Machine Learning : Cosine Similarity & Euclidean DistanceIntroduction:
This script implements a comprehensive trading strategy that adheres to the established rules and guidelines of housing trading. It leverages advanced machine learning techniques and incorporates customised moving averages, including the Conceptive Price Moving Average (CPMA), to provide accurate signals for informed trading decisions in the housing market. Additionally, signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation are utilised to enhance the signal quality and improve trading accuracy.
Features:
Market Analysis: The script utilizes advanced machine learning methods such as Lorentzian, Euclidean distance, and Cosine similarity to analyse market conditions. These techniques measure the similarity and distance between data points, enabling more precise signal identification and enhancing trading decisions.
Cosine similarity:
Cosine similarity is a measure used to determine the similarity between two vectors, typically in a high-dimensional space. It calculates the cosine of the angle between the vectors, indicating the degree of similarity or dissimilarity.
In the context of trading or signal processing, cosine similarity can be employed to compare the similarity between different data points or signals. The vectors in this case represent the numerical representations of the data points or signals.
Cosine similarity ranges from -1 to 1, with 1 indicating perfect similarity, 0 indicating no similarity, and -1 indicating perfect dissimilarity. A higher cosine similarity value suggests a closer match between the vectors, implying that the signals or data points share similar characteristics.
Lorentzian Classification:
Lorentzian classification is a machine learning algorithm used for classification tasks. It is based on the Lorentzian distance metric, which measures the similarity or dissimilarity between two data points. The Lorentzian distance takes into account the shape of the data distribution and can handle outliers better than other distance metrics.
Euclidean Distance:
Euclidean distance is a distance metric widely used in mathematics and machine learning. It calculates the straight-line distance between two points in Euclidean space. In two-dimensional space, the Euclidean distance between two points (x1, y1) and (x2, y2) is calculated using the formula sqrt((x2 - x1)^2 + (y2 - y1)^2).
Dynamic Time Windows: The script incorporates a dynamic time window function that allows users to define specific time ranges for trading. It checks if the current time falls within the specified window to execute the relevant trading signals.
Custom Moving Averages: The script includes the CPMA, a powerful moving average calculation. Unlike traditional moving averages, the CPMA provides improved support and resistance levels by considering multiple price types and employing a combination of Exponential Moving Averages (EMAs) and Simple Moving Averages (SMAs). Its adaptive nature ensures responsiveness to changes in price trends.
Signal Processing Techniques: The script applies signal processing techniques such as Know sure thing, Rational Quadratic, and sigmoid transformation to enhance the quality of the generated signals. These techniques improve the accuracy and reliability of the trading signals, aiding in making well-informed trading decisions.
Trade Statistics and Metrics: The script provides comprehensive trade statistics and metrics, including total wins, losses, win rate, win-loss ratio, and early signal flips. These metrics offer valuable insights into the performance and effectiveness of the trading strategy.
Usage:
Configuring Time Windows: Users can customize the time windows by specifying the start and finish time ranges according to their trading preferences and local market conditions.
Signal Interpretation: The script generates long and short signals based on the analysis, custom moving averages, and signal processing techniques. Users should pay attention to these signals and take appropriate action, such as entering or exiting trades, depending on their trading strategies.
Trade Statistics: The script continuously tracks and updates trade statistics, providing users with a clear overview of their trading performance. These statistics help users assess the effectiveness of the strategy and make informed decisions.
Conclusion:
With its adherence to housing trading rules, advanced machine learning methods, customized moving averages like the CPMA, and signal processing techniques such as Lorentzian, Euclidean distance, Cosine similarity, Know sure thing, Rational Quadratic, and sigmoid transformation, this script offers users a powerful tool for housing market analysis and trading. By leveraging the provided signals, time windows, and trade statistics, users can enhance their trading strategies and improve their overall trading performance.
Disclaimer:
Please note that while this script incorporates established tradingview housing rules, advanced machine learning techniques, customized moving averages, and signal processing techniques, it should be used for informational purposes only. Users are advised to conduct their own analysis and exercise caution when making trading decisions. The script's performance may vary based on market conditions, user settings, and the accuracy of the machine learning methods and signal processing techniques. The trading platform and developers are not responsible for any financial losses incurred while using this script.
By publishing this script on the platform, traders can benefit from its professional presentation, clear instructions, and the utilisation of advanced machine learning techniques, customised moving averages, and signal processing techniques for enhanced trading signals and accuracy.
