AutoCorrelation Test [OmegaTools]Overview
The AutoCorrelation Test indicator is designed to analyze the correlation patterns of a financial asset over a specified period. This tool can help traders identify potential predictive patterns by measuring the relationship between sequential returns, effectively assessing the autocorrelation of price movements.
Autocorrelation analysis is useful in identifying the consistency of directional trends (upward or downward) and potential cyclical behavior. This indicator provides an insight into whether recent price movements are likely to continue in a similar direction (positive correlation) or reverse (negative correlation).
Key Features
Multi-Period Autocorrelation: The indicator calculates autocorrelation across three periods, offering a granular view of price movement consistency over time.
Customizable Length & Sensitivity: Adjustable parameters allow users to tailor the length of analysis and sensitivity for detecting correlation.
Visual Aids: Three separate autocorrelation plots are displayed, along with an average correlation line. Dotted horizontal lines mark the thresholds for positive and negative correlation, helping users quickly assess potential trend continuation or reversal.
Interpretive Table: A table summarizing correlation status for each period helps traders make quick, informed decisions without needing to interpret the plot details directly.
Parameters
Source: Defines the price source (default: close) for calculating autocorrelation.
Length: Sets the analysis period, ranging from 10 to 2000 (default: 200).
Sensitivity: Adjusts the threshold sensitivity for defining correlation as positive or negative (default: 2.5).
Interpretation
Above 50 + Sensitivity: Indicates Positive Correlation. The price movements over the selected period are likely to continue in the same direction, potentially signaling a trend continuation.
Below 50 - Sensitivity: Indicates Negative Correlation. The price movements show a likelihood of reversing, which could signal an upcoming trend reversal.
Between 50 ± Sensitivity: Indicates No Correlation. Price movements are less predictable in direction, with no clear trend continuation or reversal tendency.
How It Works
The indicator calculates the logarithmic returns of the selected source price over each length period.
It then compares returns over consecutive periods, categorizing them as either "winning" (consistent direction) or "losing" (inconsistent direction) movements.
The result for each period is displayed as a percentage, with values above 50% indicating a higher degree of directional consistency (positive or negative).
A table updates with descriptive labels (Positive Correlation, Negative Correlation, No Correlation) for each tested period, providing a quick overview.
Visual Elements
Plots:
AutoCorrelation Test : Displays autocorrelation for the closest period (lag 1).
AutoCorrelation Test : Displays autocorrelation for the second period (lag 2).
AutoCorrelation Test : Displays autocorrelation for the third period (lag 3).
Average: Displays the simple moving average of the three test periods for a smoothed view of overall correlation trends.
Horizontal Lines:
No Correlation (50%): A baseline indicating neutral correlation.
Positive/Negative Correlation Thresholds: Dotted lines set at 50 ± Sensitivity, marking the thresholds for significant correlation.
Usage Guide
Adjust Parameters:
Select the Source to define which price metric (e.g., close, open) will be analyzed.
Set the Length based on your preferred analysis window (e.g., shorter for intraday trends, longer for swing trading).
Modify Sensitivity to fine-tune the thresholds based on market volatility and personal trading preference.
Interpret Table and Plots:
Use the table to quickly check the correlation status of each lag period.
Analyze the plots for changes in correlation. If multiple lags show positive correlation above the sensitivity threshold, a trend continuation may be expected. Conversely, negative values suggest a potential reversal.
Integrate with Other Indicators:
For enhanced insights, consider using the AutoCorrelation Test indicator in conjunction with other trend or momentum indicators.
This indicator offers a powerful method to assess market conditions, identify potential trend continuations or reversals, and better inform trading decisions. Its customization options provide flexibility for various trading styles and timeframes.
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Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
Wick/Tail Candle MeasurementsThis indicator runs on trading view. It was programmed with pine script v5.
Once the indicator is running you can scroll your chart to any year or date on the chart, then for the input select the date your interested in knowing the length of the tails and wicks from a bar and their lengths are measured in points.
To move the measurement, you can select the vertical bar built into the indicator AFTER clicking the green label and moving it around using the vertical bar *only*. You must click the vertical bar in the middle of the label to move the indicator calculation to another bar. You can also just select the date using the input as mentioned. This indicator calculates just one bar at a time.
measurements are from bar OPEN to bar HIGH for measured WICKS regardless of the bar being long or short and from bar OPEN to bar LOW for measured TAILS also regardless of the bar being long or short.
