Strategy Gaussian Anomaly DerivativeConcept behind this Strategy :
Considering a normal "buy/sell" situation, an asset would be bought in average at the median price following a Gaussian like concept. A higher or lower average trend would significate that the current perceived value is respectively higher or lower than the current median price, which mean that the buyers are evaluating the price underpriced or overpriced.
This behaviour would be even more relevent depending on its derivative evolution.
Therefore, this Strategy setup is based on this Gaussian like concept anomaly of average close positionning compare to high-low average derivative, such as the derivative of the following ploted basic signal : 1-(high+low)/(2*close).
This Strategy can actually be used like a trend change and continuation strength indicator aswell.
In the Setup Signal part :
You can define the filtering of the basis signal "1-(high+low)/(2*close)" on EMA or SMA as you wish.
You can define the corresponding period and the threathold as a mutiply of the average 1/3 of all time value of the basis signal.
You can define the SMA filtering period of the Derivative signal and the corresponding threathold on the same mutiply of the average 1/3 of all time value of the derivative.
In the Setup Strategy part :
You can set up your strategy assesment based on Long and/or Short. You can also define the considered period.
The most successful tuned strategies I did were based on the derivative indicator with periods on the basis signal and the derivative under 30, can be 1 to 3 of te derivative and 7 to 21 for the basis signal. The threathold depends on the asset volatility aswell, 1 is usually the most efficient but 0 to 10 can be relevent depending on the situation I met. You can find an example of tuning for this strategy based on Kering's case hereafter.
I hoping that you will enjoy using this Strategy, don't hesitate to comment, to question, to correct or complete it ! I would be very curious about similar famous approaches that would have already been made.
Thank to you !
Médias Móveis
[blackcat] L1 T3 MA Lite Version
Tilson T3 Moving Average (T3MA) is a type of moving average line designed to reduce lag and improve the accuracy of trend identification. It is based on a combination of multiple smoothed moving averages, with each subsequent smoothed moving average having a higher weight than the previous one. The T3MA formula includes three different smoothing coefficients and a volume coefficient or volatility coefficient, which can be adjusted according to user preferences. T3MA is commonly used by traders and investors to identify trends and generate trading signals.
The calculation method for T3MA requires the use of exponential moving averages (EMA). In Pine scripts in the TradingView community, over 90% of them use the EMA function to calculate T3MA. Specifically, in Pine scripts, it is necessary to define the length and volatility coefficient of T3MA, then calculate three different lengths of EMA separately. Next, three constants need to be calculated that are related to volatility. Finally, the weighted average value of the three EMAs and three constants is added together to obtain the value of T3MA. If you want to customize the length and volatility of T3MA, you just need to modify the parameters in the code. Overall, T3MA is a very useful technical indicator that can help traders better understand market trends and improve trading efficiency.
The improved version introduced today mainly addresses my perception that traditional T3 algorithms are too redundant with high computational complexity leading to delayed reactions. Therefore, I have developed a lightweight version called L1 T3 MA Lite Version. This doesn't bring about any qualitative changes; it simply makes adjustments in terms of computational resources and response speed. To illustrate its advantages compared with traditional T3 MA indicators, I will provide a comparison using Everget's script from TradingView community blogger everget.
The difference between these two scripts for calculating T3 Moving Average lies in their implementation methods. The first script (Everget) uses a more complex calculation formula, which requires calculating three different lengths of EMA and computing three constants based on volatility. Finally, they are weighted averaged to obtain T3MA. This complex calculation formula can enhance the sensitivity of the T3MA indicator, thereby better identifying price trends. On the other hand, the second script (Blackcat1402) uses a relatively simple calculation formula that only requires calculating three different lengths of EMA and computing three constants based on volatility. Finally, they are weighted averaged to obtain T3MA as well. This simple calculation formula reduces computational complexity and speeds up calculations. Both have slightly different effects and calculation methods; users can choose the script that suits their needs.
In summary, T3 Moving Average is a very useful technical indicator that can help traders better understand market trends and improve trading efficiency. Users can choose scripts suitable for themselves according to their needs and flexibly adjust the length and volatility coefficient of T3MA to adapt to different markets.
Day Trader's Anchored Moving Averages [wbburgin]For day traders, establishing a trend at the start of the day is critically important for setting targets and entering positions. This can be difficult when traditional moving averages lag from previous days, causing late entry and/or incorrect trend interpretation.
