Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
Pengayun
Adaptive RSI-Stoch with Butterworth Filter [UAlgo]The Adaptive RSI-Stoch with Butterworth Filter is a technical indicator designed to combine the strengths of the Relative Strength Index (RSI), Stochastic Oscillator, and a Butterworth Filter to provide a smooth and adaptive momentum-based trading signal. This custom-built indicator leverages the RSI to measure market momentum, applies Stochastic calculations for overbought/oversold conditions, and incorporates a Butterworth Filter to reduce noise and smooth out price movements for enhanced signal reliability.
By utilizing these combined methods, this indicator aims to help traders identify potential market reversal points, momentum shifts, and overbought/oversold conditions with greater precision, while minimizing false signals in volatile markets.
🔶 Key Features
Adaptive RSI and Stochastic Oscillator: Calculates RSI using a configurable period and applies a dual-smoothing mechanism with Stochastic Oscillator values (K and D lines).
Helps in identifying momentum strength and potential trend reversals.
Butterworth Filter: An advanced signal processing filter that reduces noise and smooths out the indicator values for better trend identification.
The filter can be enabled or disabled based on user preferences.
Customizable Parameters: Flexibility to adjust the length of RSI, the smoothing factors for Stochastic (K and D values), and the Butterworth Filter period.
🔶 Interpreting the Indicator
RSI & Stochastic Calculations:
The RSI is calculated based on the closing price over the user-defined period, and further smoothed to generate Stochastic Oscillator values.
The K and D values of the Stochastic Oscillator provide insights into short-term overbought or oversold conditions.
Butterworth Filter Application:
What is Butterworth Filter and How It Works?
The Butterworth Filter is a type of signal processing filter that is designed to have a maximally flat frequency response in the passband, meaning it doesn’t distort the frequency components of the signal within the desired range. It is widely used in digital signal processing and technical analysis to smooth noisy data while preserving the important trends in the underlying data. In this indicator, the Butterworth Filter is applied to the trigger value, making the resulting signal smoother and more stable by filtering out short-term fluctuations or noise in price data.
Key Concepts Behind the Butterworth Filter:
Filter Design: The Butterworth filter works by calculating weighted averages of current and past inputs (price or indicator values) and outputs to produce a smooth output. It is characterized by the absence of ripple in the passband and a smooth roll-off after the cutoff frequency.
Cutoff Frequency: The period specified in the indicator acts as a control for the cutoff frequency. A higher period means the filter will remove more high-frequency noise and retain longer-term trends, while a lower period means it will respond more to short-term fluctuations in the data.
Smoothing Process: In this script, the Butterworth Filter is calculated recursively using the following formula,
butterworth_filter(series float input, int period) =>
float wc = math.tan(math.pi / period)
float k1 = 1.414 * wc
float k2 = wc * wc
float a0 = k2 / (1 + k1 + k2)
float a1 = 2 * a0
float a2 = a0
float b1 = 2 * (k2 - 1) / (1 + k1 + k2)
float b2 = (1 - k1 + k2) / (1 + k1 + k2)
wc: This is the angular frequency, derived from the period input.
k1 and k2: These are intermediate coefficients used in the filter calculation.
a0, a1, a2: These are the feedforward coefficients, which determine how much of the current and past input values will contribute to the filtered output.
b1, b2: These are feedback coefficients, which determine how much of the past output values will contribute to the current output, effectively allowing the filter to "remember" past behavior and smooth the signal.
Recursive Calculation: The filter operates by taking into account not only the current input value but also the previous two input values and the previous two output values. This recursive nature helps it smooth the signal by blending the recent past data with the current data.
float filtered_value = a0 * input + a1 * prev_input1 + a2 * prev_input2
filtered_value -= b1 * prev_output1 + b2 * prev_output2
input: The current input value, which could be the trigger value in this case.
prev_input1, prev_input2: The previous two input values.
prev_output1, prev_output2: The previous two output values.
This means the current filtered value is determined by the combination of:
A weighted sum of the current input and the last two inputs.
A correction based on the last two output values to ensure smoothness and remove noise.
In conclusion when filter is enabled, the Butterworth Filter smooths the RSI and Stochastic values to reduce market noise and highlight significant momentum shifts.
The filtered trigger value (post-Butterworth) provides a cleaner representation of the market's momentum.
Cross Signals for Trade Entries:
Buy Signal: A bullish crossover of the K value above the D value, particularly when the values are below 40 and when the Stochastic trigger is below 1 and the filtered trigger is below 35.
Sell Signal: A bearish crossunder of the K value below the D value, particularly when the values are above 60 and when the Stochastic trigger is above 99 and the filtered trigger is above 90.
These signals are plotted visually on the chart for easy identification of potential trading opportunities.
Overbought and Oversold Zones:
The indicator highlights the overbought zone when the filtered trigger surpasses a specific threshold (typically above 100) and the oversold zone when it drops below 0.
The color-coded fill areas between the Stochastic and trigger lines help visualize when the market may be overbought (likely a reversal down) or oversold (potential reversal up).
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Dema EFI Volume | viResearchDema EFI Volume | viResearch
Conceptual Foundation and Innovation
The "Dema EFI Volume" indicator from viResearch integrates the Double Exponential Moving Average (DEMA) with the Elder Force Index (EFI), providing a dynamic approach to analyzing both price trends and volume strength. The DEMA is applied to smooth out price fluctuations while minimizing lag, which enhances the ability to detect trend direction. The EFI, developed by Dr. Alexander Elder, measures the power behind price movements by incorporating both price change and volume. This indicator, when combined with DEMA smoothing, gives traders a more accurate understanding of whether the current price movements are supported by significant volume, helping them make more informed trading decisions. The combination of DEMA and EFI allows traders to track trend strength while assessing the market’s volume dynamics, offering a more reliable method for identifying potential trend continuations or reversals.
Technical Composition and Calculation
The "Dema EFI Volume" script consists of two key components: the Double Exponential Moving Average (DEMA) and the Elder Force Index (EFI). The DEMA is applied to the selected source price over a user-defined length, providing a smoothed representation of price movements while reducing the noise that can occur with traditional moving averages. The EFI is calculated by multiplying the change in the DEMA by the volume over a user-defined period, which indicates whether the price movement is being driven by strong or weak volume. The script monitors the EFI values and volume data to generate trend signals. If the EFI is positive and volume increases, this indicates bullish pressure, while a negative EFI with decreasing volume suggests bearish conditions. The combination of these signals helps traders determine whether a price move is backed by sufficient volume, making it easier to identify trend continuations or potential reversals.
Features and User Inputs
The "Dema EFI Volume" script offers several customizable inputs, allowing traders to adapt the indicator to their specific strategies. The DEMA Length controls the smoothing applied to the price data, while the EFI Length defines the period over which the force index is calculated. Additionally, traders can set alert conditions for when a bullish or bearish EFI signal occurs, enabling them to react quickly to changing market conditions.
Practical Applications
The "Dema EFI Volume" indicator is designed for traders who want to combine price trend analysis with volume dynamics in a single tool. This makes it particularly effective for identifying trend continuations, as rising volume alongside a positive EFI suggests that the market move is supported by strong momentum. Conversely, decreasing volume and a negative EFI may indicate a weakening trend, giving traders early warning of potential reversals. The combination of DEMA and EFI also makes this indicator valuable for detecting trend strength by measuring whether price movements are backed by strong volume, confirming trend reversals by comparing price changes with volume activity, and improving trade entries and exits by analyzing both price and volume for more robust signals.
Advantages and Strategic Value
The "Dema EFI Volume" script offers significant advantages by combining the DEMA’s smoothing power with the EFI’s volume analysis. This integration allows traders to filter out noise in price data while ensuring that trend signals are backed by meaningful volume. The result is a more reliable tool for trend-following and reversal detection, making it easier for traders to stay aligned with strong market moves while avoiding false signals caused by low-volume fluctuations. The dual focus on price and volume makes the "Dema EFI Volume" an ideal tool for traders who value a comprehensive approach to market analysis.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant EFI signal occurs. The "EFI Volume Long" alert is triggered when the EFI is positive and volume increases, indicating a potential upward trend. The "EFI Volume Short" alert signals a possible downward trend when the EFI turns negative and volume decreases. Visual cues, such as the color and direction of the plotted EFI line, help traders quickly identify trend shifts and make timely decisions.
Summary and Usage Tips
The "Dema EFI Volume | viResearch" indicator provides traders with a powerful tool for analyzing both price trends and volume strength. By incorporating this script into your trading strategy, you can improve your ability to detect trend continuations and reversals, making more informed decisions based on a combination of price movement and volume dynamics. Whether you are focused on identifying trend strength or looking for early reversal signals, the "Dema EFI Volume" offers a reliable and customizable solution for traders of all levels.
Note: Backtests are based on past results and are not indicative of future performance.
RSI TreeRSI Tree is a simple way to compare the strength of several different instruments against each other.
