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.
Średnie kroczące
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
Moving Average Contrarian IndicatorThis indicator is designed to identify potential turning points in the market. By measuring the distance between the price and a moving average, and normalizing it, the MACI provides valuable insights into market sentiment and potential reversals. In this article, we will explore the calculation, interpretation, and practical applications of the MACI, along with its potential limitations.
The MACI is calculated in several steps. First, a moving average is computed using a user-defined length, representing the average price over the specified period. The distance between the current price and the moving average is then determined. This distance is normalized using the highest and lowest distances observed within the chosen length, resulting in a value between 0 and 100. Higher MACI values indicate that the price is relatively far from the moving average, potentially signaling an overextension, while lower values suggest price consolidation or convergence with the moving average.
Altering the parameters of the Moving Average Contrarian Indicator can provide traders with additional flexibility and adaptability to suit different market conditions and trading styles. By adjusting the length parameter, traders can customize the sensitivity of the indicator to price movements. A shorter length may result in more frequent and responsive signals, which can be useful for short-term traders aiming to capture quick price reversals. On the other hand, a longer length may provide smoother signals, suited for traders who prefer to focus on longer-term trends and are less concerned with minor fluctuations. Experimenting with different parameter values allows traders to fine-tune the indicator to align with their preferred trading timeframes and risk tolerance. However, it is essential to strike a balance and avoid excessive parameter adjustments that may lead to over-optimization or curve fitting. Regular evaluation and optimization based on historical data and real-time market observations can help identify the most suitable parameter values for optimal performance.
The coloration of the Moving Average Contrarian Indicator provides visual cues that assist traders in interpreting its signals. The background color, set based on the indicator's values, adds an additional layer of context to the chart. When the indicator is indicating bullish conditions, the background color is set to lime, suggesting a favorable environment for long positions. Conversely, when the indicator signals bearish conditions, the background color is set to fuchsia, indicating a potential advantage for short positions. In neutral or transitional periods, the background color is set to yellow, indicating caution and the absence of a clear bias.
The bar color complements the histogram and provides additional visual clarity. When the MACI value is greater than the MACI SMA value and exceeds the threshold of 30, the bars are colored lime, signaling potential bullish conditions. Conversely, when the MACI value is below the MACI SMA value and falls below the threshold of 70, the bars are colored fuchsia, indicating potential bearish conditions. For values that fall between these thresholds, the bars are colored yellow, highlighting a neutral or transitional state.
Practical Uses and Strategies:
The MACI offers traders and analysts valuable insights into market dynamics and potential reversal points. When the MACI is above its moving average and above a predefined threshold (e.g., 30), it suggests that prices have deviated significantly from the average and may be overbought. This could serve as an early indication for potential short-selling opportunities or taking profits on existing long positions. Conversely, when the MACI is below its moving average and below a predefined threshold (e.g., 70), it suggests oversold conditions, potentially signaling a buying opportunity. Traders can combine MACI with other technical indicators or price patterns to further refine their trading strategies.
The MACI can be a powerful tool for identifying potential market reversals. When the MACI reaches extreme levels, such as above 70 or below 30, it indicates overbought or oversold conditions, respectively. Traders can use these signals to anticipate price reversals and adjust their trading strategies accordingly. For example, when the MACI enters the overbought zone, traders may consider initiating short positions or tightening stop-loss levels on existing long positions. Conversely, when the MACI enters the oversold zone, it may indicate a buying opportunity, prompting traders to consider initiating long positions or loosening stop-loss levels.
The MACI can also be used in conjunction with price action to identify potential divergence patterns. Divergence occurs when the MACI and price move in opposite directions. For instance, if the price is making higher highs while the MACI is making lower highs, it suggests a bearish divergence, indicating a potential trend reversal. Conversely, if the price is making lower lows while the MACI is making higher lows, it suggests a bullish divergence, signaling a potential trend reversal to the upside. Traders can use these divergence patterns as additional confirmation signals when making trading decisions.
Limitations:
-- Sideways and Choppy Markets : The MACI performs best in trending markets where price movements are more pronounced. In sideways or choppy markets with limited directional bias, the MACI may generate false signals or provide less reliable indications. Traders should exercise caution when relying solely on the MACI in such market conditions and consider incorporating additional analysis techniques or filters to confirm potential signals.
-- Lagging Indicator : The MACI is a lagging indicator, as it relies on moving averages and historical price data. It may not provide timely signals for very short-term trading or capturing rapid price movements. Traders should be aware that there may be a delay between the occurrence of a signal and its confirmation by the MACI.
