Composite Trend Oscillator [ChartPrime]CODE DUELLO:
Have you ever stopped to wonder what the underlying filters contained within complex algorithms are actually providing for you? Wouldn't it be nice to actually visually inspect for that? Those would require some kind of wild west styled quick draw duel or some comparison method as a proper 'code duello'. Then it can be determined which filter can 'draw' the quickest from it's computational holster with the least amount of lag and smoothness.
In Pine we can do so, discovering how beneficial that would be. This can be accomplished by quickly switching from one filter to another by input() back and forth, requiring visual memory. A better way could be done by placing two indicators added to the chart and then eventually placed into one indicator pane on top of each other.
By adding a filter() helper function that calls other moving average functions chosen for comparison, it can put to the test which moving average is the best drawing filter suited to our expected needs. PhiSmoother was formerly debuted and now it is utilized in a more complex environment in a multitude of ways along side other commonly utilized filters. Now, you the reader, get to judge for yourself...
FILTER VERSATILITY:
Having the capability to adjust between various smoothing methods such as PhiSmoother, TEMA, DEMA, WMA, EMA, and SMA on historical market data within the code provides an advantage. Each of these filter methods offers distinct advantages and hinderances. PhiSmoother stands out often by having superb noise rejection, while also being able to manipulate the fine-tuning of the phase or lag of the indicator, enhancing responsiveness to price movements.
The following are more well-known classic filters. TEMA (Triple Exponential Moving Average) and DEMA (Double Exponential Moving Average) offer reduced transient response times to price changes fluctuations. WMA (Weighted Moving Average) assigns more weight to recent data points, making it particularly useful for reduced lag. EMA (Exponential Moving Average) strikes a balance between responsiveness and computational efficiency, making it a popular choice. SMA (Simple Moving Average) provides a straightforward calculation based on the arithmetic mean of the data. VWMA and RMA have both been excluded for varying reasons, both being unworthy of having explanation here.
By allowing for adjustment refinements between these filter methods, traders may garner the flexibility to adapt their analysis to different market dynamics, optimizing their algorithms for improved decision-making and performance on demand.
INDICATOR INTRODUCTION:
ChartPrime's Composite Trend Oscillator operates as an oscillator based on the concept of a moving average ribbon. It utilizes up to 32 filters with progressively longer periods to assess trend direction and strength. Embedded within this indicator is an alternative view that utilizes the separation of the ribbon filaments to assess volatility. Both versions are excellent candidates for trend and momentum, both offering visualization of polarity, directional coloring, and filter crossings. Anyone who has former experience using RSI or stochastics may have ease of understanding applying this to their chart.
COMPOSITE CLUSTER MODES EXPLAINED:
In Trend Strength mode, the oscillator behavior signifies market direction and movement strength. When the oscillator is rising and above zero, the market is within a bullish phase, and visa versa. If the signal filter crosses the composite trend, this indicates a potential dynamic shift signaling a possible reversal. When the oscillator is teetering on its extremities, the market is more inclined to reverse later.
With Volatility mode, the oscillator undergoes a transformation, displaying an unbounded oscillator driven by market volatility. While it still employs the same scoring mechanism, it is now scaled according to the strength of the market move. This can aid with identification of ranging scenarios. However, one side effect is that the oscillator no longer has minimum or maximum boundaries. This can still be advantageous when considering divergences.
NOTEWORTHY SETTINGS FEATURES:
The following input settings described offer comprehensive control over the indicator's behavior and visualization.
Common Controls:
Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options.
Composite Cluster Mode - Choose between "Trend Strength" and "Volatility" modes, providing insights into trend directionality or volatility weighting.
Cluster Filter and Length - Selects a filter for the cluster composition. This includes a length parameter adjustment.
Cluster Options:
Cluster Dispersion - Users can adjust the separation between moving averages in the cluster, influencing the sensitivity of the analysis.
Cluster Trimming - By modifying upper and lower trim parameters, traders can adjust the sensitivity of the moving averages within the cluster, enhancing its adaptability.
PostSmooth Filter and Length - Choose a filter to refine the composite cluster's post-smoothing with a length parameter adjustment.
Signal Filter and Length - Users can select a filter for the lagging signal plot, also having a length parameter adjustment.
Transition Easing - Sensitivity adjustment to influence the transition between bullish and bearish colors.
Enjoy
Komut dosyalarını "Exponential Moving Average" için ara
Dominant Period-Based Moving Average (DPBMA)Exploit Market Cycles with the Dominant Period-Based Moving Average Indicator
Introduction:
In the world of trading, market cycles play a crucial role in determining the rhythm of the market. These cycles often consist of recurring patterns that traders can exploit to maximize their profits. One effective way to capitalize on these cycles is by using a moving average (MA) indicator. Today, we are going to introduce you to a unique indicator that takes the most frequent dominant period of the market and uses it as the length of the moving average. This indicator is designed to adapt to the ever-changing market conditions, providing traders with a dynamic tool to better analyze the market.
Dominant Period-Based Moving Average Indicator Overview:
The Dominant Period-Based Moving Average (DPBMA) Indicator is a custom indicator designed to find the most frequent dominant period of the market and use that period as the length of the moving average. This innovative approach allows the indicator to adapt to the market cycles, making it more responsive to the market's changing conditions.
Here's a quick overview of the DPBMA Indicator's features:
Takes the most frequent dominant period of the market.
Uses the dominant period as the length of the moving average.
Adapts to the changing market cycles.
Works as an overlay on your price chart.
Using the Dominant Period-Based Moving Average Indicator:
How the Dominant Period-Based Moving Average Indicator Works:
The DPBMA Indicator works by first importing the DominantCycle function from the lastguru/DominantCycle/2 script. This function calculates the dominant cycle period of the given market data. The DPBMA Indicator then calculates the Exponential Moving Average (EMA) using the dominant period as the length parameter.