The default is to compare MSFT, NVDA, TSLA, GOOG, META, AMZN, AAPL and NASDAQ. You could do the same for currency pairs and any other instruments available in Trading View. However, it makes the most sense to compare seven instruments to an eighth underlying instrument. As you can see in the default values, we included the NASDAQ as the eighth instrument since the other seven are part of the NASDAQ composite index. If you were to trade major currency pairs, then your eighth instrument would most likely be the U.S. Dollar (DXY).
The chart setup is important as well. You need to split your chart horizontally into 4 plots. Each plot would be at a different timing interval. The example shows 4 hr, 1 hr, 15 min and 5 min (left to right) charts. Now not only can we compare the instruments against each other, but we can do it across time to get an idea of the motion of each instrument.
Note, the instrument used on the chart is somewhat important. If the chart is set to a currency pair, but you have the RSI Tree setup for equities (as in the default) then you will get some odd behavior due to the times when these are open. Equities are 0930 to 1600 EST, whereas something like a currency would be open 24 hours a day.
Layout for default settings: www.tradingview.com
Bugs?
Kindly report any issues and I'll try to fix them promptly.
Thank you!
Bitcoin Thermocap [InvestorUnknown]The Bitcoin Thermocap indicator is designed to analyze Bitcoin's market data using a variant of the "Thermocap Multiple" concept from BitBo. This indicator offers several modes for interpreting Bitcoin's historical block and price data, aiding investors and analysts in understanding long-term market dynamics and generating potential investing signals.
Key Features:
1. Thermocap Calculation
The core of the indicator is based on the Thermocap Multiple, which evaluates Bitcoin's value relative to its cumulative historical blocks mined.
Thermocap Formula:
Source: Bitbo
btc_price = request.security("INDEX:BTCUSD", "1D", close)
BTC_BLOCKSMINED = request.security("BTC_BLOCKSMINED", "D", close)
// Variable to store the cumulative historical blocks
var float historical_blocks = na
// Initialize historical blocks on the first bar
if (na(historical_blocks))
historical_blocks := 0.0
// Update the cumulative blocks for each day
historical_blocks += BTC_BLOCKSMINED * btc_price
// Calculate the Thermocap
float thermocap = ((btc_price / historical_blocks) * 1000000) // the multiplication is just for better visualization
2. Multiple Display Modes:
The indicator can display data in four different modes, offering flexibility in interpretation:
RAW: Displays the raw Thermocap value.
LOG: Applies the logarithm of the Thermocap to visualize long-term trends more effectively, especially for large-value fluctuations.
MA Oscillator: Shows the ratio between the Thermocap and its moving average (MA). Users can choose between Simple Moving Average (SMA) or Exponential Moving Average (EMA) for smoothing.
Normalized MA Oscillator: Provides a normalized version of the MA Oscillator using a dynamic min-max rescaling technique.
3. Normalization and Rescaling
The indicator normalizes the Thermocap Oscillator values between user-defined limits, allowing for easier interpretation. The normalization process decays over time, with values shrinking towards zero, providing more relevance to recent data.
Negative values can be allowed or restricted based on user preferences.
f_rescale(float value, float min, float max, float limit, bool negatives) =>
((limit * (negatives ? 2 : 1)) * (value - min) / (max - min)) - (negatives ? limit : 0)
f_max_min_normalized_oscillator(float x) =>
float oscillator = x
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
if time >= normalization_start_date
max := max * decay
min := min * decay
normalized_oscillator = f_rescale(x, min, max, lim, neg)
Usage
The Bitcoin Thermocap indicator is ideal for long-term market analysis, particularly for investors seeking to assess Bitcoin's relative value based on mining activity and price dynamics. The different display modes and customization options make it versatile for a variety of market conditions, helping users to:
Identify periods of overvaluation or undervaluation.
Generate potential buy/sell signals based on the MA Oscillator and its normalized version.
By leveraging this Thermocap-based analysis, users can gain a deeper understanding of Bitcoin's historical and current market position, helping to inform investment strategies.
RSItrendsThis is to my friends and to my sons to use.
What Is the Relative Strength Index (RSI)?
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems.
1
The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
Adaptive LSMA Regression OscillatorOverview:
The Adaptive LSMA Regression Oscillator is an open-source technical analysis tool designed to reflect market price deviations from an adaptive least squares moving average (LSMA). The adaptive length of the LSMA changes dynamically based on the volatility of the market, making the indicator responsive to different market conditions.
Key Features:
Adaptive Length Adjustment : The base length of the LSMA is adjusted based on market volatility, measured by the Average True Range (ATR). The more volatile the market, the longer the adaptive length, and vice versa.
Oscillator : The indicator calculates the difference between the closing price and the adaptive LSMA. This difference is plotted as a histogram, showing whether prices are above or below the LSMA.
Color-Coded Histogram:
Positive values (where price is above the LSMA) are colored green.
Negative values (where price is below the LSMA) are colored red.
Debugging Information: The adaptive length is plotted for transparency, allowing users to see how the length changes based on the multiplier and ATR.
How It Works:
Inputs:
Base Length : This defines the starting length of the LSMA. It is adjusted based on market conditions.
Multiplier : A customizable multiplier is used to control how much the adaptive length responds to changes in volatility.
ATR Period : This determines the lookback period for the Average True Range calculation, a measure of market volatility.
Dynamic Adjustment:
The length of the LSMA is dynamically adjusted by multiplying the base length by a factor derived from ATR and the average close price.
This helps the indicator adapt to different market conditions, staying shorter during low volatility and longer during high volatility.
Example Use Cases:
Trend Analysis: By observing the oscillator, traders can see when prices deviate from a dynamically adjusted LSMA. This can be used to evaluate potential trend direction or changes in market behavior.
Volatility-Responsive Indicator: The adaptive length ensures that the indicator responds appropriately in both high and low volatility environments.
Potential Divergence Checker#### Key Features
1. Potential Divergence Signals:
Potential divergences can signal a change in price movement before it occurs. This indicator identifies potential divergences instead of waiting for full confirmation, allowing it to detect signs of divergence earlier than traditional methods. This provides more flexible entry points and can act as a broader filter for potential setups.
2. Exposing Signals for External Use:
One of its advanced features is the ability to expose signals for use in other scripts. This allows users to integrate divergence signals and related entry/exit points into custom strategies or automated systems.
3. Custom Entry/Exit Timing Based on Years and Days:
The indicator provides entry and exit signals based on years and days, which could be useful for time-specific market behavior, long-term trades, and back testing.
#### Basic Usage
This indicator can check for all types of potential divergences: bullish, hidden bullish, bearish, hidden bearish. All you need to do is choose the type you want to check for under “DIVERGENCE TYPE” in the settings. On the chart, potential bullish divergences will show up as triangles below the price candles. one the chart potential bearish divergences will show up as upside down triangles above the price candles
#### Signals for Advanced Usage
You can use this indicator as a source in other indicators or strategies using the following information:
“ PD: Bull divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBull divergence(hidden bull) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: Bear divergence signal ” will return “1” when a divergence is present and “0” when not present
“ PD: HBear divergence(hidden bear) signal ” will return “1” when a divergence is present and “0” when not present
“ PD: enter ” signal will return a “1” when both the days and years criteria in the “entry filter settings” are met and “0” when not met.
“ PD: exit ” signal will return a “1” when the days criteria in the “exit filter settings” are met and “0” when not met.
#### Examples of Using Signals
1. If you are testing a long strategy for Bitcoin and do not want it to run during bear market years(e.g., the second year after a US presidential election), you can enable the “year and day filter for entry,” uncheck the following years in the settings: 2010, 2014, 2018, 2022, 2026, and reference the signal below in our strategy
signal: “ PD: enter ”
2. Let’s say you have a good long strategy, but want to make it a bit more profitable, you can tell the strategy not to run on days where there is potential bearish divergence and have it only run on more profitable days using these signals and the appropriate settings in the indicator
signal: “ PD: Bear divergence signal ” will return a ‘0’ with no bearish divergence present
signal: “ PD: enter ” will return a “1” if the entry falls on a specific, more profitable day chosen in the settings
#### Disclaimer
The "Potential Divergence Checker" indicator is a tool designed to identify potential market signals. It may have bugs and not do what it should do. It is not a guarantee of future trading performance, and users should exercise caution when making trading decisions based on its outputs. Always perform your own research and consider consulting with a financial advisor before making any investment decisions. Trading involves significant risk, and past performance is not indicative of future results.
Relative Rating Index (RRI)The technical rating is one of the most perfect indicators. The reason is that this indicator is based on a majority vote of multiple indicators. It is logical that the judgment based on a majority vote of multiple indicators would not be inferior to the judgment made using only a single indicator. However, just as any indicator has its shortcomings, the technical rating also has weaknesses. The most significant issue is that it primarily provides only a momentary evaluation of the current situation.