-- False Signals : Like any technical indicator, the MACI is not immune to false signals. It is essential to use the MACI in conjunction with other technical indicators, chart patterns, or fundamental analysis to increase the probability of accurate predictions. Combining multiple confirmation signals can help filter out false signals and enhance the overall reliability of trading decisions.
-- Market Conditions : It's important to consider that the effectiveness of the MACI may vary across different markets and asset classes. Each market has its own characteristics, and what works well in one market may not work as effectively in another. Traders should evaluate the performance of the MACI within their specific trading environment and adapt their strategies accordingly.
This indicator can be a valuable addition to a trader's toolkit, offering insights into potential entry and exit points. However, it should be used in conjunction with other analysis techniques and should not be relied upon as a standalone trading signal. Understanding its calculation, interpreting its values, and considering its limitations will empower traders to make more informed decisions in their pursuit of trading success.
Moving Average Reversals [QuantVue]Moving Average Reversals
Description:
The Moving Average Reversals indicator gives a quick visual representation of when a stock gets extended up or down from a user selected moving average.
The color of the histogram dynamically changes as price becomes extended or within it’s normal trading range.
The indicator also highlights the largest extensions over the past year or 252 bars if using intraday.
Lastly a simple moving average of the extensions is calculated and used to confirm a change of character.
Settings:
🔹Use different MA types - EMA, SMA, HMA, WMA, VWMA
🔹Adjustable MA length
🔹Change distance measurement source - open, close, high, low, hl2, hlc3, ohlc4, hlcc4
🔹Extension highlighting
🔹Toggle MA extensions
Don't hesitate to reach out with any questions or concerns. We hope you enjoy!
Cheers.
MADI(Moving average deviation rate index)This script is "Moving average deviation rate" to Indexing.
index = average deviation rate / (Sigma * (input:SIgma)) * 100
It's for people who like simplicity.
Biddles OIWAP-Price SpreadThis indicator is the companion to my OIWAP (Open Interested-Weighted Average price) open source indicator.
In observing the OIWAP, what seemed most interesting was the distance between price and OIWAP.
This indicator plots that spread in a histogram.
It seems when price is too high above all OIWAPs, it's locally overbought (sentiment is overly bullish), and vice versa when it's too far below all OIWAPs (sentiment is overly bearish).
But I think there are more unique observations to be made beyond that - I am still in discovery phase myself.
For example: Looking at the SPX while using the ticker override to display BINANCE:BTCUSDT.P OI-Price spread data.
It works on any asset that Tradingview has OI data for. But it's also interesting to view correlated assets by using ticker override in the indicator settings (open the correlated asset w/o OI data in your chart, then set ticker override to a symbol with OI data, like the SPX example above).
>> If you find any interesting observations using it, have suggestions for improving the script, etc., hit me up on Twitter!
>>> @thalamu_
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
Adaptive Gaussian Moving AverageThe Adaptive Gaussian Moving Average (AGMA) is a versatile technical indicator that combines the concept of a Gaussian Moving Average (GMA) with adaptive parameters based on market volatility. The indicator aims to provide a smoothed trend line that dynamically adjusts to different market conditions, offering a more responsive analysis of price movements.
Calculation:
The AGMA is calculated by applying a weighted moving average based on a Gaussian distribution. The length parameter determines the number of bars considered for the calculation. The adaptive parameter enables or disables the adaptive feature. When adaptive is true, the sigma value, which represents the standard deviation, is dynamically calculated using the standard deviation of the closing prices over the volatilityPeriod. When adaptive is false, a user-defined fixed value for sigma can be input.
Interpretation:
The AGMA generates a smoothed line that follows the trend of the price action. When the AGMA line is rising, it suggests an uptrend, while a declining line indicates a downtrend. The adaptive feature allows the indicator to adjust its sensitivity based on market volatility, making it more responsive during periods of high volatility and less sensitive during low volatility conditions.
Potential Uses in Strategies:
-- Trend Identification : Traders can use the AGMA to identify the direction of the prevailing trend. Buying opportunities may arise when the price is above the AGMA line during an uptrend, while selling opportunities may be considered when the price is below the AGMA line during a downtrend.
-- Trend Confirmation : The AGMA can be used in conjunction with other technical indicators or trend-following strategies to confirm the strength and sustainability of a trend. A strong and steady AGMA line can provide additional confidence in the prevailing trend.