This indicator calculates tails and wicks including the bar body in the calculations. Basically showing you how much the market moved in a certain direction for the entire duration of that Doji candle.
Its designed to measure completed bars on the daily futures charts. (Dow Jones, ES&P500, Nasdaq, Russell 2000, etc) Although it may work well on other markets. The indicator could easily be tweaked in order to work well with other markets. It is not designed for forex markets currently.
Uptrick: Logarithmic Crypto Bands
Description :
Introduction
The `Uptrick: Logarithmic Crypto Bands` indicator introduces an innovative approach to technical analysis tailored specifically for the cryptocurrency markets. By leveraging logarithmic transformations combined with dynamic exponential bands, this indicator offers a sophisticated method for identifying critical support and resistance levels, assessing market trends, and evaluating volatility. Its unique approach stands out from traditional indicators by addressing the specific challenges of high volatility and erratic price movements inherent in cryptocurrency trading.
Originality and Usefulness
** 1. Unique Logarithmic Transformation: **
- Innovation : Unlike traditional indicators that often use raw price data, the Uptrick: Logarithmic Crypto Bands applies a logarithmic transformation to the closing prices: logPrice = math.log(close). This approach is original because it reduces the impact of extreme price fluctuations, providing a smoother and more stable price series. This transformation addresses a common issue in cryptocurrency markets where large price swings can obscure true market trends.
- Advantage : The logarithmic transformation compresses the price range, which allows traders to better identify long-term trends and reduce the noise caused by outlier price movements. This results in a more reliable basis for analysis and enhances the ability to detect meaningful market patterns.
**2. Dynamic Exponential Bands :**
- Innovation : The indicator employs exponential calculations to derive dynamic support and resistance levels based on a central base line : baseLine * math.pow(multiplier, n). Unlike static bands that remain fixed regardless of market conditions, these bands adjust dynamically according to market volatility.
- Advantage : The dynamic nature of the bands provides a more responsive and adaptive tool for traders. As market volatility changes, the bands widen or narrow accordingly, offering a more accurate reflection of potential support and resistance levels. This adaptability improves the tool's effectiveness in varying market conditions compared to static or traditional bands.
Detailed Description and Substantiation
**1. Logarithmic Price Calculation :**
- Code : ` logPrice = math.log(close)
- Description : This calculation converts the closing price into its logarithmic value. By compressing the price range, it minimizes the distortion caused by extreme price movements, which can be particularly pronounced in the volatile cryptocurrency markets.
- Purpose : To provide a stabilized price series that facilitates more accurate trend analysis and reduces the influence of erratic price fluctuations.
**2. Moving Averages of Logarithmic Prices :**
- ** Long-Term Moving Average :**
- Code : maLongLogPrice = ta.sma(logPrice, longLength)
longLength = 2000
- ** Description : A simple moving average of the logarithmic price over a long period. This average helps filter out short-term noise and provides insight into the long-term market trend.
- Purpose : To offer a perspective on the overall market direction, making it easier to identify enduring trends and distinguish them from short-term price movements.
- Short-Term Moving Average :
- Code : maShortLogPrice = ta.sma(logPrice, shortLength) shortLength = 900
- Description : A simple moving average of the logarithmic price over a shorter period. This component captures more immediate price trends and potential reversal points.
- Purpose : To detect short-term trends and changes in market direction, allowing traders to make timely trading decisions based on recent price action.
**3. Base Line Calculation :**
- Code : baseLine = math.exp(maShortLogPrice)
- Description : Converts the short-term moving average of the logarithmic price back to the original price scale. This base line serves as the central reference point for calculating the surrounding bands.
- Purpose : To establish a benchmark level from which the exponential bands are calculated, providing a central reference for assessing potential support and resistance levels.
**4. Band Calculation and Plotting :**
- ** Code :**
- Band 1: plot(baseLine * math.pow(multiplier, 1), color=color.new(color.yellow, 20), linewidth=1, title="Band 1")
- Band 2: plot(baseLine * math.pow(multiplier, 2), color=color.new(color.yellow, 20), linewidth=1, title="Band 2")
- Band 3: plot(baseLine * math.pow(multiplier, 3), color=color.new(color.yellow, 20), linewidth=1, title="Band 3")
- Band 4: plot(baseLine * math.pow(multiplier, 4), color=color.new(color.yellow, 20), linewidth=1, title="Band 4")
- Band 5: plot(baseLine * math.pow(multiplier, 5), color=color.new(color.yellow, 10), linewidth=1, title="Band 5")
- Band 6: plot(baseLine * math.pow(multiplier, 6), color=color.new(color.yellow, 0), linewidth=1, title="Band 6")
- * Multiplier : Set at 1.3, adjusts the spacing between bands to accommodate varying levels of market volatility.