The Day Trader's Anchored MA indicator plots three dynamic moving averages which restart on each new period (session or monthly - more coming soon). This eliminates the lag in traditional moving averages while better identifying the trend, as the moving averages essentially 'build up' their lengths as the day progresses, until they reach your chosen maximum length.
This means that these anchored moving averages are
Quicker to identify the start-of-day trend, as markets tend to establish and then follow one trend throughout the day;
Dynamically increasing throughout the day (to your specifications)
Completely independent from previous days
Quick usage note: make sure that your moving average length is less than the number of bars in the period, or it won't reach the maximum length you specified.
TL;DR: Moving average that resets every day and does not lag. Inspired by the VWAP.
Sudden increase in volume [PINESCRIPTLABS]The indicator plots buying and selling histograms on the price chart, as well as graphical signals in the form of triangles to highlight buying and selling conditions. Buying conditions are based on a sudden increase in volume and oversold RSI, while selling conditions are based on a sudden increase in volume and overbought RSI.
In summary, this strategy aims to identify moments when there is a significant surge in trading volume along with overbought or oversold conditions in the RSI. These moments are considered potential signals for buying or selling in the market.
Sudden Volume Surge: It checks if the current volume is greater than a multiple of the exponential moving average of volume (EMA) calculated with a specific length (ema_length). This indicates a sudden surge in trading volume.
RSI Overbought and Oversold Levels: Two RSI values, rsi_overbought and rsi_oversold, are used as references. If the RSI value is below the rsi_oversold level, it is considered to be in oversold territory, and if the RSI value is above the rsi_overbought level, it is considered to be in overbought territory.
El indicador plotea histogramas de compra y venta en el gráfico de precios, así como señales gráficas en forma de triángulos para resaltar las condiciones de compra y venta. Las condiciones para la compra se basan en un aumento brusco de volumen y un RSI en sobreventa, mientras que las condiciones para la venta se basan en un aumento brusco de volumen y un RSI en sobrecompra.
En resumen, esta estrategia busca identificar momentos en los que haya un aumento significativo en el volumen de operaciones junto con condiciones de sobrecompra o sobreventa en el RSI. Estos momentos se consideran señales potenciales de compra o venta en el mercado.
Aumento brusco de volumen: Se verifica si el volumen actual es mayor que un múltiplo del promedio móvil exponencial del volumen (EMA) calculado con una longitud específica (ema_length). Esto indica un aumento repentino en el volumen de operaciones.
Niveles de RSI en sobrecompra y sobreventa: Se utilizan dos valores de RSI como referencia, rsi_overbought y rsi_oversold. Si el valor del RSI está por debajo del nivel rsi_oversold, se considera que está en territorio de sobreventa, y si el valor del RSI está por encima del nivel rsi_overbought, se considera que está en territorio de sobrecompra.
DynamicEMA-RSI IndicatorIntroducing the 'Custom EMA and RSI Indicator' – a powerful trading tool compatible with US30 and USDJPY. This indicator is designed to provide high-precision trading signals once a day. It combines the expertise of Exponential Moving Averages (EMA) and Relative Strength Index (RSI) to identify optimal entry points in the market. With a track record of high accuracy, this indicator can help you make informed trading decisions. It's the perfect addition to your trading arsenal for precision trading on the US30 and USDJPY currency pairs."
3kilos BTC 15mThe "3kilos BTC 15m" is a comprehensive trading strategy designed to work on a 15-minute timeframe for Bitcoin (BTC) or other cryptocurrencies. This strategy combines multiple indicators, including Triple Exponential Moving Averages (TEMA), Average True Range (ATR), and Heikin-Ashi candlesticks, to generate buy and sell signals. It also incorporates risk management features like take profit and stop loss.
Indicators
Triple Exponential Moving Averages (TEMA): Three TEMA lines are used with different lengths and sources:
Short TEMA (Red) based on highs
Long TEMA 1 (Blue) based on lows
Long TEMA 2 (Green) based on closing prices
Average True Range (ATR): Custom ATR calculation with EMA smoothing is used for volatility measurement.
Supertrend: Calculated using ATR and a multiplier to determine the trend direction.
Simple Moving Average (SMA): Applied to the short TEMA to smooth out its values.
Heikin-Ashi Close: Used for additional trend confirmation.
Entry & Exit Conditions
Long Entry: Triggered when the short TEMA is above both long TEMA lines, the Supertrend is bullish, the short TEMA is above its SMA, and the Heikin-Ashi close is higher than the previous close.
