3-Signal Directional Trend Strategy for E-MinisThis is a conceptual strategy intended for E-mini S&P 500 futures with hourly bars.
It uses three signals, going long or short when two or more change in the same direction.
First is MACD. A positive oscillator is considered a bullish signal and a falling oscillator is interpreted bearishly.
Next, stochastics are used as an overbought/oversold indicator. Overbought conditions are considered bearish and oversold readings are viewed as bullish.
Third is a custom indicator based on our Moving Average Speed script. It takes the rate of change of the 50-hour simple moving average (SMA), and then smooths it using a 10-period average. This provides a directional signal.
Traders may want to experiment with different settings for moving average speed.
Note: This is intended for use with stock index futures, which have round-the clock price data to populate the data in the indicators. It may not yield good results with stocks or ETFs.
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M-oscillator
Buyers & Sellers / RangeBuyers & Sellers / Range
Volatility oscillator that measures the relationship of Buying & Selling Pressure to True Range.
In other words, how much % Buyers and Sellers separately occupy the Bar
BSP is a part of Bar Range. Entire bar metrics will always have bigger value than its composite elements (body and wicks).
Since there will be NO chance of BP or SP being more than ATR, their ratio would serve crucial Volatility details.
Hence, we can relate each of them to the overall range.
As a result we have simultaneous measurements of proportions buyers and sellers to the bar.
Default mode shows BP/ATR and SP/ATR mirrored. When one rises, the other falls to compensate.
Buying Pressure / True Range ⬆️🟢 ⬇️🔵
Selling Pressure / True Range ⬆️🔴 ⬇️🟠
They are being averaged in 2 different ways:
Pre-average first, then relate as ratio
Related first, then Averaged
Enable "Preaveraged" to use already averaged BSP and Ranges in ratio instead of averaging the ratio of BSP to individual bar. For example, we're looking BP/ATR, in calculation of buyers / Range it will use "MA(Buying Pressure) / MA(True Range)" instead of "MA(Buying Pressure / True Range)".
Due such calculation, it is going to be more lagging than in off mode. Nevertheless, it reduces noise from the impact of individual bar change.
Second way of noise reduction is enabling "Body / Range"
BSP Body / Range where Bullish & Bearish Body = Buying & Selling Pressure - Relevant Wick
Buying Body = Buying Pressure - Lower Wick
Selling Body = Selling Pressure - Upper Wick
And only then it is divided to ATR.
Note that Balance line differs because body is less than it used to be with wicks. So change in wicks won't play any role in computing the ratio anymore. Thus, signals of their crossings will be more reliable than in default mode.
Pseudo-Entropy Oscillator with Standard Deviation (modified)Intuition: The Pseudo-Entropy Oscillator with Standard Deviation (PEO_SD) was created to provide traders with a way to analyze market momentum and potential reversals. It combines the concepts of entropy, standard deviation, and moving averages to offer insights into market behavior.The oscillator's core idea is to measure the pseudo-entropy of the market using standard deviation. Pseudo-entropy refers to the degree of disorder or randomness in the price data. By calculating the standard deviation of the closing prices over a specified period, the oscillator quantifies the market's volatility.To enhance the usefulness of the pseudo-entropy measurement, the oscillator incorporates moving averages. The entropy delta is calculated by applying momentum analysis to the pseudo-entropy values. This helps identify short-term changes in the entropy, indicating shifts in market sentiment or momentum.The oscillator further smoothes the pseudo-entropy values by calculating the simple moving average (SMA) over a specified length. This helps filter out noise and provides a clearer representation of the market's overall momentum.
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The "Pseudo-Entropy Oscillator with Standard Deviation" (PEO_SD) is a custom indicator designed to help traders analyze market momentum and potential reversal points. It can be applied to various markets like stocks, commodities, forex, or cryptocurrencies. By using this indicator, you can gain insights into the market's behavior and make more informed trading decisions.
The PEO_SD indicator plots three lines on your chart: the fast pseudo-entropy line, the medium pseudo-entropy line, and the slow pseudo-entropy line. Each line represents the combined pseudo-entropy values, which are calculated using standard deviation and moving averages.
The lines are color-coded for easy identification. The fast line is represented by blue, the medium line by yellow, and the slow line by red. Additionally, three horizontal reference lines are plotted: the mid line (at 50), the lower bound (at 20), and the upper bound (at 80).
To use this indicator effectively, you can observe the interactions of the lines with the reference lines. For example, when any of the lines cross above the mid line, it might indicate a bullish signal, suggesting an upward price movement. Conversely, a crossover below the mid line could be a bearish signal, indicating a potential downward price movement. If the lines reach the upper bound, it might suggest that the market is overbought, and a reversal could be imminent. Conversely, reaching the lower bound may indicate that the market is oversold, possibly leading to a price reversal.
By applying the PEO_SD indicator and studying the lines' movements, you can gain valuable insights into market momentum, identify potential reversal points, and make more informed trading decisions.