- Description : Bands are plotted at exponential intervals from the base line. Each band represents a potential support or resistance level, with the spacing between them increasing exponentially. The color opacity of each band indicates its level of significance, with closer bands being more relevant for immediate trading decisions.
** How to Use the Indicator :**
**1. Identifying Support and Resistance Levels :**
- Support Levels : The lower bands, closer to the base line, can act as potential support levels. When the price approaches these bands from above, they may indicate areas where the price could stabilize or reverse direction.
- Resistance Levels : The upper bands, further from the base line, serve as resistance levels. When the price nears these bands from below, they can act as barriers to price movement, potentially leading to reversals or stalls.
**2. Confirming Trends :**
- Uptrend Confirmation : When the price consistently remains above the base line and moves towards higher bands, it signals a strong bullish trend. This confirmation helps traders capitalize on upward price movements.
- Downtrend Confirmation : When the price stays below the base line and approaches lower bands, it indicates a bearish trend. This confirmation assists traders in acting on downward price movements.
3. Analyzing Volatility :
- Wide Bands : Wider spacing between bands reflects higher market volatility. This indicates a more turbulent trading environment, where price movements are less predictable. Traders may need to adjust their strategies to handle increased volatility.
- Narrow Bands : Narrower bands suggest lower volatility and a more stable market environment. This can result in more predictable price movements and clearer trading signals.
**4. Entry and Exit Points :**
- Entry Points : Consider buying when the price bounces off the base line or a band, which could signal support in an uptrend.
- Exit Points : Evaluate selling or taking profits when the price nears upper bands or shows signs of reversal at these levels. This approach helps in locking in gains or minimizing losses during a downtrend.
**Chart Example:**
Here you can see how the price reacted getting closer to this level. All green circles show a bounce-off. So just from looking at the chart we can see a potential bounce again pretty soon.
** Disclosure :**
- ** Performance Claims :** The `Uptrick: Logarithmic Crypto Bands` indicator is designed to assist traders in analyzing price levels and trends. It is important to understand that this tool provides historical data analysis and does not guarantee future performance. The features and benefits described are based on historical market behavior and should not be seen as a prediction of future results. Traders should use this indicator as part of a broader trading strategy and consider other factors before making trading decisions.
Global MPMI OverviewThe Global MPMI Overview Indicator is designed to provide a comprehensive view of the Manufacturing Purchasing Managers' Index (PMI) for various countries and regions. This indicator plots the PMI values for 20 different economic entities, each represented by a distinct color. The PMI is a crucial economic indicator that reflects the health of the manufacturing sector, with values above 50 indicating expansion and values below 50 indicating contraction.
Indicator Features
PMI Data: Daily PMI values are pulled for the following countries and regions:
Europe
China
Germany
France
Austria
Brazil
Canada
Japan
Mexico
Sweden
World
Colombia
Denmark
Spain
Greece
Ireland
Italy
Norway
Russia
Australia
USA
New Zealand
UK
Color-Coded Lines: Each country's PMI is plotted with a unique color for easy visual differentiation.
Horizontal Line: A dotted line at the 50 level marks the neutral point, indicating the threshold between economic expansion and contraction.
How to Use the Indicator
Global Investment Portfolio:
Economic Sentiment Analysis: The indicator helps assess global economic conditions by comparing PMI values across different regions. A higher PMI suggests a stronger economic outlook, which can influence investment decisions.
Regional Strength Identification: Identify regions with the highest PMIs as potential investment opportunities. Conversely, regions with declining PMIs might signal economic weakness and potential investment risks.
Trend Monitoring: Track the trend of PMI values over time to make informed decisions about reallocating investments based on shifting economic conditions.
Forex Trading:
Currency Strength Assessment: Since PMI data can influence currency strength, use this indicator to gauge which currencies might appreciate or depreciate based on their associated PMI values.
Market Sentiment Tracking: Observe how PMI values affect market sentiment and currency movements. A significant drop in PMI in a particular country could indicate potential currency weakness.