Short Entry: Triggered when the short TEMA is below both long TEMA lines, the Supertrend is bearish, the short TEMA is below its SMA, and the Heikin-Ashi close is lower than the previous close.
Take Profit and Stop Loss: Both are calculated as a percentage of the entry price, and they are set for both long and short positions.
Risk Management
Take Profit: Set at 1% above the entry price for long positions and 1% below for short positions.
Stop Loss: Set at 3% below the entry price for long positions and 3% above for short positions.
Commission and Pyramiding
Commission: A 0.07% commission is accounted for in the strategy.
Pyramiding: The strategy does not allow pyramiding.
Note
This strategy is designed for educational purposes and should not be considered as financial advice. Always do your own research and consider consulting a financial advisor before engaging in trading.
Longonly. ema cross tester WithTolerenceJust a sample script to test ema cross strategy.
Tolerance is included to make the signal tunable.
SMA RSI Fractal Entry & Exit PointsUsing the 20, 50, 200 SMA, RSI, and Fractals to indicate when to exit buy/sells or move SL if your not trailing to protect profits
SMA RSI Fractal Strategy V4 Edit 1Made from RSI, SMA, and fractals. With the bands and signals for buy and sell entry. The colors are of opposite.
RSI+SMA AL SATrsi ve sma'nın kesiştiği dönemlerde yükseliş ve düşüş dalgalarını bulmaya yarıyan indikator
En ideal kullanım 8e 8 değerleri
Engulfing and emaThis is a Pine Script script that helps you see the Engulfing Candlestick and Inside Bar (Boring Candle) candle patterns on the TradingView chart, as well as drawing two Exponential Moving Averages (EMA). Here's a simple explanation:
1. **Candle Pattern**:
- This script identifies the Engulfing Candlestick pattern, which indicates potential changes to the price. If this pattern is detected, the script will show a green (for buy) or red (for sell) arrow above or below that candle.
- The script also identifies the Inside Bar (Boring Candle), which indicates the period area in the market. This candle will be the color you choose (default is orange).
2. **Moving Average (EMA)**:
- This script also plots two Exponential Moving Averages (EMA) on the chart. EMA is a tool that helps you see price trends more clearly.
3. **Risk Management**:
- This script calculates the Stop Loss (SL) and Take Profit (TP) levels for each Engulfing pattern. This helps you manage your trading risks.
- Labels are displayed on the charts for SL and TP, so you know where to place them.
With the help of this script, you can easily identify important patterns in the market and manage your risks better. Make sure to choose a demo account before using it in real trading.
EMA & Camarilla StrategyChat GPT based , 20, 200 EMA Strategy
This script calculates EMAs (5, 20, and 200), Camarilla Pivot Points, and checks for your specified candlestick pattern conditions. It then generates buy and sell signals based on the EMA crossover and the candlestick pattern. Stop loss is calculated as the lowest low of the last 5 bars, and the target is set at the Camarilla pivot point (you can customize these values).
EMA x 3 MAsThis indicator can be used for moving average strategies based on a EMA trigger over MAs (SMAs) : MA1 , MA2 , MA3 .
Based on those crossings, the background color will change for the upcoming candle showing green for upper crossing change (the more MA are crossed, the darker is the background). Order and priority of background colors :
1/ EMA x MA1
2/ EMA x MA2 (if EMA x MA1 confirmed)
3/ EMA x MA3 (if EMA x MA1and EMA x MA2 confirmed)
EMA and MAs can also be tuned with your own values in the parameters, therefore allowing you to try different strategies and to use the EMA and MAs as support/resistance indication.
You can set up the background and lines colors in the Style in the parameters.
[blackcat] L1 Magic Moving AverageThis is a code snippet written in the Pine programming language for TradingView platform. It is an implementation of a custom technical indicator called "L1 Magic Moving Average".
Moving averages are widely used in technical analysis to identify trends and reversals in the price of an asset. The idea behind moving averages is to smooth out the price data by calculating the average price over a certain period of time. This helps to filter out the noise in the price data and provides a clearer picture of the underlying trend.
The Magic Moving Average (MMA) is a custom moving average that is calculated using a combination of three different types of moving averages: simple moving average (SMA), exponential moving average (EMA), and weighted moving average (WMA). The MMA is designed to be more responsive to changes in the price of an asset compared to traditional moving averages.
