NEoWave Cash Data Pro by ArshiaRahimiNEoWave Cash Data Pro by ArshiaRahimi (Cash Data Display Indicator)
By using this indicator, you can see cash data in the Trading View Charts. Cash Data is NEoWave approach data and is used for wave counting of this type. Analysts of Elliot Wave approach can also benefit from this data.
In Cash Data, the state of high and low of the candles or in other words their chronology will be determined and the path of price movement will be indicated clearly.
You will have no limit to view cash data using this indicator and you will be able to view the cash data of any part of the chart you would like with a 100 percent precision. By default, Indicator shows MonoWave 500 in the ending part of the chart but in order to view the cash data of other parts, you only need to activate the option “ Custom Start” and by adjusting the date of drawing the cash data, you can make the cash data of the part you want to be displayed.
The cash data of each chart is displayed in 20 different timeframes including:
• Annual timeframe
• Monthly, 3month, 6 month timeframe
• weekly, 2 week timeframe
• daily, 2 day, 3 day timeframe
• 6 hour, 12 hour timeframe
• 4 hour, 8 hour timeframe
• 1 hour, 2 hour, 3 hour timeframe
• 5 minute, 10 minute, 15 minute, 30 minute timeframe
Other features are also incorporated in this indicator including:
• determination of cash data thickness
• determination of ascending MonoWaves color
• determination of descending MonoWaves color
• determination of connecting MonoWaves color
• displaying the MonoWaves which might be in question (when high and low occur in a candle)
• determination of the questionable MonoWaves color
• determination of the date and starting time of cash data drawing
• Drawing of the last cash data live and the possibility of determining its drawing delay.
• Displaying time slot separator lines
• Determination of separator lines color and transparency
• Displaying Fade Chart behind cash data
• determination of fade chart candles color and transparency
• displaying information table of cash data in the corner of the chart which include displaying time frame of the cash data and the number of MonoWaves that exist in the chart.
This indicator is designed by Arshia Rahimi of Iran NEoWave Institute. You can be in touch through “ArshiaRahimi” ID.
The Indicator will continuously receive its new updates. after publishing, each update will replace the previous version by trading view.
Komut dosyalarını "elliott" için ara
TopTenAlg0 1. Sentiment & MomentumEN: Mum Sentiment & Momentum is an indicator that measures the psychological thresholds of the O candle and the rate of change of the price (Rate of Chance / Bar Momentum). Each price action is a separate action with flexibility. Mum Sentiment & Momentum shows you the speed and direction of this price action. If sentiment and momentum are green, the rise will continue, if it is much above momentum sentiment, it indicates the presence of an enthusiastic psychological movement. If sentiment and momentum are red, a correction may come and a decrease is expected, and if momentum is well below sentiment, there is an enthusiastic sale.
This algorithm is prepared with @Top10Algo ... Optimization periods
TR: Mum Sentiment & Momentum her barda ayrı ayrı olmak üzere O muma ait psikolojik eşikleri ve fiyatın değişim hızını ( Rate of Chance / Mum Momentumu ) ölçen bir göstergedir. Her bir fiyat hareketi esnekliği olan ayrı birer aksiyondur. Mum Sentiment & Momentum size bu fiyat aksiyonunun hızını ve yönünün ne olduğunu gösterir. Eğer sentiment ve momentum yeşil ise yükselişin devam edeceğini, momentum sentiment’ in çok üstünde ise coşkulu bir psikolojik hareketin varlığını gösterir. Eğer sentiment ve momentum kırmızı ise düzeltme gelebileceğini ve düşüş beklenildiğini, momentum ise sentiment’in çok altında ise coşkulu bir satış’ ın olduğunu gösterir.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Periyotlar optimize edilmiştir.
TopTenAlgo 3. Cursor Trend with SQZ MOM(Without Volume Ind.)EN: Indicator Trend is a momentum algorithm that measures the direction of the trend. It recalculates the Volume Weighted Moving Average and Tilson functions included with a certain frequency value according to the closing price and this trend helps us determine trend times. The size of the frequency correction motion. It Looks at the Logarithmic to functions. Is the zigzag of argument correction? otherwise it is a shortcut for a flat / flat correction . You can use the minus frequency value minus in zigzags, while it is handled with lower frequencies in flat or flat corrections . For symbols for which the Volume Indicator cannot be read.
This algorithm is prepared with @Top10Algo ... Improvements have been made regarding short periods.
TR: Gösterge Trend, trendin yönünü ölçen bir momentum algoritmasıdır. İçeriğinde bulunan Volume Weighted Moving Average ve Tilson fonksiyonlarını belli bir frekans değeri ile kapanış fiyatına göre yeniden hesaplar ve bu sayede trend değişim zamanlarını belirlememize yardımcı olur. Frekans değeri düzeltme hareketinin boyutuna göre değişiklik gösterir. Fonsiyonlara Logaritmik bakar.Frekans değerini belirlememizde yardımcı olan argüman düzeltmenin zigzag mı? yoksa yassı/flat bir düzeltmemi olacağını kestirmektir. Zigzaglarda frekans değeri eksi yönde daha fazla büyürken yassı yada flat düzeltmelerde daha düşük frekanslarla ele alınır. Hacim Göstergesinin okunamadığı semboller içindir.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Kodlamadaki katkılarından ve yol göstericiliğinden dolayı teşekkürü bir borç bilirim. Kısa Periyotlar için iyileştirmeler yapıldı...
TopTenAlgo 3. Cursor Trend with SQZ MOM (Include Volume Ind.)EN: Indicator Trend is a momentum algorithm that measures the direction of the trend. It recalculates the Volume Weighted Moving Average and Tilson functions included with a certain frequency value according to the closing price and this trend helps us determine trend times. The size of the frequency correction motion. It Looks at the Logarithmic to functions. Is the zigzag of argument correction? otherwise it is a shortcut for a flat / flat correction . You can use the minus frequency value minus in zigzags, while it is handled with lower frequencies in flat or flat corrections .
This algorithm is prepared with @Top10Algo ... Improvements have been made regarding short periods.
TR: Gösterge Trend, trendin yönünü ölçen bir momentum algoritmasıdır. İçeriğinde bulunan Volume Weighted Moving Average ve Tilson fonksiyonlarını belli bir frekans değeri ile kapanış fiyatına göre yeniden hesaplar ve bu sayede trend değişim zamanlarını belirlememize yardımcı olur. Frekans değeri düzeltme hareketinin boyutuna göre değişiklik gösterir. Fonsiyonlara Logaritmik bakar.Frekans değerini belirlememizde yardımcı olan argüman düzeltmenin zigzag mı? yoksa yassı/flat bir düzeltmemi olacağını kestirmektir. Zigzaglarda frekans değeri eksi yönde daha fazla büyürken yassı yada flat düzeltmelerde daha düşük frekanslarla ele alınır.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Kodlamadaki katkılarından ve yol göstericiliğinden dolayı teşekkürü bir borç bilirim. Kısa Periyotlar için iyileştirmeler yapıldı...
TopTenAlgo 4. Trend Velocity & Quality with Missmatch AlertEN: The Trend Velocity & Quality oscillator, in addition to a classic Rsi indicator, precisely measures the speed and quality of the trend. Rsi is actually a tense indicator that makes technical analysis difficult. For this reason, it makes it difficult for you to get false signals and trade the trend by not being able to analyze the direction of the trend clearly. The Rsi Trend Velocity & Quality oscillator produces more meaningful thresholds with the functions it contains, showing tighter postures that are not tense. It also causes Rsi to move faster without fear of distortion due to excessive noise, causing you to receive signals earlier. In short, it is a smoother oscillator that produces tighter postures, better thresholds, a faster Rsi and early signals.
This algorithm is prepared with @Top10Algo ... Add Mismatch Alerts
TR: Trend Velocity & Quality osilatörü klasik bir Rsi indikatörüne ek olarak trendin hızını ve kalitesini hassas bir biçimde ölçer. Rsi aslında teknik analizi zorlaştıran gergin bir indikatördür. Bu sebeple yanlış sinyaller almanıza ve trendin yönünü net analiz edememenize sebep olarak trade etmenizi zorlaştırır. Rsi Trend Velocity & Quality osilatörü içerdiği fonksiyonlar ile gergin olmayan daha sıkı duruşlar sergileyerek daha anlamlı eşikler üretir. Ayrıca aşırı gürültüye bağlı bozulma korkusu olmadan Rsi’ ın daha hızlı hareket etmesine sebep olarak daha erken sinyal almanıza vesile olur. Yani özetle daha sıkı duruşlar, daha iyi eşikler, daha hızlı bir Rsi ve erken sinyaller üreten pürüzsüz bir osilatördür.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Uyumsuzluk Uyarıları ve Alarmları Eklendi...
TopTenAlgo 5. Missmatch OscillatorEN: The Incompatibility Oscillator is an indicator used to detect trend turns and to catch mismatches in rising or falling waves. The Incompatibility Oscillator measures the mismatch between artificial pricing and actual price with a trend in the market compared to a Center Of Gravity . When designing the oscillator, my goal was to catch positive or negative mismatches as in RSI . Because most of the RSI incompatibilities are not working or running late, especially on short term charts. My goal was to eliminate the illusion here. I do not use any predefined indicators ( RSI etc.) in the Incompatibility Osilautre. It consists of a multiline mathematical function that scans the oscillator price movement in 100 steps. The aim here is to measure the price and the speed of the trend at the same time and catch the mismatches at the end of the trend.
This algorithm is prepared with @Top10Algo ...
