sentiment, and hence this range can be used to predict the price movement of the following days. This indicator was first introduced by Mark Fisher in this book “The Logical Trader”. Frank Ochoa added another dimension, central pivot point to this indicator. Practical Applications: CPR Breakout: Any high volume breakout above or below the TC and BC lines respectively indicates a high probability that the movement will continue. CPR Width The width of the CPR lines very accurately gives an idea of the expected price movement. If CPR width is narrow, that is the distance between TC and BC lines of CPR is very low, then it indicates a trending market. While if the distance between TC and BC lines is relatively higher it indicates sideways market. CPR as Support and Resistance CPR lines can also act as support and resistance. Market may takes support or resistance at the CPR and reverse. ATR Stop: I am adding another useful indicator known as ATR stop with CPR. Once market takes support and resistance at the CPR, trade can be taken with stoploss under/above (as the case may be) the ATR stop line. It would help in absorbing the intraday volatility in a stock or instrument. Pivot Points: Pivot points can be taken as target points where partial or full profit (depending upon market conditions and momentum) can be taken. I hope this indicator would help some traders in taking better trading decisions. Regards jjsingh_2020
Penunjuk Pine Script®
oleh Bravetotrade
17
Realized Variables for Options ComparisonThese variables can be used in comparison with the implied volatility of options. Variables: Realized Volatility mathematical notation lowercase 'sigma' Realized Variance mathematical notation lowercase 'sigma' squared Realized Beta mathematical notation lowercase 'beta' Timeframes: Yearly = 250 or 365 Quarterly = 50 or 90 Monthly = 20 or 30 Important Note: Options Contract Expiry = barmerge.lookahead_on "Merge strategy for the requested data position. Requested barset is merged with current barset in the order of sorting bars by their opening time. This merge strategy can lead to undesirable effect of getting data from "future" on calculation on history. This is unacceptable in backtesting strategies, but can be useful in indicators." [ All other timeframes barmerge.lookahead is disabled.
Penunjuk Pine Script®
oleh luminaryfi
Bollinger Bands Breakout StrategyBollinger Bands Breakout Strategy is the strategy version of Bollinger Bands Filter study version, which can be found under my scripts page. The strategy goes long when price closes above the upper band and goes short signal when price closes below the lower band. Bollinger Bands is a classic indicator that uses a simple moving average of 20 periods, along with plots of upper and lower bands that are 2 standard deviations away from the basis line. These bands help visualize price volatility and trend based on where the price is, in relation to the bands. The strategy doesn't take into account any other parameters such as Volume / RSI / Fundamentals etc, so user must use discretion based on confirmations from another indicator or based on fundamentals. The strategy results are based on purely long and short trades and doesn't take into account any user defined targets or stop losses. The strategy works great when the price closes above/below upper/lower bands with continuation on next bar. It is definitely useful to have this strategy or the Bollinger Bands filter along with other indicators to get early glimpse of breach/fail of bands on candle close during BB squeeze or based on volatility . This can be used on Heikin Ashi candles for spotting trends, but HA candles are not recommended for trade entries as they don't reflect true price of the asset. The strategy settings default is 55 SMA and 1 standard deviation for Bollinger Bands filter, but these can be changed from settings. It is definitely worth reading the 22 rules of Bollinger Bands written by John Bollinger if interested in trading Bollinger Bands successfully.
Strategi Pine Script®
oleh TradeChartist
48