The code starts by defining the input parameters for the indicator. The length parameter determines the number of periods used for calculating the moving averages. The source parameter specifies the price data used to calculate the moving averages. Finally, the smoothness parameter adjusts the weighting of the WMA component of the MMA.
Once the input parameters are defined, the code calculates the MMA by adding the SMA, EMA, and WMA components. The SMA and EMA components are calculated using the standard functions provided by TradingView. The WMA component is calculated using a custom function that takes into account the smoothness parameter.
After the MMA is calculated, the code plots it on the chart as two lines, one for the current value and one for the previous value. The two lines are then filled with colors depending on the position of the current MMA relative to its previous value. If the current value is higher than the previous value, the plot is filled with yellow color, otherwise, it is filled with fuchsia color.
In addition to the plot, the code also includes logic for generating buy and sell signals based on the crossover of the MMA and its previous value. If the MMA crosses above its previous value, a buy signal is generated. Conversely, if the MMA crosses below its previous value, a sell signal is generated. When a signal is generated, an alert is triggered to notify the user.
Finally, the code also includes labels for the generated signals. When a buy signal is generated, a green "B" label is placed at the bottom of the candle. Similarly, when a sell signal is generated, a red "S" label is placed at the top of the candle. These labels help the user to quickly identify the signals on the chart.
Overall, this code provides a simple yet effective way of generating trading signals based on the Magic Moving Average. By using a combination of different types of moving averages, the indicator is able to capture different aspects of the price movement and generate signals that are more reliable. The flexibility of the input parameters also allows the user to adjust the indicator to their specific trading needs.
TTP Green/Red Consecutive CandlesThis indicator counts consecutive green/red candles offering some basic statistics and signals/alerts.
Features
- Counts consecutive green/red candles in an oscillator chart
- Moving average of the counting helps spotting when the consecutive candles are away from the mean. MA length and multiplier to adjust the signal sensitivity.
- Thresholds can be set to backtest and send alerts on any number of arbitrary consecutive candles of the same color.
- All time highs: the indicator keeps track of when the maximum has been reached
- Distribution data: the number of times each number of consecutive color candles has been reached is offered
Signals
- Threshold signal triggers when the number of candles of the same color is above the specified threshold.
- MA cross signal triggers when the number of candles of the same color is above the MA.
[blackcat] L1 Guppy Multiple Moving Average (GMMA)Guppy Multiple Moving Average (GMMA) is a widely used technical analysis tool that can help traders identify price trends, determine entry and exit points, and identify signals of price reversal. The inventor of GMMA is Daryl Guppy, an Australian trader and technical analyst who developed this technical analysis tool in the late 1980s and early 1990s. GMMA is based on multiple moving averages (MA), including short-term and long-term moving averages (EMA). The short-term MA group consists of 6 MAs, and the long-term MA group also consists of 6 MAs. These MAs are grouped by color to make them easy to identify.
The basic principle of GMMA is that when prices are in an uptrend, the short-term MA group will be above the long-term MA group, and when prices are in a downtrend, the short-term MA group will be below the long-term MA group. The cross of the short-term MA group and the long-term MA group can help traders determine the direction and strength of the price trend. When the short-term MA group crosses and rises, traders can choose to enter the market, and when the short-term MA group crosses and falls, they can choose to exit the market. In addition, GMMA can also help traders identify signals of price reversal. When prices are in an uptrend, if the short-term MA group starts to cross down, this may be a signal of price reversal. Conversely, when prices are in a downtrend, if the short-term MA group starts to cross up, it may be a signal of price reversal.
The advantages of GMMA are that it can help traders identify price trends and signals of price reversal, thereby determining entry and exit points. In addition, the way GMMA is plotted makes the difference between the short-term and long-term MA groups more obvious, making it easy to identify. However, GMMA also has some disadvantages. For example, it can only provide limited information and cannot predict future price trends. In addition, GMMA needs to be combined with other technical indicators and fundamental analysis for trading decisions.
Overall, Guppy Multiple Moving Average (GMMA) is a powerful technical analysis tool that can help traders identify price trends, determine entry and exit points, and identify signals of price reversal. If traders can use GMMA correctly and combine it with other technical indicators and fundamental analysis, they can achieve better trading results.
VARGAS"VARGAS" is an indicator that can be used in all timeframes on charts in the stock, crypto, and commodity markets. It allows trades to be opened according to the intersections of moving averages in different time periods.