Let's consider this in more detail. In the technical rating, an evaluation of 1.0 by the majority vote of indicators is considered a strong buy. However, in the market, there are naturally varying levels of strength. For example, would a market that only once reached an evaluation of 1.0 within a given period be considered the same as a market that consistently maintains an evaluation of 1.0? The latter clearly shows a stronger trend, but the technical rating does not provide an objective criterion for such differentiation. While it is possible to check the histogram to see how long the buy or sell rating has continued, there is no objective standard for judgment.
The indicator I have created this time compensates for this weakness by using the concept of RSI. As is well known, RSI is an indicator that shows the momentum of the market. RSI typically calculates the strength of the price increase during a 14-period by dividing the total upward movement by the total movement range. Similarly, I thought that if we divide the positive evaluations of the technical rating during a given period by the total evaluations, we could calculate the "momentum of the technical rating," which shows how often positive ratings have appeared during that period.
Below is the calculation formula.
1. Setting the Evaluation Period
Decide the period to calculate (e.g., 14 periods). This is denoted as `n`.
2. Total Positive Ratings of the Technical Rating
Calculate the total number of times the technical rating is evaluated as "strong buy" or "buy" during each period. This is called `positive_sum`.
3. Total Ratings
Count the total number of ratings (including buy, sell, and neutral) during the period. This is called `total_sum`.
4. Calculating the Upward Strength
Divide `positive_sum` by `total_sum` to calculate the ratio of positive ratings in the technical rating. This is called the "ratio of positive ratings."
The ratio of positive ratings, denoted as `P`, is calculated as follows:
P = positive_sum / total_sum
5. Calculating RRI
Following the calculation method of RSI, RRI is calculated by the following formula:
RRI = 100 - (100 / (1 + (P / (1 - P))))
As you can see, the calculation method is similar to that of RSI. Therefore, initially, I intended to name this indicator the Technical Rating RSI. However, RSI calculates based on the difference between the previous bar's price and the current bar's price, whereas this indicator calculates by summing the values of the technical ratings themselves. In the case of prices, if the difference between bars is zero, it indicates a flat market, but in the case of technical rating values, if 1.0 continues for two consecutive periods, it signifies an extremely strong buy rather than a flat market. For this reason, I decided that the calculation method could no longer be considered the same as the traditional RSI, and to avoid confusion, I chose to give this new indicator the name "Relative Rating Index" (RRI), as it provides a new type of numerical evaluation.
The information provided by this indicator is simple. When RRI exceeds 50, it means that more than 50% of the technical rating evaluations during the set period (I recommend 50 periods, but please determine the optimal value based on your timeframe) are buy evaluations. However, since there may be many false signals around exactly 50, I define it as buy-dominant when the value exceeds 60 and sell-dominant when it falls below 40. Additionally, if the graph itself is rising, it indicates that the buying momentum is strengthening, and if it is falling, it indicates that the selling momentum is increasing.
Furthermore, there are lines drawn at 90 and 10, but please note that unlike RSI, these do not indicate overbought or oversold conditions. When RRI exceeds 90, it means that over 90% of the technical rating evaluations during the specified period are buy evaluations, indicating an ongoing extremely strong buy trend. Until the RRI graph turns downward and falls below 90, it should rather be considered a buying opportunity.
With this new indicator, the technical rating becomes an indicator with depth, providing evaluations not only for the moment but over a specified period. I hope you find it helpful in your market analysis.
Dema DMI | viResearchDema DMI | viResearch
Conceptual Foundation and Innovation
The "Dema DMI" indicator integrates the Double Exponential Moving Average (DEMA) with the Directional Movement Index (DMI), creating a more responsive and precise trend-following system. The DEMA is used to smooth price data while minimizing lag, making it highly effective for trend detection. The DMI, on the other hand, measures the strength and direction of a trend by analyzing positive and negative directional movements. By combining these two elements, the "Dema DMI" offers traders a powerful tool for identifying trend changes and evaluating the strength of ongoing trends. This combination helps filter out noise in price data while maintaining sensitivity to market movements, providing better trend signals and decision-making opportunities.
Technical Composition and Calculation
The "Dema DMI" script uses two main components: the Double Exponential Moving Average (DEMA) and the Directional Movement Index (DMI). The DEMA is applied to both the high and low prices, creating smoothed versions of these prices based on a user-defined length. The DMI is then calculated by comparing changes in the smoothed high and low prices to measure directional movement. Positive directional movement (DM+) and negative directional movement (DM−) are calculated by evaluating whether the price is trending upward or downward, and the Average Directional Index (ADX) is computed to measure the strength of the trend. The ADX is smoothed to provide a more stable signal of trend strength.
Features and User Inputs
The "Dema DMI" script provides several customizable inputs, enabling traders to tailor the indicator to their strategies. The DEMA Length controls the period over which the DEMA is calculated for both high and low prices. The DMI Length sets the window for calculating directional movement, while the ADX Smoothing Length determines how smooth the ADX line appears, making it easier to assess whether a trend is strengthening or weakening. The script also includes customizable bar colors and alert conditions, providing traders with clear visual cues and notifications when a trend change occurs.
Practical Applications
The "Dema DMI" indicator is designed for traders looking to assess trend strength and direction more effectively. The DEMA smooths price movements, while the DMI highlights shifts in directional movement, providing early signals of potential trend reversals. The ADX helps gauge whether a trend is gaining momentum, allowing traders to improve the timing of trade entries and exits. Additionally, the customizable inputs make the indicator adaptable to different market conditions, ensuring its usefulness in both trending and ranging environments.
Advantages and Strategic Value
The "Dema DMI" script offers significant value by merging the smoothing effects of DEMA with the directional analysis of the DMI. This combination reduces the lag commonly associated with trend-following indicators, providing more timely and accurate trend signals. The ADX further enhances the indicator’s utility by measuring the strength of the trend, helping traders filter out weak signals and stay aligned with stronger trends. This makes the "Dema DMI" an ideal tool for traders seeking to improve their trend-following strategies and optimize their market positioning.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant trend change occurs. The "Dema DMI Long" alert is triggered when the indicator detects an upward trend, while the "Dema DMI Short" alert signals a potential downward trend. Visual cues, such as changes in the bar color and the difference between positive and negative directional movement, help traders quickly identify trend shifts and act accordingly.
Summary and Usage Tips
The "Dema DMI | viResearch" indicator combines the smoothing benefits of the DEMA with the directional analysis of the DMI, providing traders with a reliable tool for detecting trend changes and confirming trend strength. By incorporating this script into your trading strategy, you can improve your ability to detect early trend reversals, confirm trend direction, and reduce noise in price data. The "Dema DMI" is a flexible and adaptable solution for traders looking to enhance their technical analysis in various market conditions.
Note: Backtests are based on past results and are not indicative of future performance.
Ema Z-score | viResearchEma Z-score | viResearch
Conceptual Foundation and Innovation
The "Ema Z-score" indicator introduces a novel method of analyzing price deviations from the mean by combining the Exponential Moving Average (EMA) with a Z-score calculation. The Z-score is a statistical measure that quantifies how far a value deviates from the mean in terms of standard deviations. By applying the Z-score to an EMA, this indicator provides traders with insights into the strength and momentum of price movements relative to a smoothed average. This enables better detection of overbought and oversold conditions, as well as potential trend reversals.
The use of the Z-score helps filter out noise and provides more robust signals by highlighting extreme deviations from the mean, allowing traders to make more informed decisions in both trending and ranging markets.
Technical Composition and Calculation
The "Ema Z-score" script consists of two main components: the Exponential Moving Average (EMA) and the Z-score calculation. The EMA is calculated over a user-defined length, smoothing price movements to provide a clearer trend line. The Z-score is then derived by measuring the deviation of the current EMA value from the mean of the EMA over a lookback period, divided by the standard deviation of the EMA during that same period.
For the Z-score calculation, the script first computes the mean EMA over the lookback period using the ta.ema function. It then calculates the standard deviation of the EMA over the same period using the ta.stdev function. The Z-score is determined by subtracting the mean EMA from the current EMA value and dividing by the standard deviation, producing a normalized measure of deviation from the average.
Features and User Inputs
The "Ema Z-score" script offers several customizable inputs that allow traders to adjust the indicator according to their strategies. The EMA Length controls the smoothing period of the EMA, while the Lookback Period defines how far back the script looks when calculating the mean and standard deviation for the Z-score. Customizable thresholds allow traders to define when the Z-score signals potential uptrends or downtrends, based on their chosen levels of deviation.
Practical Applications
The "Ema Z-score" indicator is designed for traders who want to better understand price deviations from the mean and use those insights to identify potential trading opportunities. This tool is particularly effective for:
Identifying Overbought and Oversold Conditions: The Z-score provides a quantitative measure of how far the price has deviated from the mean, helping traders spot extreme conditions that could lead to reversals. Detecting Trend Reversals: By monitoring when the Z-score crosses certain thresholds, traders can identify potential trend reversals early and adjust their positions accordingly. Confirming Trend Strength: The Z-score can help confirm whether a price move is backed by momentum or is likely to revert to the mean, providing additional context for trade entries and exits.