The EMA calculation uses an alpha factor, which is calculated as 2 / (length + 1). The alpha factor is then used to smooth the source data (closing prices) and calculate the adaptive moving average.
The DPBMA Indicator also includes a harmonic input, which allows you to multiply the dominant cycle period by an integer value. This can help you fine-tune the indicator to better fit your trading strategy or style.
The Raw Dominant Frequency:
The raw dominant frequency represents the primary cycle period present in the given market data. By identifying the raw dominant frequency, traders can gain insights into the market's current cycle and use this information to make informed trading decisions. The raw dominant frequency can be useful for detecting major trend reversals, support and resistance levels, and potential entry and exit points.
However, using the raw dominant frequency alone has its limitations. For instance, it may not always provide a clear picture of the market's prevailing trend, especially during periods of high market volatility. Additionally, relying solely on the raw dominant frequency may not capture the nuances of shorter-term cycles that can also impact price movements.
The Most Likely Dominant Frequency:
Our approach takes a different angle by focusing on the most likely dominant frequency. This method aims to identify the frequency with the highest probability of being the dominant frequency in the market data. The idea behind this approach is to filter out potential noise and improve the accuracy of the dominant frequency analysis. By using the most likely dominant frequency, traders can gain a more reliable understanding of the market's primary cycle, which can lead to better trading decisions.
In our Dominant Period-Based Moving Average Indicator, we calculate the most likely dominant frequency by analyzing an array of cycle periods and their occurrences in the given market data. We then determine the cycle period with the highest occurrence, representing the most likely dominant frequency. This method allows the indicator to be more adaptive and responsive to the changing market conditions, capturing the nuances of both long-term and short-term cycles.
Why Not the Average Dominant Frequency?
While using the average dominant frequency might seem like a reasonable approach, it can be less effective in accurately capturing the market's primary cycle. Averaging the dominant frequencies may dilute the impact of the true dominant frequency, resulting in a less accurate representation of the market's current cycle. By focusing on the most likely dominant frequency, our approach provides a more accurate and reliable analysis of the market's primary cycle, which can ultimately lead to more effective trading decisions.
Conclusion:
The Dominant Period-Based Moving Average Indicator, enhanced with the most likely dominant frequency approach, offers traders a powerful tool for exploiting market cycles. By adapting to the most frequent dominant period and focusing on the most likely dominant frequency, this indicator provides a more accurate and reliable analysis of the market's primary cycle. As a result, traders can make better-informed decisions, ultimately leading to improved trading performance. Incorporate the DPBMA Indicator into your trading toolbox today, and take advantage of the enhanced market analysis it provides.
MACD Chebyshev (CMACD)Introducing the Advanced MACD Chebyshev Indicator
Enhanced Convergence Divergence with Gate Compressor for Improved Trading Signals
Introduction
We are excited to introduce a new, advanced Moving Average Convergence Divergence (MACD) indicator that we've developed, called the MACD Chebyshev (CMACD). This innovative indicator uses the dominant period to determine the frequency of the band pass and employs a delayed version of the signal for better convergence divergence. To further enhance the quality of the signals, we've incorporated a gate compressor in the histogram. In this blog post, we will provide an extensive overview of the CMACD indicator, detailing its features and explaining how it works.
The MACD Chebyshev Indicator
The CMACD indicator is based on the well-known MACD indicator, which is a popular technical analysis tool for identifying potential trend reversals in financial markets. The MACD indicator calculates the difference between two Exponential Moving Averages (EMAs) and plots a histogram to represent the convergence and divergence between these EMAs. The CMACD indicator builds on this concept by using the Chebyshev Type I and Type II Moving Averages, which offer superior smoothing and reduced lag compared to traditional EMAs.
The main components of the CMACD indicator are:
1. Signal Line (Blue Line)
2. Delay Line (Orange Line)
3. Histogram (Green and Red bars)
4. Zero Line (Gray Line)
The indicator calculates the difference between the two Chebyshev Moving Averages and plots the histogram based on this difference. The histogram bars change color depending on whether they are above or below the zero line and whether they are growing or falling.
Custom Functions and Features
The CMACD indicator includes several custom functions and features that set it apart from the standard MACD indicator:
1. Dominant Period: The CMACD indicator uses the dominant period to determine the frequency of the band pass. This ensures that the indicator is more responsive to the current market conditions, as it adapts to the dominant cycle in the price data.
2. Delayed Signal: The CMACD indicator employs a delayed version of the signal to provide better convergence divergence. This helps to reduce false signals and improve the accuracy of the indicator.
3. Ripple: The Ripple parameter allows users to adjust the smoothing factor of the Chebyshev Moving Averages. This can be customized to suit individual trading preferences and strategies.
4. Gate Compressor: The CMACD indicator incorporates a gate compressor in the histogram. This unique feature allows users to specify a Percent Rank for the gate signal level, a Gate Ratio, and a Knee Type (either "hard" or "soft"). The gate compressor works by reducing the amplitude of the histogram bars when their absolute value is below the specified threshold. This helps to filter out noise and improve the clarity of the signals generated by the indicator.
Color Scheme
The CMACD indicator features an intuitive color scheme for easy interpretation of the histogram:
1. Green Bars (Above Zero Line): The histogram bars are green when they are above the zero line. The darker green color indicates a growing bar, while the lighter green color represents a falling bar.
2. Red Bars (Below Zero Line): The histogram bars are red when they are below the zero line. The darker red color indicates a growing bar, while the lighter red color represents a falling bar.