TR: Uyumsuzluk Osilatörü trend dönüşlerini tespit etmek için ve yükseliş yada düşüş dalgalarındaki uyumsuzlukları yakalamak için kullanılan bir göstergedir. Uyumsuzluk Osilatörü piyasada trendle birlikte oluşa yapay fiyatlama ile gerçek fiyat arasındaki uyumsuzluğu bir ağırlık merkezine göre(Center Of Gravity ) ölçer. Osilatörü tasarlarken amacım RSI’ daki gibi pozitif yada negatif uyumsuzlukları yakalamaktı. Çünkü RSI uyumsuzlukların çoğu özelliklede kısa vade grafiklerde ya çalışmıyor yada geç çalışıyor. Amacım burdaki yanılgıyı ortadan kaldırmaktı. Uyumsuzluk Osilaötründe herhangi bir ön tanımlı gösterge( RSI vs.) kullanmıyorum. Osilatör fiyat hareketini 100 adımda tarayan bir multiline matemetiksel fonksiyondan oluşuyor. Burada amaç fiyat ile trendin hızını aynı anda ölçmek ve trend sonlarındaki uyumsuzlukları yakalamaktır.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır...
TopTenAlgo 6. Trading IndexEN: Trend & Trading Index Oscillator is an indicator developed using Stochastic which makes your day trading easier. Is it to measure price swings with a more sensitive and close to zero error margin, and is the price movement and the direction of the trend compatible? is the ideal guide to look at. The oscillator consists of a 5 step system. Depressions below -0.85 are measured to determine the intake region (Lowlander 2) at the bottom of the step. At the top of the step, enthusiastic movements above 0.90 are detected to determine the sales region(Highlander 2). The buffer zone is the BALANCE "0" zone and its highlander "0. 40 zone close to enthusiasm, and the Lowlander "-0.50" zone close to depression.
This algorithm is prepared with @Top10Algo ... Study modify...
TR: Trend & Trading Index Osiatörü Stochastic kullanırak geliştirilen ve gün içi al satlarınızı kolaylaştıran bir göstergedir. Fiyat salınımlarını daha hassas ve sıfıra yakın bir hatalama payıyla ölçmek ve fiyat hareketi ile trendin yönü uyumlu mu? bakmak için en ideal yol göstericidir. Osilatör 5 basamaklı bir sistemden oluşmaktadır. Basamağın en altında alım bögesini belirlemek için -0.85 değerinin altındaki depresyonlar(Lowlander 2) ölçülür. Basamağın en üstünde ise satış bölgesini belirlemek için 0.90 değerinin üstündeki coşkulu hareketler (Highlander 2) tespit edilir. Ara bölge ise BALANCE “0” bögesi ve onun coşkuya yakın Highlander 1 “0.40" bölgesi ile depresyona yakın Lowlander 1 “-0.50" bölgesi yer alır.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Çalışma Prensipleri modifiye edildi...
TopTenAlgo 7. Linear Trend Tracking (Without Volume & Coloring)EN:
Dogrusal Trend Takipcisi is used in conjunction with Gosterge Trend. Both indicators are for approval of each other. While the Indicator looks at Logarithmic to prices, It looks at Linear. Although its mathematical function is stuck between two trend lines like Gösterge Trend, the Dogrusal Trend Takipcisi can also be used as the main histogram, the absolute value of the difference between the trend and the down trend line .
If the uptrend line is larger than the downtrend, histogram bars are light green or dark green areas. When the bullish trend line now crosses the down trend line , the bar is dark green. When the up trend line is larger than the down trend line and the up trend line increases, the bars also become dark green. This tendency starts to keep getting stronger. If the bullish trend line is larger than the bearish trend line but decreases, the bars are light green. This is when the bullish trend loses strength, So, Uptrend is weakening.
If the downtrend line is larger than the bullish trend line , a negative occur, and the bars become red or light red. If the bearish trend line has exceeded the bullish trend line or the value is increasing, the bar is in red. If the bearish trend line is larger than the bullish trend line but the value is decreasing, the bars are light red. This comes when the downward trend is losing power. So, Downtrend is weakening. For symbols for which the Volume Indicator cannot be read.
This algorithm is prepared with @Top10Algo ...
TR: Doğrusal Trend Takipçisi Gösterge Trendle ile beraber kullanılır. Her iki göstergede birbirinin onayını almak içindir. Gösterge Trend fiyatlara logaritmik bakarken, Doğrusal Tren Takipçisi Linear bakar. Matematiksel fonsiyonu Gösterge Trend gibi iki trend çizgisi arasına sıkışmış olsada Doğrusal Trend Takipçisi ayrıca ana histogram olarak gösterilen yukarı trend ve aşağı trend çizgisi arasındaki farkın mutlak değerini linear olarak hesaplayarak momentumun gücünü ölçer ve size zayıflayan trendleri haber eder.gösterir.
Yukarı trend çizgisi aşağı trendden büyükse (bu nedenle pozitif hareketi gösterir), histogram çubukları açık yeşil veya koyu yeşil olacaktır. Artış trendi çizgisi şimdi aşağı trend çizgisini geçtiğinde, çubuk koyu yeşil olacaktır. Yukarı trend çizgisi aşağı trend çizgisinden daha büyük olduğunda ve yukarı trend çizgisi arttığında çubuklar da koyu yeşil olur. Bu eğilimin güçlenmeye devam ettiği anlamına geliyor. Yükseliş trendi çizgisi düşüş trendi çizgisinden büyükse ancak azalıyorsa, çubuklar açık yeşil olacaktır. Bu yükseliş eğiliminin güç kaybettiği anlamına gelir.Yani yükseliş trendi zayıflıyordur.
Düşüş trendi çizgisi yükseliş trendi çizgisinden büyükse, olumsuz bir eğilim oluşur ve çubuklar kırmızı veya açık kırmızı olur. Düşüş trendi çizgisi yükseliş trendi çizgisini aştıysa veya değer artıyorsa, çubuk kırmızı olacaktır. Düşüş trendi çizgisi yükseliş trendi çizgisinden büyükse, ancak değer azalıyorsa, çubuklar açık kırmızı olacaktır. Bu düşüş eğiliminin güç kaybettiği anlamına gelir. Yani düşüş trendi zayıflıyordur. Hacim Göstergesinin okunamadığı semboller içindir.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır...
TopTenAlgo 7. Linear Trend Tracking (Include Volume & Coloring)EN:
Dogrusal Trend Takipcisi is used in conjunction with Gosterge Trend. Both indicators are for approval of each other. While the Indicator looks at Logarithmic to prices, It looks at Linear. Although its mathematical function is stuck between two trend lines like Gösterge Trend, the Dogrusal Trend Takipcisi can also be used as the main histogram, the absolute value of the difference between the trend and the down trend line .
If the uptrend line is larger than the downtrend, histogram bars are light green or dark green areas. When the bullish trend line now crosses the down trend line , the bar is dark green. When the up trend line is larger than the down trend line and the up trend line increases, the bars also become dark green. This tendency starts to keep getting stronger. If the bullish trend line is larger than the bearish trend line but decreases, the bars are light green. This is when the bullish trend loses strength, So, Uptrend is weakening.
If the downtrend line is larger than the bullish trend line , a negative occur, and the bars become red or light red. If the bearish trend line has exceeded the bullish trend line or the value is increasing, the bar is in red. If the bearish trend line is larger than the bullish trend line but the value is decreasing, the bars are light red. This comes when the downward trend is losing power. So, Downtrend is weakening.
This algorithm is prepared with @Top10Algo ...
TR: Doğrusal Trend Takipçisi Gösterge Trendle ile beraber kullanılır. Her iki göstergede birbirinin onayını almak içindir. Gösterge Trend fiyatlara logaritmik bakarken, Doğrusal Tren Takipçisi Linear bakar. Matematiksel fonsiyonu Gösterge Trend gibi iki trend çizgisi arasına sıkışmış olsada Doğrusal Trend Takipçisi ayrıca ana histogram olarak gösterilen yukarı trend ve aşağı trend çizgisi arasındaki farkın mutlak değerini linear olarak hesaplayarak momentumun gücünü ölçer ve size zayıflayan trendleri haber eder.gösterir.
Yukarı trend çizgisi aşağı trendden büyükse (bu nedenle pozitif hareketi gösterir), histogram çubukları açık yeşil veya koyu yeşil olacaktır. Artış trendi çizgisi şimdi aşağı trend çizgisini geçtiğinde, çubuk koyu yeşil olacaktır. Yukarı trend çizgisi aşağı trend çizgisinden daha büyük olduğunda ve yukarı trend çizgisi arttığında çubuklar da koyu yeşil olur. Bu eğilimin güçlenmeye devam ettiği anlamına geliyor. Yükseliş trendi çizgisi düşüş trendi çizgisinden büyükse ancak azalıyorsa, çubuklar açık yeşil olacaktır. Bu yükseliş eğiliminin güç kaybettiği anlamına gelir.Yani yükseliş trendi zayıflıyordur.
Düşüş trendi çizgisi yükseliş trendi çizgisinden büyükse, olumsuz bir eğilim oluşur ve çubuklar kırmızı veya açık kırmızı olur. Düşüş trendi çizgisi yükseliş trendi çizgisini aştıysa veya değer artıyorsa, çubuk kırmızı olacaktır. Düşüş trendi çizgisi yükseliş trendi çizgisinden büyükse, ancak değer azalıyorsa, çubuklar açık kırmızı olacaktır. Bu düşüş eğiliminin güç kaybettiği anlamına gelir. Yani düşüş trendi zayıflıyordur.
Bu algoritma @Top10Algo ile beraber hazırlanmıştır...