Advantages and Strategic Value
The "Ema Z-score" script offers a significant advantage by combining the smoothing effect of the EMA with the precision of Z-score analysis. This approach reduces the impact of market noise while highlighting meaningful deviations from the norm. The ability to quantify deviations in terms of standard deviations gives traders a statistical edge in identifying overbought or oversold conditions and potential trend shifts. This makes the "Ema Z-score" an effective tool for both trend-following and contrarian strategies.
Alerts and Visual Cues
The script includes alert conditions to notify traders of key Z-score threshold crossings. The "Ema Z-score Long" alert is triggered when the Z-score exceeds the upper threshold, signaling a potential upward trend. Conversely, the "Ema Z-score Short" alert signals a possible downward trend when the Z-score falls below the lower threshold. Visual cues such as color changes in the bar chart and Z-score plot help traders easily identify these conditions on the chart.
Summary and Usage Tips
The "Ema Z-score | viResearch" indicator offers a unique combination of EMA smoothing and Z-score analysis, giving traders a statistical measure of price deviations and improving their ability to detect overbought or oversold conditions, trend reversals, and trend confirmations. By incorporating this script into your trading strategy, you can better quantify price extremes and make more informed decisions in both volatile and stable markets. Whether you're focused on spotting early reversals or confirming ongoing trends, the "Ema Z-score" provides a reliable and customizable solution.
Note: Backtests are based on past results and are not indicative of future performance.
Median For Loop | viResearchMedian For Loop | viResearch
Conceptual Foundation and Innovation
The "Median For Loop" indicator provides an innovative approach to analyzing market data by combining the power of the Median Price with a dynamic scoring system based on a for loop mechanism. This unique script evaluates the median price of the market over a user-defined period, then applies a loop function to generate a score that helps traders detect trends, reversals, and market momentum.
The median, being a robust measure of central tendency, helps filter out noise and better represent the middle of a price range. By applying a loop function that compares the current median to historical values, this script offers a detailed view of price momentum, allowing traders to detect potential trend changes with improved accuracy.
Technical Composition and Calculation
The "Median For Loop" script is composed of two primary components:
Median Calculation: The indicator calculates the median price of the market based on the chosen input source (default is HLC3: the average of high, low, and close) and the specified length. This creates a central value around which market movements can be evaluated.
For Loop Scoring System: This system compares the current median value with past values within a user-defined range, generating a score that reflects how the market is trending. The loop mechanism dynamically sums the score based on whether the current median is higher or lower than historical medians, providing a clear signal of trend strength and direction.
Key Calculations:
Median Calculation: The median is calculated using the percentile_nearest_rank function, providing the 50th percentile of the selected price data over the given length.
For Loop Scoring:
The loop evaluates the median over a defined range (from and to), comparing the current median to historical values.
If the current median is higher than a previous value, a positive score is added; if it is lower, a negative score is added. This forms the final total score, indicating the trend strength.
Features and User Inputs
The "Median For Loop" script offers flexibility and customization options for traders to adapt it to various market conditions and trading strategies:
Median Length: Control the period over which the median price is calculated, affecting the responsiveness of the indicator to price changes.
Loop Range (From and To): Define the range over which the loop evaluates historical median values, allowing traders to adjust how far back the script looks when assessing momentum.
Thresholds: User-defined thresholds are available to specify when the score indicates an uptrend or downtrend. This provides traders with control over the sensitivity of the trend signals.
Practical Applications
The "Median For Loop" indicator is ideal for traders seeking a balanced, noise-filtered approach to trend detection. It is particularly effective for:
Detecting Early Trend Reversals: The loop-based scoring system offers early signals of potential reversals by comparing the current median with past medians, giving traders an advantage in volatile markets.
Confirming Trend Strength: By analyzing the median over time, the script helps confirm whether trends are gaining or losing momentum, improving the accuracy of trade entries and exits.
Strategic Positioning: The customizable parameters allow traders to adapt the script to various market conditions, enhancing their ability to position themselves effectively in both trending and ranging markets.
Advantages and Strategic Value
The key advantage of the "Median For Loop" script is its ability to reduce market noise by focusing on the median price while providing a dynamic scoring system for trend detection. The combination of median calculation and loop-based evaluation offers a more refined view of market momentum, reducing false signals and increasing the reliability of trend identification. This makes it a valuable tool for traders aiming to enhance their market timing and strategy development.
Alerts and Visual Cues
The script includes built-in alerts to notify traders of potential trend changes:
Median For Loop Long: Triggers when the score exceeds the upper threshold, indicating a possible upward trend.
Median For Loop Short: Triggers when the score falls below the lower threshold, signaling a potential downward trend.
Visual cues are also provided, with background colors highlighting potential trend shifts when the score crosses certain levels, offering traders an easy-to-read signal on the chart.
Summary and Usage Tips
The "Median For Loop | viResearch" indicator provides a powerful combination of median price smoothing and dynamic trend scoring, allowing traders to gain a clearer understanding of market momentum. By incorporating this script into your trading strategy, you can improve your ability to detect trends and reversals while reducing the noise that often affects price data. Whether you're focusing on early reversals or confirming the strength of existing trends, this indicator offers a reliable and customizable solution.
Note: Backtests are based on past results and are not indicative of future performance.
Lsma For Loop | viResearchLsma For Loop | viResearch
Conceptual Foundation and Innovation
The "Lsma For Loop" indicator offers a unique combination of the Least Squares Moving Average (LSMA) with a dynamic scoring system based on a loop function. By comparing the current LSMA value with historical values over a user-defined range, this indicator generates a detailed score that helps detect trend strength and potential reversals. This approach provides traders with a more nuanced analysis of price action, allowing them to identify trends earlier and with more accuracy.
The LSMA, which minimizes lag compared to traditional moving averages, is ideal for detecting trends as it provides a smooth and quick-to-respond line. When combined with the loop-based scoring system, traders can benefit from a powerful tool for analyzing market momentum and capturing profitable trends.
Technical Composition and Calculation
The "Lsma For Loop" script features two essential components:
Least Squares Moving Average (LSMA): The LSMA is calculated over a user-defined length using a linear regression model. It provides a smooth line that follows price trends more closely, reducing the noise that is often present in simple moving averages.
For Loop Scoring System: This system evaluates the LSMA over a range of previous values, generating a score based on whether the current LSMA is higher or lower than its previous values within the specified range. The resulting score reflects the strength of the trend, with higher scores indicating a stronger uptrend and lower scores signaling a downtrend.
Key Calculations:
LSMA Calculation: The LSMA is derived from the closing price over the selected period (len), providing a smooth moving average that fits the price data closely.
For Loop Scoring:
The loop iterates over a range of previous LSMA values, comparing the current LSMA to each past value.
If the current LSMA is higher than a previous value, a positive score is added; if it is lower, a negative score is added. The sum of these comparisons forms the overall score.
Features and User Inputs
The "Lsma For Loop" script offers a range of customization options, allowing traders to tailor the indicator to their specific trading strategies and market conditions:
LSMA Length: Adjust the length of the LSMA, controlling the smoothness of the indicator and how quickly it reacts to price changes.
Loop Range (From and To): Define the range over which the for loop evaluates LSMA values. This provides flexibility in assessing momentum over different timeframes.
Thresholds: Customizable threshold levels are used to define when the score indicates an uptrend or downtrend. This allows traders to fine-tune the sensitivity of the indicator to market movements.
Practical Applications
The "Lsma For Loop" is a versatile tool for traders who want to leverage the advantages of LSMA smoothing while gaining a more detailed view of trend strength. This indicator is particularly useful for:
Identifying Trend Reversals: The loop-based scoring system provides an early indication of potential trend reversals, allowing traders to react before major market movements.
Confirming Trend Strength: By evaluating the LSMA against a range of previous values, the script helps confirm whether a trend is strengthening or weakening.
Enhanced Market Positioning: The customizable range and thresholds enable traders to adapt the script to different market conditions, whether they are day trading or swing trading.
Advantages and Strategic Value
The primary advantage of the "Lsma For Loop" script lies in its ability to provide a more granular analysis of LSMA behavior through the use of the for loop. This dynamic approach reduces the likelihood of false signals and offers greater accuracy in detecting trends. The indicator’s versatility makes it a valuable tool for both short-term and long-term trading strategies.
Alerts and Visual Cues
The script includes built-in alert conditions to notify traders of key trend changes:
Lsma For Loop Long: Indicates a potential upward trend when the score exceeds the upper threshold.
Lsma For Loop Short: Signals a potential downward trend when the score falls below the lower threshold.
Additionally, visual cues such as background color changes highlight when the score crosses certain key levels, providing an easy-to-read representation of market trends directly on the chart.
Summary and Usage Tips
The "Lsma For Loop | viResearch" indicator provides traders with a powerful tool that combines LSMA smoothing with a dynamic loop-based scoring system for trend detection. Incorporating this script into your trading strategy can help improve trend identification and enhance decision-making around entries and exits. Whether you are trading in trending markets or looking for early reversal signals, this script offers a reliable and flexible solution.