It is an indicator using weighted moving averages. Using a weighted moving average has the following benefits for traders:
1) Precision and Smoothness: The WMA typically gives more weight to recent prices and therefore reacts faster to more recent data. This helps you catch price movements faster and recognize trend changes faster. On the other hand, the WMA is smoother than the simple moving average (SMA), which makes it less likely to generate false signals.
2) Trend Identification: The WMA is used to identify and analyze price trends. It is especially important for traders who want to track short-term movements. The WMA is used to assess the direction and strength of the trend.
3) Trading Signals: The WMA is used as part of various trading strategies. It is especially used in moving average crossover strategies. For example, a short-term WMA crossing the long-term WMA to the upside can be considered a buy signal, while a reversal can be interpreted as a sell signal.
4) Adaptability to Volatility: WMA can adapt to volatility by changing weighting factors. Investors can adopt a more flexible approach by assigning different weights based on market conditions and asset classes.
5) Data Correction: WMA can be helpful in reducing data noise. A single large price fluctuation can cause the SMA to be more affected, while the WMA reduces the impact of these fluctuations.
In our VARGAS coding, the intersection times of the 9-day and 15-day weighted moving averages allow us to decide the direction of the trend. The green and red cloud areas following the price candles make the strategy easy for the user to follow.
At the intersection between the 9-day weighted moving average and the 15-day weighted moving average, we can use buy and sell signals as follows:
If the 9-day weighted moving average crosses the 15-day weighted moving average upwards, buy,
Sell if the 9-day weighted moving average crosses the 15-day weighted moving average downwards.
Within the scope of this strategy, GOLDEN CROSS and DEATH CROSS intersections, which guide us for trend changes, are also included in the coding. Thus, it is aimed to add strength to our WMA 9 and WMA 15 intersection strategy as an idea.
VARGAS indicator gives better results for longer periods of 4 hours and above. As the time period increases, the probability of correct results will increase.
**
"VARGAS" hisse senedi, kripto, ve emtia piyasalarındaki grafiklerde her türlü zaman diliminde kullanılabilen bir indikatördür. Farklı zaman periyotlarındaki hareketli ortalamaların kesişimlerine göre işlem açılmasını sağlar.
Ağırlıklı hareketli ortalamalar kullanılarak hazırlanmış bir göstergedir. Ağırlıklı hareketli ortalama kullanmanın yatırımcılara aşağıdaki gibi faydaları bulunmaktadır:
1) Duyarlılık ve Pürüzsüzlük: WMA, tipik olarak son dönem fiyatlarına daha fazla ağırlık verir ve bu nedenle daha güncel verilere daha hızlı tepki verir. Bu, fiyat hareketlerini daha hızlı yakalamanıza ve daha hızlı trend değişikliklerini tanımanıza yardımcı olur. Diğer yandan, WMA, basit hareketli ortalamaya (SMA) göre daha pürüzsüzdür, bu da yanlış sinyal üretme olasılığını azaltır.
2) Trend Belirleme: WMA, fiyat trendlerini belirlemek ve analiz etmek için kullanılır. Özellikle kısa vadeli hareketleri izlemek isteyen yatırımcılar için önemlidir. WMA, trendin yönünü ve gücünü değerlendirmek için kullanılır.
3) Ticaret Sinyalleri: WMA, çeşitli ticaret stratejilerinin bir parçası olarak kullanılır. Özellikle hareketli ortalama crossover stratejilerinde kullanılır. Örneğin, kısa vadeli WMA'nın uzun vadeli WMA'yı yukarı yönlü kesmesi bir alım sinyali olarak kabul edilebilir, tersine dönmesi ise bir satış sinyali olarak yorumlanabilir.
4) Volatiliteye Uyarlanabilirlik: WMA, ağırlıklandırma faktörlerini değiştirerek volatiliteye uyum sağlayabilir. Yatırımcılar, piyasa koşullarına ve varlık sınıflarına göre farklı ağırlıklar atayarak daha esnek bir yaklaşım benimseyebilirler.
5) Veri Düzeltme: WMA, veri gürültüsünü azaltmada yardımcı olabilir. Tek bir büyük fiyat dalgalanması, SMA'nın daha fazla etkilenmesine neden olabilirken, WMA bu dalgalanmaların etkisini azaltır.