TopTenAlgo 10. SQZMOM_LSvwMA with Bar ColorEN: This Algorithm is a derivative of John Carter's "TTM Squeeze" volatility indicator. Many strategists have taken the indicator on Tradingview with simple moving averages and have looked at the biggest mistake only by dealing with squeeze and exit processes to squeeze. But I used the algorithm to determine where the markets would actually explode. For example, instead of using SMAs , I tested them on the Linear Regression Curve using Volume Weighted Moving Averages and Hull MAs. This gave me the opportunity to develop a more responsive algorithm and identify where the actual explosion would occur. The Gray Circles in the midline show that the market is entering a new jam (in the Bollinger Bands and Keltner Channel). This means low volatility , the market prepares itself for an explosive move (up or down). White Circles mean that it is about to get out of the jam. The Blue Circles, which no one can calculate, now inform that the exit is no longer jammed and that the explosion has taken place.
Mr. Carter recommends that you wait until the first gray after a gray cross and take a position in the momentum direction (for example, if the momentum value is above zero, relax). Exit position when the momentum changes (increase or decrease, this is indicated by a color change). In this algorithm, I tried to achieve good entry points using an additional indicator such as ADX and WaveTrend. To draw the histogram, I used a different method based on Linear Regression . Mr.Carter uses a simple momentum indicator .
In summary, this algorithm is a strict algorithm in which additional 4-5 indicators are blended. Conveniences for Everyone ...
This algorithm is prepared with @Top10Algo ...
TR: Bu Algoritma John Carter'ın "TTM Squeeze" volatilite göstergesinin bir türevidir. Bir çok stratejist Tradingview' de gösterge' yi basit hareketli ortalamalarla ele almış ve en büyük hatayı sadece sıkışma ve sıkışmadan çıkış süreçlerini ele alarak bakmışlardır. Fakat ben algoritmayı piyasaların asıl patlama yapacağı yeri tespit etmek için kullandım. Örneğin SMA' ları kullanmak yerine Hacim Ağırlıklı Hareketli Ortalamaları ve Hull MA' ları kullanarak onları Linerar Regresyon Eğrisinde stress testine tabi tuttum. Buda bana daha duyarlı bir algoritma geliştirmem ve asıl patlamanın olacağı yerleri tespit etmem için fırsat verdi. Orta hattaki Gri Daireler, piyasanın yeni bir sıkışmaya girdiğini gösteriyor ( Bollinger Bantları ve Keltner Kanalı'nda). Bu, düşük volatilite anlamına gelir, piyasa kendisini patlayıcı bir harekete hazırlar (yukarı veya aşağı). Beyaz Daireler ise sıkışmadan çıkmak üzere olduğu anlamına gelir. Hiç kimsenin hesap edemediği Mavi Daireler ise artık sıkışmadan çıkıldığını ve patlamanın gerçekleştiğini haber verir.
Mr.Carter, gri bir çarpı işaretinden sonra ilk griye kadar beklemenizi ve momentum yönünde bir pozisyon almanızı önerir (örneğin, momentum değeri sıfırın üstünde ise, rahat olun). Momentum değiştiğinde pozisyondan çıkın (artırma veya azaltma, bunu o bir renk değişikliği ile belirtilir). Bu algoritmada ben, ADX ve WaveTrend gibi ek bir gösterge kullanarak iyi giriş noktalarıelde etmeye çalıştım. Histogramı çizmek için ise Linear Regresyon tabanlı farklı bir yöntem kullandım. Mr.Carter basit bir momentum göstergesi kullanır.
Özetle bu algoritma ek 4-5 göstergenin harmanlandığı sıkı bir algoritmadır. Herkese Kolaylıklar dilerim...
Bu algoritma @Top10Algo ile beraber hazırlanmıştır... Kodlamadaki katkılarından ve yol göstericiliğinden dolayı teşekkürü bir borç bilirim.
TopTenAlgo 10. SQZMOM_LSvwMA with Bar Color (Not Based Volume)EN: This Algorithm is a derivative of John Carter's "TTM Squeeze" volatility indicator. Many strategists have taken the indicator on Tradingview with simple moving averages and have looked at the biggest mistake only by dealing with squeeze and exit processes to squeeze. But I used the algorithm to determine where the markets would actually explode. For example, instead of using SMAs , I tested them on the Linear Regression Curve using Volume Weighted Moving Averages and Hull MAs. This gave me the opportunity to develop a more responsive algorithm and identify where the actual explosion would occur. The Gray Circles in the midline show that the market is entering a new jam (in the Bollinger Bands and Keltner Channel). This means low volatility , the market prepares itself for an explosive move (up or down). White Circles mean that it is about to get out of the jam. The Blue Circles, which no one can calculate, now inform that the exit is no longer jammed and that the explosion has taken place.
Mr. Carter recommends that you wait until the first gray after a gray cross and take a position in the momentum direction (for example, if the momentum value is above zero, relax). Exit position when the momentum changes (increase or decrease, this is indicated by a color change). In this algorithm, I tried to achieve good entry points using an additional indicator such as ADX and WaveTrend. To draw the histogram, I used a different method based on Linear Regression . Mr.Carter uses a simple momentum indicator .
In summary, this algorithm is a strict algorithm in which additional 4-5 indicators are blended. Conveniences for Everyone ... (For Symbols that cannot be read on the Volume Indicator)
This algorithm is prepared with @Top10Algo ...
TR: Bu Algoritma John Carter'ın "TTM Squeeze" volatilite göstergesinin bir türevidir. Bir çok stratejist Tradingview' de gösterge' yi basit hareketli ortalamalarla ele almış ve en büyük hatayı sadece sıkışma ve sıkışmadan çıkış süreçlerini ele alarak bakmışlardır. Fakat ben algoritmayı piyasaların asıl patlama yapacağı yeri tespit etmek için kullandım. Örneğin SMA' ları kullanmak yerine Hacim Ağırlıklı Hareketli Ortalamaları ve Hull MA' ları kullanarak onları Linerar Regresyon Eğrisinde stress testine tabi tuttum. Buda bana daha duyarlı bir algoritma geliştirmem ve asıl patlamanın olacağı yerleri tespit etmem için fırsat verdi. Orta hattaki Gri Daireler, piyasanın yeni bir sıkışmaya girdiğini gösteriyor ( Bollinger Bantları ve Keltner Kanalı'nda). Bu, düşük volatilite anlamına gelir, piyasa kendisini patlayıcı bir harekete hazırlar (yukarı veya aşağı). Beyaz Daireler ise sıkışmadan çıkmak üzere olduğu anlamına gelir. Hiç kimsenin hesap edemediği Mavi Daireler ise artık sıkışmadan çıkıldığını ve patlamanın gerçekleştiğini haber verir.
Mr.Carter, gri bir çarpı işaretinden sonra ilk griye kadar beklemenizi ve momentum yönünde bir pozisyon almanızı önerir (örneğin, momentum değeri sıfırın üstünde ise, rahat olun). Momentum değiştiğinde pozisyondan çıkın (artırma veya azaltma, bunu o bir renk değişikliği ile belirtilir). Bu algoritmada ben, ADX ve WaveTrend gibi ek bir gösterge kullanarak iyi giriş noktalarıelde etmeye çalıştım. Histogramı çizmek için ise Linear Regresyon tabanlı farklı bir yöntem kullandım. Mr.Carter basit bir momentum göstergesi kullanır.
Özetle bu algoritma ek 4-5 göstergenin harmanlandığı sıkı bir algoritmadır. Herkese Kolaylıklar dilerim... (Hacim Göstergesi okunamayan Semboller için)
Bu algoritma @Top10Algo ile beraber hazırlanmıştır...
Ranked TickThe NYSE TICK is, very simply, the number of stocks ticking down or up at any given time. It is, therefore, an internal indication of buying and selling pressure. By itself, it can be difficult to interpret. This “Ranked Tick” makes the TICK an oscillator that varies from 0 to 100. This indicator can be of great help in determining when the market is overbought or oversold.
This oscillator is a percentile ranking of the high + low of the current bar of the TICK compared to the recent values of the same sum over a certain number of bars, which the user can set as an input, the “Rank Length”. This indicator can be of great help in determining when the market is overbought or oversold.
It was conceived by SergioT for TradeStation, and he was gracious enough to share his TradeStation script with all the traders at elliottwavetrader.net. I transcribed it into Pine Script so that everyone at TradingView could also have it.
Trend Velocity & Quality
TR: Trend Velocity & Quality osilatörü klasik bir Rsi indikatörüne ek olarak trendin hızını ve kalitesini hassas bir biçimde ölçer. Rsi aslında teknik analizi zorlaştıran gergin bir indikatördür. Bu sebeple yanlış sinyaller almanıza ve trendin yönünü net analiz edememenize sebep olarak trade etmenizi zorlaştırır. Rsi Trend Velocity & Quality osilatörü içerdiği fonksiyonlar ile gergin olmayan daha sıkı duruşlar sergileyerek daha anlamlı eşikler üretir. Ayrıca aşırı gürültüye bağlı bozulma korkusu olmadan Rsi’ dan daha hızlı hareket ederek daha erken sinyal almanıza vesile olur. Yani özetle daha sıkı duruşlar, daha iyi eşikler, daha hızlı bir momentum göstergesi ve erken sinyaller üreten pürüzsüz bir osilatördür. Osilatörle ilgili daha fazla bilgi edinmek ve nasıl kullanıldığını öğrenmek için lütfen youtube videosunu izleyin.
Matematiksel Fonksiyon ;
Önce periyotluk Tipik Fiyat (Typical Price) Hesaplanır ve sonra Tipik Fiyat 100 ile çarpılırak Gecikmiş Tipik Fiyat bulunur ve bir önceki Gecikmiş Tipik Fiyat hesaplanır. Ardından bir önceki Gecikmiş Tipik Fiyattan mevcut Gecikmiş Tipik Fiyat çıkarılır ;
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Typical Price =
Latency TPC = 100 x Typical Price
Latency TPC = 100 x Typical Price
LagTP = Latency TPC – Latency TPC
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Daha sonra Laguerre Filtresi uygulanan fiyat için bir periyot belirlenirek hem Kümülatif Periyot hemde Multiline Fonksiyon kullanılarak iki farklı Kümülatif Tipik Fiyat hesaplanır. Bu genellikle saatlik ve altındaki grafikleri için 5 yada 8’ dir.