-- Volatility-Based Strategies : Traders can utilize the adaptive feature of the AGMA to build volatility-based strategies. By adjusting the sigma value based on market volatility, the indicator can dynamically adapt to changing market conditions, potentially improving the accuracy of entry and exit signals.
Limitations:
-- Lagging Indicator : Like other moving averages, the AGMA is a lagging indicator that relies on historical price data. It may not provide timely signals during rapidly changing market conditions or sharp price reversals.
-- Whipsaw in Sideways Markets : During periods of low volatility or when the market is moving sideways, the AGMA may generate false signals or exhibit frequent crossovers around the price, leading to whipsaw trades.
-- Subjectivity of Parameters : The choice of length, adaptive parameters, and volatility period requires careful consideration and customization based on individual preferences and trading strategies. Traders need to adjust these parameters to suit the specific market and timeframe they are trading.
Overall, the Adaptive Gaussian Moving Average can be a valuable tool in trend identification and confirmation, especially when combined with other technical analysis techniques. However, traders should exercise caution, conduct thorough analysis, and consider the indicator's limitations when incorporating it into their trading strategies.
Chilllax Moving Averages with Qullamaggie colors// Display 2 Moving Averages. Default is 10d sma and 20d sma. You can choose any length. Choose sma, or ema. Choose ma of Open, High, Low, or Close
// Color code is based on Qullamaggie's idea:
// Dark green = 10d ma > 20d ma, and both trending up
// Light green = 10d ma > 20d ma, but only 10d ma trending up
// Yellow = 10d ma > 20d ma, but neither trending up
// You can change the color
// You can hide the colors, then it will simply show 2 moving averages of your choice
// Trend is comparing the ma from X trendlen days ago. Default to 5 days ago. So, if today's ma is > 5 days ago, it is trending up
Nonlinear Regression, Zero-lag Moving Average [Loxx]Nonlinear Regression and Zero-lag Moving Average
Technical indicators are widely used in financial markets to analyze price data and make informed trading decisions. This indicator presents an implementation of two popular indicators: Nonlinear Regression and Zero-lag Moving Average (ZLMA). Let's explore the functioning of these indicators and discuss their significance in technical analysis.
Nonlinear Regression
The Nonlinear Regression indicator aims to fit a nonlinear curve to a given set of data points. It calculates the best-fit curve by minimizing the sum of squared errors between the actual data points and the predicted values on the curve. The curve is determined by solving a system of equations derived from the data points.
We define a function "nonLinearRegression" that takes two parameters: "src" (the input data series) and "per" (the period over which the regression is calculated). It calculates the coefficients of the nonlinear curve using the least squares method and returns the predicted value for the current period. The nonlinear regression curve provides insights into the overall trend and potential reversals in the price data.
Zero-lag Moving Average (ZLMA)
Moving averages are widely used to smoothen price data and identify trend directions. However, traditional moving averages introduce a lag due to the inclusion of past data. The Zero-lag Moving Average (ZLMA) overcomes this lag by dynamically adjusting the weights of past values, resulting in a more responsive moving average.
We create a function named "zlma" that calculates the ZLMA. It takes two parameters: "src" (the input data series) and "per" (the period over which the ZLMA is calculated). The ZLMA is computed by first calculating a weighted moving average (LWMA) using a linearly decreasing weight scheme. The LWMA is then used to calculate the ZLMA by applying the same weight scheme again. The ZLMA provides a smoother representation of the price data while reducing lag.
Combining Nonlinear Regression and ZLMA
The ZLMA is applied to the input data series using the function "zlma(src, zlmaper)". The ZLMA values are then passed as input to the "nonLinearRegression" function, along with the specified period for nonlinear regression. The output of the nonlinear regression is stored in the variable "out".
To enhance the visual representation of the indicator, colors are assigned based on the relationship between the nonlinear regression value and a signal value (sig) calculated from the previous period's nonlinear regression value. If the current "out" value is greater than the previous "sig" value, the color is set to green; otherwise, it is set to red.
The indicator also includes optional features such as coloring the bars based on the indicator's values and displaying signals for potential long and short positions. The signals are generated based on the crossover and crossunder of the "out" and "sig" values.
Wrapping Up
This indicator combines two important concepts: Nonlinear Regression and Zero-lag Moving Average indicators, which are valuable tools for technical analysis in financial markets. These indicators help traders identify trends, potential reversals, and generate trading signals. By combining the nonlinear regression curve with the zero-lag moving average, this indicator provides a comprehensive view of the price dynamics. Traders can customize the indicator's settings and use it in conjunction with other analysis techniques to make well-informed trading decisions.