Conclusion
The MACD Chebyshev (CMACD) indicator is an innovative and powerful tool for technical analysis, offering superior performance compared to the standard MACD indicator. With its advanced features, such as the dominant period, delayed signal, ripple adjustment, and gate compressor, the CMACD indicator provides more accurate and reliable trading signals. Incorporate the CMACD indicator into your trading strategy today and experience the enhanced convergence divergence for better trading decisions.
TRIX with Momentum----------- ENGLISH --------------
This indicator is called "TRIX with Momentum" and is used to analyze the momentum of an asset's price and predict potential trend reversals. The logic of operation is based on the combination of two indicators: the Triple Exponential Moving Average (TRIX) and the momentum oscillator.
The TRIX is calculated using three exponential moving averages (EMA) of the asset's closing price, with a user-defined length (set to 14 by default). The TRIX is then normalized and centered around 0 to facilitate analysis of its relationship with the momentum oscillator.
The momentum oscillator is calculated using the EMA of the normalized TRIX with a user-defined length (set to 14 by default).
The indicator plots the normalized TRIX and the momentum oscillator on a chart, using different colors to indicate whether the TRIX is above or below 0. Additionally, the color of the y-axis label changes based on the position of the oscillator, while the color of the x-axis label remains gray.
The indicator uses a weighted average between the normalized TRIX and the momentum oscillator to create a colored background of the chart, which changes based on the weighted average. If the weighted average is positive, the chart's background is green, otherwise it is red. Finally, a horizontal line is drawn at point 0 to facilitate visual analysis of the chart.
------------ ITALIANO -------------
Questo indicatore è chiamato "TRIX with Momentum" ed è utilizzato per analizzare il momentum del prezzo di un asset e prevedere eventuali inversioni di trend. La logica di funzionamento è basata sulla combinazione di due indicatori: il TRIX (Indicatori di media mobile Tripla Esponenziale) e l'oscillatore momentum.
L'indicatore consente all'utente di impostare la lunghezza del TRIX e dell'oscillatore momentum come input personalizzato. Il TRIX viene calcolato utilizzando tre medie mobili esponenziali (EMA) della chiusura dei prezzi dell'asset, mentre l'oscillatore momentum viene calcolato utilizzando l'EMA del TRIX normalizzato.
Il TRIX normalizzato viene centrato intorno allo 0 per facilitare l'analisi della sua relazione con l'oscillatore momentum. L'indicatore plotta il TRIX normalizzato e l'oscillatore momentum su un grafico, utilizzando diversi colori per indicare se il TRIX è sopra o sotto lo 0.
L'indicatore utilizza una media pesata tra il TRIX normalizzato e l'oscillatore momentum per creare uno sfondo colorato del grafico, che cambia in base alla media pesata. L'utente può impostare il peso da dare al TRIX e all'oscillatore momentum come input personalizzato, e il peso dell'oscillatore momentum verrà automaticamente impostato come complementare al peso del TRIX.
Se la media pesata è positiva, lo sfondo del grafico è verde, altrimenti è rosso. Viene tracciata anche una linea orizzontale al punto 0 per facilitare l'analisi visiva del grafico.
Infine, il colore dell'etichetta dell'asse y cambia in base alla posizione dell'oscillatore, mentre il colore dell'etichetta dell'asse x rimane sempre grigio.
UB Profit Signal IndicatorThe UB Profit Signal indicator is a technical analysis tool designed to identify potential buy and sell signals in the market. The indicator is based on four technical indicators - Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), Bollinger Bands (BB), and volume moving average.
The script starts by defining input variables such as MACD Fast Length, MACD Slow Length, MACD Signal Length, RSI Length, etc. These variables are used to customize the indicator based on the user's preference.
The MACD is calculated using the ta.macd function, which returns three variables: the MACD Line, Signal Line, and Histogram. The MACD line is calculated as the difference between two exponential moving averages of the price. The signal line is a moving average of the MACD line. The histogram shows the difference between the MACD line and the signal line.
The RSI is calculated using the ta.rsi function, which calculates the RSI value based on the number of periods specified in the RSI Length input variable. The RSI is a momentum oscillator that measures the speed and change of price movements.
The Bollinger Bands are calculated using the ta.sma and ta.stdev functions. The Simple Moving Average (SMA) is calculated using the close price over 21 periods, while the Standard Deviation is calculated using the close price over the same 21 periods. The upper and lower bands are then calculated based on the SMA and Standard Deviation.
Finally, the buy and sell signals are generated based on specific conditions that combine the MACD, RSI, and BB values. For example, a buy signal is generated when the RSI value is greater than 30, the volume is greater than the volume moving average, the close price is greater than the 9-period SMA, and the close price is between the upper and lower BBs. Similarly, a sell signal is generated when the RSI value is less than 40, the volume is greater than the volume moving average, the close price is less than the 9-period SMA, and the close price is between the upper and lower BBs.
The buy and sell signals are plotted on the chart using the plotshape function, which creates triangular shapes above and below the bars to indicate the signals. Green triangles indicate a buy signal, while red triangles indicate a sell signal. Overall, the UB Profit Signal indicator can be useful for traders looking to identify potential buy and sell signals in the market and take advantage of price movements.
ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
oussamacryptoWhat Is an Exponential Moving Average (EMA)?
An exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average (SMA), which applies an equal weight to all observations in the period.
Fisher Transform of MACD w/ Quantile Bands [Loxx]Fisher Transform of MACD w/ Quantile Bands is a Fisher Transform indicator with Quantile Bands that takes as it's source a MACD. The MACD has two different source inputs for fast and slow moving averages.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What is Quantile Bands?