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Lenght = 8
Lenght C = 3 / (Lenght + 2)
Cumulative L = 1 - Lenght C
Cumulative TP = Cumulative L x Cumulative TP + Lenght C x LagTP
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En sonundada kümülatif fiyatlarla gecikmiş Tipik Fiyatlar kullanılarak Kümülatif RSI ve RSI T-V&Q hesaplanır.
Cumulative RSI = Lenght C x Cumulative TP + Cumulative L x Cumulative RSI
RSI T-V&Q = Cumulative TP x 1.618 - Cumulative RSI x 0.618
EN: The Trend Velocity & Quality oscillator precisely measures the speed and quality of the trend, in addition to a classic Rsi indicator. Rsi is actually a tense indicator that makes technical analysis difficult. For this reason, it makes it difficult for you to get false signals and trade the trend by not being able to analyze the direction of the trend clearly. Rsi Trend Velocity & Quality oscillator produces more meaningful thresholds with the functions it contains, showing tighter postures that are not tense. It also allows you to get signals earlier by moving faster than Rsi without fear of distortion due to excessive noise. In other words, it is a smooth oscillator that produces tighter postures, better thresholds, a faster momentum indicator and early signals. To learn more about the oscillator and how to use it, please watch the youtube tuttorial video.
Mathematical Function;
The Periodic Price is calculated first, and then the Typical Price is multiplied by 100 to find the Delayed Typical Price, and the previous Delayed Typical Price is calculated. The current Delayed Typical Price is then subtracted from the previous Delayed Typical Price;
-----------------------------------------
Typical Price =
Latency TPC = 100 x Typical Price
Latency TPC = 100 x Typical Price
LagTP = Latency TPC - Latency TPC
-----------------------------------------
Then, two different Cumulative Typical Prices are calculated by using both the Cumulative Period and the Multiline Function by determining a period for the price applied to the Laguerre Filter. This is usually 5 or 8 for hourly and below charts.
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Lenght = 8
Lenght C = 3 / (Lenght + 2)
Cumulative L = 1 - Lenght C
Cumulative TP = Cumulative L x Cumulative TP + Lenght C x LagTP
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Finally, Cumulative RSI and RSI T-V & Q are calculated using delayed Typical Prices with cumulative prices.
Cumulative RSI = Lenght C x Cumulative TP + Cumulative L x Cumulative RSI
RSI T-V & Q = Cumulative TP x 1.618 - Cumulative RSI x 0.618
RSI or MACD + Tendance Kijun LTThis script is an update of my previous script "RSI + Tendance Kijun LT", I will not explain it here, if needed have a look at it :
I made a new script (and not update the previous one) because some people may not be interested by MACD and for performance perspective they may be interested to only have RSI (since you can't have both but only switch from RSI and MACD)
So now, you can choose to have MACD instead of RSI with long term trend based on Kijun still dispaying. Why am I adding MACD even if most of the time I never use it ? It's for Elliott Wave purpose and principaly for triangle. With MACD, you can easily identify if you're forming a triangle or not in an Elliott Wave perspective (I'm not speaking about chartist triangle).
As an example, you can see ETHUSD in daily and something looking similar to a triangle. We can trade it with many possibility (breakout, support/resistance) but I'm interested in to identify if it's a triangle with an EW count (not chartist) and if it's the case I will consider different scenario (triangle are most of the time wave 4 so we could have one more push leg down on this ticker)
So, in my daytrading I'm still always using RSI except when I want to verify if we have a triangle :) and I need to switch to MACD for that to check the following things :
- am I able to draw a triangle as the price did
- may I able to join A to C and B to D and still have a triangle on MACD
- If Yes, I will take care of E point because it's the start of the 5th wave (E point may be a truncated wave of the triangle and not join the line of points A to C)
By adding this in my strategy, I can anticipate different scenarios and invalidate them if I didn't get the triangle on MACD (by having a D point on MACD not respecting the triangle form). Don't forget, we can decide to don't trade a triangle as an EW count but still trade it as a chartist form (breakout or anything else).
In summary for the next days/weeks, on ETHUSD in daily time unit I will therefore wait and see if the price goes up to point D by being validated on the MACD. If so, then I will look at the possible formation of point E around prices 141$ and 156$, if at these prices I have short signals then it will be interesting to go back in short position
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Ce script est une mise à jour de mon script précédent "RSI + Tendance Kijun LT", je ne l'expliquerai pas ici, si besoin jetez-y un oeil :
J'ai fait un nouveau script (sans forcer la mise à jour du précédent) parce que certaines personnes peuvent ne pas être intéressées par MACD et pour des raisons de performance, elles peuvent être intéressées à n'avoir que RSI (puisque vous ne pouvez pas avoir les deux en même temps mais seulement passer de RSI et MACD)
Donc maintenant, vous pouvez choisir d'avoir MACD au lieu de RSI avec une tendance à long terme basée sur Kijun qui s'affiche toujours. Pourquoi est-ce que j'ajoute MACD même si la plupart du temps je ne l'utilise jamais ? C'est pour Elliott Wave et surtout pour le triangle. Avec MACD, vous pouvez facilement identifier si vous formez un triangle ou non dans une perspective Elliott Wave (je ne parle pas de triangle chartiste).
Par exemple, vous pouvez voir que sur ETHUSD en unité de temps journalière nous avons quelque chose qui ressemble à un triangle. Nous pouvons faire des trade de pleins de manières différentes (cassure d'oblique, support/résistance) mais je suis intéressé d'identifier si c'est un triangle avec un compte EW (pas chartiste) et si c'est le cas, je vais envisager un scénario différent (sachant que les triangles sont la plupart du temps la vague 4 et donc envisager à la sortie une dernière poussée baissière type vague 5 sur ETHUSD)
Donc, dans mon daytrading, j'utilise toujours RSI sauf quand je veux vérifier si nous avons un triangle :) et j'ai besoin de passer à MACD afin de vérifier les éléments suivantes :
- Suis-je capable de dessiner un triangle comme le prix le dessine
- puis-je joindre A à C et B à D et toujours avoir un triangle sur MACD ?
- Si oui, je m'occupe du point E car c'est le début de la 5ème vague (le point E peut être une onde tronquée du triangle et ne pas joindre la ligne des points A à C).
En ajoutant cela dans ma stratégie, je peux anticiper différents scénarios et les invalider si je n'ai pas obtenu le triangle sur MACD (en ayant un point D sur MACD ne respectant pas la forme du triangle). N'oubliez pas, nous pouvons décider de ne pas le trade comme un triangle d'un décompte EW mais de le trade simplement comme un triangle chartiste (breakout ou autre chose).
En résumé pour les prochains jours/semaines, sur ETHUSD en unité de temps journalière je vais donc patienter et voir si le prix va jusqu'au point D en étant validé sur le MACD. Si oui, alors je regarderai l'éventuelle formation du point E autour des prix 141$ et 156$, si à ces prix j'ai des signaux vendeurs alors il sera intéressant de rentrer en position short
qEMA 3 LineMy scenario consists of 3 ema lines which are ema 34, ema89, ema 144.
3 ema lines are important in elliott waves:
- A complete elliott wave of 144 waves
- An eliott wave has 89 waves
- In wave with wave, in wave 89 again wave 34 waves
I used to find the waves in elliott, know where the cycle elliott will end up (when the price hit ema144)
Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment
## 1. Introduction
Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985).
The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014).
## 2. Theoretical Foundation
### 2.1 Momentum Theory and Market Anomalies
The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015).
### 2.2 Drawdown Analysis and Risk Management
Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators.
### 2.3 Adaptive Smoothing and Market Regimes
The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets.
## 3. Methodology
### 3.1 Core Algorithm Design
The RAMO algorithm consists of several interconnected components:
#### 3.1.1 Risk-Adjusted Momentum Calculation
The fundamental innovation of RAMO lies in its risk adjustment mechanism:
Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor)
Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05)
This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952).
#### 3.1.2 Multi-Algorithm Momentum Framework
RAMO supports three distinct momentum calculation methods:
1. Rate of Change: Traditional percentage-based momentum (Pring, 2002)
2. Price Momentum: Absolute price differences
3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997)
This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013).
### 3.2 Leading Indicator Components
#### 3.2.1 Momentum Acceleration Analysis
The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes:
Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n)
This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969).
#### 3.2.2 Linear Regression Prediction
RAMO incorporates linear regression-based prediction to project momentum values forward:
Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset)
This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes.
#### 3.2.3 Volume-Based Exhaustion Detection
The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns:
Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20)
This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989).
### 3.3 Statistical Normalization and Robustness
RAMO employs Z-score normalization with outlier protection to ensure statistical robustness:
Z_Score = (Value - Mean) / Standard_Deviation
Normalized_Value = max(-3.5, min(3.5, Z_Score))
This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions.
### 3.4 Adaptive Threshold Calculation
Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992):
Upper_Threshold = Mean + (Multiplier × Standard_Deviation)
Lower_Threshold = Mean - (Multiplier × Standard_Deviation)
This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992).
## 4. Implementation Details
### 4.1 Adaptive Smoothing Algorithm
The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility:
Volatility_Percentile = Percentrank(Volatility, 100)
Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100)
This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995).
### 4.2 Risk Environment Classification
RAMO classifies market conditions into three risk environments:
- Low Risk: Current_DD < 30% × Max_DD
- Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD
- High Risk: Current_DD ≥ 70% × Max_DD
This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014).
## 5. Signal Generation and Interpretation
### 5.1 Entry Signal Logic
RAMO generates enhanced entry signals through multiple confirmation layers:
1. Primary Signal: Crossover between indicator and signal line
2. Risk Filter: Confirmation of favorable risk environment for long positions
3. Leading Component: Early warning signals via acceleration analysis
4. Exhaustion Filter: Volume-based reversal detection
This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992).