Note: Backtests are based on past results and are not indicative of future performance.
RSI Standard Deviation | viResearchRSI Standard Deviation | viResearch
The "RSI Standard Deviation" indicator, developed by viResearch, introduces a new approach to combining the Relative Strength Index (RSI) with a standard deviation measure to offer a more dynamic view of market momentum. By applying standard deviation to the RSI values, this indicator refines the traditional RSI, providing a more precise and adaptive way to measure overbought and oversold conditions. This unique combination allows traders to better understand the underlying volatility in RSI movements, leading to more informed decisions in trending and ranging markets.
Technical Composition and Calculation:
The core of the "RSI Standard Deviation" lies in calculating the RSI based on user-defined input parameters and then applying standard deviation to these RSI values. This method enhances the sensitivity of the RSI, making it more responsive to market volatility.
RSI Calculation:
RSI Length (len): The script computes the Relative Strength Index over a customizable length (default: 21), offering a traditional measure of momentum in the market. The RSI tracks the speed and change of price movements, oscillating between 0 and 100 to indicate overbought and oversold conditions.
Standard Deviation Applied to RSI:
Standard Deviation Length (sdlen): The script calculates the standard deviation of the RSI values over a user-defined period (default: 35). This standard deviation represents the volatility in RSI movements, adding a new layer of analysis to traditional RSI.
Upper (u) and Lower (d) Bands:
The standard deviation values are used to create upper and lower bands around the RSI, offering an adaptive range that expands or contracts based on market volatility. This helps traders identify moments when the market is more likely to reverse or continue its trend.
Trend Identification:
Uptrend (L): The script identifies an uptrend when the RSI moves above the lower band and stays above the midline (50). This indicates that the market is gaining upward momentum, potentially signaling a long position.
Downtrend (S): A downtrend is identified when the RSI moves below 50, suggesting a weakening market and a potential short position.
Features and User Inputs:
The "RSI Standard Deviation" script offers various customization options, enabling traders to tailor it to their specific needs and strategies:
RSI Length: Traders can adjust the length of the RSI calculation to control how quickly the indicator responds to price movements.
Standard Deviation Length: Adjusting the standard deviation length allows users to control the sensitivity of the upper and lower bands, fine-tuning the indicator’s responsiveness to market volatility.
Source Input: The script can be applied to different price sources, offering flexibility in how it calculates RSI and standard deviation values.
Practical Applications:
The "RSI Standard Deviation" indicator is particularly useful in volatile markets, where traditional RSI may produce false signals due to rapid price movements. By adding a standard deviation measure, traders can filter out noise and better identify trends.
Key Uses:
Trend Following: The standard deviation bands provide a clearer view of momentum shifts in the RSI, allowing traders to follow the trend more confidently.
Volatility Assessment: The indicator dynamically adjusts to market volatility, making it easier to assess when the market is overbought or oversold and when a trend reversal is likely.
Signal Confirmation: By comparing the RSI to the adaptive standard deviation bands, traders can confirm signals and avoid false entries during periods of high volatility.
Advantages and Strategic Value:
The "RSI Standard Deviation" offers several advantages:
Enhanced Precision: The combination of RSI and standard deviation results in a more refined momentum indicator that adapts to market conditions.
Noise Reduction: The standard deviation bands help filter out short-term market noise, making it easier to identify significant trend changes.
Dynamic Volatility Awareness: By using standard deviation, the indicator adjusts its bands based on real-time volatility, providing more accurate overbought and oversold signals.
Summary and Usage Tips:
The "RSI Standard Deviation" is a powerful tool for traders looking to enhance their RSI analysis with volatility measures. For optimal performance, traders should experiment with different RSI and standard deviation lengths to suit their trading timeframe and strategy. Whether used to follow trends or confirm momentum signals, the "RSI Standard Deviation" provides a reliable and adaptive solution for modern trading environments.
HMA Smoothed RSI [Pinescriptlabs]This indicator uses a modified version of the RSI (Relative Strength Index) weighted by volume. This means it not only takes into account the price but also the amount of volume supporting those price movements, making the indicator more sensitive to real market fluctuations.
Hull Moving Average (HMA) Applied to RSI: To smooth the volume-weighted RSI, a Hull Moving Average (HMA) is applied. The HMA is known for its ability to reduce market "noise" and quickly react to trend changes. This process helps better identify when an asset is overbought or oversold.
Overbought and Oversold Regions: The indicator sets clear overbought and oversold levels, which are adjustable. By default, the overbought level is set at 20 and the oversold level at -20, but you can customize these values. Additionally, there are extreme overbought and oversold levels to help identify more extreme market conditions where a price reversal is more likely.
Buy and Sell Signals:
Buy Signal: This is generated when the modified RSI crosses above the oversold level. This indicates that the price has dropped enough and may be about to rise.
Sell Signal: This occurs when the RSI crosses below the overbought level. This suggests that the price has risen too much and could be about to fall.
Dynamic Visualization and Colors: The indicator is displayed with different colors based on its behavior:
When the RSI is within normal levels, the color is neutral.
If it is above the overbought level, the color turns red (sell alert).
If it is below the oversold level, the color turns green (buy alert).
Alerts: This indicator also allows you to set up alerts. You will receive automatic notifications when buy or sell signals are generated, helping you make decisions without constantly monitoring the chart.
Español:
Este indicador utiliza una versión modificada del RSI (Índice de Fuerza Relativa), ponderado por volumen. Esto significa que no solo tiene en cuenta el precio, sino también la cantidad de volumen que respalda esos movimientos de precios, haciendo que el indicador sea más sensible a las fluctuaciones reales del mercado.
Media Móvil Hull (HMA) aplicada al RSI: Para suavizar el RSI ponderado por volumen, se le aplica una Media Móvil Hull (HMA). La HMA es conocida por su capacidad para reducir el "ruido" del mercado y reaccionar rápidamente a los cambios de tendencia. Este proceso ayuda a identificar mejor cuándo un activo está sobrecomprado o sobrevendido.
Regiones de sobrecompra y sobreventa: El indicador establece niveles claros de sobrecompra y sobreventa que son ajustables. Por defecto, el nivel de sobrecompra está en 20 y el de sobreventa en -20, pero puedes personalizar estos valores. Además, hay niveles extremos de sobrecompra y sobreventa que te ayudan a identificar condiciones más extremas del mercado, donde una reversión de precio es más probable.
Señales de compra y venta:
Señal de compra: Se genera cuando el RSI modificado cruza hacia arriba el nivel de sobreventa. Esto indica que el precio ha bajado lo suficiente y puede estar a punto de subir.
Señal de venta: Se produce cuando el RSI cruza hacia abajo el nivel de sobrecompra. Esto indica que el precio ha subido demasiado y podría estar a punto de bajar.
Visualización y colores dinámicos: El indicador se muestra con diferentes colores según su comportamiento:
Cuando el RSI está dentro de los niveles normales, el color es neutro.
Si está por encima del nivel de sobrecompra, el color se vuelve rojo (señal de alerta de venta).
Si está por debajo del nivel de sobreventa, el color se vuelve verde (señal de alerta de compra).
Alertas: Este indicador también te permite configurar alertas. Así, recibirás notificaciones automáticas cuando se generen señales de compra o venta, ayudándote a tomar decisiones sin estar constantemente monitoreando el gráfico.
Inverted SD Dema RSI | viResearchInverted SD Dema RSI | viResearch
The "Inverted SD Dema RSI" developed by viResearch introduces a new approach to trend analysis by combining the Double Exponential Moving Average (DEMA), Standard Deviation (SD), and Relative Strength Index (RSI). This unique indicator provides traders with a tool to capture market trends by integrating volatility-based thresholds. By using the smoothed DEMA along with standard deviation, the indicator offers improved responsiveness to price fluctuations, while RSI thresholds offer insight into overbought and oversold market conditions.
At the core of the "Inverted SD Dema RSI" is the combination of DEMA and standard deviation for a more nuanced view of market volatility. The use of RSI further aids in detecting price extremes and potential trend reversals.
DEMA Calculation (sublen): The Double Exponential Moving Average (DEMA) smoothes out price data over a user-defined period, reducing lag compared to traditional moving averages. This provides a clearer representation of the market's overall direction.
Standard Deviation Calculation (sublen_2): The standard deviation of the DEMA is used to define the upper (u) and lower (d) bands, highlighting areas where price volatility may signal a change in trend. These dynamic bands help traders gauge price volatility and potential breakouts or breakdowns.
RSI Calculation (len): The script applies the Relative Strength Index (RSI) to the smoothed DEMA values, allowing traders to detect momentum shifts based on a modified data set. This provides a more accurate reflection of market strength when combined with the DEMA.
Thresholds: The RSI is compared to user-defined thresholds (70 for overbought and 55 for oversold conditions). These thresholds help in identifying potential market reversals, especially when the price breaks outside of the calculated standard deviation bands.