Top - Bottom Using MAThis script is used decide weather stock is overbought or oversold in given length/days from the settings.
using close difference from ohlc4 moving average ratio.
Settings Available
1) moving average length
2) Highest / Lowest ratio length
3) Difference Between Highest and Lowest Line
this script plot/display 4 lines
1) highest difference from moving averages in provided length.
2) lowest difference from moving averages in provided length.
3) ratio of moving average and ohlc4
4) linear regression moving averages of ratio of moving average and ohlc4
How to use this script
1) when ratio line is touch 2 days to highest ratio line means we are consider stock is in overbought levels or linear regression moving average above highest ratio line means overbought.
2) when ratio lines cross below its linear regression moving average then we consider final exit or book profit.
3) when linear regression moving average below lowest ratio line means stock is in oversold.
4) when linear regression moving average below lowest ratio line and linear regression line start rising after fall it means there is change in trend.
5) when linear regression moving average cross above lowest ratio line it means trend is changed and linear regression line turns green.
MACD Fake Filter [RH]Introducing a new indicator for the TradingView community based on the MACD indicator! This innovative tool goes beyond traditional MACD signals by analyzing positive and negative waves to determine the average height of the waves to filter false cross-over or cross-under signals during the sideways market.
There are two types of waves created by the MACD line, one is a positive wave above the "zero" line and another is a negative wave below "zero" line. Each wave has peaks. This indicator will find the average height of the positive waves' peaks and plot as a green line(by default). Vice-versa it will also find the average height of the negative waves' peaks and plot as a red line(by default).
Example :
This indicator will show labels when the MACD line crosses-under the MACD signal line above the average height of the positive waves.
Vice-versa, the indicator will show labels when the MACD line crosses-above the MACD signal line below the average height of the negative waves.
Example:
Alerts are also available for these types of cross-over and cross-under.
ARSIXARSIX
I have written this indicator after two years of continuous experience in writing and backtesting for several different indicators, and I believe that this indicator with its high capabilities can show you the best point of entry into the market as well as exit from it. arsix should work with any time frame and any instrument used.
This indicator has many points to understand so that you can make the best possible use of it, in the following I will try to bring you some of the most important points:
First, we will have an introduction of the different parts of the indicator:
The above line is a relatively simple but very useful formula to determine the momentum of chart. To understand the exact formula, you can refer to the source of the program itself, and its two colors are used to determine the direction of movement.
At the bottom, we have three opposing elements.
The first is the RSI14 line with dark blue color, the second is the RMA or Relative Momentum Index(RMI20) line with the number 20 for Momentum , which will significantly help us understand the overall momentum of the chart, this part is also made in two colors to increase or It will show the decline of the overall momentum of the chart.
And finally, we have a bar chart that is again created in two colors, and this histogram also calculates the momentum chart with a different formula.
And now let's talk about how to interpret these tools and how to use them for Trading:
At first, you may have the question that all these different indicators are not excessive to determine the momentum chart and are all of them necessary? In response, I must say that yes, each of these parts has been selected and made with great care and with my previous experience, the full explanation of each of these parts is beyond the scope of this article, and I will try to explain it in short words. I will give you a general understanding of each one of them and the rest is up to you to find out their capabilities by working more with these tools.
The main thing is to know that none of these tools alone will bring you success and it is their teamwork together that will help you achieve success.
For the sake of simplicity, I will tell you when to open a buy position with this indicator And you can then use this definition of the main thread to interpret the rest of the capabilities of this indicator.
To open a buy position, first the upper indicator should turn light blue, at the same time, the RMI indicator should also turn light blue, and you should also see that this RMI indicator shows the momentum of the overall chart in order to increase. in this case you will be almost sure that the general trend of the chart is towards the rise of the price. In the next step, to determine the exact point of the Entry, you have to wait until the RSI indicator passes the number 50 in this state and at the same time, make sure that the histogram also turns green and shows the increasing direction of momentum in the market, when the RSI is in This state crossed the number 50, you can enter the buy position, it should be noted that due to a series of restrictions, I have moved the RSI indicator down by 50 numbers, so as a result, the number 50 for RSI here is equivalent to The same number zero.
This was an example of how to work with this indicator, I hope that it helped you to understand how to use this indicator. In the end, I would like to point out again that the main topic is understanding the group and mutual behavior of each of the indicators' tools together. For example, if the RSI indicator crosses the number 50 here, but the histogram does not grow or shows a small growth, this indicates that the movement will be low, or for another example, if the RSI indicator cross over From the RMI indicator, This means that the market is very high, and as a result, it is a great opportunity to hold a buy position. In the same way, other parts of this indicator can also be interpreted in opposition to each other.
I hope this indicator will help you in better trades. I look forward to your constructive comments. Thanks Hamid Moradi.
Advanced Volatility-Adjusted Momentum IndexAdvanced Volatility-Adjusted Momentum Index (AVAMI)
The AVAMI is a powerful and versatile trading index which enhances the traditional momentum readings by introducing a volatility adjustment. This results in a more nuanced interpretation of market momentum, considering not only the rate of price changes but also the inherent volatility of the asset.