### 5.2 Divergence Analysis
RAMO incorporates both traditional and leading divergence detection:
- Traditional Divergence: Price and indicator divergence over 3-5 periods
- Slope Divergence: Momentum slope versus price direction
- Acceleration Divergence: Changes in momentum acceleration
This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999).
## 6. Empirical Advantages and Applications
### 6.1 Risk-Adjusted Performance
The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980).
### 6.2 Regime Awareness
RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments.
### 6.3 Institutional Applications
The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013).
## 7. Limitations and Future Research
### 7.1 Parameter Sensitivity
Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions.
### 7.2 Market Microstructure Considerations
RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance.
### 7.3 Transaction Cost Integration
Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004).
## References
Aldridge, I. (2013). *High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems*. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Ang, A. (2014). *Asset Management: A Systematic Approach to Factor Investing*. New York: Oxford University Press.
Arms, R. W. (1989). *The Arms Index (TRIN): An Introduction to the Volume Analysis of Stock and Bond Markets*. Homewood, IL: Dow Jones-Irwin.
Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. *Journal of Finance*, 68(3), 929-985.
Barroso, P., & Santa-Clara, P. (2015). Momentum has its moments. *Journal of Financial Economics*, 116(1), 111-120.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. New York: McGraw-Hill.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. *Journal of Finance*, 47(5), 1731-1764.
Calmar, T. (1991). The Calmar ratio: A smoother tool. *Futures*, 20(1), 40.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). *The Econometrics of Financial Markets*. Princeton, NJ: Princeton University Press.
Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58.
Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247.
Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. *Journal of Finance*, 51(1), 55-84.
Granville, J. E. (1963). *Granville's New Key to Stock Market Profits*. Englewood Cliffs, NJ: Prentice-Hall.
Guidolin, M. (2011). Markov switching models in empirical finance. In D. N. Drukker (Ed.), *Missing Data Methods: Time-Series Methods and Applications* (pp. 1-86). Bingley: Emerald Group Publishing.
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. *Econometrica*, 57(2), 357-384.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. *Journal of Finance*, 48(1), 65-91.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291.
Kaufman, P. J. (1995). *Smarter Trading: Improving Performance in Changing Markets*. New York: McGraw-Hill.
Korajczyk, R. A., & Sadka, R. (2004). Are momentum profits robust to trading costs? *Journal of Finance*, 59(3), 1039-1082.
Leland, H. E. (1980). Who should buy portfolio insurance? *Journal of Finance*, 35(2), 581-594.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. *Journal of Finance*, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. *Journal of Finance*, 7(1), 77-91.
Murphy, J. J. (1999). *Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications*. New York: New York Institute of Finance.
Prechter, R. R., & Frost, A. J. (1978). *Elliott Wave Principle: Key to Market Behavior*. Gainesville, GA: New Classics Library.
Pring, M. J. (2002). *Technical Analysis Explained: The Successful Investor's Guide to Spotting Investment Trends and Turning Points*. 4th ed. New York: McGraw-Hill.
Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press.
Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790.
Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House.
Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314.
Treadway, A. B. (1969). On rational entrepreneurial behavior and the demand for investment. *Review of Economic Studies*, 36(2), 227-239.
Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Greensboro, NC: Trend Research.
NEoWave Chart Cash Data The NEoWave Chart Cash Data indicator is an efficient tool for generating wave charts or cash data based on the NeoWave method, benefiting not only NeoWave analysts but also Elliott Wave practitioners. This indicator produces cash data with exceptional precision.
Developed by Glenn Neely, NeoWave is considered a more complete, scientific, and innovative iteration of the Elliott Wave theory. This method relies on a specialized chart known as a "wave chart" or "cash data," which, when drawn manually by recording the highest and lowest prices in their order of occurrence, is a complex and time-consuming process. However, this indicator automatically and in real-time identifies the highest and lowest prices for any symbol and time frame, plotting them in sequence. For instance, in a daily time frame, it separates each month's data and prepares a "monthly cash data chart" for analysis using the NeoWave method.
Fully compatible with all account types, this tool enables the creation of cash data across various time frames (from minutes to years) and customizable scales. Its standout features include real-time updates, watermarking capabilities, display of useful data in tables, detection of suspicious monowaves (where the highest and lowest prices occur within the same candlestick), simultaneous display of two cash data charts with different time frames, and the ability to view cash data for any desired time period.
CASH DATA TIMEFRAMES
The core feature of this indicator is CASH DATA TIMEFRAMES, which generates and displays Cash Data based on your base timeframe. Here’s how it works:
.1 Minute ("1"): Cash Data: 5, 10, 15, 30, 60, 120, 180 minutes
.3 Minutes ("3"): Cash Data: 30, 60, 120, 180, 240 minutes
.5 Minutes ("5"): Cash Data: 30, 60, 120, 180, 240 minutes, 1 day (1D)
.15 Minutes ("15"): Cash Data: 120, 180, 240 minutes, 1 day (1D), 2 days (2D), 3 days (3D)
.30 Minutes ("30"): Cash Data: 180, 240 minutes, 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W)
.1 Hour ("60"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W)
.2 Hours ("120"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M)
.3 Hours ("180"): Cash Data: 1 day (1D), 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M)
.4 Hours ("240"): Cash Data: 2 days (2D), 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M), 2 months (2M)
.Daily ("D"): Cash Data: 1 week (1W), 2 weeks (2W), 1 month (1M), 2 months (2M), 3 months (3M), 6 months (6M), 12 months (12M)
.Weekly ("W"): Cash Data: 2 months (2M), 3 months (3M), 6 months (6M)
.Monthly ("M"): Cash Data: 6 months (6M), 12 months (12M)
Suspicious monowaves
Suspicious monowaves, visible in the "Inputs" section under the label "Sus Monowaves," are highlighted in red upon detection. This occurs when the highest and lowest prices within a given time period appear in a single candlestick. As illustrated, suspicious monowaves are marked with red squares, and the candlestick indicated by a red arrow is the trigger for identifying these monowaves.
In such instances, our indicator automatically plots the monowaves with high precision. This feature is tailored for users seeking cash data of the utmost accuracy. Whenever these monowaves appear on the chart, it is recommended that users examine the suspicious monowaves in a lower time frame for further analysis.
Other Cash Data TF
One of the key features of this indicator is the "Other Cash Data TF" option, which, when enabled, allows you to create two cash data charts with different time frames within your base time frame. This feature becomes particularly useful when, for example, your base time frame is daily, and you’ve identified a pattern like a zigzag in the monthly cash data. To confirm this pattern, you need to examine the internal waves A and C to determine whether they are impulsive. By activating this option and setting "Other TF" to a weekly time frame, you can easily analyze the internal waves of your chosen wave without altering the base time frame.
When this option is activated, a column is added to the table, indicating that the "Base TF" is daily, "Cash Data TF" is monthly, and "Other Cash Data TF" is weekly (as shown in the image below).
Other features of the indicator include:
.A Table providing useful information such as the symbol, base time frame, cash data time frame (Cash Data TF), number of monowaves, and live price.
.Customizable options for the table (including color, size, and column removal), watermark, cash data lines, suspicious monowaves, and more.
.A Time Separator that divides the chart into equal periods.
.The ability to add a watermark.
Supply & Demand Zones
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Supply and Demand Zones
This indicator displays valid Supply and Demand zones on any chart and timeframe, using dynamically updating visuals. Users can see the moment that zones become validated, used, and then invalidated during live sessions. It is sleek, lightweight, and offers a feature-rich settings panel that allows customization of how each element appears and functions. Zones can enhance the probability of successful trades by locating areas that are most likely to contain resting orders of Supply or Demand, which are needed for price reversals.
Disclaimer
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Like all indicators, this can be a valuable tool when incorporated into a comprehensive, risk-based trading system.
Supply and Demand is not the same thing as Support and Resistance.
Trading based on price hitting a zone without understanding which zones are of higher quality and which are of lower quality (only discernible with a trained human eye) will yield poor results.
Supply and Demand works well as a system and even better when added to an existing one. However, like all effective trading techniques, it requires diligent study, practice, and repetition to become proficient. This is an indicator for use with Supply and Demand concepts, not a replacement for learning them.
Features
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Once a valid candle sequence is confirmed, a box will appear that displays the zone over the precise zone range. At 50% zone penetration, a zone becomes used , and at 100% it becomes invalidated . Each of these zone classifications changes the behavior of the zone on the chart immediately. The settings panel offers custom colors for Supply , Demand , Used , and Invalidated zone types.
Borders : The subtle border colors can be changed or hidden.
Boxes or Bases : Advanced users can opt to hide zone boxes and instead display small, subtle tags over base candle groups. This allows for more customizable selection over what is displayed and how.
Max Zones and Hide Invalidated :
There are limitations on how many objects TradingView allows at once. Because of this, once zones go from used to invalidated , they are hidden (deleted) by default. This allows the zones index to be allocated to display more valid , usable zones instead. If a user prefers to keep invalidated zones visible, they can be enabled; however, this will result in showing more recent zones for fewer historical zones.
All zones share one pool, so if you allow fifty max zones, forty-five might be supply while five might be demand on a big sell-off trend. You will always see the most recent zones, regardless of type or status.
It’s up to you how much clutter you want on your screen and how much improved load time you want - but once loaded, zone creation and function are always instantaneous.
Load Time
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Load time refers to the time it takes from when you switch tickers or timeframes before the zones are displayed initially. There is zero lag in the dynamic function and minimal load time, regardless of settings. However, if you are a fine-tuner or multi-screener, the number of Max Zones displayed is the only major variable affecting load time.