I extend my gratitude to TradingView, LUX ALGO, and JDEHORTY for their invaluable contributions to the trading community. Their innovative scripts, meticulous coding patterns, and insightful ideas have profoundly enriched traders' strategies, including my own.
Médias Móveis
T3 JMA KAMA VWMAEnhancing Trading Performance with T3 JMA KAMA VWMA Indicator
Introduction
In the dynamic world of trading, staying ahead of market trends and capitalizing on volume-driven opportunities can greatly influence trading performance. To address this, we have developed the T3 JMA KAMA VWMA Indicator, an innovative tool that modifies the traditional Volume Weighted Moving Average (VWMA) formula to increase responsiveness and exploit high-volume market conditions for optimal position entry. This article delves into the idea behind this modification and how it can benefit traders seeking to gain an edge in the market.
The Idea Behind the Modification
The core concept behind modifying the VWMA formula is to leverage more responsive moving averages (MAs) that align with high-volume market activity. Traditional VWMA utilizes the Simple Moving Average (SMA) as the basis for calculating the weighted average. While the SMA is effective in providing a smoothed perspective of price movements, it may lack the desired responsiveness to capitalize on short-term volume-driven opportunities.
To address this limitation, our T3 JMA KAMA VWMA Indicator incorporates three advanced moving averages: T3, JMA, and KAMA. These MAs offer enhanced responsiveness, allowing traders to react swiftly to changing market conditions influenced by volume.
T3 (T3 New and T3 Normal):
The T3 moving average, one of the components of our indicator, applies a proprietary algorithm that provides smoother and more responsive trend signals. By utilizing T3, we ensure that the VWMA calculation aligns with the dynamic nature of high-volume markets, enabling traders to capture price movements accurately.
JMA (Jurik Moving Average):
The JMA component further enhances the indicator's responsiveness by incorporating phase shifting and power adjustment. This adaptive approach ensures that the moving average remains sensitive to changes in volume and price dynamics. As a result, traders can identify turning points and anticipate potential trend reversals, precisely timing their position entries.
KAMA (Kaufman's Adaptive Moving Average):
KAMA is an adaptive moving average designed to dynamically adjust its sensitivity based on market conditions. By incorporating KAMA into our VWMA modification, we ensure that the moving average adapts to varying volume levels and captures the essence of volume-driven price movements. Traders can confidently enter positions during periods of high trading volume, aligning their strategies with market activity.
Benefits and Usage
The modified T3 JMA KAMA VWMA Indicator offers several advantages to traders looking to exploit high-volume market conditions for position entry:
Increased Responsiveness: By incorporating more responsive moving averages, the indicator enables traders to react quickly to changes in volume and capture short-term opportunities more effectively.
Enhanced Entry Timing: The modified VWMA aligns with high-volume periods, allowing traders to enter positions precisely during price movements influenced by significant trading activity.
Improved Accuracy: The combination of T3, JMA, and KAMA within the VWMA formula enhances the accuracy of trend identification, reversals, and overall market analysis.
Comprehensive Market Insights: The T3 JMA KAMA VWMA Indicator provides a holistic view of market conditions by considering both price and volume dynamics. This comprehensive perspective helps traders make informed decisions.
Analysis and Interpretation
The modified VWMA formula with T3, JMA, and KAMA offers traders a valuable tool for analyzing volume-driven market conditions. By incorporating these advanced moving averages into the VWMA calculation, the indicator becomes more responsive to changes in volume, potentially providing deeper insights into price movements.
When analyzing the modified VWMA, it is essential to consider the following points:
Identifying High-Volume Periods:
The modified VWMA is designed to capture price movements during high-volume periods. Traders can use this indicator to identify potential market trends and determine whether significant trading activity is driving price action. By focusing on these periods, traders may gain a better understanding of the market sentiment and adjust their strategies accordingly.
Confirmation of Trend Strength:
The modified VWMA can serve as a confirmation tool for assessing the strength of a trend. When the VWMA line aligns with the overall trend direction, it suggests that the current price movement is supported by volume. This confirmation can provide traders with additional confidence in their analysis and help them make more informed trading decisions.
Potential Entry and Exit Points:
One of the primary purposes of the modified VWMA is to assist traders in identifying potential entry and exit points. By capturing volume-driven price movements, the indicator can highlight areas where market participants are actively participating, indicating potential opportunities for opening or closing positions. Traders can use this information in conjunction with other technical analysis tools to develop comprehensive trading strategies.