Volatility SpeedometerThe Volatility Speedometer indicator provides a visual representation of the rate of change of volatility in the market. It helps traders identify periods of high or low volatility and potential trading opportunities. The indicator consists of a histogram that depicts the volatility speed and an average line that smoothes out the volatility changes.
The histogram displayed by the Volatility Speedometer represents the rate of change of volatility. Positive values indicate an increase in volatility, while negative values indicate a decrease. The height of the histogram bars represents the magnitude of the volatility change. A higher histogram bar suggests a more significant change in volatility.
Additionally, the Volatility Speedometer includes a customizable average line that smoothes out the volatility changes over the specified lookback period. This average line helps traders identify the overall trend of volatility and its direction.
To enhance the interpretation of the Volatility Speedometer, color zones are used to indicate different levels of volatility speed. These color zones are based on predefined threshold levels. For example, green may represent high volatility speed, yellow for moderate speed, and fuchsia for low speed. Traders can customize these threshold levels based on their preference and trading strategy.
By monitoring the Volatility Speedometer, traders can gain insights into changes in market volatility and adjust their trading strategies accordingly. For example, during periods of high volatility speed, traders may consider employing strategies that capitalize on price swings, while during low volatility speed, they may opt for strategies that focus on range-bound price action.
Adjusting the inputs of the Volatility Speedometer indicator can provide valuable insights and flexibility to traders. By modifying the inputs, traders can customize the indicator to suit their specific trading style and preferences.
One input that can be adjusted is the "Lookback Period." This parameter determines the number of periods considered when calculating the rate of change of volatility. Increasing the lookback period can provide a broader perspective of volatility changes over a longer time frame. This can be beneficial for swing traders or those focusing on longer-term trends. On the other hand, reducing the lookback period can provide more responsiveness to recent volatility changes, making it suitable for day traders or those looking for short-term opportunities.
Another adjustable input is the "Volatility Measure." In the provided code, the Average True Range (ATR) is used as the volatility measure. However, traders can choose other volatility indicators such as Bollinger Bands, Standard Deviation, or custom volatility measures. By experimenting with different volatility measures, traders can gain a deeper understanding of market dynamics and select the indicator that best aligns with their trading strategy.
Additionally, the "Thresholds" inputs allow traders to define specific levels of volatility speed that are considered significant. Modifying these thresholds enables traders to adapt the indicator to different market conditions and their risk tolerance. For instance, increasing the thresholds may highlight periods of extreme volatility and help identify potential breakout opportunities, while lowering the thresholds may focus on more moderate volatility shifts suitable for range trading or trend-following strategies.
Remember, it is essential to combine the Volatility Speedometer with other technical analysis tools and indicators to make informed trading decisions.
Pure Morning 2.0 - Candlestick Pattern Doji StrategyThe new "Pure Morning 2.0 - Candlestick Pattern Doji Strategy" is a trend-following, intraday cryptocurrency trading system authored by devil_machine.
The system identifies Doji and Morning Doji Star candlestick formations above the EMA60 as entry points for long trades.
For best results we recommend to use on 15-minute, 30-minute, or 1-hour timeframes, and are ideal for high-volatility markets.
The strategy also utilizes a profit target or trailing stop for exits, with stop loss set at the lowest low of the last 100 candles. The strategy's configuration details, such as Doji tolerance, and exit configurations are adjustable.
In this new version 2.0, we've incorporated a new selectable filter. Since the stop loss is set at the lowest low, this filter ensures that this value isn't too far from the entry price, thereby optimizing the Risk-Reward ratio.
In the specific case of ALPINE, a 9% Take-Profit and and Stop-Loss at Lowest Low of the last 100 candles were set, with an activated trailing-stop percentage, Max Loss Filter is not active.
Name : Pure Morning 2.0 - Candlestick Pattern Doji Strategy
Author : @devil_machine
Category : Trend Follower based on candlestick patterns.
Operating mode : Spot or Futures (only long).
Trades duration : Intraday
Timeframe : 15m, 30m, 1H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility .
Entry : When a Doji or Morning Doji Star formation occurs above the EMA60.
Exit : Profit target or Trailing stop, Stop loss on the lowest low of the last 100 candles.