I run everything at Max when I develop. When I trade, I run mine at 25 max zones because I change timeframes often and want a very quick display of zones when I do. I have invalidated hidden, and simply enable it if I want to check an old zone. This gives me more zones than I need and reduces the load time to right where I like it.
Thresholds
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It is recommended to leave these as the default.
Base Body Threshold : Determines the maximum ratio of a candle’s body to wick before invalidation. Default (50% or 0.5). A higher number loosens thresholds, resulting in more zones being displayed.
Unrequire 2nd FT if LO is Strong & Strength Multiplier :
The standard logic sequence requires two Follow-Through candles. Under some strong price movement, Leg-Out candles can make an explosive directional move from a base, making a convincing argument for supply and demand perfectly at work, if not for a single Follow-Through candle instead of two.
By enabling this feature, you can tell the script to ignore second Follow-Through candles, if and only if, the Leg-Out candle's range is (Strength) X the base range. exceeds the range of the Base by a factor of X (Strength). ie: At 5x, this would require a Leg-Out range to be 500% the range of the Base.
If enabled and the Leg-Out is not strong enough, the default logic kicks in, and a second follow-through candle will validate the zone as per usual. This loosens thresholds overall and should result in more zones.
Recommended Usage
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Form a thesis using your primary trend trading system (eg: Elliott Wave, Structure Reversal, TheStrat, et al) to identify locations of a pullback for a long or short entry.
Identify a pullback area using your system, then use this indicator to find a high-quality zone on your chosen timeframe.
Once located, draw your own channel over the indicator's zone box. Start on 1m, check for zones, 2m, 3m, and so on. When you see a zone you like, recreate it; thus, when finished, you can see every timeframe’s highest-quality zones that you created, regardless of what timeframe you switch to. Tip: Be selective
To make the process faster, save a channel design in settings for “Demand” and one for “Supply”, then you can quickly get through this process in less than a minute with practice.
Optional: Use additional methods (eg: Fibonacci retracements, Elliott Wave Theory, Anchored VWAPs) to find congruent confirmation.
Version 1.0
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No known bugs remain from the closed beta.
In Development
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Powerful combination zones occur when standard zone sequences are extended with additional levels of demand or supply by adding more conditionals to the state machine logic. Got this mostly working in a dev version and it adds minimal extra resources. Set aside to polish a clean standard 1.0 for release first, but now displaying these extended zones is my top priority for next version.
MTF support is essentially working in a dev copy, but adds resources. Not sure if it is in the spirit of price action being the primary focus of a chart for serious traders, rather than indicators. If there is demand for it, I'll consider it.
Additional Threshold Settings
Thanks!
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Thank you for your interest in my work. This was a personal passion project of mine, and I was delighted it turned out better than I hoped, so I decided to share it. If you have any comments, bugs, or suggestions, please leave them here, or you can find me on Twitter or Discord.
@ ContrarianIRL
Open-source developer for over 25 years
Trend of Multiple Oscillator Dashboard ModifiedDescription: The "Trend of Multiple Oscillator Dashboard Modified" is a powerful Pine Script indicator that provides a dashboard view of various oscillator and trend-following indicators across multiple timeframes. This indicator helps traders to assess trend conditions comprehensively by integrating popular technical indicators, including MACD, EMA, Stochastic, Elliott Wave, DID (Curta, Media, Longa), Price Volume Trend (PVT), Kuskus Trend, and Wave Trend Oscillator. Each indicator’s trend signal (bullish, bearish, or neutral) is displayed in a color-coded dashboard, making it easy to spot the consensus or divergence in trends across different timeframes.
Key Features:
Multi-Timeframe Analysis: Displays trend signals across five predefined timeframes (1, 2, 3, 5, and 10 minutes) for each included indicator.
Customizable Inputs: Allows for customization of key parameters for each oscillator and trend-following indicator.
Trend Interpretation: Each indicator is visually represented with green (bullish), red (bearish), and yellow (neutral) trend markers, making trend identification intuitive and quick.
Trade Condition Controls: Input options for the number of positive and negative conditions needed to trigger entries and exits, allowing users to refine the decision-making criteria.
Delay Management: Options for re-entry conditions based on both price movement (in points) and the minimum number of candles since the last exit, giving users flexibility in managing trade entries.
Usage: This indicator is ideal for traders who rely on multiple oscillators and moving averages to gauge trend direction and strength across timeframes. The dashboard allows users to observe trends at a glance and make informed decisions based on the alignment of various trend indicators. It’s particularly useful in consolidating signals for strategies that require multiple conditions to align before entering or exiting trades.
Note: Ensure that you’re familiar with each oscillator’s functionality, as some indicators like Elliott Wave and Wave Trend are simplified for visual coherence in this dashboard.
Disclaimer: This script is intended for educational and informational purposes only. Use it with caution and adapt it to your specific trading plan.
Developer's Remark: "This indicator's comprehensive design allows traders to filter noise and identify the most robust trends effectively. Use it to visualize trends across timeframes, understand oscillator behavior, and enhance decision-making with a more strategic approach."
Multi-Timeframe Recursive Zigzag [Trendoscope®]🎲 Welcome to the Advanced World of Zigzag Analysis
Embark on a journey through the most comprehensive and feature-rich Zigzag implementation you’ll ever encounter. Our Multi-Timeframe Recursive Zigzag Indicator is not just another tool; it's a groundbreaking advancement in technical analysis.
🎯 Key Features
Multi Time-Frame Support - One of the rare open-source Zigzag indicators with robust multi-timeframe capabilities, this feature sets our tool apart, enabling a broader and more dynamic market analysis.
Innovative Recursive Zigzag Algorithm - At its core is our unique Recursive Zigzag Algorithm, a pioneering development that powers multiple Zigzag levels, offering an intricate view of market movements. This proprietary algorithm is the backbone of our advanced pattern recognition indicators.
Sub-Waves and Micro-Waves Analysis - Dive deeper into market trends with our Sub-Waves and Micro-Waves feature. Sub-Waves reveal the interconnectedness of various Zigzag levels, while Micro-Waves offer insight into the fundamental waves at the base level.
Enhanced Indicator Tracking - Integrate and track your custom indicators or oscillators with the zigzag, capturing their values at each Zigzag level, complete with retracement ratios. This offers a comprehensive view of market dynamics.
Curved Zigzag Visualization - Experience a new way of visualizing market movements with our Curved Zigzag Display, employing Pine Script’s polyline feature for a more intuitive and visually appealing representation.
Built-in Customizable Alerts - Stay ahead with built-in alerts that can be customized via user input settings.
🎯 Practical Applications
Our Zigzag Indicator is designed with an understanding of its inherent nature - the last unconfirmed pivot that consistently repaints. This characteristic, while by design, directs its usage more towards pattern recognition rather than direct identification of market tops and bottoms. Here's how you can leverage the Zigzag Indicator:
Harmonic Patterns - Ideal for those familiar with harmonic patterns, this tool simplifies the manual spotting of complex XABCD, ABC, and ABCD patterns on charts.
Chart Patterns - Effortlessly identify patterns like Double/Triple Taps, Head and Shoulders, Inverse Head and Shoulders, and Cup and Handle patterns with enhanced clarity. Navigate through challenging patterns such as Triangles, Wedges, Flags, and Price Channels, where the Zigzag Indicator adds a layer of precision to your breakout strategy.
Elliott Wave Components - The indicator's detailed pivot highlighting aids in identifying key Elliott Wave components, enhancing your wave analysis and decision-making process.
🎲 Deep Dive into Indicator Features
Join us as we explore the intricate features of our indicator in more detail.
🎯 Multi-Timeframe Capability
Our indicator comes equipped with an input option for selecting the desired resolution. This unique feature allows users to view higher timeframe Zigzag patterns directly on their lower timeframe charts.
🎯 Recursive Multi Level Zigzag
Our advanced recursive approach creates multi-level Zigzags from lower-level data. For instance, the level 0 Zigzag forms the base, calculated from specified length and depth parameters, while level 1 Zigzag is derived using level 0 as its foundation, and so forth.
The indicator not only displays multiple Zigzag levels but also offers settings to emphasize specific levels for more detailed analysis.
🎯 Sub-Components and Micro-Components of Zigzag Wave
Sub-components within a Zigzag wave consist of the previous level's Zigzag pivots. Meanwhile, the micro-components are composed of the base level (Level 0) Zigzag pivots encapsulated within the wave.
🎯 Curved Zigzag
Experience a new perspective with our curved Zigzag display. This innovative feature utilizes the polyline curved option to automatically generate sinusoidal waves based on multiple points.
🎯 Indicator Tracking
Default indicators such as RSI, MFI, and OBV are included, alongside the ability to track one external indicator at each Zigzag pivot.
🎯 Customizable Alerts
Our indicator employs the `alert()` function for alert creation. While this means the absence of a customization text box in the alert settings, we've included a custom text area for users to create their own alert templates.
Template placeholders include:
{alertType} - type of alert. Either Confirmed Pivot Update or Last Pivot Update. Depends on the alert type selected in the inputs.
When Last Pivot Update type is selected, the alerts are triggered whenever there is a new Zigzag Pivot. This may also be a repaint of last unconfirmed pivot.
When Confirmed Pivot Update type is selected, the alerts are triggered only when a pivot becomes a confirmed pivot.
{level} - Zigzag level on which the alert is triggered.
{pivot} - Details of the last pivot or confirmed pivot including price, ratio, indicator values and ratios, subcomponent and micro-component pivots.
🎲 User Settings Overview
🎯 Zigzag and Generic Settings
This involves some generic zigzag calculation settings such as length, depth, and timeframe. And few display options such as theme, Highlight Level and Curved Zigzag. By default, zigzag calculation is done based on the latest real time bar. An option is provided to disable this and use only confirmed bars for the calculation.
Indicator Settings
Allows users to track one or more oscillators or volume indicators. Option to add any indicator via external input is provided.