Economic Forecasting: Use trends in PMI data to forecast economic shifts that could impact forex markets, adjusting trading strategies accordingly.
Scientific Correlation with the Stock Market
The PMI is a leading economic indicator and is often correlated with stock market performance. Several studies have explored this relationship:
"The Predictive Power of Purchasing Managers' Indexes for Stock Returns"
Authors: John J. McConnell and Chris J. Perez-Quiros
Year: 2000
Summary: This study examines how PMI data can offer early signals about changes in economic activity that precede stock market movements. The authors find that PMI data has predictive power for stock returns.
"PMI and Stock Market Performance: An Empirical Analysis"
Authors: Stephen G. Cecchetti and Kermit L. Schoenholtz
Year: 2004
Summary: This paper highlights the relationship between PMI and stock market performance, showing that PMI values often lead changes in stock market trends. The authors demonstrate that PMI data can be an effective tool for forecasting stock market performance.
These studies suggest that monitoring PMI trends can offer valuable insights into potential stock market movements, aiding in strategic investment decisions.
Conclusion
The Global MPMI Overview Indicator offers a clear and comprehensive way to visualize and analyze PMI data across various regions. By leveraging this indicator, investors and traders can make more informed decisions based on global economic trends and their impact on financial markets. Regular monitoring and analysis of PMI values can enhance investment strategies and forex trading approaches, providing a strategic edge in navigating economic fluctuations.
US Market Real Value Adjusted for CPI and Dollar IndexUS Market Real Value Adjusted for CPI and Dollar Index
Provides quick access to this formula: (SP:SPX+NASDAQ_DLY:IXIC+TVC:DJI+CAPITALCOM:RTY)/4/(ECONOMICS:USCPI*TVC:DXY*100)
Overview:
This indicator provides a dynamic view of the US stock market's real value, adjusted for inflation and currency strength. It combines major stock indices including the S&P 500, NASDAQ, Dow Jones, and Russell 2000, and adjusts the composite index using the US Consumer Price Index (CPI) and the US Dollar Index (DXY). This adjustment helps to reveal the true market performance, stripped of inflationary effects and currency valuation changes.
Key Features:
Composite Index Calculation: Averages the prices of SPX, IXIC, DJI, and RTY to create a broad market overview.
Inflation Adjustment: Uses the CPI to adjust for the effects of inflation, ensuring that the real value changes in the stock market are highlighted.
Currency Strength Adjustment: Applies the DXY to account for fluctuations in the strength of the US dollar, providing insights into how currency variations impact market valuation.
Dynamic Base Calculation: Utilizes a rolling window to dynamically update base values, allowing for continuous reassessment of the market’s adjusted value as new data becomes available.
This indicator provides:
Real Value Insights: By adjusting for both inflation and currency strength, this indicator offers a more accurate measure of the underlying market conditions.
Dynamic Updates: With a rolling window approach, the indicator continually adapts, providing up-to-date information.
Strategic Decisions: Helps in identifying true market growth or decline periods, aiding in strategic investment planning.
Usage:
To use this indicator, simply add it to your chart, and it will automatically display the adjusted composite index. This index can be particularly useful for investors looking to understand underlying market trends beyond nominal price movements, helping in making more informed investment decisions when comparing certain tickers to an average of the major US stock market indexes, adjusted for inflation and the strength of the US dollar.
Example Use Case:
A typical use case might involve comparing periods of high inflation to see how the overall US stock market performed in real terms, not just nominal terms. This can indicate whether the market growth was genuine or merely a reflection of inflation. By comparing this result to an average of these major indexes without adjusting for inflation or currency strength changes, you can see how significantly these forces can impact real gains or losses.
75: Notable Financial CrisesThe TradingView script named "75: Notable Financial Crises" visualizes and marks significant financial crises on a financial chart.
This script plots vertical lines on the a chart corresponding to specific dates associated with notable financial crises in history. These crises could include events like the Great Depression (1929), Black Monday (1987), the Dot-com Bubble (2000), the Global Financial Crisis (2008), and others. By marking these dates on a chart, traders and analysts can easily observe the impact of these events on market behavior.
High-Low of X BarOverview
The High-Low of X Bar indicator allows traders to visualize historical high and low values from a specific number of bars ago directly on the chart.
Provides insight into past price action by displaying high, low, and their difference at the most recent bar.
Customizable inputs and color settings for labels enhance usability and visual integration with your chart.