In statistics and the theory of probability, quantiles are cutpoints dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one less quantile than the number of groups created. Thus quartiles are the three cut points that will divide a dataset into four equal-size groups (cf. depicted example). Common quantiles have special names: for instance quartile, decile (creating 10 groups: see below for more). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.
q-Quantiles are values that partition a finite set of values into q subsets of (nearly) equal sizes. There are q − 1 of the q-quantiles, one for each integer k satisfying 0 < k < q. In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables. When the cumulative distribution function of a random variable is known, the q-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values {1/q, 2/q, …, (q − 1)/q}.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
Signals
Loxx's Expanded Source Types
35+ moving average types
2 MA Ratio Can Help with Moving AveragesMany technical analysts use moving average crosses to assess trend changes. A faster-moving MA crossing above a slower-moving line may be viewed as a bullish signal. The opposite can apply to the downside.
While these methods may help analyze price direction, they can often force traders to wait until the cross occurs. Sometimes it may be useful to anticipate the event – or at least know it’s getting close.
That’s where the custom script 2 MA Ratio can be useful because it tracks the fast and slow moving averages. The fast MA is then shown as a percent of the slow MA. Positive readings indicate a bullish condition and vice versa for the negative.
It’s also color-coded to clearly illustrate when the crosses occur.
2 MA Ratio can handle simple moving averages (SMAs) and exponential moving averages (EMAs). It even lets you compare SMAs to EMAs. Users can choose between using open, high, low or closing prices as the inputs. (It defaults to Close.)
The chart above shows the short-term pair of the 8- and 21-day EMAs on Tesla (TSLA). The second chart below shows the same stock with the slower 50- and 200-day SMAs. Notice the “Golden Cross” last summer and the “Death Cross” in May:
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MTF MACD (PPO) [TANHEF]Mult-Timeframe Moving Average Convergence Divergence (MACD) and Percentage Price Oscillator (PPO) indicator that allows for viewing of 1 to 5 different Timeframes.
Brief Summary
The primary benefit of multi-timeframe indicators is getting better entries and confirmation from viewing multiple time frames at once, which can often get overlooked.
MACD shouldn't be only used by itself, it is a lot more consistent when applied in the same direction as the trend as well as multiple other things including support, resistance, and volume improve the outcomes of the MACD results.
Personally, I look for good entries on higher and lower time frames (multiple timeframes must agree with the buying or selling). For example, if a higher timeframe looks like a good long entry (MACD line is crossing up and below the zero line), then the lower timeframes should be checked to ensure they are not oversold or overextended (the MACD line must be low or below the zero), once the lower and higher timeframes are in agreeance an entry can be made.
What is Moving Average Convergence Divergence (MACD)?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of the price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
What is the Percentage Price Oscillator (PPO)?
The PPO is identical to the MACD indicator, except the PPO measures percentage difference between two EMAs, while the MACD measures absolute (or dollar) difference. The PPO has the advantage of being comparable to other assets with different prices, whereas MACD readings are not comparable. For example, regardless of the asset's price, a PPO result of 10 means the short-term average is 10% above the long-term average.
A signal line can be displayed on Timeframe, including:
- MACD & Signal Line crosses (Green when MACD above Signal Line and Red when MACD below Signal Line)
- Histogram Direction (fast and slow EMA gap)
- SuperTrend for identifying trend direction (green for uptrend, red for downtrend)
- EMA Trend for identifying trend direction (above EMA = up trend and green, below EMA = down trend and red)
Cross Dots and Potential cross dots
- Green Dot, is displayed when the MACD crosses the Signal Line
- Red Dot, is displayed when the MACD crosses the Signal Line
- Yellow Dot. Potential cross up (green dot) on next bar. Displayed when if the same distance a MACD moves on a bar is applied to the next bar will cause a MACD and Signal Line Cross. This is calculated by checking if the value change of one bar is added to the current MACD value would lead to a cross on the next bar, the it is a potential up dot.
- Purple Dot. Potential cross down (red dot) on next bar. Displayed when if the same distance a MACD moves on a bar is applied to the next bar will cause a MACD and Signal Line Cross. This is calculated by checking if the value change of one bar is added to the current MACD value would lead to a cross on the next bar, the it is a potential down dot.
Best Fit Settings
- Can be applied to the MACD, Signal Line, and Histogram to re-scale (stretch) to fit them within the space of the +2 and -2 range that each timeframe is provided on this indicator.
- The lookback distance value is used to lookback a certain distance to ensure everything scaled to fit well.
Labels are displayed on the right of the indicators, including:
- a label identifying 'line indicator' is currently being displayed
- the Timeframe corresponding to each MACD or PPO indicator
- the MACD or PPO of each Timeframe
SuperTrended Moving AveragesA different approach to SuperTrend:
adding 100 periods Exponential Moving Average in calculation of SuperTrend and also 0.5 ATR Multiplier to have a clear view of the ongoing trend and also provides significant Supports and Resistances.
Default Moving Average type set as EMA (Exponential Moving Average) but users can choose from 11 different Moving Average types as:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average a.k.a. VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
Credits going to @CryptoErge for sharing his development to public.
Moving Averages Different Type & SourceThis is a indicator to plot moving averages. User has the option to choose whether to plot SMA (simple moving average) or EMA (exponential moving average). Length of the averages also can be changed by user. The main feature also is use of different source for different length of MAs. Like you can plot 9SMA High with 20EMA Close etc. So, you can plot different types of combinations with type of MA (sma and ema) and Source type (high, low, open, close etc.).
A table also added in the right top to show the values of MA in selected timeframe. The red color indicate current price is below that ma and green color indicate current price is above that ma. Same feature added in plot of ma line by checking toggle color feature option on. It will show green color ma when price is above it and red color ma lines when price is below it.
EMA Multi CrossThis is just a very simple EMA indicator that shows the 20, 50, 100, and 200 Exponential Moving Averages and plots some shapes when the lines cross from the 20 & 50, the 50 & 200, and the 100 & 200.
I know there are many EMA indicators out there, but I couldn't find one that let me edit the colors, values, and toggle the crossings. Maybe some of you will find usefulness in having some of these extra options too.