Settings and Parameters:
Momentum Length: This parameter sets the number of periods used to calculate the momentum, which is essentially the rate of change of the asset's price. A shorter length value means the momentum calculation will be more sensitive to recent price changes. Conversely, a longer length will yield a smoother and more stabilized momentum value, thereby reducing the impact of short-term price fluctuations.
Volatility Length: This parameter is responsible for determining the number of periods to be considered in the calculation of standard deviation of returns, which acts as the volatility measure. A shorter length will result in a more reactive volatility measure, while a longer length will produce a more stable, but less sensitive measure of volatility.
Smoothing Length: This parameter sets the number of periods used to apply a moving average smoothing to the AVAMI and its signal line. The purpose of this is to minimize the impact of volatile periods and to make the indicator's lines smoother and easier to interpret.
Lookback Period for Scaling: This is the number of periods used when rescaling the AVAMI values. The rescaling process is necessary to ensure that the AVAMI values remain within a consistent and interpretable range over time.
Overbought and Oversold Levels: These levels are thresholds at which the asset is considered overbought (potentially overvalued) or oversold (potentially undervalued), respectively. For instance, if the AVAMI exceeds the overbought level, traders may consider it as a possible selling opportunity, anticipating a price correction. Conversely, if the AVAMI falls below the oversold level, it could be seen as a buying opportunity, with the expectation of a price bounce.
Mid Level: This level represents the middle ground between the overbought and oversold levels. Crossing the mid-level line from below can be perceived as an increasing bullish momentum, and vice versa.
Show Divergences and Hidden Divergences: These checkboxes give traders the option to display regular and hidden divergences between the AVAMI and the asset's price. Divergences are crucial market structures that often signal potential price reversals.
Index Logic:
The AVAMI index begins with the calculation of a simple rate of change momentum indicator. This raw momentum is then adjusted by the standard deviation of log returns, which acts as a measure of market volatility. This adjustment process ensures that the resulting momentum index encapsulates not only the speed of price changes but also the market's volatility context.
The raw AVAMI is then smoothed using a moving average, and a signal line is generated as an exponential moving average (EMA) of this smoothed AVAMI. This signal line serves as a trigger for potential trading signals when crossed by the AVAMI.
The script also includes an algorithm to identify 'fractals', which are distinct price patterns that often act as potential market reversal points. These fractals are utilized to spot both regular and hidden divergences between the asset's price and the AVAMI.
Application and Strategy Concepts:
The AVAMI is a versatile tool that can be integrated into various trading strategies. Traders can utilize the overbought and oversold levels to identify potential reversal points. The AVAMI crossing the mid-level line can signify a change in market momentum. Additionally, the identification of regular and hidden divergences can serve as potential trading signals:
Regular Divergence: This happens when the asset's price records a new high/low, but the AVAMI fails to follow suit, suggesting a possible trend reversal. For instance, if the asset's price forms a higher high but the AVAMI forms a lower high, it's a regular bearish divergence, indicating potential price downturn.
Hidden Divergence: This is observed when the price forms a lower high/higher low, but the AVAMI forms a higher high/lower low, suggesting the continuation of the prevailing trend. For example, if the price forms a lower low during a downtrend, but the AVAMI forms a higher low, it's a hidden bullish divergence, signaling the potential continuation of the downtrend.
As with any trading tool, the AVAMI should not be used in isolation but in conjunction with other technical analysis tools and within the context of a well-defined trading plan.
Volume Price Trend (VPT)
The Volume Price Trend (VPT) is a technical analysis indicator that combines price and volume data. It's used to identify the direction of a trend or to confirm the strength of a trend. The indicator was developed on the premise that volume often precedes price.
Working of VPT:
VPT is calculated by adding or subtracting a multiple of the percentage change in the share price trend and current volume, depending upon the direction of the share price. The starting point of the VPT line is arbitrary.
The formula for calculating VPT is:
VPT = Previous VPT + Volume x (Today's Close - Previous Close)
This formula adds the total volume traded on the days the price went up, and subtracts the total volume on the days the price went down.
For each period:
If the closing price is higher than the previous closing price, the volume for that period is added to the previous VPT.
If the closing price is lower than the previous closing price, the volume for that period is subtracted from the previous VPT.
If the closing price is the same as the previous closing price, the volume for that period does not affect the VPT (i.e., it remains the same as the previous VPT).
Usage and Interpretation of VPT:
The primary use of the VPT is to help confirm the condition of prices. It’s usually used in combination with other technical analysis indicators. Here are some ways traders use the VPT:
Trend Confirmation: A rising VPT line typically confirms an uptrend as it shows that volume is increasing as prices increase. Conversely, a falling VPT line confirms a downtrend.
Divergences: Traders often look for divergences between the VPT and price movements as a sign of upcoming reversals. If prices are rising and the VPT is falling, it suggests that the upward trend may not sustain because it isn't being supported by volume. Similarly, if prices are falling and the VPT is rising, it suggests the downward trend may reverse soon.