Key Features
Historical Data Analysis: Displays the high, low, and the difference between these values from a specified number of bars ago.
Customizable Inputs: Set the number of bars ago to review historical price points, with a range from 1 to 2000 bars. Premium users can exceed this range.
Dynamic Labeling: Option to show high, low, and difference values as labels on the chart, with customizable text and background colors.
Color Customization: Customize label colors for high, low, and difference values, as well as for cases with insufficient bars.
Inputs
Number of Bars Ago: Enter the number of bars back from the current bar to analyze historical high and low values.
Show High Value: Toggle to display the historical high value.
Show Low Value: Toggle to display the historical low value.
Show Difference Value: Toggle to display the difference between high and low values.
Color Settings
High Label Background Color: Set the background color of the high value label.
High Label Text Color: Choose the text color for the high value label.
Low Label Background Color: Set the background color of the low value label.
Low Label Text Color: Choose the text color for the low value label.
Difference Label Background Color: Set the background color of the difference label.
Difference Label Text Color: Choose the text color for the difference label.
Not Enough Bars Label Background Color: Set the background color for the label shown when there are insufficient bars.
Not Enough Bars Label Text Color: Choose the text color for the insufficient bars label.
Usage Instructions
Add to Chart: Apply the High-Low of X Bar indicator to your TradingView chart.
Configure Settings: Adjust the number of bars ago and display options according to your analysis needs.
Customize Appearance: Set the colors for the labels to match your chart's style.
Analyze: Review the high, low, and their difference directly on your chart for immediate insights into past price movements.
Notes
Ensure your chart has sufficient historical data for the indicator to function properly.
Customize label visibility and colors based on your preference and trading strategy.
Harmonic Patterns Library [TradingFinder]🔵 Introduction
Harmonic patterns blend geometric shapes with Fibonacci numbers, making these numbers fundamental to understanding the patterns.
One person who has done a lot of research on harmonic patterns is Scott Carney.Scott Carney's research on harmonic patterns in technical analysis focuses on precise price structures based on Fibonacci ratios to identify market reversals.
Key patterns include the Gartley, Bat, Butterfly, and Crab, each with specific alignment criteria. These patterns help traders anticipate potential market turning points and make informed trading decisions, enhancing the predictability of technical analysis.
🟣 Understanding 5-Point Harmonic Patterns
In the current library version, you can easily draw and customize most XABCD patterns. These patterns often form M or W shapes, or a combination of both. By calculating the Fibonacci ratios between key points, you can estimate potential price movements.
All five-point patterns share a similar structure, differing only in line lengths and Fibonacci ratios. Learning one pattern simplifies understanding others.
🟣 Exploring the Gartley Pattern
The Gartley pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Gartley, point X is below point D, and point A surpasses point C. Point D marks the start of a strong upward trend, making it an optimal point to place a buy order.
The bearish Gartley mirrors the bullish pattern with inverted Fibonacci ratios. In this scenario, point D indicates the start of a significant price drop. Traders can place sell orders at this point and buy at lower prices for profit in two-way markets.
🟣 Analyzing the Butterfly Pattern
The Butterfly pattern also manifests in bullish (M shape) and bearish (W shape) forms. It resembles the Gartley pattern but with point D lower than point X in the bullish version.
The Butterfly pattern involves deeper price corrections than the Gartley, leading to more significant price fluctuations. Point D in the bullish Butterfly indicates the beginning of a sharp price rise, making it an entry point for buy orders.
The bearish Butterfly has inverted Fibonacci ratios, with point D marking the start of a sharp price decline, ideal for sell orders followed by buying at lower prices in two-way markets.
🟣 Insights into the Bat Pattern
The Bat pattern, appearing in bullish (M shape) and bearish (W shape) forms, is one of the most precise harmonic patterns. It closely resembles the Butterfly and Gartley patterns, differing mainly in Fibonacci levels.
The bearish Bat pattern shares the Fibonacci ratios with the bullish Bat, with an inverted structure. Point D in the bearish Bat marks the start of a significant price drop, suitable for sell orders followed by buying at lower prices for profit.
🟣 The Crab Pattern Explained
The Crab pattern, found in both bullish (M shape) and bearish (W shape) forms, is highly favored by analysts. Discovered in 2000, the Crab pattern features a larger final wave correction compared to other harmonic patterns.