Interpretation of Angle and Gradient:
The modified VWMA incorporates an angle calculation and color gradient to further enhance interpretation. The angle of the VWMA line represents the slope of the indicator, providing insights into the momentum of price movements. A steep angle indicates strong momentum, while a shallow angle suggests a slowdown. The color gradient helps visualize this angle, with green indicating bullish momentum and purple indicating bearish momentum.
Conclusion
By modifying the VWMA formula to incorporate the T3, JMA, and KAMA moving averages, the T3 JMA KAMA VWMA Indicator offers traders an innovative tool to exploit high-volume market conditions for optimal position entry. This modification enhances responsiveness, improves timing, and provides comprehensive market insights.
Enjoy checking it out!
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Credits to:
◾ @cheatcountry – Hann Window Smoothing
◾ @loxx – T3
◾ @everget – JMA
Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
SA 2.0The 100/200 EMA crossover strategy is a popular trend-following strategy used in technical analysis. It aims to identify potential buy and sell signals based on the crossover of two exponential moving averages (EMAs), specifically the 100-period EMA and the 200-period EMA. This strategy is designed to capture the momentum of the market and take advantage of sustained trends in the price of US30. This strategy can also work on other instruments, just backtest the winrate.
How it Works:
Timeframe Selection: The strategy is optimized for the US30 index and is implemented on both the 5-minute and 3-minute charts. These shorter timeframes provide more frequent trading opportunities and allow for quicker decision-making.
EMA Crossover: The strategy focuses on the crossover of the 100-period EMA and the 200-period EMA. When the 100 EMA crosses above the 200 EMA, it generates a bullish signal, indicating a potential upward trend. Conversely, when the 100 EMA crosses below the 200 EMA, it generates a bearish signal, suggesting a potential downward trend.
Rejection Confirmation: To filter out false signals and increase the reliability of the strategy, it incorporates a rejection confirmation. After the initial crossover, the strategy looks for price rejections near the 100 EMA. A rejection occurs when the price briefly moves below the 100 EMA and then quickly bounces back above it, indicating potential support and a possible continuation of the trend. It is during this rejection that the strategy generates the buy or sell signal.
Buy and Sell Signals: When a rejection occurs after the crossover, the strategy generates a buy signal if the rejection is above the 100 EMA. This suggests that the price is likely to continue its upward momentum. On the other hand, a sell signal is generated if the rejection occurs below the 100 EMA, indicating a potential continuation of the downward trend. These signals help traders identify favorable entry points for long or short positions.
Risk Management: As with any trading strategy, proper risk management is crucial. Traders can use stop-loss orders to limit potential losses in case the market moves against their positions. Additionally, setting profit targets or trailing stops can help secure profits as the trend progresses.
It's important to note that no trading strategy guarantees success, and it's recommended to test the strategy on historical data or in a demo trading environment before applying it with real funds. Furthermore, regular monitoring and adjustment may be necessary to adapt to changing market conditions.
Disclaimer: This description is for informational purposes only and should not be considered as financial advice. Trading carries risks, and individuals should exercise caution and consult with a qualified financial professional before making any investment decisions.
EMA ProHi Traders!
This Improved EMA Cross Pro Indicator does a few things that Ease Up Our Charting.
Personally it Saved me Tons of Time searching for structure highs / lows, measuring ranges and distances from my entry to stop or take profit.
It's like having most of your trade in front of you, charted for you.
Works Across Assets & Time Frames.
The Functions
1. Signals EMA Crosses - green for Bull Cross & Red for Bear Cross
2. Signals Touches to the 55 EMA
a. In a Bull Cross it will only signal touches and closes Above the 55
b. In a Bear Cross it will only signal touches and closes Under the 55
3. Plots Current Horizontals:
a. The current position of the 55
b. The last High & Low
4. Calculation:
a. % from the 55 to the High & Low
b. Risk / Reward Ratio ("Bad Risk Management" message appears if ratio is not favorable)
c. Over Range between the Low and the High
5. Labels - Current prices for all horizontals marked as Entry, Exit & Stop
Notes:
* This Indicator is Interchanging between bull and bear crosses, it recognizes the trend and adapts its high and low output.
* You Can and Should make your personal changes. everything can be changed in the settings inputs.
* You can Turn On & Off most functions in the settings inputs.