Uptrend (L): An uptrend signal is generated when the RSI exceeds the upper threshold (70) and the price is not above the upper standard deviation band, indicating that there may be room for further price appreciation.
Downtrend (S): A downtrend signal occurs when the RSI falls below the lower threshold (55), indicating that the price may continue to decline.
The "Inverted SD Dema RSI" offers a wide range of customizable settings, allowing traders to adjust the indicator based on their trading style or market conditions.
DEMA Length (sublen): Controls the period used to smooth the price data, impacting the sensitivity of the DEMA to recent price movements.
Standard Deviation Length (sublen_2): Defines the length over which the standard deviation is calculated, helping traders control the width of the upper and lower bands.
RSI Length (len): Adjusts the period used for the RSI calculation, providing flexibility in determining overbought and oversold conditions.
RSI Thresholds: Traders can define their own levels for detecting trend reversals, with default values of 70 for an uptrend and 55 for a downtrend.
The "Inverted SD Dema RSI" is particularly well-suited for traders looking to capture trends while accounting for volatility and momentum. By using a smoothed DEMA as the foundation, it effectively filters out noise, making it ideal for detecting reliable trends in volatile markets.
Key Uses:
Trend Following: The indicator’s combination of DEMA, standard deviation, and RSI helps traders follow trends more effectively by reducing noise and identifying key momentum shifts.
Volatility Filtering: The use of standard deviation bands provides a dynamic measure of volatility, ensuring that traders are aware of potential breakouts or breakdowns in the market.
Momentum Detection: The inclusion of RSI ensures that the indicator is not only focused on trend direction but also on the strength of the underlying momentum, helping traders avoid entering trades during weak trends.
The "Inverted SD Dema RSI" provides several key advantages over traditional trend-following indicators:
Reduced Lag: The use of DEMA ensures faster trend detection, reducing the lag associated with simple moving averages.
Noise Reduction: The integration of standard deviation helps filter out irrelevant price movements, making it easier to identify significant trends.
Momentum Awareness: The addition of RSI provides valuable insight into the strength of trends, helping traders avoid false signals during periods of weak momentum.
The "Inverted SD Dema RSI" offers a powerful blend of trend-following and momentum detection, making it a versatile tool for modern traders. By integrating DEMA, standard deviation, and RSI, the indicator provides a comprehensive view of market trends and volatility. Traders are encouraged to experiment with different settings for the DEMA length, standard deviation, and RSI thresholds to fine-tune the indicator for their specific trading strategies. Whether used for trend confirmation, volatility assessment, or momentum analysis, the "Inverted SD Dema RSI" offers a valuable tool for traders seeking a comprehensive approach to market analysis.
Composite Momentum█ Introduction
The Composite Momentum Indicator is a tool we came across that we found to be useful at detecting implied tops and bottoms within quick market cycles. Its approach to analyzing momentum through a combination of moving averages and summation techniques makes it a useful addition to the range of available indicators on TradingView.
█ How It Works
This indicator operates by calculating the difference between two moving averages—one fast and one slow, which can be customized by the user. The difference between these two averages is then expressed as a percentage of the fast moving average, forming the core momentum value which is then smoothed with an Exponential Moving Average is applied. The smoothed momentum is then compared across periods to identify directional changes in direction
Furthermore, the script calculates the absolute differences between consecutive momentum values. These differences are used to determine periods of momentum acceleration or deceleration, aiming to establish potential reversals.
In addition to tracking momentum changes, the indicator sums positive and negative momentum changes separately over a user-defined period. This summation is intended to provide a clearer picture of the prevailing market bias—whether it’s leaning towards strength or weakness.
Finally, the summed-up values are normalized to a percentage scale. This normalization helps in identifying potential tops and bottoms by comparing the relative strength of the momentum within a given cycle.
█ Usage
This indicator is primarily useful for traders who focus on detecting quick cycle tops and bottoms. It provides a view of momentum shifts that can signal these extremes, though it’s important to use it in conjunction with other tools and market analysis techniques. Given its ability to highlight potential reversals, it may be of interest to those who seek to understand short-term market dynamics.
█ Disclaimer
This script was discovered without any information about its author or original intent but was nonetheless ported from its original format that is available publicly. It’s provided here for educational purposes and should not be considered a guaranteed method for market analysis. Users are encouraged to test and understand the indicator thoroughly before applying it in real trading scenarios.
Uptrick: Dual Moving Average Volume Oscillator
Title: Uptrick: Dual Moving Average Volume Oscillator (DPVO)
### Overview
The "Uptrick: Dual Moving Average Volume Oscillator" (DPVO) is an advanced trading tool designed to enhance market analysis by integrating volume data with price action. This indicator is specially developed to provide traders with deeper insights into market dynamics, making it easier to spot potential entry and exit points based on volume and price interactions. The DPVO stands out by offering a sophisticated approach to traditional volume analysis, setting it apart from typical volume indicators available on the TradingView platform.
### Unique Features
Unlike traditional indicators that analyze volume and price movements separately, the DPVO combines these two critical elements to offer a comprehensive view of market behavior. By calculating the Volume Impact, which involves the product of the exponential moving averages (EMAs) of volume and the price range (close - open), this indicator highlights significant trading activities that could indicate strong buying or selling pressure. This method allows traders to see not just the volume spikes, but how those spikes relate to price movements, providing a clearer picture of market sentiment.
### Customization and Inputs
The DPVO is highly customizable, catering to various trading styles and strategies:
- **Oscillator Length (`oscLength`)**: Adjusts the period over which the volume and price difference is analyzed, allowing traders to set it according to their trading timeframe.
- **Fast and Slow Moving Averages (`fastMA` and `slowMA`)**: These parameters control the responsiveness of the DPVO. A shorter `fastMA` coupled with a longer `slowMA` can help in identifying trends quicker or smoothing out market noise for more conservative approaches.
- **Signal Smoothing (`signalSmooth`)**: This input helps in reducing signal noise, making the crossover and crossunder points between the DVO and its smoothed signal line clearer and easier to interpret.
### Functionality Details
The DPVO operates through a sequence of calculated steps that integrate volume data with price movement:
1. **Volume Impact Calculation**: This is the foundational step where the product of the EMA of volume and the EMA of price range (close - open) is calculated. This metric highlights trading sessions where significant volume accompanies substantial price movements, suggesting a strong market response.
2. **Dynamic Volume Oscillator (DVO)**: The heart of the indicator, the DVO, is derived by calculating the difference between the fast EMA and the slow EMA of the Volume Impact. This result is then normalized by dividing by the EMA of the volume over the same period to scale the output, making it consistent across various trading environments.
3. **Signal Generation**: The final output is smoothed using a simple moving average of the DVO to filter out market noise. Buy and sell signals are generated based on the crossover and crossunder of the DVO with its smoothed version, providing clear cues for market entry or exit.
### Originality
The DPVO's originality lies in its innovative integration of volume and price movement, a novel approach not typically observed in other volume indicators. By analyzing the product of volume and price change EMAs, the DPVO captures the essence of market dynamics more holistically than traditional tools, which often only reflect volume levels without contextualizing them with price actions. This dual analysis provides traders with a deeper understanding of market forces, enabling them to make more informed decisions based on a combination of volume surges and significant price movements. The DPVO also introduces a unique normalization and smoothing technique that refines the oscillator's output, offering cleaner and more reliable signals that are adaptable to various market conditions and trading styles.
### Practical Application
The DPVO excels in environments where volume plays a crucial role in validating price movements. Traders can utilize the buy and sell signals generated by the DPVO to enhance their decision-making process. The signals are plotted directly on the trading chart, with buy signals appearing below the price bars and sell signals above, ensuring they are prominent and actionable. This setup is particularly useful for day traders and swing traders who rely on timely and accurate signals to maximize their trading opportunities.
### Best Practices
To maximize the effectiveness of the DPVO, traders should consider the following best practices:
- **Market Selection**: Use the DPVO in markets known for strong volume-price correlation such as major forex pairs, popular stocks, and cryptocurrencies.
- **Signal Confirmation**: While the DPVO provides powerful signals, confirming these signals with additional indicators such as RSI or MACD can increase trade reliability.
- **Risk Management**: Always use stop-loss orders to manage risks associated with trading signals. Adjust the position size based on the volatility of the asset to avoid significant losses.
### Practical Example + How to use it
Practical Example1: Day Trading Cryptocurrencies
For a day trader focusing on the highly volatile cryptocurrency market, the DPVO can be an effective tool on a 15-minute chart. Suppose a trader is monitoring Bitcoin (BTC) during a period of high market activity. The DPVO might show an upward crossover of the DVO above its smoothed signal line while also indicating a significant increase in volume. This could signal that strong buying pressure is entering the market, suggesting a potential short-term rally. The trader could enter a long position based on this signal, setting a stop-loss just below the recent support level to manage risk. If the DPVO later shows a crossover in the opposite direction with decreasing volume, it might signal a good exit point, allowing the trader to lock in profits before a potential pullback.