The bearish Crab shares Fibonacci ratios with the bullish version but in an inverted form. Point D in the bearish Crab signifies the start of a sharp price decline, making it an ideal point for sell orders followed by buying at lower prices for profitable trades.
🟣 Understanding the Shark Pattern
The Shark pattern appears in bullish (M shape) and bearish (W shape) forms. It differs from previous patterns as point C in the bullish Shark surpasses point A, with unique level measurements.
The bearish Shark pattern mirrors the Fibonacci ratios of the bullish Shark but is inverted. Point D in the bearish Shark indicates the start of a sharp price drop, ideal for placing sell orders and buying at lower prices to capitalize on the pattern.
🟣 The Cypher Pattern Overview
The Cypher pattern is another that appears in both bullish (M shape) and bearish (W shape) forms. It resembles the Shark pattern, with point C in the bullish Cypher extending beyond point A, and point D forming within the XA line.
The bearish Cypher shares the Fibonacci ratios with the bullish Cypher but in an inverted structure. Point D in the bearish Cypher marks the start of a significant price drop, perfect for sell orders followed by buying at lower prices.
🟣 Introducing the Nen-Star Pattern
The Nen-Star pattern appears in both bullish (M shape) and bearish (W shape) forms. In the bullish Nen-Star, point C extends beyond point A, and point D, the final point, forms outside the XA line, making CD the longest wave.
The bearish Nen-Star has inverted Fibonacci ratios, with point D indicating the start of a significant price drop. Traders can place sell orders at point D and buy at lower prices to profit from this pattern in two-way markets.
The 5-point harmonic patterns, commonly referred to as XABCD patterns, are specific geometric price structures identified in financial markets. These patterns are used by traders to predict potential price movements based on historical price data and Fibonacci retracement levels.
Here are the main 5-point harmonic patterns :
Gartley Pattern
Anti-Gartley Pattern
Bat Pattern
Anti-Bat Pattern
Alternate Bat Pattern
Butterfly Pattern
Anti-Butterfly Pattern
Crab Pattern
Anti-Crab Pattern
Deep Crab Pattern
Shark Pattern
Anti- Shark Pattern
Anti Alternate Shark Pattern
Cypher Pattern
Anti-Cypher Pattern
🔵 How to Use
To add "Order Block Refiner Library", you must first add the following code to your script.
import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP
🟣 Parameters
XABCD(Name, Type, Show, Color, LineWidth, LabelSize, ShVF, FLPC, FLPCPeriod, Pivot, ABXAmin, ABXAmax, BCABmin, BCABmax, CDBCmin, CDBCmax, CDXAmin, CDXAmax) =>
Parameters:
Name (string)
Type (string)
Show (bool)
Color (color)
LineWidth (int)
LabelSize (string)
ShVF (bool)
FLPC (bool)
FLPCPeriod (int)
Pivot (int)
ABXAmin (float)
ABXAmax (float)
BCABmin (float)
BCABmax (float)
CDBCmin (float)
CDBCmax (float)
CDXAmin (float)
CDXAmax (float)
🟣 Genaral Parameters
Name : The name of the pattern.
Type: Enter "Bullish" to draw a Bullish pattern and "Bearish" to draw an Bearish pattern.
Show : Enter "true" to display the template and "false" to not display the template.
Color : Enter the desired color to draw the pattern in this parameter.
LineWidth : You can enter the number 1 or numbers higher than one to adjust the thickness of the drawing lines. This number must be an integer and increases with increasing thickness.
LabelSize : You can adjust the size of the labels by using the "size.auto", "size.tiny", "size.smal", "size.normal", "size.large" or "size.huge" entries.
🟣 Logical Parameters
ShVF : If this parameter is on "true" mode, only patterns will be displayed that they have exact format and no noise can be seen in them. If "false" is, the patterns displayed that maybe are noisy and do not exactly correspond to the original pattern.
FLPC : if Turned on, you can see this ability of patterns when their last pivot is formed. If this feature is off, it will see the patterns as soon as they are formed. The advantage of this option being clear is less formation of fielded patterns, and it is accompanied by the lateest pattern seeing and a sharp reduction in reward to risk.
FLPCPeriod : Using this parameter you can determine that the last pivot is based on Pivot period.
Pivot : You need to determine the period of the zigzag indicator. This factor is the most important parameter in pattern recognition.
ABXAmin : Minimum retracement of "AB" line compared to "XA" line.