Change in Trend: A sudden sharp increase in the VPT could signal a possible change in trend. This is based on the belief that volume changes before price.
In the script provided, the VPT is calculated and then rescaled to a 0-100 scale, which makes it easier to compare across different stocks or time periods. This script also colors the VPT line based on whether it's increasing or decreasing. The color is green when VPT is increasing, and red when it's decreasing.
Enjoy!
kyle algo v1
Integration of multiple technical indicators: The strategy mainly combines two technical indicators - Keltner Channels and Supertrend, to generate trading signals. It also calculates fifteen exponential moving averages (EMAs) for the high price with different periods ranging from 9 to 51.
Unique combination of indicators: The traditional Supertrend typically uses Average True Range (ATR) to calculate its upper and lower bands. In contrast, this script modifies the approach to use Keltner Channels instead.
Flexible sensitivity adjustment: This strategy provides a "sensitivity" input parameter for users to adjust, which controls the multiplier for the range in the Supertrend calculation. This can make the signals more or less sensitive to price changes, allowing users to tailor the strategy to their own risk tolerance and trading style.
EMA Energy Representation: The code offers a visualization of "EMA Energy", which color-codes the EMA lines based on whether the closing price is above or below the EMA line. This can provide an intuitive understanding of market trends.
Clear visual signals: The strategy generates clear "BUY" and "SELL" signals, represented as labels on the chart. This makes it easy to identify potential entry and exit points in the market.
Customizable: The script provides several user inputs, making it possible to fine-tune the strategy according to different market conditions and individual trading preferences.
EMA (Exponential Moving Average) Principle:
The EMA is a type of moving average that assigns more weight to the most recent data.
It responds more quickly to recent price changes and is used to capture short-term price trends.
Principle of Color Change :
In this trading strategy, the color of the EMA line changes based on whether the closing price is above or below the EMA. If the closing price is above the EMA, the EMA line turns green,
indicating an upward price trend. Conversely, if the closing price is below the EMA, the EMA line turns red,
indicating a downward price trend. These color changes help traders to more intuitively identify price trends
In short, our team provides a lot of practical space
That is your development space
adaptive_mfi
█ Description
Money flow an indexed value-based price and volume for the specified input length (lookback period). In summary, a momentum indicator that attempt to measure the flow of money (identify buying/selling pressure) through the asset within a specified period of time. MFI will oscillate between 0 to 100, oftentimes comprehend the analysis with oversold (20) or overbought (80) level, and a divergence that spotted to signaling a further change in trend/direction. As similar to many other indicators that use length (commonly a fixed value) as an input parameter, can be optimized by applied an adaptive filter (Ehlers), to solve the measuring cycle period. In this indicator, the adaptive measure of dominant cycle as an input parameter for the lookback period/n, will be applied to the money flow index.
█ Money Flow Index
mfi = 100 - (100/(1 + money_flow_ratio))
where:
n = int(dominant_cycle)
money_flow_ratio = n positive raw_money_flow / n negative raw_money_flow
raw_money_flow = typical_price * volume
typical_price = hlc3
█ Feature
The indicator will have a specified default parameter of: hp_period = 48; source = ohlc4
Horizontal line indicates positive/negative money flow
MFI Color Scheme: Solid; Normalized
TTM Waves ABC ATR AO MOM SQZ//All code picked from many indicators, if you recognize your code, pls comment so people can see your awesome work! I only edited and added them all together so people don't use all their indicator slots. Hope this indicator helps as many people as it can. LFG!!!
AO (Awesome Oscillator) Useful to find potential reversals in trend.
MOM (Momentum) An oscillator that measures momentum.
ATR (Average True Range) Measures the upside and downside from the average price movement occuring. 1 ATR is the general measurement. Many traders use 2ATR to set a stop and 4ATR to set take profit from their entry based on current reading from the ATR.
SQZ ( TTM Squeeze) Measures when bollinger bands have left the interior of the Keltner Channel in an attempt to predict volatility thats about to happen to either side. Green = Move is probably about to happen.
TTM Waves ( Waves A, B, and C) Measure the previous candles to determine chop, positive or negative trends. C measures the previous 30 candles or so, B the last 15 or so, and A measures the last 8 or so. You can use all three or just one. You can sneak in a move if the 2 fastest ones have moved into your preferred area. (Positive or Negative) If the wave is not fully positve or negative then that is probably chop.
-Penguincryptic
RSI Chart LevelsThe RSI Chart Levels shows you in a simple way where Support/Resistance might be. You want to make sure all settings are the same in the RSI that you are using with this overlay to be accurate.
This is also good at spotting divergence in real-time. If price goes over the Higher High but the RSI hasn't gained a new Higher High it is showing divergence, vice versa for Lower Low.
This overlay was created with the idea of RSI Divergence Scanner by zdmre indicator. Add his RSI and match the settings to the chart overlay. The default Zigzag is set to 7 which zdmre settings is different so change to whatever you prefer.
Shoutout to zdmre original work!