VARGAS isimli kodlamamızda ise 9 günlük ve 15 günlük ağırlıklı hareketli ortalamaların kesişme zamanları trendin yönüne karar vermemizi sağlar. Fiyat mumlarını takip eden yeşil ve kırmızı bulut alanları stratejinin kullanıcı tarafından kolaylıkla takip edilmesini sağlamaktadır.
9 Günlük Ağırlıklı hareketli ortalama, 15 Günlük Ağırlıklı hareketli ortalama arasındaki kesişimde al ve sat sinyallerini şu şekilde kullanabiliriz:
Eğer 9 günlük ağırlıklı hareketli ortalama 15 günlük ağırlıklı hareketli ortalamayı yukarı doğru kesiyorsa al,
Eğer 9 günlük ağırlıklı hareketli ortalama, 15 günlük ağırlıklı hareketli ortalamayı aşağı doğru keserse sat.
Bu strateji kapsamında trend değişimleri için bizlere yön veren GOLDEN CROSS ve DEATH CROSS kesişimleri de kodlamanın içerisinde dahil edilmiştir. Böylelikle WMA 9 ve WMA 15 kesişim stratejimize fikir olarak güç katması hedeflenmiştir.
VARGAS indikatörü 4 saat ve üzeri daha uzun periyotlarda daha iyi sonuçlar vermektedir. Zaman periyodu büyüdükçe doğru sonuç verme olasılığı artacaktır.
Gaussian RibbonThe Gaussian Ribbon utilizes two "Arnaud Legoux" moving averages with the same length to identify changes in trend direction. The plotted channel consists of two lines, one based on the default offset and sigma values, and the other with slightly adjusted customizable parameters.
ALMA is a type of moving average that is related to the Gaussian function through its mathematical formula and the concept of weighted averages.
The ALMA is designed to reduce lag in moving averages and provide more timely responses to price changes. It achieves this by applying a Gaussian distribution (bell-shaped curve) as a weighting function to the price data.
The Gaussian function is used to calculate the weights in the ALMA formula. These weights give more importance to recent price data while gradually reducing the influence of older data points. This results in a smoother and more responsive moving average.
In summary, the Gaussian Ribbon uses the offset and power of the second ALMA to create a lag that still calculates using the same length.
[blackcat] L1 Variable Index Dynamic Average (VIDYA)Variable Index Dynamic Average (VIDYA) is a technical indicator that adjusts its sensitivity to market volatility. VIDYA is an exponential moving average (EMA) that uses the standard deviation of price as a measure of volatility. When the market is volatile, the indicator places more weight on recent prices, and when the market is stable, it places more weight on older prices. This makes VIDYA more responsive to market conditions than a regular EMA.
This script is a powerful tool that traders can use to gain valuable insights into market trends and make informed trading decisions. The L1 Variable Index Dynamic Average (VIDYA) is a technical indicator that adjusts its sensitivity to market volatility, making it more responsive to market conditions than a regular EMA. By incorporating the standard deviation of price as a measure of volatility, VIDYA can provide a more accurate representation of the market's current state, which can be especially useful in volatile markets.
One of the key features of this script is that it allows the user to customize the period and alpha inputs used in the VIDYA calculation. This means that traders can tailor the indicator to their specific trading strategies and preferences. By adjusting the period and alpha inputs, traders can fine-tune the sensitivity of the indicator to match the volatility of the market they're trading in.
In addition to plotting the VIDYA line on the chart, this script generates alerts and labels for buy and sell signals based on the crossover and crossunder of the VIDYA line. These alerts and labels can be incredibly helpful in identifying potential trading opportunities and avoiding costly mistakes. By being alerted to buy and sell signals in real-time, traders can take advantage of market movements and make trades quickly and confidently.
Another advantage of this script is that it is written in TradingView's Pine programming language, which is specifically designed for technical analysis and trading. Pine is a user-friendly language that allows traders to create custom indicators and strategies without having to learn a complex programming language. This means that even traders with little to no programming experience can use this script to gain valuable insights into the market.
Overall, this script is an excellent tool for traders who are looking for a powerful and customizable technical indicator that can help them make informed trading decisions. With its ability to adjust to market volatility, generate alerts and labels, and be customized to match individual trading strategies, the L1 Variable Index Dynamic Average (VIDYA) is a valuable addition to any trader's toolkit.
Price Strength Index + RSI Buy/Sell ZonesThe Price Strength Index + RSI Buy/Sell Zones indicator is a technical analysis tool designed to evaluate the strength of a financial asset's price movement by comparing it with a series of Volume Weighted Moving Averages (VWMAs) of different lengths calculated from historical data.