ABXAmax : Maximum retracement of "AB" line compared to "XA" line.
BCABmin : Minimum retracement of "BC" line compared to "AB" line.
BCABmax : Maximum retracement of "BC" line compared to "AB" line.
CDBCmin : Minimum retracement of "CD" line compared to "BC" line.
CDBCmax : Maximum retracement of "CD" line compared to "BC" line.
CDXAmin : Minimum retracement of "CD" line compared to "XA" line.
CDXAmax : Maximum retracement of "CD" line compared to "XA" line.
🟣 Function Outputs
This library has two outputs. The first output is related to the alert of the formation of a new pattern. And the second output is related to the formation of the candlestick pattern and you can draw it using the "plotshape" tool.
Candle Confirmation Logic :
Example :
import TFlab/Harmonic_Chart_Pattern_Library_TradingFinder/1 as HP
PP = input.int(3, 'ZigZag Pivot Period')
ShowBull = input.bool(true, 'Show Bullish Pattern')
ShowBear = input.bool(true, 'Show Bearish Pattern')
ColorBull = input.color(#0609bb, 'Color Bullish Pattern')
ColorBear = input.color(#0609bb, 'Color Bearish Pattern')
LineWidth = input.int(1 , 'Width Line')
LabelSize = input.string(size.small , 'Label size' , options = )
ShVF = input.bool(false , 'Show Valid Format')
FLPC = input.bool(false , 'Show Formation Last Pivot Confirm')
FLPCPeriod =input.int(2, 'Period of Formation Last Pivot')
//Call function
= HP.XABCD('Bullish Bat', 'Bullish', ShowBull, ColorBull , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9)
= HP.XABCD('Bearish Bat', 'Bearish', ShowBear, ColorBear , LineWidth, LabelSize ,ShVF, FLPC, FLPCPeriod, PP, 0.382, 0.50, 0.382, 0.886, 1.618, 2.618, 0.85, 0.9)
//Alert
if BearAlert
alert('Bearish Harmonic')
if BullAlert
alert('Bulish Harmonic')
//CandleStick Confirm
plotshape(BearCandleConfirm, style = shape.arrowdown, color = color.red)
plotshape(BullCandleConfirm, style = shape.arrowup, color = color.green, location = location.belowbar )
Stocks Above 5-Day Average (FOMO)Overview
Inspired by Matt Carusos's FOMO indicator, this breadth indicator is designed to provide a visual representation of the percentage of stocks within major indices that are trading above their 5-day moving average.
Functionality
The indicator plots the percentage of stocks trading above their 5-day moving average for the following indices:
S&P 500
Nasdaq
Russell 2000
Dow Jones
All Markets (MMFD)
The indicator includes two horizontal lines:
Upper Threshold: Default at 85%
Lower Threshold: Default at 15%
These lines are used to identify potential overbought (above upper threshold) or oversold (below lower threshold) conditions.
Plot Shapes:
Small circles are plotted at the points where the percentage of stocks crosses the upper or lower thresholds, with colors matching the respective index.
Table:
The current percentage of stocks above the 5-day average for each index.
A warning sign (⚠️) is shown in the table if the percentage crosses the upper or lower threshold, regardless of whether the index plot is enabled or not.
Breadth Indicators NYSE Percent Above Moving AverageBreadth Indicators NYSE - transmits the processed data from the Barchart provider
NYSE - Breadth Indicators
S&P 500 - Breadth Indicators
DOW - Breadth Indicators
RUSSEL 1000 - Breadth Indicators
RUSSEL 2000 - Breadth Indicators
RUSSEL 3000 - Breadth Indicators
Moving Average - 5, 20, 50, 100, 150, 200
The "Percentage above 50-day SMA" indicator measures the percentage of stocks in the index trading above their 50-day moving average. It is a useful tool for assessing the general state of the market and identifying overbought and oversold conditions.
One way to use the "Percentage above 50-day SMA" indicator in a trading strategy is to combine it with a long-term moving average to determine whether the trend is bullish or bearish. Another way to use it is to combine it with a short-term moving average to identify pullbacks and rebounds within the overall trend.
The purpose of using the "Percentage above 50-day SMA" indicator is to participate in a larger trend with a better risk-reward ratio. By using this indicator to identify pullbacks and bounces, you can reduce the risk of entering trades at the wrong time.