Price and Indicator CorrelationFIRST, CHANGE SOURCE OF INDICATOR FROM CLOSE TO WHATEVER INDICATOR YOU ARE COMPARING TO PRICE!!!!
Confirming Indicator Validity: By calculating the correlation coefficient between the price and a specific indicator, you can assess the degree to which the indicator and price move together. If there is a high positive correlation, it suggests that the indicator tends to move in the same direction as the price, increasing confidence in the indicator's validity. On the other hand, a low or negative correlation may indicate a weaker relationship between the indicator and price, signaling caution in relying solely on that indicator for trading decisions.
Identifying Divergence: Divergence occurs when the price and the indicator move in opposite directions. By monitoring the correlation coefficient, you can identify periods of divergence between the price and the selected indicator. Divergence may signal a potential reversal or significant price move, providing an opportunity to enter or exit trades.
Enhancing Trading Strategies: The correlation coefficient can be used to enhance trading strategies by incorporating the relationship between the price and the indicator. For example, if the correlation coefficient consistently shows a strong positive correlation, you may use the indicator as a confirmation tool for price-based trading signals. Conversely, if the correlation is consistently negative, it may indicate an inverse relationship that could be used for contrarian trading strategies.
Indicator Optimization : The correlation coefficient can help traders compare the effectiveness of different indicators. By calculating the correlation coefficient for multiple indicators against the price, you can identify which indicators have a stronger or weaker relationship with price movements. This information can guide the selection and optimization of indicators in your trading strategy.
Example:
RSI MACDDifferent Perspective : By using the RSI as the source for MACD calculation, you are incorporating the RSI's characteristics into the MACD indicator. The RSI measures the speed and change of price movements, while the MACD focuses on the convergence and divergence of moving averages. Combining these two indicators may provide a different perspective on market conditions.
Smoothed MACD : Since the RSI is being used as the source for the MACD calculation, the resulting MACD line (macd1 in the code) may exhibit smoother movements compared to a traditional MACD calculated directly from price data. This smoothing effect could potentially help filter out noise and provide a clearer representation of trend changes.
RSI Confirmation : The RSI is often used to identify overbought and oversold conditions. By incorporating the RSI into the MACD calculation, you can potentially gain additional confirmation when the MACD line crosses above or below zero. For example, if the MACD line crosses above zero and the RSI is in an oversold region, it could provide stronger confirmation for a bullish signal.
Example:
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
Z-Score Heikin-Ashi TransformedThe Z-Score Heikin-Ashi Transformed (𝘡 𝘏-𝘈) indicator is a powerful technical tool that combines the principles of Z-Score and Heikin Ashi to provide traders with a smoothed representation of price movements and a standardized measure of market volatility.
The 𝘡 𝘏-𝘈 indicator applies the Z-Score calculation to price data and then transforms the resulting Z-Scores using the Heikin Ashi technique. Understanding the individual components of Z-Score and Heikin Ashi will provide a foundation for comprehending the methodology and unique features of this indicator.
Z-Score:
Z-Score is a statistical measure that quantifies the distance between a data point and the mean, relative to the standard deviation. It provides a standardized value that allows traders to compare different data points on a common scale. In the context of the 𝘡 𝘏-𝘈 indicator, Z-Score is calculated based on price data, enabling the identification of extreme price movements and the assessment of their significance.
Heikin Ashi:
Heikin Ashi is a popular charting technique that aims to filter out market noise and provide a smoother representation of price trends. It involves calculating each candlestick based on the average of the previous candle's open, close, high, and low prices. This approach results in a chart that reduces the impact of short-term price fluctuations and reveals the underlying trend more clearly.
Methodology:
The 𝘡 𝘏-𝘈 indicator starts by calculating the Z-Score of the price data, which provides a standardized measure of how far each price point deviates from the mean. Next, the resulting Z-Scores are transformed using the Heikin Ashi technique. Each Z-Score value is modified according to the Heikin Ashi formula, which incorporates the average of the previous Heikin Ashi candle's open and close prices. This transformation smooths out the Z-Score values and reduces the impact of short-term price fluctuations, providing a clearer view of market trends.
This tool enables traders to identify significant price movements and assess their relative strength compared to historical data. Positive transformed Z-Scores indicate that prices are above the average, suggesting potential overbought conditions, while negative transformed Z-Scores indicate prices below the average, suggesting potential oversold conditions. Traders can utilize this information to identify potential reversals, confirm trend strength, and generate trading signals.
Utility:
The indicator offers valuable insights into price volatility and trend analysis. By combining the standardized measure of Z-Score with the smoothing effect of Heikin Ashi, traders can make more informed trading decisions and improve their understanding of market dynamics. 𝘡 𝘏-𝘈 can be used in various trading strategies, including identifying overbought or oversold conditions, confirming trend reversals, and establishing entry and exit points.
Note that the 𝘡 𝘏-𝘈 should be used in conjunction with other technical indicators and analysis tools to validate signals and avoid false positives. Additionally, traders are encouraged to conduct thorough backtesting and experimentation with different parameter settings to optimize the effectiveness of the indicator for their specific trading approach.