Hypothesis :
The core hypothesis behind this indicator is that assessing the relationship between the current price and a range of VWMAs with varying lengths can provide valuable insights into the strength and direction of a price trend. Additionally, it incorporates Relative Strength Index (RSI) conditions to further refine potential buy and sell signals.
How It Works :
Multiple VWMA Calculation: The indicator calculates multiple VWMAs, each with a different length, using historical price data and volume. These VWMAs represent weighted moving averages over various periods, helping to capture different aspects of the price trend.
Comparison with Current Price : For each of these VWMAs, the indicator compares the current bar's price with the VWMA value. This comparison is crucial in understanding how the current price relates to historical averages, shedding light on the strength and direction of the prevailing trend.
SMA of Percentage Above VWMA : The indicator calculates the Simple Moving Average (SMA) of the percentage of prices above the various VWMAs over a specified period. This moving average smoothens out the percentage data, providing a clearer trend signal.
Buy and Sell Zones : User-defined upper and lower thresholds for the percentage of prices above the VWMAs are used to define buy and sell zones. When the percentage falls below the lower threshold, it signals a potential buy zone, suggesting a weakening trend. Conversely, when it exceeds the upper threshold, it signifies a potential sell zone, indicating a strengthening trend.
RSI Integration : The RSI is calculated for the selected price source with a specified length. When the SMA of the percentage above VWMAs falls within the buy zone and the RSI is below the lower RSI threshold, it indicates an oversold condition, potentially signaling a buy opportunity. Conversely, when the SMA falls within the sell zone and the RSI is above the upper RSI threshold, it suggests an overbought condition, possibly signaling a sell opportunity.
Color Coding : The indicator employs color-coding to visually represent the buy and sell zones, as well as extreme RSI conditions. Green color denotes the buy zone, red represents the sell zone, and orange lines indicate the median and potential reversal points.
In summary, the Price Strength Index + RSI Buy/Sell Zones indicator leverages multiple VWMAs of different lengths to assess the relationship between current prices and historical moving averages. This comprehensive analysis, coupled with RSI conditions, aids traders in identifying potential buy and sell zones, as well as extreme RSI points within those zones, enhancing the evaluation of price strength and potential trend reversals.
VWMA/SMA Delta Volatility (Statistical Anomaly Detector)The "VWMA/SMA Delta Volatility (Statistical Anomaly Detector)" indicator is a tool designed to detect and visualize volatility in a financial market's price data. The indicator calculates the difference (delta) between two moving averages (VWMA/SMA) and uses statistical analysis to identify anomalies or extreme price movements. Here's a breakdown of its components:
Hypothesis:
The hypothesis behind this indicator is that extreme price movements or anomalies in the market can be detected by analyzing the difference between two moving averages and comparing it to a statistically derived normal distribution. When the MA delta (the difference between two MAs: VWMA/SMA) exceeds a certain threshold based on standard deviation and the Z-score coefficient, it may indicate increased market volatility or potential trading opportunities.
Calculation of MA Delta:
The indicator calculates the MA delta by subtracting a simple moving average (SMA) from a volume-weighted moving average (VWMA) of a selected price source. This calculation represents the difference in the market's short-term and long-term trends.
Statistical Analysis:
To detect anomalies, the indicator performs statistical analysis on the MA delta. It calculates a moving average (MA) of the MA delta and its standard deviation over a specified sample size. This MA acts as a baseline, and the standard deviation is used to measure how much the MA delta deviates from the mean.
Delta Normalization:
The MA delta, lower filter, and upper filter are normalized using a function that scales them to a specific range, typically from -100 to 100. Normalization helps in comparing these values on a consistent scale and enhances their visual representation.
Visual Representation:
The indicator visualizes the results through histograms and channels:
The histogram bars represent the normalized MA delta. Red bars indicate negative and below-lower-filter values, green bars indicate positive and above-upper-filter values, and silver bars indicate values within the normal range.
It also displays a Z-score channel, which represents the upper and lower filters after normalization. This channel helps traders identify price levels that are statistically significant and potentially indicative of market volatility.
In summary, the "MA Delta Volatility (Statistical Anomaly Detector)" indicator aims to help traders identify abnormal price movements in the market by analyzing the difference between two moving averages and applying statistical measures. It can be a valuable tool for traders looking to spot potential opportunities during periods of increased volatility or to identify potential market anomalies.