- **Swing Trading Stocks**: For a swing trader looking at stocks, the DPVO could be applied on a daily chart. If the oscillator shows a consistent downward trend along with increasing volume, this could suggest a potential sell-off, providing a sell signal before a significant downturn.
You can look for:
--> Increase in volume - You can use indicators like 24-hour-Volume to have a better visualization
--> Uptrend/Downtrend in the indicator (HH, HL, LL, LH)
--> Confirmation (Buy signal/Sell signal)
--> Correct Price action (Not too steep moves up or down. Stable moves.) (Optional)
--> Confirmation with other indicators (Optional)
Quick image showing you an example of a buy signal on SOLANA:
### Technical Notes
- **Calculation Efficiency**: The DPVO utilizes exponential moving averages (EMAs) in its calculations, which provides a balance between responsiveness and smoothing. EMAs are favored over simple moving averages in this context because they give more weight to recent data, making the indicator more sensitive to recent market changes.
- **Normalization**: The normalization of the DVO by the EMA of the volume ensures that the oscillator remains consistent across different assets and timeframes. This means the indicator can be used on a wide variety of markets without needing significant adjustments, making it a versatile tool for traders.
- **Signal Line Smoothing**: The final signal line is smoothed using a simple moving average (SMA) to reduce noise. The choice of SMA for smoothing, as opposed to EMA, is intentional to provide a more stable signal that is less prone to frequent whipsaws, which can occur in highly volatile markets.
- **Lag and Sensitivity**: Like all moving average-based indicators, the DPVO may introduce a slight lag in signal generation. However, this is offset by the indicator’s ability to filter out market noise, making it a reliable tool for identifying genuine trends and reversals. Adjusting the `fastMA`, `slowMA`, and `signalSmooth` inputs allows traders to fine-tune the sensitivity of the DPVO to match their specific trading strategy and market conditions.
- **Platform Compatibility**: The DPVO is written in Pine Script™ v5, ensuring compatibility with the latest features and functionalities offered by TradingView. This version takes advantage of optimized functions for performance and accuracy in calculations, making it well-suited for real-time analysis.
Conclusion
The "Uptrick: Dual Moving Average Volume Oscillator" is a revolutionary tool that merges volume analysis with price movement to offer traders a more nuanced understanding of market trends and reversals. Its ability to provide clear, actionable signals based on a unique combination of volume and price changes makes it an invaluable addition to any trader's toolkit. Whether you are managing long-term positions or looking for quick trades, the DPVO provides insights that can help refine any trading strategy, making it a standout choice in the crowded field of technical indicators.
Nothing from this indicator or any other Uptrick Indicators is financial advice. Only you are ultimately responsible for your choices.
True Strength Index with Buy/Sell Signals and AlertsThe True Strength Index (TSI) is a momentum oscillator that helps traders identify trends and potential reversal points in the market. Here’s how it works:
1. **Price Change Calculation**:
- **`pc = ta.change(price)`**: This calculates the change in price (current price minus the previous price).
2. **Double Smoothing**:
- **`double_smooth(src, long, short)`**: This function smooths the price change data twice using two Exponential Moving Averages (EMAs):
- The first EMA smooths the raw data.
- The second EMA smooths the result of the first EMA.
- **`double_smoothed_pc`**: The double-smoothed price change.
- **`double_smoothed_abs_pc`**: The double-smoothed absolute price change, which helps normalize the TSI value.
3. **TSI Calculation**:
- **`tsi_value = 100 * (double_smoothed_pc / double_smoothed_abs_pc)`**: This calculates the TSI by dividing the double-smoothed price change by the double-smoothed absolute price change, then multiplying by 100 to scale the value.
- The TSI oscillates around the zero line, indicating momentum. Positive values suggest bullish momentum, while negative values suggest bearish momentum.
4. **Signal Line**:
- **`signal_line = ta.ema(tsi_value, signal)`**: This creates a signal line by applying another EMA to the TSI value. The signal line is typically used to identify entry and exit points.
5. **Buy and Sell Signals**:
- **Buy Signal**: Occurs when the TSI crosses above the signal line (`ta.crossover(tsi_value, signal_line)`), indicating that bullish momentum is strengthening, which might suggest a buying opportunity.
- **Sell Signal**: Occurs when the TSI crosses below the signal line (`ta.crossunder(tsi_value, signal_line)`), indicating that bearish momentum is strengthening, which might suggest a selling opportunity.
6. **Visual Representation**:
- The TSI line and the signal line are plotted on the chart.
- Buy signals are marked with green "BUY" labels below the bars, and sell signals are marked with red "SELL" labels above the bars.
**How to Use It**:
- **Trend Identification**: When the TSI is above zero, it suggests an uptrend; when it's below zero, it suggests a downtrend.
- **Buy/Sell Signals**: Traders often enter a buy trade when the TSI crosses above the signal line and enter a sell trade when the TSI crosses below the signal line.
- **Divergences**: TSI can also be used to spot divergences between the indicator and price action, which can signal potential reversals.
The TSI is particularly useful in identifying the strength of a trend and the potential turning points, making it valuable for trend-following and swing trading strategies.
Standardized PSAR Oscillator [AlgoAlpha]Enhance your trading experience with the "Standardized PSAR Oscillator" 🪝, a powerful tool that combines the Parabolic Stop and Reverse (PSAR) with standardization techniques to offer more nuanced insights into market trends and potential reversals.
🔑 Key Features:
- 🛠 Customizable PSAR Settings: Adjust the starting point, increment, and maximum values for the PSAR to tailor the indicator to your strategy.
- 📏 Standardization: Smooth out volatility by standardizing the PSAR values using a customizable EMA, making reversals easier to identify.
- 🎨 Dynamic Color-Coding: The oscillator changes colors based on market conditions, helping you quickly spot bullish and bearish trends.
- 🔄 Divergence Detection: Automatic detection of bullish and bearish divergences with customizable sensitivity and confirmation settings.
- 🔔 Alerts: Set up alerts for key events like zero-line crossovers and trend weakening, ensuring you never miss a critical market move.
🚀 How to Use:
✨ Add the Indicator: Add the indicator to favorites by pressing the star icon, adjust the settings to suite your needs.
👀 Monitor Signals: Watch for the automatic plotting of divergences and reversal signals to identify potential market entries and exits.
🔔 Set Alerts: Configure alerts to get notified of key changes without constantly monitoring the charts.
🔍 How It Works:
The Standardized PSAR Oscillator is an advanced trading tool that refines the traditional PSAR (Parabolic Stop and Reverse) indicator by incorporating several key enhancements to improve trend analysis and signal accuracy. The script begins by calculating the PSAR, a widely used indicator known for its effectiveness in identifying trend reversals. To make the PSAR more adaptive and responsive to market conditions, it is standardized using an Exponential Moving Average (EMA) of the high-low range over a user-defined period. This standardization helps to normalize the PSAR values, making them more comparable across different market conditions.
To further enhance signal clarity, the standardized PSAR is then smoothed using a Weighted Moving Average (WMA). This combination of EMA and WMA creates an oscillator that not only captures trend direction but also smooths out market noise, providing a cleaner signal. The oscillator's values are color-coded to visually indicate its position relative to the zero line, with additional emphasis on whether the WMA is rising or falling—this helps traders quickly interpret the trend’s strength and direction.
The oscillator also includes built-in divergence detection by comparing pivot points in price action with those in the oscillator. This feature helps identify potential discrepancies between the price and the oscillator, signaling possible trend reversals. Alerts can be configured for when the oscillator crosses the zero line or when a trend shows signs of weakening, ensuring that traders receive timely notifications to act on emerging opportunities. These combined elements make the Standardized PSAR Oscillator a robust tool for enhancing your trading strategy with more reliable and actionable signals
Periodical Trend [BigBeluga]The Periodical Trend indicator is designed to provide a detailed analysis of market trends and volatility. It utilizes a combination of Moving Averages and volatility measures to plot trend line, highlight potential trend reversals, and indicate mean reversion opportunities. The indicator offers customizable display options, allowing traders to adjust for sensitivity, volatility bands, and price deviation visibility.
🔵 KEY FEATURES
● Periodical Trend Analysis
Uses (high + volatility) or (low - volatility) as the foundation for trend analysis with a set period.
// Condition to update the AVG array based on the selected mode
if mode == "Normal"
? bar_index == 122
: bar_index % period == 0
AVG.push(close) // Add the close price to the AVG array
// Update AVG array based on the period and price comparison
if bar_index % period == 0
if close > AVG.last() // If the current close is greater than the last stored value in AVG
AVG.push(low - vlt) // Add the low price minus volatility to the array
if close < AVG.last() // If the current close is lower than the last stored value in AVG
AVG.push(high + vlt) // Add the high price plus volatility to the array
Provides adjustable sensitivity modes ("Normal" and "Sensitive") for different market conditions.