BYBIT:BTCUSDT.P
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
EMA orderly stacked or notThis script plots a green circle on top of the chart when the EMAs are stacked positively, a red circle if they are stacked negatively and gray if neither positively nor negatively stacked.
The EMAs used are:
8 EMA
21 EMA
34 EMA
55 EMA
89 EMA
Useful when you look for a quick and easy way to see if these EMAs are stacked positively or negatively as a confirmation to the Squeeze Pro indicator if going long or short (Squeeze Pro is developed by John Carter at SimplerTrading.com and can be purchased there).
Default 100 bars back, but that can be adjusted.
Remember to do your own research.
Feel free to adjust the script to your liking.
The script is not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by me.
Have fun!
Recursive Moving Average DifferenceThe relative difference between a moving average and the price can be a useful tool for interpreting trend direction and identifying pullbacks or breakdowns. This indicator recursively finds all the relative moving average differences between two simple moving averages of your choosing and weighs them by their lengths. It then returns a value that represents the weighted average of all the moving average differences. This can represent the gradient of motion between moving averages, or the path of least resistance, which the price may revert to in certain situations.
For the settings: minimum MA represents the minimum simple moving average to consider for the total weighted average. Maximum MA represents the maximum simple moving average to consider. "Move By" is the increment that you want to move between these two moving averages.
A positive moving average difference indicates that the price is above the moving average difference (i.e. the weighted average of all moving average differences between your two selected moving averages). A negative moving average difference indicates that the price is below the moving average difference. I have added a signal with a configurable length input as well to smooth out trends.
You can configure colors and lengths, as well as the counting increment. Future updates may include different ways to calculate weights, perhaps on overlay or strategy.
ADW - MomentumADW - Momentum is a trading indicator based on the Relative Momentum Index (RMI) and Exponential Moving Averages (EMAs). This indicator plots the RMI along with its EMAs and highlights regions where RMI crosses its slow EMA. Additionally, it provides alerts when the momentum flips bullish or bearish.
Key Features:
The RMI helps to identify momentum in the market.
Three EMAs (Fast, Standard, and Slow) were calculated on the RMI. These can be utilized to analyze the momentum trend over different periods.
Highlighted regions and colour coding to indicate when RMI crosses its Slow EMA, signalling potential momentum shifts.
Customizable parameters: Users can specify the lengths of the RMI and EMAs, boundaries for RMI, and colours for various components of the plot.
Alerts: The script can alert users when the momentum has flipped bullish or bearish.
The script is organized into several sections:
Inputs: The user can customize several parameters including the RMI averaging length, momentum lookback, RMI boundaries, and the EMA lengths. In addition, users can also specify the colours for the RMI line, Slow EMA line, and the fill colour.
RMI Calculation: The script calculates the RMI based on the user-provided length and momentum lookback. This is done by first calculating two EMAs - one for the positive differences between closing prices (emaInc), and one for the negative differences (emaDec). Then, the RMI is computed using these EMAs.
Plotting: The script plots the RMI line, Slow EMA line, and two horizontal lines indicating the RMI boundaries. In addition, it also fills the region between the RMI and Slow EMA lines.
Conditions: The script computes the conditions for bullish and bearish momentum flips. These are defined as when the RMI crosses above or below the Slow EMA respectively.
Alerts: Finally, the script sets up two alert conditions based on the bullish and bearish conditions. These alert the user when the momentum has flipped bullish or bearish, with a message that includes the current RMI value.
ADW - Colour TrendColour Trend is an indicator that will give you a visual representation of the trend in a selected market, and alert you when the trend changes. The green colour represents a bullish trend (prices are going up), the red colour represents a bearish trend (prices are going down), and silver represents a neutral trend (prices are relatively stable). The script calculates these trends based on the relative price levels and their moving averages.
Below is a breakdown of the script so you can better understand how these trends are defined.
Function f_p(_length, price) : This function calculates the price relative to its highest and lowest point over the given `_length` of time. This calculation is normalized by multiplying it by 100, giving us a percentage-like measure.
User Inputs : The length of the period (default 12), you can choose to show or hide bar colours (default is true).
Variables cycle_avg, cycle_counter, cycle_count, cycle_trend, cycle_col : These variables are used to calculate the trend cycles. The `cycle_avg` is the average trend cycle, `cycle_counter` keeps track of the current trend cycle, `cycle_count` counts the total number of cycles, `cycle_trend` keeps track of the direction of the cycle (1 for up, -1 for down), and `cycle_col` defines the colour of the current cycle.