I use this occasionally on the Bitcoin 1 hour charts to see how the long-term trend is going.
Here are some ways to read EMA lines:
Slope: A rising moving average generally reflects a rising trend, while a falling moving average points to a falling trend.
Crosses: Seeing when a slower moving average crosses over/under a faster moving average can be an indication of a trend. If a shorter moving average remains above the longer moving average after they cross, the uptrend is considered intact. The trend is seen as down when the shorter moving average is below the longer moving average.
I prefer the slope of the two since crosses can cause some false positives if you are relying on it for trades.
Adam Khoo Moving AveragesThis indicator will plot the simple and exponential moving averages Adam Khoo is also looking at for buying opportunities.
The best timeframe to use this indicator is the daily chart . The weekly moving averages are hard coded and don't change on any other timeframe. The other moving averages will show the values of your current timeframe.
In the settings you have the option to change the values of the moving averages and to show or not show the current timeframe moving averages or the weekly moving averages.
A label will also show the current value of all moving averages. To hide this label, go into the settings and click on 'Style' and at the bottom uncheck 'Labels'.
Happy trading ;-)
SMA Simple, EMA Exponential Moving Averages with high lowThis is a rewrite of my previous moving average script.
In this version, I have added the 3 day high and low as these are often used as short term trend following entry points
Traders often try to buy the 3 day average of lows in an uptrend and sell the 3 day average of highs in a downtrend
In the same fashion, I have added the 3 week high and low averages for longer term trend following for swing trading
I have added the 18 day, week, month simple moving averages ( SMA ) as I follow these from Ira Epsteins free you tube trading videos).
His 50 years of experience has taught him these are best
I have also added some longer term SMA , 100 day, 200 day, 100w, and 200w
Exponential EMA averages for longer term charts are included 100d, 200d, 100w, 100m, 200m
You can configure the script in the options to remove the ones you don't want to follow
I have removed the micro averages from my previous script since they are for short term scalping day trading hyper-trading which I don't do
Exponential averages are shown as crosses
some of the longer term averages are circles just to set them apart
Overbought or Oversold? Check Distance From MAMoving averages are one of the most basic tools for technical analysts. They can be useful for both trend analysis and for mean reversion.
But how can you know when price is historically overbought or oversold relative to a moving average? Distance from MA can help.
This indicator calculates the distance from a moving average as a percentage and plots the result as an oscillator. Values above 0 appear in green, while negative readings are colored red.
This chart highlights the depth of the S&P 500's recent selloff. As you can see, the close dipped to 25 percent below its 50-day SMA on Monday. That was its most oversold condition since November 20, 2008 -- in the middle of the subprime financial crisis.
Distance from MA can handle five types of moving average. Simply change the "AvgType" input according to this key:
1 - Simple Moving Average
2 - Exponential Moving Average
3 - Hull Moving Average
4 - Weighted Moving Average
5 - Volume-Weighted Moving Average
All Moving averagesI have added an option to turn on or off any Moving average by choice and if needed, Heikin-ashi used as source (instead of close)
List of Moving Averages which you can use
T3 - Tillson Moving Average
DEMA - Double Exponential Moving Average
ALMA - Arnaud Legoux moving average
LSMA - Least Squares Moving Average
MA - Simple Moving Average
EMA - Exponential Moving Average
WMA - Weighted Moving Average
SMMA -The Smoothed Moving Average
TEMA - triple exponential moving average
HMA - The Hull Moving Average
AMA - Adaptive Moving Average
FAMA - Fractal Adaptive Moving Average
VIDYA - Variable Index Dynamic Average
TRIMA - Triangular Moving Average
Consider a tip in ETH to
0xac290B4A721f5ef75b0971F1102e01E1942A4578
Thank you and have a nice day
CryptoJoncis
MACD percentage price oscillatorMACD Percentage Price Oscillator is a variation of the MACD indicator. Signal line crossovers are almost identical. The major difference is the MACD Percentage scale which enables comparison between stocks at different prices.
MACD Percentage Price Oscillator's trading signals are the same as for the MACD indicator. The MACD indicator is primarily used to trade trends and should not be used in a ranging market. Signals are taken when MACD crosses its signal line, calculated as a 9 day exponential moving average of MACD.
First check whether price is trending. If the MACD indicator is flat or stays close to the zero line, the market is ranging and signals are unreliable.
Signals are far stronger if there is either:
- a divergence on the MACD indicator; or
- a large swing above or below the zero line.
- Unless there is a divergence, do not go long if the signal is above the zero line, nor go short if the signal is below zero. Place stop-losses below the last minor Low when long, or the last minor High when short.
The main advantage of MACD Percentage over MACD is the ability to compare indicator values across stocks.
The only difference with MACD Percentage Price Oscillator is that the difference between the fast and slow moving averages is calculated as a percentage of the slow moving average: MACD = (12 Day EMA - 26 Day EMA) / 26 Day EMA
PhenLabs - Market Fluid Dynamics📊 Market Fluid Dynamics -
Version: PineScript™ v6
📌 Description
The Market Fluid Dynamics - Phen indicator is a new thinking regarding market analysis by modeling price action, volume, and volatility using a fluid system. It attempts to offer traders control over more profound market forces, such as momentum (speed), resistance (thickness), and buying/selling pressure. By visualizing such dynamics, the script allows the traders to decide on the prevailing market flow, its power, likely continuations, and zones of calmness and chaos, and thereby allows improved decision-making.
This measure avoids the usual difficulty of reconciling multiple, often contradictory, market indications by including them within a single overarching model. It moves beyond traditional binary indicators by providing a multi-dimensional view of market behavior, employing fluid dynamic analogs to describe complex interactions in an accessible manner.