Key Features:
Optional Reversion Doritos
Adjustable Reversion Threshold
2 Adjustable EMAs
Example Charts:
See Also:
On Balance Volume Heikin-Ashi Transformed
RSI Trend Transform [wbburgin]The RSI Trend Transform indicator is a dual-concept indicator that transforms volume data and price data into two different RSI values, which can then be used together to determine trend strength and momentum. The volume RSI does not use any price data in its calculation - it is purely a transform from nondirectional volume into a directional indicator.
The RSI for all three RSI values (price, volume,combined average) can be plotted as either stochastic or normal. The RSI calculation is adapted for use on volume, which is why the normal ta.rsi() function is not used for the price RSI calculation; both use the same formula for indicator consistency.
How to Use the Indicator
In the examples below, the Price RSI is plotted in yellow and the Volume RSI is plotted in red (length = 200, which is why the indicator is large in these examples). The indicator can be used on any timeframe and any asset, provided volume data is provided by the vendor to TradingView.
Identifying Bullish Trends
A rising volume RSI with a rising price RSI signifies a bullish trend. Example 1:
Example 2:
You can use the combined RSI (the average of the volume RSI and the price RSI) to help with the identification of these trends:
Identifying Bearish Trends
A falling volume RSI with a falling price RSI signifies a bearish trend:
Example 2:
Settings
Source is the source of the price RSI, the volume RSI will by default use volume in its calculations. If you have other indicators on-chart, you could even use the ATR, a volatility indicator, or any nondirectional or directional indicator and transform it into the "price" RSI.
Length is both the length of the RSI and the stochastic.
The next three rows are for each RSI you can plot on the indicator: price RSI, volume RSI, and combined RSI (average of price and volume). The first checkbox plots/removes them from the chart, you can subsequently choose the type of RSI (regular or stochastic), the color of the plot, and the length of the EMA smoothing applied afterward to the plot.
Upper Band and Lower Band refer to the overbought and oversold lines, respectively.
A note about the combined RSI- you will be unable to spot divergences if the combined RSI is the only plot on the indicator, so I encourage you to use the combined RSI as a way to confirm the overall trend if you notice the price RSI and the volume RSI and trending similarly.
Momentum Oscillator, Divergences & Signals [TrendAlpha]The "Momentum, Real Time Divergences & Signals " indicator is designed to provide traders with insights into market momentum, identify potential divergences, and generate buy and sell signals. It offers a comprehensive set of features to assist traders in making informed trading decisions.
The indicator starts by calculating the momentum oscillator based on user-defined parameters.
- Traders can adjust the "Length" parameter to customize the sensitivity of the oscillator. The default value is set to 7, but it can be modified according to individual preferences.
- The "Source" parameter allows traders to select the input source for the oscillator calculation, with the default being the closing price of the asset.
- Traders have the option to display divergence lines by switching on the "Show Lines" parameter. This feature helps identify potential divergences between the oscillator and the price.
The oscillator is calculated using a two-step process. First, a smoothing function is applied to the source data using the "sma" (simple moving average) function. Then, the rate of change is computed over the specified length using the "mom" (momentum) function. Positive oscillator values indicate upward momentum, while negative values indicate downward momentum.
The indicator also generates buy and sell signals by identifying bullish and bearish divergences. A bullish divergence occurs when the oscillator is negative and crosses above zero, while a bearish divergence occurs when the oscillator is positive and crosses below zero. The indicator checks for specific conditions to confirm the divergences, such as comparing the current oscillator value with the previous value and validating the corresponding price action.
When a bullish or bearish divergence is detected, the indicator plots circles to highlight these signals on the chart. A green circle indicates a bullish signal, suggesting a potential buying opportunity, while a red circle indicates a bearish signal, suggesting a potential selling opportunity. In addition to circles, the indicator also displays labels to provide further clarity on the signals. A "Buy" label is shown for bullish signals, and a "Sell" label is shown for bearish signals.
To visually represent the divergences, the indicator plots lines connecting the corresponding points on the oscillator. A green line is drawn for bullish divergences, while a red line is drawn for bearish divergences. Traders can easily observe the divergence patterns and their relationships with the price action, aiding them in making trading decisions.
- The indicator also includes alert conditions for both bullish and bearish divergences. Traders can set up alerts to receive notifications when potential divergences occur, allowing them to take timely action.
Rough AverageThe Rough Average indicator is a unique technical tool that calculates a modified average to provide insights into market conditions. It incorporates a combination of mathematical operations and existing indicators to offer traders a different perspective on price movements.
The Rough Average indicator aims to capture market dynamics through a specific calculation method. It utilizes two main components: a check for the approximate scale of the price and a profile calculation based on the Relative Strength Index (RSI) of the closing price.