Variables ph, pl, avg, mean : These variables calculate the price level relative to the highest and lowest prices (`ph` and `pl`), the average of these two levels (`avg`), and the cumulative average of the price level (`mean`).
Conditionals for cycle trend : The if-statements are checking whether the price level has reached a trend extreme and then updating the trend cycle, colour, count, and average accordingly.
Variable col and bar color : The variable `col` is used to define the colour of the bars based on the average price level. If the `show_barcolor` is true, the colour is determined based on the `avg` value.
Alert Conditions : These are conditions that will send alerts to the user when the trend changes. Specifically, the alerts occur when the colour changes from non-green to green (bull trend), from non-red to red (bear trend), or from non-silver to silver (no trend).
RSI of Zero Lag MA (ValueRay)The RSI of a Zero Lag Moving Average a powerful tool for for reliable exit signals.
The Relative Strength Index (RSI) is a widely recognized momentum oscillator that measures the speed and change of price movements. It provides valuable insights into overbought and oversold conditions, enabling traders to identify potential reversal points and take advantage of market inefficiencies.
The RSI of a Zero Lag Indicator takes this concept a step further by incorporating the Zero Lag Moving Average. The Zero Lag Moving Average is a cutting-edge indicator that minimizes lag and provides a smoother representation of price action, allowing for quicker and more precise responses to market movements.
By combining the RSI with the Zero Lag Moving Average, this indicator offers traders a superior exit strategy. When the RSI reaches extreme levels of overbought or oversold conditions, it indicates a potential reversal in the market. The Zero Lag Moving Average further enhances this signal by reducing delays and providing timely exit points.
Moreover, the RSI of a Zero Lag Indicator is not limited to mean reversion strategies. While it excels in identifying mean reversion opportunities, it can also be used in conjunction with other trading approaches. Traders can take advantage of its objective signals to exit trades profitably, regardless of their chosen strategy.
With its ability to accurately pinpoint overbought and oversold conditions, the RSI of a Zero Lag Indicator offers traders a competitive edge in the market. By providing timely exit signals and minimizing lag, it helps traders optimize their trading decisions and increase their chances of success.
Multi-Divergence Buy/Sell IndicatorThe "Multi-Divergence Buy/Sell Indicator" is a technical analysis tool that combines multiple divergence signals from different indicators to identify potential buy and sell opportunities in the market. Here's a breakdown of how the indicator works and how to use it:
Input Parameters:
RSI Length: Specifies the length of the RSI (Relative Strength Index) calculation.
MACD Short Length: Specifies the short-term length for the MACD (Moving Average Convergence Divergence) calculation.
MACD Long Length: Specifies the long-term length for the MACD calculation.
MACD Signal Smoothing: Specifies the smoothing length for the MACD signal line calculation.
Stochastic Length: Specifies the length of the Stochastic oscillator calculation.
Stochastic Overbought Level: Defines the overbought level for the Stochastic oscillator.
Stochastic Oversold Level: Defines the oversold level for the Stochastic oscillator.
Calculation of Indicators:
RSI: Calculates the RSI based on the specified RSI Length.
MACD: Calculates the MACD line, signal line, and histogram based on the specified MACD parameters.
Stochastic: Calculates the Stochastic oscillator based on the specified Stochastic parameters.
Divergence Detection:
RSI Divergence: Identifies a bullish divergence when the RSI crosses above its 14-period simple moving average (SMA).
MACD Divergence: Identifies a bullish divergence when the MACD line crosses above the signal line.
Stochastic Divergence: Identifies a bullish divergence when the Stochastic crosses above its 14-period SMA.
Buy and Sell Conditions:
Buy Condition: Triggers a buy signal when all three divergences (RSI, MACD, and Stochastic) occur simultaneously.
Sell Condition: Triggers a sell signal when both RSI and MACD divergences occur, but Stochastic divergence does not occur.
Plotting Buy/Sell Signals:
The indicator plots green "Buy" labels below the price bars when the buy condition is met.
It plots red "Sell" labels above the price bars when the sell condition is met.
Usage:
The indicator can be used on any timeframe and for any trading instrument.
Look for areas where all three divergences (RSI, MACD, and Stochastic) align to generate stronger buy and sell signals.
Consider additional technical analysis and risk management strategies to validate the signals and manage your trades effectively.
Remember, no indicator guarantees profitable trades, so it's essential to use this indicator in conjunction with other tools and perform thorough analysis before making trading decisions.