Trend direction is visualized with dynamic color coding based on the relationship between the trend line and price.
● Volatility Bands
Displays upper and lower volatility bands derived from a moving average of price volatility (high-low).
The bands help identify potential breakout zones, overbought, or oversold conditions.
Users can toggle the visibility of the bands to suit their trading style.
● Mean Reversion Signals
Detects mean reversion opportunities when price deviates significantly from the trend line.
Includes both regular and strong mean reversion signals, marked directly on the chart.
Signals are based on oscillator crossovers, offering potential entry and exit points.
● Price Deviation Oscillator
Plots an oscillator that measures the deviation of price from the average trend line.
The oscillator is normalized using standard deviation, highlighting extreme price deviations.
Traders can choose to display the oscillator for in-depth analysis of price behavior relative to the trend.
● Dynamic Trend Coloring
The indicator colors the background on the direction of the trend.
Green indicates bullish trends, while blue indicates bearish trends.
The trend colors adapt dynamically to market conditions, providing clear visual cues for traders.
🔵 HOW TO USE
● Trend Analysis
The trend line represents the current market direction. A green trend line suggests a bullish trend, while a blue trend line indicates a bearish trend.
Use the trend line in conjunction with volatility bands to confirm potential breakouts or areas of consolidation.
● Volatility Bands
Volatility bands offer insight into potential overbought or oversold conditions.
Price exceeding these bands can signal a strong trend continuation or a possible reversal.
● Mean Reversion Strategies
Look for mean reversion signals (regular and strong) when price shows signs of reverting to the trend line after significant deviation.
Regular signals are represented by small dots, while strong signals are represented by larger circles.
These signals can be used as entry or exit points, depending on the market context.
● Price Deviation Analysis
The oscillator provides a detailed view of price deviations from the trend line.
A positive oscillator value indicates that the price is above the trend, while a negative value suggests it is below.
Use the oscillator to identify potential overbought or oversold conditions within the trend.
🔵 USER INPUTS
● Period
Defines the length of the period used for calculating the trend line. A higher period smooths out the trend, while a shorter period makes the trend line more sensitive to price changes.
● Mode
Choose between "Normal" and "Sensitive" modes for trend detection. The "Sensitive" mode responds more quickly to price changes, while the "Normal" mode offers smoother trend lines.
● Volatility Bands
Toggle the display of upper and lower volatility bands. These bands help identify potential areas of price exhaustion or continuation.
● Price Deviation
Toggle the display of the price deviation oscillator. This oscillator shows the deviation of the current price from the trend line and highlights extreme conditions.
● Mean Reversion Signals
Toggle the display of mean reversion signals. These signals highlight potential reversal points when the price deviates significantly from the trend.
● Strong Mean Reversion Signals
Toggle the display of stronger mean reversion signals, which occur at more extreme deviations from the trend.
● Width
Adjust the thickness of the trend line for better visibility on the chart.
🔵 CONCLUSION
The Periodical Trend indicator combines trend analysis, volatility bands, and mean reversion signals to provide traders with a comprehensive tool for market analysis. By offering customizable display options and dynamic trend coloring, this indicator can adapt to different trading styles and market conditions. Whether you are a trend follower or a mean reversion trader, the Periodical Trend indicator helps identify key market opportunities and potential reversals.
For optimal results, it is recommended to use this indicator alongside other technical analysis tools and within the context of a well-structured trading strategy.
Pulse Oscillator [UAlgo]The "Pulse Oscillator " is a trading tool designed to capture market momentum and trend changes by combining the strengths of multiple well-known technical indicators. By integrating the RSI (Relative Strength Index), CCI (Commodity Channel Index), and Stochastic Oscillator, this indicator provides traders with a comprehensive view of market conditions, offering both trend filtering and precise buy/sell signals. The oscillator is customizable, allowing users to fine-tune its parameters to match different trading strategies and timeframes. With its built-in smoothing techniques and level adjustments, the Pulse Oscillator aims to be a reliable tool for both trend-following and counter-trend trading strategies.
🔶 Key Features
Multi-Indicator Integration: Combines RSI, CCI, and Stochastic Oscillator to create a weighted momentum oscillator.
Why Use Multi-Indicator Integration?
Script uses Multi-Indicator Integration to combine the strengths of different technical indicators—such as RSI, CCI, and Stochastic Oscillator—into a single tool. This approach helps to reduce the weaknesses of individual indicators, providing a more comprehensive and reliable analysis of market conditions. By integrating multiple indicators, we can generate more accurate signals, filter out noise, and enhance our trading decisions.
Customizable Parameters: Allows users to adjust weights, periods, and smoothing techniques, providing flexibility to adapt the indicator to various market conditions.
Trend Filtering Option: An optional trend filter is available to enhance the accuracy of buy and sell signals, reducing the risk of false signals in choppy markets.
Dynamic Levels: The indicator dynamically calculates multiple levels of support and resistance, adjusting to market conditions with customizable decay factors and offsets.
Visual Clarity: The indicator visually represents different levels and trends with color-coded plots and fills, making it easier for traders to interpret market conditions at a glance.
Alerts: Configurable alerts for buy and sell signals, as well as trend changes, enabling traders to stay informed of key market movements without constant monitoring.
🔶 Interpreting the Indicator
Buy Signal: A buy signal is generated when the Slow Line crosses under the Fast Line during an uptrend or when the trend filter is disabled. This indicates a potential bullish reversal or continuation of an upward trend.
Sell Signal: A sell signal occurs when the Slow Line crosses above the Fast Line during a downtrend or when the trend filter is disabled, signaling a potential bearish reversal or continuation of a downward trend.
Trend Change: The indicator detects trend changes when the Fast Line shifts from increasing to decreasing or vice versa, providing early warning of possible market reversals.
Dynamic Levels: The indicator calculates upper and lower levels based on the Fast Line's values. These levels can be used to identify overbought or oversold conditions and potential areas of support or resistance.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Realized Price Oscillator [InvestorUnknown]Overview
The Realized Price Oscillator is a fundamental analysis tool designed to assess Bitcoin's price dynamics relative to its realized price. The indicator calculates various metrics using data from the realized market capitalization and total supply. It applies normalization techniques to scale values within a specified range, helping investors identify overbought or oversold conditions over the long time horizon. The oscillator also features DCA-based signals to assist in strategic market entry and exit.
Key Features
1. Normalization and Scaling:
The indicator scales values using a limit that can be adjusted for decimal precision (Limit). It allows for both positive and negative values, providing flexibility in analysis.
Decay functionality is included to progressively reduce the extreme values over time, ensuring recent data impacts the oscillator more than older data.
f_rescale(float value, float min, float max, float limit, bool negatives) =>
((limit * (negatives ? 2 : 1)) * (value - min) / (max - min)) - (negatives ? limit : 0)
2. Realized Price Oscillator Calculation:
Realized Price Oscillator is computed using logarithmic differences between the open, high, low, and close prices and the realized price. This helps in identifying how the current market price compares with the average cost basis of the Bitcoin supply.
f_realized_price_oscillator(float realized_price) =>
rpo_o = math.log(open / realized_price)
rpo_h = math.log(high / realized_price)
rpo_l = math.log(low / realized_price)
rpo_c = math.log(close / realized_price)
3. Oscillator Normalization:
The normalized oscillator calculates the range between the maximum and minimum values over time. It adjusts the oscillator values based on these bounds, considering a decay factor. This normalized range assists in consistent signal generation.
normalized_oscillator(float x, float b) =>
float oscillator = b
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
if time >= normalization_start_date
max := max * decay
min := min * decay
normalized_oscillator = f_rescale(x, min, max, lim, neg)
4. Dollar-Cost Averaging (DCA) Signals:
DCA-based signals are generated using user-defined thresholds (DCA IN and DCA OUT). The oscillator triggers buy signals when the normalized low value falls below the DCA IN threshold and sell signals when the normalized high value exceeds the DCA OUT threshold.
5. Visual Representation:
The indicator plots candlestick representations of the normalized Realized Price Oscillator values (open, high, low, close) over time, starting from a specified date (plot_start_date).
Colors are dynamically adjusted using a gradient to represent the state of the oscillator, ranging from green (buy zone) to red (sell zone). Background and bar colors also change based on DCA conditions.
How It Works
Data Sourcing: Realized price data is sourced using Bitcoin’s realized market cap (BTC_MARKETCAPREAL) and total supply (BTC_SUPPLY).
Realized Price Oscillator Metrics: Logarithmic differences between price and realized price are computed to generate Realized Price Oscillator values for open, high, low, and close.
Normalization: The indicator rescales the oscillator values based on a defined limit, adjusting for negative values if allowed. It employs a decay factor to reduce the influence of historical extremes.
Conclusion
The Realized Price Oscillator is a sophisticated tool that combines market price analysis with realized price metrics to offer a robust framework for understanding Bitcoin's valuation. By leveraging normalization techniques and DCA thresholds, it provides actionable insights for long-term investing strategies.