Methodology:
Approximate Scale: The indicator determines the approximate scale of the price by analyzing the magnitude of the closing price. This step involves a mathematical process that identifies the power of 10 that best represents the scale. This function reduces overall lag and gives a better smoothing to the output of the calculation
Profile Calculation: The indicator calculates a profile value by summing the absolute values of the RSI of the closing price over a specified period. The RSI provides insights into the strength or weakness of price movements. The profile calculation considers a range of prices based on the determined scale.
Indicator Calculation:
The Rough Average is derived by applying the Exponential Moving Average (EMA) to the calculated profile. The EMA is a smoothing technique that emphasizes recent price data. The resulting value represents the modified average of the indicator.
Utility:
The Rough Average indicator offers traders an alternative perspective on market conditions. By utilizing a modified average calculation, it can reveal potential trends, reversals, or periods of market strength or weakness. Traders can use the Rough Average to complement their analysis and identify possible trading opportunities.
It is important to note that the effectiveness of the Rough Average indicator may vary depending on the specific market and trading strategy. It is recommended to combine its analysis with other technical indicators and conduct thorough testing before making trading decisions.
Key Features:
Customizable OB\OS Levels
Bar coloring methods: Trend, Reversions, Extremities
Example Charts:
Open interest flow / quantifytools- Overview
Open interest flow detects inflows (positions opening) and outflows (positions closing) using open interest and estimates delta (net buyers/sellers) for the flows. Users are able to choose any open interest source available on Tradingview, by default set to BTCUSDT OI fetched from Binance. Using historical open interest flows, bands depicting typical magnitude of flows are formed for benchmarking intensity of flows. On the inflow side, +1 represents average inflows while +2 represents 2x above average inflows, a level considered an extreme. In a vice versa manner, -1 represents average outflows while -2 represents 2x above average outflows. Extreme inflows indicate aggressive position opening, in other words exuberance. Extreme outflows on the other hand indicate forced exiting of positions, in other words liquidations.
- Concept
Open interest flow is calculated using position of OI source relative to its moving average (by default set to SMA 10), referred to as relative open interest from hereon. When relative OI is positive (open interest is above its moving average), new positions are considered to enter the market. When relative OI is negative (open interest is below its moving average), existing positions are considered to exit the market. Open interest delta (side opening/closing positions, either net buyers/sellers) is calculated using relative price in a similar fashion to relative OI, but using close of viewed symbol as source. Price is considered to be up when relative price is positive, down when relative price is negative. Using relative OI and relative price in tandem, the following assumptions are applied:
Price up, open interest up = longs entering market
Price down, open interest up = shorts entering market
Price down, open interest down = longs exiting market
Price up, open interest down = shorts exiting market
Bands depicting magnitude of open interest flows are calculated using average turning points in relative OI. +1 and -1 represent levels where flows on average turn towards mean rather than continue to increase/decrease. These levels are then multiplied up to +2 and -2, representing two times larger deviations from the normal. When inflows are above 1, positions opening have reached a point where flows historically turn down. Therefore, anything above 1 would be abnormal amount of open interest entering, an extreme stretch being at 2 or above. Same logic applies to outflows, but in a vice versa manner (below -1 abnormal, extreme at -2)
Flow bursts further refine indications of aggressive inflows/outflows by taking into account change in open interest flows. Burst indications are activated when open interest is above its average turning point, coupled with a sufficient increase/decrease in flows simultaneously. Bursts are essentially a filtered version of abnormal flows and therefore a more reliable indication of exuberance/liquidations. Burst sensitivity can be adjusted via input menu, available in 5 settings. 1 sets OI burst requirements to loosest (more signals, more noise) while 5 sets OI burst requirements to strictest (less signals, less noise). Exact criteria applied to bursts can be viewed via input menu tooltip.
- Features
Users can opt for OI source auto-select for CRYPTO/USDT pairs. When auto-select is enabled and another chart is opened, corresponding open interest source is automatically selected as long as requirements mentioned above are met.
Open interest flows can be visualized as chart color, available separately for flow states and flow bursts.
Relative price line and flow guidelines (reminders for flow interpretation) can be enabled via input menu. All colors are customizable.
- Alerts
Available alerts are the following:
- Abnormal long inflows/outflows
- Abnormal short inflows/outflows
- Abnormal inflows/outflows from either side
- Aggressive longs/shorts (flow burst up)
- Liquidated longs/shorts (flow burst down)
- Aggressive or liquidated longs/shorts
- Practical guide
Open interest as a standalone data point does not reveal which side is likely opening/exiting positions and how extreme the participant behavior is. Using the additional data provided by open interest flows, moments of greed and fear can be detected. Smart money does not short into dips and buy into rips. When buyers or sellers have participated in a large move and continue to show interest even when efforts are not rewarded at an already overextended price, participants are asking for trouble.
Similar events can be observed when extreme outflows take place, indicating forced exits such as stop-losses triggering. When enough participants are forced out, price is likely to take the path of least resistance which is to the opposite direction.
Autocorrelation OscillatorReleasing the autocorrelation oscillator.
NOTE! Please be sure to read the description. This is a theoretical indicator and its important to understand the theory behind its use.