🎯 Alert Settings
Has input fields required to select and customize alerts.
MTF Smart Money ConceptsOverview
This indicator displays major elements of Smart Money Concepts and price action trading with multi-timeframes(MTF) and layered market structures with color visualization.
What is Smart Money Concepts?
Smart Money Concepts(SMC) is one of the methodologies to interpret how financial market moves and to analyze it and execute trades, focusing on liquidity and order flow of financial institutions.
Smart money means the funds invested by large financial institutions such as banks, institutional traders/investors, market makers, hedge funds etc. contrary to retail traders/investors' money.
It is important to note that there is no proof or evidence that those institutions move the market as described in Smart Money Concepts.
Personally speaking, it is one of the interpretation of the market and another angle to view the market just like other technical analysis methodologies such as Elliott Wave Principle, Gann Theory, Wyckoff Method and even traditional price action trading.
Importance of MTF Analysis
MTF analysis(a.k.a Topdown analysis) is the foundation to technically analyze charts and the most fundamental skill in trading because lower timeframes are always influenced by upper timeframes where large financial institutions operate.
How to use
This indicator is designed to help traders analyze how the market moves in terms of SMC and price action with multi-timeframes and color visualization of the market structures, which makes this indicator unique and different from other indicators.
There is two key settings that you can use based on your trading style.
1.Upper timeframe selection
You have two options to determine upper timeframe; Auto mode and Manual mode.
When Auto mode selected, upper timeframe will be determined based on chart timeframe as follows.
Chart timeframe => Upper timeframe
1M=>15M
5M/15M=>1H
30M/1H=>4H
4H=>D
D=>W
W=>M
If you select Manual mode, you can fix an upper timeframe.
2.High/low settings
This affects all other settings of the indicator and most importantly designs the market structure.
This is the key setting to determine how you view the market as price action trading is all about highs and lows and story of how highs and lows have been created with the market structure.
You can specify left bars and right bars to identify swing highs/lows and these highs/lows become the basis to design the market structure and determine how SMC elements are displayed.
Example:
Left bar&right bar: 10
You can see bigger wave(magenta line) in the market structure(stepped line).
(Magenta line is a drawn object by manual)
Left bar&right bar: 4
With this setting, you can see smaller wave in the market structure.
Since market moves like wave as there is a lot of wave theories in financial investment/trading industry such as Elliott wave, Wolf wave etc., users can define market structure with this setting depending on what degree of wave they aim to trade.
Functions:
MTF Order Block
Concept
Order block is a block of orders where buying orders and selling orders are accumulated. Order blocks are created when the institutions move the market up and down, temporality placing orders in an opposite direction to the way they want to move, in order to match their own orders with counter-orders.
Visualization by the indicator
The indicator displays both chart timeframe's order blocks and upper timeframe's order blocks(MTF).
You can also select from two options how to display order blocks;
1. Show all order blocks
2. Show strong order blocks only
Note: Strong order blocks mean order blocks created at strong highs/lows. See also strong high/low below.
Alerts can be set when prices reach strong order blocks.
MTF Fair Value Gap(FVG)/Imbalance
Concept
Fair Value Gap(FVG)(Imbalance) is a void generated among three consecutive candlesticks.
FVG(s) is created when the market moves so rapidly generating buy side or sell side order imbalances.
FVG(s) is characterized by price action that prices tend to come back to the area where FVG(s) exists, filling in the space among the candlesticks.
Visualization by the indicator
The indicator displays both chart timeframe's FVG and upper timeframe's FVG.
MTF Liquidity Grab
Concept
Liquidity grab is price action to sweep liquidity for the institutions to move the market.
This price action often happens because the size of their orders is so huge and they need a bunch of counter-orders to match their orders. This is why prices sometimes come to areas where liquidity rest and swipe them before the market goes up/down.
Liquidity visualization
Where does liquidity rest?
The answer is above highs(buy side liquidity) and below lows(sell side liquidity).
Among all highs and lows, swing highs and lows are where liquidity is accumulated the most because swing highs and lows can be created only by the institutions, therefore massive liquidity is indicated.
Visualization by the indicator
The indicator displays liquidity dots so that users can easily identify where liquidity rests and liquidity grab of both a chart timeframe and an upper timeframe.
Alerts can be set when liquidity grab happens.
MTF Strong High/Low
Concept
Strong high/low literally means strong highs and lows among all highs and lows including swing highs and lows.
There is a few different definitions of strong high/low in price action trading and the definition in this indicator is as follows.
Strong high
A high that that breaks higher low or lower low
Strong low
A low that breaks lower high or higher high
Visualization by the indicator
The indicator displays strong highs and lows of both a chart timeframe and an upper timeframe.
MTF Market Structure Visualization
Concept
Market structure is a series of price movement with highs and lows which outlines the way the market directs. It is a basis to see trend occurrence, trend reversal and sideways and analyzing the market structures in multi-timeframes is the most fundamental technical skill in trading/investment.
Visualization by the indicator
The indicator displays market structures of both a chart timeframe and an upper timeframe and provide color visualization depending on bullish and bearish market structures.
The definition of bullish and bearish market structure is as follows.
Bullish market structure
When a price breaks a Lower High or Higher High
Bearish market structure
When a price breaks a Higher Low or Lower Low
Settings
All the functions above, colors and line settings are parameterized and can be turned on/off depending on users’ needs.
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概要
Smart Money Concepts(SMC)およびプライスアクショントレードにおける重要な要素をマルチタイムフレームで表示することのできるインジケーターです。
相場構造(Market structure)をマルチタイムフレームで表示し、相場構造の強弱を色で可視化することができます。
Smart Money Concepts(スマートマネーコンセプト)とは？
Smart Money Concepts(以下SMC) は金融市場がどのように動くかを解釈し、分析し、取引を執行するための相場理論の一つであり、Liquidity(リクイディティ)および機関投資家のオーダーフロー(注文の流れ)に焦点を置いていることが特徴です。
Smart Money(スマートマネー)とは、銀行や機関投資家、マーケットメーカー、ヘッジファンドといった金融機関が動かす資金を意味し、個人投資家の資金と対をなす概念です。
重要な点は、実際に上記の金融機関がSmart Money Conceptsで語られているような相場の動かし方をしているかどうかを証明する明確なエビデンスはないということです。
個人的には、エリオット波動理論やギャン理論、ワイコフ理論、伝統的なプライスアクショントレーディングの方法論と同様に、マーケットの動きを解釈するための一つの方法論であり、マーケットの動きを別の角度から見る枠組みと捉えています。
マルチタイムフレーム(MTF)分析の重要性
MTF分析はチャートをテクニカルに分析する上での基礎であり、トレードにおいて最も重要なスキルです。なぜなら下位のタイムフレームは上記のような金融機関が資金運用を行う上位のタイムフレームの影響を常に受けるためです。
使い方
このインジケーターは、SMCまたはプライスアクショントレードの観点から、トレーダーがマーケットをマルチタイムフレームで分析することを支援するために開発しています。
相場構造(Market structure/マーケットストラクチャー)を方向性に応じて色で可視化することができるため、視覚的に相場の構造を判断できることがこのインジケータのユニークな点であり、他のインジケーターと異なる点です。
ユーザーのトレードスタイルに応じて、以下の二つの設定を行うことができます。
1.上位足の決定方法
ユーザーは上位足のタイムフレームを決定するにあたり、AutoモードとManualモードを選択することができます。
Autoモードを選択した場合、上位足はチャートのタイムフレームに応じて以下のように決定されます。
チャートタイムフレーム => 上位足タイムフレーム
1M=>15M
5M/15M=>1H
30M/1H=>4H
4H=>D
D=>W
W=>M
Manualモードを選択すると上位足のタイムフレームを固定することができます。
2.High/low(高値/安値) 設定
当設定はインジケーターの他の全ての機能に影響し、また最も重要である相場構造の定義に影響します。
当設定はユーザーがマーケットをどのように見るか(=どの程度の粒度)を決定する重要な設定です。なぜならプライスアクショントレードは、高値、安値とそれらが相場構造をどのように構築してきたかの一連の流れを分析することが全てだからです。
ユーザーは相場構造を決定付けるスイングハイ·スイングローを特定するためのバーの本数を設定することができます。ここで設定した内容が、相場構造を定義し、以下で説明するSMCの要素の表示を決定することになります。
例:
Left bar&right bar(左右のバーの数): 10
この場合、ステップラインで示した相場構造の中に大きな波(マゼンタの波)を見ることができます。
(マゼンタのラインは手動で描いたオブジェクト)
Left bar&right bar: 4
この設定では、上記に比べて小さい波を描いていることが確認できます。
相場理論の中にエリオット波動理論やウォルフ波動といった数多くの波動理論があることからわかるように、相場は波として動きます。どの粒度の波を狙うかというトレーダーのスタイルに応じて、設定を変更することができます。
機能
MTFオーダーブロック
コンセプト
オーダーブロックとは買い注文と売り注文が一連となって蓄積されたオーダー(注文)のブロックのことです。
オーダーブロックは機関投資家が相場を動かす際に、本来意図する方向とは一時的に逆に動かすことで、彼ら自身の注文をマッチングさせるための反対注文を発生させることで形成されます。
インジケーターによる表示
インジケーターはチャートタイムフレームのオーダーブロックと上位足のオーダーブロックの両方を表示することができます。
また、オーダーブロックの表示オプションとして、
1.全てのオーダーブロックを表示
2.Strong(ストロング)オーダーブロックのみを表示
を選択することが可能です。
注: StrongオーダーブロックはStrong High/Lowで形成されるオーダーブロックを指します。(下記参照)
また、オーダーブロック到達でのアラート設定も可能です。
MTFフェアーバリューギャップ(FVG)/インバランス
コンセプト
フェアーバリューギャップ(FVG)/インバランスとは連続する3つのローソク足の間に形成される溝(Gap)のことです。
フェアーバリューギャップはマーケットが非常に早く動いたことにより、買いオーダーと売りオーダーの需給バランスが崩れることによって発生します。
フェアーバリューギャップには、価格がフェアーバリューギャップが発生したエリアまで戻ってくる傾向があるという特徴が存在します。
インジケーターによる表示
インジケーターはチャートタイムフレームのフェアーバリューギャップと上位足のフェアーバリューギャップの両方を表示することができます。
MTF Liquidity Grab(リクイディティ·グラブ)
コンセプト
Liquidity(リクイディティ)とはマネー、つまり注文です。
Liquidity Grab(リクイディティ·グラブ)とは、機関投資家がマーケットを動かす際にLiquidityを取得するプライスアクションのことを指します。
このプライスアクションは、機関投資家が処理する注文サイズが非常に大きいため、自身の注文を出す際に大量の反対注文を必要とすることからしばしば発生します。