🚀 Points of Innovation
Integrated Fluid Dynamics Model: Combines velocity, viscosity, pressure, and turbulence into a single indicator.
Normalized Metrics: Uses ATR and other normalization techniques for consistent readings across different assets and timeframes.
Dynamic Flow Visualization: Main flow line changes color and intensity based on direction and strength.
Turbulence Background: Visually represents market stability with a gradient background, from calm to turbulent.
Comprehensive Dashboard: Provides an at-a-glance summary of key fluid dynamic metrics.
Multi-Layer Smoothing: Employs several layers of EMA smoothing for a clearer, more responsive main flow line.
🔧 Core Components
Velocity Component: Measures price momentum (first derivative of price), normalized by ATR. It indicates the speed and direction of price changes.
Viscosity Component: Represents market resistance to price changes, derived from ATR relative to its historical average. Higher viscosity suggests it’s harder for prices to move.
Pressure Component: Quantifies the force created by volume and price range (close - open), normalized by ATR. It reflects buying or selling pressure.
Turbulence Detection: Calculates a Reynolds number equivalent to identify market stability, ranging from laminar (stable) to turbulent (chaotic).
Main Flow Indicator: Combines the above components, applying sensitivity and smoothing, to generate a primary signal of market direction and strength.
🔥 Key Features
Advanced Smoothing Algorithm: Utilizes multiple EMA layers on the raw flow calculation for a fluid and responsive main flow line, reducing noise while maintaining sensitivity.
Gradient Flow Coloring: The main flow line dynamically changes color from light to deep blue for bullish flow and light to deep red for bearish flow, with intensity reflecting flow strength. This provides an immediate visual cue of market sentiment and momentum.
Turbulence Level Background: The chart background changes color based on calculated turbulence (from calm gray to vibrant orange), offering an intuitive understanding of market stability and potential for erratic price action.
Informative Dashboard: A customizable on-screen table displays critical metrics like Flow State, Flow Strength, Market Viscosity, Turbulence, Pressure Force, Flow Acceleration, and Flow Continuity, allowing traders to quickly assess current market conditions.
Configurable Lookback and Sensitivity: Users can adjust the base lookback period for calculations and the sensitivity of the flow to viscosity, tailoring the indicator to different trading styles and market conditions.
Alert Conditions: Pre-defined alerts for flow direction changes (positive/negative crossover of zero line) and detection of high turbulence states.
🎨 Visualization
Main Flow Line: A smoothed line plotted below the main chart, colored blue for bullish flow and red for bearish flow. The intensity of the color (light to dark) indicates the strength of the flow. This line crossing the zero line can signal a change in market direction.
Zero Line: A dotted horizontal line at the zero level, serving as a baseline to gauge whether the market flow is positive (bullish) or negative (bearish).
Turbulence Background: The indicator pane’s background color changes based on the calculated turbulence level. A calm, almost transparent gray indicates low turbulence (laminar flow), while a more vibrant, semi-transparent orange signifies high turbulence. This helps traders visually assess market stability.
Dashboard Table: An optional table displayed on the chart, showing key metrics like ‘Flow State’, ‘Flow Strength’, ‘Market Viscosity’, ‘Turbulence’, ‘Pressure Force’, ‘Flow Acceleration’, and ‘Flow Continuity’ with their current values and qualitative descriptions (e.g., ‘Bullish Flow’, ‘Laminar (Stable)’).
📖 Usage Guidelines
Setting Categories
Show Dashboard - Default: true; Range: true/false; Description: Toggles the visibility of the Market Fluid Dynamics dashboard on the chart. Enable to see key metrics at a glance.
Base Lookback Period - Default: 14; Range: 5 - (no upper limit, practical limits apply); Description: Sets the primary lookback period for core calculations like velocity, ATR, and volume SMA. Shorter periods make the indicator more sensitive to recent price action, while longer periods provide a smoother, slower signal.
Flow Sensitivity - Default: 0.5; Range: 0.1 - 1.0 (step 0.1); Description: Adjusts how much the market viscosity dampens the raw flow. A lower value means viscosity has less impact (flow is more sensitive to raw velocity/pressure), while a higher value means viscosity has a greater dampening effect.
Flow Smoothing - Default: 5; Range: 1 - 20; Description: Controls the length of the EMA smoothing applied to the main flow line. Higher values result in a smoother flow line but with more lag; lower values make it more responsive but potentially noisier.
Dashboard Position - Default: ‘Top Right’; Range: ‘Top Right’, ‘Top Left’, ‘Bottom Right’, ‘Bottom Left’, ‘Middle Right’, ‘Middle Left’; Description: Determines the placement of the dashboard on the chart.
Header Size - Default: ‘Normal’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’, ‘Huge’; Description: Sets the text size for the dashboard header.
Values Size - Default: ‘Small’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’; Description: Sets the text size for the metric values in the dashboard.
✅ Best Use Cases
Trend Identification: Identifying the dominant market flow (bullish or bearish) and its strength to trade in the direction of the prevailing trend.
Momentum Confirmation: Using the flow strength and acceleration to confirm the conviction behind price movements.
Volatility Assessment: Utilizing the turbulence metric to gauge market stability, helping to adjust position sizing or avoid choppy conditions.
Reversal Spotting: Watching for divergences between price and flow, or crossovers of the main flow line above/below the zero line, as potential reversal signals, especially when combined with changes in pressure or viscosity.
Swing Trading: Leveraging the smoothed flow line to capture medium-term market swings, entering when flow aligns with the desired trade direction and exiting when flow weakens or reverses.
Intraday Scalping: Using shorter lookback periods and higher sensitivity to identify quick shifts in flow and turbulence for short-term trading opportunities, particularly in liquid markets.
⚠️ Limitations
Lagging Nature: Like many indicators based on moving averages and lookback periods, the main flow line can lag behind rapid price changes, potentially leading to delayed signals.