Feel free to ask any questions
Price Action (ValueRay)With this indicator, you gain access to up to 5 moving averages from a selection of 15 different types. This flexibility allows you to customize your trading strategy based on your preferences and market conditions. Whether you're a fan of simple moving averages, exponential moving averages, or weighted moving averages, our indicator has got you covered! Additionally, all the MAs are Multi-Time-Frame!
The indicator also provides trading signals. By analyzing market trends and price movements, it generates accurate buy and sell signals, providing you with clear entry and exit points. You can choose between Fast, Mid, and Slow signal speeds.
Trendlines are another crucial aspect of effective trading, and our indicator seamlessly integrates them, helping you visualize the market's direction.
Furthermore, the indicator empowers you with recent highs and lows. By highlighting these key levels, it becomes easier than ever to spot support and resistance areas, aiding you in making well-informed trading choices.
Additionally, you can switch the ADR% (Average Daily Range as a Percentage) on and off. This number instantly provides you with information on how much the stock usually moves per day as a percentage.
Key Features:
Up to 5 Moving Averages, each with its own timeframe.
SMA, EMA, WMA, RMA, Triangular, Volume Weighted, Elastic Volume Weighted, Least Squares, ZLEMA, Hull, Double EMA, Triple EMA, T3, ALMA, KAMA (more to come in future versions).
Recent High and Low Pivot Points acting as support/resistance.
Trendline indicating the current trend.
Buy/Sell Signals (recommended for use as exit points, stop loss, or take profit levels).
Signals can have three different speeds: Fast, Mid, and Slow. You can switch them anytime depending on how quickly or slowly you want to exit a trade.
The predefined colors are best suited for a dark background, and the predefined settings provide a solid starting point that many traders use in their daily work.
Unlock the full potential of your trading strategy with our comprehensive indicator and start making informed trading decisions today!
Moving Averages + BB & R.VWAP StDev (multi-tf)█ Moving Averages + Bollinger Bands and Rolling Volume Weighted Average Price with Standard Deviation Bands (Multi Timeframe)
Multiple moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines and colors are customizable too.
This script can display:
Moving Averages
Bollinger Bands
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Based on the previous script :
Discrete Fourier Transform Overlay [wbburgin]The discrete Fourier transform (DFT) overlay uses a discrete Fourier transform algorithm to identify trend direction. This is a simpler interpretation that only uses the magnitude of the first frequency component obtained from the DFT algorithm, but can be useful for visualization purposes. I haven't seen many Fourier scripts on TradingView that actually have the magnitude plotted on the chart (some have lines, for instance, but that makes it difficult to look into the past or to see previous lines).
About the Discrete Fourier Transform
The DFT is a mathematical transformation that decomposes a time-domain signal into its constituent frequency components. By applying the DFT to OHLC data, we can interpret the periodicities and trends present in the market. I've designed the overlay so that you can choose your source for the Fourier transform, as well as the length.
Settings and Configuration
The "Fourier Period" is the transform length of the DFT algorithm. This input indicates the number of data points considered for the DFT calculation. For example, if this input is set to 20, the DFT will be performed on the most recent 20 data points of the input series. The transform length affects the resolution and accuracy of the frequency analysis. A shorter transform length may provide a broader frequency range but with less detail, while a longer transform length can provide finer frequency resolution but may be computationally more intensive (I recommend using under 100 - anything above that might take too much time to load on the platform).
The "Fourier X Series" is the source you want the Fourier transform to be applied to. I have it set in default to the close.
"Kernel Smoothing" is the bar-start of the rational quadratic kernel used to smooth the frequency component. Think of it just like a normal moving average if you are unfamiliar with the concept, it functions similarly to the "length" value of a moving average.
TTP NVT StudioNVT Studio is an indicator that aims to find areas of reversal of the Bitcoin price based on the extreme areas of Network Value Transaction.
Instructions:
- We recommend using it on INDEX:BTCUSD
- Use the daily or weekly timeframe
The indicator works as an oscillator and offers to visualisation modes.
1) Showing the short term oscillations of NVT showing signals in potential areas of reversal.
2) The actual value of NVT displayed. When in green is an area of value and in red when its overextended.
This indicator can be used based on the signals or based on breakouts of trend lines drawn in the oscillator mode.
Red/green dots: signal type 1 - extremes with confirmation, these might trigger late
Yellow/Orange: signal type 2 - extremes without confirmation, might trigger too soon