これが、価格がLiquidity(注文)の集まっているエリアに接近し、それら注文をスワイプ(狩り取る)した後に上昇·下落する理由です。
Liquidityの可視化
一般的にLiquidityは高値の上(buy side liquidity)、安値の下(sell side liquidity)に存在します。
全ての高値·安値の中で、スイングハイ·ローがliquidityが最も蓄積されているエリアということができます。なぜならスイングハイ·ローは機関投資家の注文によってのみ形成されるからです。
インジケーターによる表示
ユーザーがLiquidityポイントを簡単に識別できるようにLiquidityをドット表示することが可能です。またチャートタイムフレームと上位足の両方のLiquidity Grabを表示することができます。
Liquidity Grab発生時にアラートも設定可能です。
MTF Strong High/Low(ストロングハイ·ロー)
コンセプト
Strong high/lowは文字通り、強い高値·安値のことを指します。
トレーダーの間でいくつかの異なる定義が存在しますが、当インジケーターでの定義は以下の通りです。
Strong high
Higher low(ハイアーロー) または Lower low(ロワーロー)をブレイクした高値
Strong low
Lower higher (ロワーハイ) または Higher High(ハイアーハイ)をブレイクした安値
インジケーターによる表示
チャートタイムフレーム、上位足のStrong High/Lowを表示することが可能です。
相場構造可視化
コンセプト
相場構造(Market structure/マーケットストラクチャー)とは、相場の流れを成り立たせる高値と安値を元にした一連の値動きです。建物における骨組みに該当します。
トレンドの発生、転換、レンジを見極めるための基礎であり、マルチタイムフレームで相場構造を分析することは、投資·トレードにおいて最も重要なテクニカルスキルです。
インジケーターによる表示
チャートタイムフレームと上位足タイムフレーム両方の相場構造を表示することができます。
また、相場構造が強気の状態か弱気の状態かを色で可視化するため、上位足含めた相場の流れを視覚的に判断することが可能です。
相場構造の強弱の定義は以下の通りです。
強気の相場構造(Bullish market structure)
価格がLower HighまたはHigher Highをブレイクしたとき
弱気の相場構造(Bearish market structure)
価格がHigher LowまたはLower Lowをブレイクしたとき
設定
上記の全ての機能は色やライン設定含めパラメーターで設定が可能です。またユーザの必要に応じて表示·非表示を切り替えることができます。
Auto Motive Wave [Trendoscope]Earlier we created an interactive script to study Motive Waves by manually selecting the wave patterns on the chart.
You can find the open source script here:
In this indicator, we will try to do it automatically. Hence, you don't need to draw the waves manually to check anymore. The indicator will do it for you.
🎲 Conditions for Motive Wave
Rules for Motive Waves remain same as before. Motive wave can be either Impulse or Diagonal Wave. Diagonal wave can be either expanding or contracting diagonals. To learn more about diagonal waves, please go through this idea.
🎲 Rules for generic motive waves are as below
Pivots in order - Checks wether the pivots selected are in progressive order.
Directions in order - Checks if the pivot directions are correct - either PH, PL, PH, PL, PH, PL or PL, PH, PL, PH, PL, PH
Wave 2 never moves beyond the start of wave 1 - Wave 2 retracement is less than 100% of wave1
Wave 3 always moves beyond the end of wave 1 - Wave 3 retracement is more than 100% of wave2
Wave 3 is never the shortest one - Checks if Wave 3 is bigger than either Wave 1 or wave 5 or both.
🎲 Now, these are the specific rules for Impulse Waves on top of Motive Wave conditions
Wave 4 never moves beyond the end of Wave 1 - meaning wave 1 and wave 4 never overlap on price scale.
Wave 1, 3, 5 are all not extended. We check for retracement ratios of more than 200% to be considered as extended wave.
🎲 Below are the conditions for Diagonal Waves on top of Motive Wave conditions
Wave4 never moves beyond the start of Wave 3 - Wave 4 retracement is less than 100%
Wave 4 always ends within the price territory of Wave 1 - Unlike impulse wave, wave 4 intersects with wave 1 in case of diagonal waves. This is the major difference between impulse and diagonal wave.
Waves are progressively expanding or contracting - Wave1 > Wave3 > Wave5 and Wave2 > Wave4 to be contracting diagonal. Wave1 < Wave3 < Wave5 and Wave2 < Wave4 to be expanding diagonal wave.
Settings are for the indicator include option to select zigzag length, theme color, and few constraints about the waves to be scanned. You can use the tooltips to find more about them
Volatility Percentile (H-LINES)A simple script that adjusts the Volatility Percentile Indicator visibly in order to better accommodate entries/exits and certain trading setups/strategies.
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TL;DR - Remember after a full reset, we are looking for initial crosses UP on the UpperSwingline and crosses DOWN on the LowerSwingline for primary and secondary signal derivation.
Vice versa also works great but the prior method mentioned is a little more consistent in my experience, but you should mess around and optimise this for your own setups and strategies anyway.
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ORIGINAL SCRIPT HERE:
^Click image for a redirect to that script.
ALL CREDIT GOES TO: www.tradingview.com
He wrote everything so give credit where it's due, good bit of kit this here script is.
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HOW I USE MY VISUALLY ALTERED VERSION OF THIS SCRIPT
First of all, the alterations I've made seem only to be consistently viable with renko charts though if you can get the sought after results using candles or any other chart type then perfect, but be wary. All my back-testing done only with LinReg, HMA and SWMA - ATR type settings exclusively on renko charts. The changes I've made to the original script essentially just turns it visibly into an oscillator and uses a couple horizontal lines to generate signals, very simple - absolutely nothing has changed in the actual code of calculating this indicator.
What I believe my adjustments have achieved is quite simple. A full reset/oscillation on the indicator tries to map the strongest parts of a move or at least the part of the move where volume and the rate of transactions is at its peak to even facilitate said move. *take this statement with a pinch of salt though I do believe it's interacting with accumulation/distribution patterns, which is expected of volatility*
For ease of communication let's refer to the area between the the first UpperSwingline cross to the subsequent LowerSwingline cross, as the primary move. Then afterwards when it crosses the UpperSwingline again to make the full reset, the area in between those two points referred to as the secondary move.
Though more interestingly/practically the indicator ends up giving you two signals. In order for this to work we have to first decide that a spike up in volatility which crosses the UpperSwingline implies a significant level of interest at that price level. Usually that means a reversal is brewing, if price has already moved, trended and is approaching a certain area of value; which causes a spike of new positions to be taken, then you know that this is a level where contrarians are looking to enter. Now here's the tricky part, when volatility crosses the LowerSwingline price action becomes a little more open for interpretation, the way I personally like to look at this secondary signal is the potential for an exhaustion period to prolong itself a little longer. I know that's not the perfect analysis for what's going on, a more in-depth look into what's going on would best be described using Elliott Wave Theory, if a cross on the UpperSwingline near a significant area of value gives us a reversal trade lets just assume for the sake of argument that a new Elliott Wave can begin forming here. Making the move from that initial UpperSwngline cross to the cross on the LowerSwingline, the area that encompasses those two points: the impulse wave. After this point my analogy kind of falls apart and sadly my knowledge just isn't what it needs to be in order for me to properly analyse what's going on here but I must digress. Price after crossing the LowerSwingline up until the point where it makes a full reset by crossing the UpperSwingline again, within this area price seems to do either one of two things:
Situation 1 - Most likely occurs after a major trend reversal from major support/resistance or area of value (price has trended to new territory, maybe spent time a little time consolidating but hasn't broken the key level, momentum shifts, price action breaks current structure and you get the signal that primary move is a reversal) = Exhaustion Period, price will continue in direction of primary move during the secondary move. This here is for our trend-followers, you wanna take a continuation trade? Just wait for the pullback/rally to hit a FiB retracement level and enter - or any other means to find a decent support/resistance to enter.
Situation 2 - Most likely occurs when market enters a range or consolidation (price was previously seen as being at either a discount or premium so Situation 1 could have already played out and now you're looking at a full reset after that, imagine this spot to be the centre line of a linear regression channel or bang in the middle of your range, could even occur if price breaks a key moving average and decides it ought to consolidate around it for a while. Basically at any point where a somewhat prolonged consolidation is expected and not a quick reversal) = Corrective Wave, price will move against the direction of primary move during the secondary move. Now you might be expecting me to say this ones for you reversal traders but not really, if this is occurring then there probably isn't a definitive direction the market has chosen so you can use this opportunity to take range trades in the direction or against the direction of whatever the current trend or latest trend was depending on whatever slight bias you may have. <--- Situation 2 is very useful for finding cleaner entries if you do have a trend bias, say price underwent Situation 1, is now at key moving average but your bias is that it will break and continue up, so you wait and allow the secondary move of Situation 2 to take your entry to a much better R:R before entering a position.
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