Whipsaws in Ranging Markets: During periods of low volatility or sideways price action (high viscosity, low flow strength), the indicator might produce frequent buy/sell signals (whipsaws) as the flow oscillates around the zero line.
Not a Standalone System: While comprehensive, it should be used in conjunction with other forms of analysis (e.g., price action, support/resistance levels, other indicators) and not as a sole basis for trading decisions.
Subjectivity in Interpretation: While the dashboard provides quantitative values, the interpretation of “strong” flow, “high” turbulence, or “significant” acceleration can still have a subjective element depending on the trader’s strategy and risk tolerance.
💡 What Makes This Unique
Fluid Dynamics Analogy: Its core strength lies in translating complex market interactions into an intuitive fluid dynamics framework, making concepts like momentum, resistance, and pressure easier to visualize and understand.
Market View: Instead of focusing on a single aspect (like just momentum or just volatility), it integrates multiple factors (velocity, viscosity, pressure, turbulence) to provide a more comprehensive picture of market conditions.
Adaptive Visualization: The dynamic coloring of the flow line and the turbulence background provide immediate, adaptive visual feedback that changes with market conditions.
🔬 How It Works
Price Velocity Calculation: The indicator first calculates price velocity by measuring the rate of change of the closing price over a given ‘lookback’ period. The raw velocity is then normalized by the Average True Range (ATR) of the same lookback period. Normalization enables comparison of momentum between assets or timeframes by scaling for volatility. This is the direction and speed of initial price movement.
Viscosity Calculation: Market ‘viscosity’ or resistance to price movement is determined by looking at the current ATR relative to its longer-term average (SMA of ATR over lookback * 2). The further the current ATR is above its average, the lower the viscosity (less resistance to price movement), and vice-versa. The script inverts this relationship and bounds it so that rising viscosity means more resistance.
Pressure Force Measurement: A ‘pressure’ variable is calculated as a function of the ratio of current volume to its simple moving average, multiplied by the price range (close - open) and normalized by ATR. This is designed to measure the force behind price movement created by volume and intraday price thrusts. This pressure is smoothed by an EMA.
Turbulence State Evaluation: A equivalent ‘Reynolds number’ is calculated by dividing the absolute normalized velocity by the viscosity. This is the proclivity of the market to move in a chaotic or orderly fashion. This ‘reynoldsValue’ is smoothed with an EMA to get the ‘turbulenceState’, which indicates if the market is laminar (stable), transitional, or turbulent.
Main Flow Derivation: The ‘rawFlow’ is calculated by taking the normalized velocity, dampening its impact based on the ‘viscosity’ and user-input ‘sensitivity’, and orienting it by the sign of the smoothed ‘pressureSmooth’. The ‘rawFlow’ is then put through multiple layers of exponential moving average (EMA) smoothing (with ‘smoothingLength’ and derived values) to reach the final ‘mainFlow’ line. The extensive smoothing is designed to give a smooth and clear visualization of the overall market direction and magnitude.
Dashboard Metrics Compilation: Additional metrics like flow acceleration (derivative of mainFlow), and flow continuity (correlation between close and volume) are calculated. All primary components (Flow State, Strength, Viscosity, Turbulence, Pressure, Acceleration, Continuity) are then presented in a user-configurable dashboard for ease of monitoring.
💡 Note:
The “Market Fluid Dynamics - Phen” indicator is designed to offer a unique perspective on market behavior by applying principles from fluid dynamics. It’s most effective when used to understand the underlying forces driving price rather than as a direct buy/sell signal generator in isolation. Experiment with the settings, particularly the ‘Base Lookback Period’, ‘Flow Sensitivity’, and ‘Flow Smoothing’, to find what best suits your trading style and the specific asset you are analyzing. Always combine its insights with robust risk management practices.
TrendTwisterV1.5 (Forex Ready + Indicators)A Precision Trend-Following TradingView Strategy for Forex**
HullShiftFX is a Pine Script strategy for TradingView that combines the power of the **Hull Moving Average (HMA)** and a **shifted Exponential Moving Average (EMA)** with multi-layered momentum filters including **RSI** and **dual Stochastic Oscillators**.
It’s designed for traders looking to catch high-probability breakouts with tight risk management and visual clarity.
Chart settings:
1. Select "Auto - Fits data to screen"
2. Please Select "Scale Price Chart Only" (To make the chart not squished)
### ✅ Entry Conditions
**Long Position:**
- Price closes above the 12-period Hull Moving Average.
- Price closes above the 5-period EMA shifted forward by 2 bars.
- RSI is above 50.
- Stochastic Oscillator (12,3,3) %K is above 50.
- Stochastic Oscillator (5,3,3) %K is above 50.
- Hull MA crosses above the shifted EMA.
**Short Position:**
- Price closes below the 12-period Hull Moving Average.
- Price closes below the 5-period EMA shifted forward by 2 bars.
- RSI is below 50.
- Stochastic Oscillator (12,3,3) %K is below 50.
- Stochastic Oscillator (5,3,3) %K is below 50.
- Hull MA crosses below the shifted EMA.
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## 📉 Risk Management
- **Stop Loss:** Set at the low (for long) or high (for short) of the previous 2 candles.
- **Take Profit:** Calculated at a risk/reward ratio of **1.65x** the stop loss distance.
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## 📊 Indicators Used
- **Hull Moving Average (12)**
- **Exponential Moving Average (5) **
- **Relative Strength Index (14)**
- **Stochastic Oscillators:**
- %K (12,3,3)
- %K (5,3,3)
DT Bollinger BandsIndicator Overview
Purpose: The script calculates and plots Bollinger Bands, a technical analysis tool that shows price volatility by plotting:
A central moving average (basis line).