Configuration :
- Doji Settings (tolerances) for Entry Condition
- Max Loss Filter (Lowest Low filter)
- Exit Long configuration
- Trailing stop
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: ALPINEUSDT
⁃ Timeframe: 30m
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start: 2022-02-28 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Inverted ProjectionThe "Inverted Projection" indicator calculates the Simple Moving Average (SMA) and draws lines representing an inverted projection. The indicator swaps the highs and lows of the projection to provide a unique perspective on price movement.
This indicator is a simple study that should not be taken seriously as a tool for predicting future price movements; it is purely intended for exploratory purposes.
Non Adaptive Moving Average - Quan DaoThis Non-Adaptive Moving Average (NAMA) is my origin work. It came from the issues that I always face when using existing famous MA like EMA or RMA:
- What length should I choose for the MA for this security?
- Is there a length that works for multiple timeframes?
- Is there a length that works for multiple securities in multiple markets?
Choosing the right length for an MA is a tedious and boring work and is very subjective. One day in early 2023, I decided to create a new MA that will not be dependant a lot (non-adaptive) on the length of it, to make my life a little bit easier. The idea came from the formula of EMA and RMA:
ma = alpha * src + (1 - alpha) * ma
in which,
alpha = 1 / length for RMA
alpha = 2 / (length + 1) for EMA
I decided to use a constant alpha for the formula, which happened to be: 1.618 / 100 (i.e., golden ratio / 100)
This NAMA is using the length in the start only, after running for a while the MA value will be the same for every value of its length, which resolves good my 3 questions above.
The application of this NAMA is wide, I think.
- It can be used like a normal MA but you don't have to choose its length anymore.
- It can be used like EMA in DEMA, TEMA (I called it DNAMA, TNAMA)
- It can be used in calculating some famous indicators (RSI, TR, ...) so that these indicators will not be dependant on the length as well
In this example script, I included an EMA (in blue color) as well so that you can see how the EMA changes and NAMA stays the same when changing the value of its Length.
Consensio Allocation ToolOriginally created and taught by Taylor Jenks, this indicator provides portfolio allocation suggestions based on the behaviour of price and 3 simple moving averages (4/10/40 by default)
(ie. when short & medium term SMAs are above the long term then allocation is to be 100%).
This percentage allocated to the stock/commodity is to be reduced as it passes below the SMA's, particularly as each moving average crosses.
Consensio is useful for scaling in and out of a position as the portfolio allocation will change according to the momentum of the asset.
The rules below are my own based on understanding of the trading system developed by Jenks and his online content.
This script has the following rules:
if fastAboveSlowMA and not mediumAboveSlowMA
allocation := 30.0
else if longAboveFastMA
allocation := 0.0
else if fastAboveMediumMA and fastAboveSlowMA
allocation := 100.0
else if not fastAboveMediumMA and fastAboveSlowMA
allocation := 80.0
else if not fastAboveMediumMA and not fastAboveSlowMA
allocation := 50.0
else if not mediumAboveSlowMA and fastAboveSlowMA
allocation := 50.0
// Calculate adjusted allocation percentage based on crossing moving averages
allocation := allocation + (priceAboveFastMA ? 10.0 : -10.0)
allocation := allocation + (priceAboveMediumMA ? 10.0 : -10.0)
VWAP + 2 Moving Averages + RSI + Buy and SellIndicator: VWAP + 2 Moving Averages + RSI + Buy and Sell
Buy and Sell Arrows (Great for use alone or in conjunction with other scripts on the chart)
This indicator displays BUY (BUY) and SELL (SELL) arrows on the chart based on a combination of moving averages, VWAP and RSI. Arrows are a visual way to identify trading opportunities and can be useful for traders who want to follow a strategy based on these conditions.
The indicator uses two moving averages (20 and 50 periods) to identify upward crosses (buy) and downward crosses (sell). In addition, it takes into account VWAP (Volume Weighted Average Price) and RSI (Relative Strength Index) as additional filters to confirm buy and sell signals.
This script is great for use both independently and in conjunction with other indicators and strategies. You can combine it with other indicators and customize it to your preferences to create a more comprehensive trading strategy.
Please remember that this indicator is provided for educational purposes only and does not constitute financial advice. It is always recommended to carry out a thorough analysis before making any trading decisions.
Give this indicator a try and enjoy clear visualization of buy and sell arrows on your chart. Happy trading!
Volume Indicator (MA)Displays candles which have volume larger than the volume moving average (14-bars). Red is for down candles and Green is for up candles, works best on a light background.