About the indicator:
Before getting into the indicator and its functionality, its important to discuss the theoretical underpinnings of the indicator.
The autocorrelation oscillator operates on two theories of market behaviour that go hand in hand. Those theories are the market efficiency theory and the random walk theory (or hypothesis ).
Market efficiency theory: The market efficiency theory or "Efficient Market Hypothesis (EMH)" postulates that all available information is reflected in a ticker's price almost instantaneously and thus it is impossible for an investor or trader to get ahead of the market because we cannot respond to the speed that the market responds. Of course, there are many holes in this theory, the most notable being that the market is a function of humans. Absent humans and their technological integrations into the market, the market would cease to react at all. But that's besides the point. This is a widely accepted theory and one in which I can mathematically observe through statistical tests. The truth behind this theory is the market is efficient for responding to evolving economic and financial information, likely owning to huge amounts of computer and algorithmic integration into trading, and thus the market is more efficient than the average person is capable (absent computerized algorithms and integration) of ascertaining nuanced financial and economic circumstances. By the time we the people can appraise information, the market has already acted on it. And that is the main premise of the EMH.
The next theory is the Random Walk Theory or Hypothesis (RWH). This builds on the EMH and essentially postulates that the market reacts so quickly to price in current circumstances that it is too random for people to truly exploit and benefit from.
The result of these two theories is two-fold and can be summarized as such:
a) The market behaves in a chaotic fashion that is seemingly random and is incapable of being predicted effectively; and
b) The market is more efficient than a person in incorporating key fundamental information, contributing to the high degree of seemingly random behaviour.
So, how does this help us?
It is said, because of the EMH and the RWH, the only way to truly exploit the market for profit is by:
a) Buying and holding and investing under the bias that stocks will eventually rise in value; or
b) For short term trading, exploiting the pricing anomalies within the data.
So how do we exploit pricing anomalies within the data?
Well, in my own research on market efficiency and behaviour, I have identified many ways of figuring out some anomalies. One of the most effective ways is by looking at simple correlation of lagged values, or autocorrelation for short.
What is autocorrelation and how to use it in relation to EMH and RWH?
Autocorrelation refers to the correlative relationship among the values in a series. Put simply, its the relationship of the same variable over time. For example, if we wanted to look at the auto-correlation of a ticker's high price, we would take, say, 5 to 7 previous high prices and correlate them with the current high price in a series dataset. If the EMH and RWH are true, the correlation among all the variables should have an average less than 0.5 or greater than -0.5. This would indicate true randomness in the dataset and thus an efficient market.
However, if the average of all of the sum's of these correlations are greater than or equal to 0.5 or less than or equal to -0.5, that indicates there is a high degree of autocorrelation and thus the EMH ad RWH is being invalidated as the market is not operating efficiently. This is an anomaly and this anomaly can be exploited.
So how do we exploit it?
Well, when the EMH and RWH hypothesis is being invalidated, we can expect what I coin as a "Regression to Chaos" i.e. the market will revert back to an efficient equilibrium state. So if we have a high correlation of the lagged variables and a strong uptrend or downtrend correlation, we can expect an inefficient market to correct back to an efficient market (i.e. have a reversal from the current trend).
So how does the indicator work?
The indicator measures the lagged correlation of the previous 5 highs and lows of a ticker. A high correlation among all of the highs and lows that exceeds 0.8 would be an invalidation of the EMH and RWH and thus signal a correction to come (i.e. a Regression to Chaos).
The indicator will display this by changing colour. Red for a bearish reversal and green for a bullish. Let's take a look below using the ticker MSFT:
Above we can see the indicator identifying observed inefficiencies within the MSFT ticker on the 1 minute timeframe. The green vertical lines correspond to potential bullish reversals as a result of bearish inefficiencies, the red correspond to bearish reversals as a result of bullish inefficiencies.
You can see these lead to reversals within the ticker.
Components of the indicator:
In the chart above we see the following that are being indicated by arrows:
Red Arrows: Show the identified inefficiencies. Red for bullish inefficiencies (i.e. bearish reversal), green for bearish inefficiencies (i.e. bullish reversal)
Yellow Arrow: The lagged variable chart. This will display the current correlation among all the lagged variables the indicator is assessing.
Teal arrow: Displays the current strength of the trend by correlating the trend to time. A strong negative value (i.e. a value less than or equal to -0.5) indicates a strong downtrend, a strong positive value indicates the inverse.
You can unselect the data-tables in the settings menu if you just want to view the correlation line itself. This part of the indicator is customizable. You can also define the lookback period; however, it is strongly recommended to leave it at 14 as this maintains the use of this indicator as an oscillator.
And that is the indicator! Let me know your comments, questions and feedback below.
Safe trades everyone!
Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Correlation for Major Markets This indicator plots the correlation of major markets as an indicator. The major markets covered are the following:
DXY
GC
CL
ES
RTY
ZN
The chart shows all the correlations and cross-correlations of the above instruments plotted together. The user can go in the settings and choose what correlation to see, or if multiple correlations, choose to plot the indicator a second time.