Upper and lower bands representing price deviation from the moving average.
Additional bands for a higher deviation threshold (3 standard deviations).
Customization: Users can customize:
The length of the moving average.
The type of moving average (e.g., SMA, EMA).
The price source (e.g., close price).
Standard deviation multipliers for the bands.
Fixed Time Frame: The script can use a fixed time frame (e.g., daily) for calculations, regardless of the chart's time frame.
Key Features
Moving Average Selection:
The user can select the type of moving average for the basis line:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA/RMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Standard Deviation Multipliers:
Two multipliers are used:
Standard (default = 2.0): For the original Bollinger Bands.
Larger (default = 3.0): For additional bands.
Bands Calculation:
Basis Line: The selected moving average.
Upper Band: Basis + Standard Deviation.
Lower Band: Basis - Standard Deviation.
Additional Bands: Representing ±3 Standard Deviations.
Plots:
Plots the basis, upper, and lower bands.
Fills the area between the bands for visual clarity.
Plots and fills additional bands for ±3 Standard Deviations with lighter colors.
Alerts:
Generates an alert when the price enters the range between the 2nd and 3rd standard deviation bands.
The alert can be used to notify when price volatility increases significantly.
Background Highlighting:
Colors the chart background based on alert conditions:
Green if the price is above the basis line.
Red if the price is below the basis line.
Offset:
Adds an optional horizontal offset to the plots for fine-tuning their alignment.
How It Works
Input Parameters:
The user specifies settings such as moving average type, length, multipliers, and fixed time frame.
Calculations:
The script computes the basis (moving average) and standard deviations on the fixed time frame.
Bands are calculated using the basis and multipliers.
Plotting:
The basis line and upper/lower bands are plotted with distinct colors.
Additional 3 StdDev bands are plotted with lighter colors.
Alerts:
An alert condition is created when the price moves between the 2nd and 3rd standard deviation bands.
Visual Enhancements:
Chart background changes color dynamically based on the price’s position relative to the basis line and alert conditions.
Usage
This script is useful for traders who:
Want a detailed visualization of price volatility.
Use Bollinger Bands to identify breakout or mean-reversion trading opportunities.
Need alerts when the price enters specific volatility thresholds.
Algorithmic Signal AnalyzerMeet Algorithmic Signal Analyzer (ASA) v1: A revolutionary tool that ushers in a new era of clarity and precision for both short-term and long-term market analysis, elevating your strategies to the next level.
ASA is an advanced TradingView indicator designed to filter out noise and enhance signal detection using mathematical models. By processing price movements within defined standard deviation ranges, ASA produces a smoothed analysis based on a Weighted Moving Average (WMA). The Volatility Filter ensures that only relevant price data is retained, removing outliers and improving analytical accuracy.
While ASA provides significant analytical advantages, it’s essential to understand its capabilities in both short-term and long-term use cases. For short-term trading, ASA excels at capturing swift opportunities by highlighting immediate trend changes. Conversely, in long-term trading, it reveals the overall direction of market trends, enabling traders to align their strategies with prevailing conditions.
Despite these benefits, traders must remember that ASA is not designed for precise trade execution systems where accuracy in timing and price levels is critical. Its focus is on analysis rather than order management. The distinction is crucial: ASA helps interpret price action effectively but may not account for real-time market factors such as slippage or execution delays.
Features and Functionality
ASA integrates multiple tools to enhance its analytical capabilities:
Customizable Moving Averages: SMA, EMA, and WMA options allow users to tailor the indicator to their trading style.
Signal Detection: Identifies bullish and bearish trends using the Relative Exponential Moving Average (REMA) and marks potential buy/sell opportunities.
Visual Aids: Color-coded trend lines (green for upward, red for downward) simplify interpretation.
Alert System: Notifications for trend swings and reversals enable timely decision-making.
Notes on Usage
ASA’s effectiveness depends on the context in which it is applied. Traders should carefully consider the trade-offs between analysis and execution.
Results may vary depending on market conditions and chart types. Backtesting with ASA on standard charts provides more reliable insights compared to non-standard chart types.
Short-term use focuses on rapid trend recognition, while long-term application emphasizes understanding broader market movements.
Takeaways
ASA is not a tool for precise trade execution but a powerful aid for interpreting price trends.
For short-term trading, ASA identifies quick opportunities, while for long-term strategies, it highlights trend directions.
Understanding ASA’s limitations and strengths is key to maximizing its utility.
ASA is a robust solution for traders seeking to filter noise, enhance analytical clarity, and align their strategies with market movements, whether for short bursts of activity or sustained trading goals.
Trend Condition [TradersPro]
OVERVIEW
The Trend Condition Indicator measures the strength of the bullish or bearish trend by using a ribbon pattern of exponential moving averages and scoring system. Trend cycles naturally expand and contract as a normal part of the cycle. It is the rhythm of the market. Perpetual expansion and contraction of trend.
As trend cycles develop the indicator shows a compression of the averages. These compression zones are key locations as trends typically expand from there. The expansion of trend can be up or down.
As the trend advances the ribbon effect of the indicator can be seen as each average expands with the price action. Once they have “fanned” the probability of the current trend slowing is high.
This can be used to recognize a powerful trend may be concluding. Traders can tighten stops, exit positions or utilize other prudent strategies.
CONCEPTS
Each line will display green if it is higher than the prior period and red if it is lower than the prior period. If the average is green it is considered bullish and will score one point in the bullish display. Red lines are considered bearish and will score one point in the bearish display.
The indicator can then be used at a quick glance to see the number of averages that are bullish and the number that are bearish.
A trader may use these on any tradable instrument. They can be helpful in stock portfolio management when used with an index like the S&P 500 to determine the strength of the current market trend. This may affect trade decisions like possession size, stop location and other risk factors.