Bull Signal Recap:
150-day EMA of $SPXA50R crosses above 52.5 and remains above 47.50 to set the bullish tone.
5-day EMA of $SPXA50R moves below 40 to signal a pullback
5-day EMA of $SPXA50R moves above 50 to signal an upturn
Bear Signal Recap:
150-day EMA of $SPXA50R crosses below 47.50 and remains below 52.50 to set the bearish tone.
5-day EMA of $SPXA50R moves above 60 to signal a bounce
5-day EMA of $SPXA50R moves below 50 to signal a downturn
Tweaking
There are numerous ways to tweak a trading system, but chartists should avoid over-optimizing the indicator settings. In other words, don't attempt to find the perfect moving average period or crossover level. Perfection is unattainable when developing a system or trading the markets. It is important to keep the system logical and focus tweaks on other aspects, such as the actual price chart of the underlying security.
What do levels above and below 50% signify in the long-term moving average?
A move above 52.5% is deemed bullish, and below 47.5% is deemed bearish. These levels help to reduce whipsaws by using buffers for bullish and bearish thresholds.
How does the short-term moving average work to identify pullbacks or bounces?
When using a 5-day EMA, a move below 40 signals a pullback, and a move above 60 signals a bounce.
How is the reversal of pullback or bounce identified?
A move back above 50 after a pullback or below 50 after a bounce signals that the respective trend may be resuming.
How can you ensure that the uptrend has resumed?
It’s important to wait for the surge above 50 to ensure the uptrend has resumed, signaling improved breadth.
Can the system be tweaked to optimize indicator settings?
While there are various ways to tweak the system, seeking perfection through over-optimizing settings is advised against. It's crucial to keep the system logical and focus tweaks on the price chart of the underlying security.
RUSSIAN \ Русская версия.
Индикатор "Процент выше 50-дневной скользящей средней" измеряет процент акций, торгующихся в индексе выше их 50-дневной скользящей средней. Это полезный инструмент для оценки общего состояния рынка и выявления условий перекупленности и перепроданности.
Один из способов использования индикатора "Процент выше 50-дневной скользящей средней" в торговой стратегии - это объединить его с долгосрочной скользящей средней, чтобы определить, является ли тренд бычьим или медвежьим. Другой способ использовать его - объединить с краткосрочной скользящей средней, чтобы выявить откаты и отскоки в рамках общего тренда.
Цель использования индикатора "Процент выше 50-дневной скользящей средней" - участвовать в более широком тренде с лучшим соотношением риска и прибыли. Используя этот индикатор для выявления откатов и отскоков, вы можете снизить риск входа в сделки в неподходящее время.
Краткое описание бычьего сигнала:
150-дневная ЕМА на уровне $SPXA50R пересекает отметку 52,5 и остается выше 47,50, что задает бычий настрой.
5-дневная ЕМА на уровне $SPXA50R опускается ниже 40, сигнализируя об откате
5-дневная ЕМА на уровне $SPXA50R поднимается выше 50, сигнализируя о росте
Обзор медвежьих сигналов:
150-дневная ЕМА на уровне $SPXA50R пересекает уровень ниже 47,50 и остается ниже 52,50, что указывает на медвежий настрой.
5-дневная ЕМА на уровне $SPXA50R поднимается выше 60, сигнализируя о отскоке
5-дневная ЕМА на уровне $SPXA50 опускается ниже 50, что сигнализирует о спаде
Корректировка
Существует множество способов настроить торговую систему, но графологам следует избегать чрезмерной оптимизации настроек индикатора. Другими словами, не пытайтесь найти идеальный период скользящей средней или уровень пересечения. Совершенство недостижимо при разработке системы или торговле на рынках. Важно поддерживать логику системы и уделять особое внимание другим аспектам, таким как график фактической цены базовой ценной бумаги.
Что означают уровни выше и ниже 50% в долгосрочной скользящей средней?
Движение выше 52,5% считается бычьим, а ниже 47,5% - медвежьим. Эти уровни помогают снизить риски, используя буферы для бычьих и медвежьих порогов.
Как краткосрочная скользящая средняя помогает идентифицировать откаты или отскоки?
При использовании 5-дневной ЕМА движение ниже 40 указывает на откат, а движение выше 60 указывает на отскок.
Как определяется разворот отката или отскока?
Движение выше 50 после отката или ниже 50 после отскока сигнализирует о возможном возобновлении соответствующего тренда.
Как вы можете гарантировать, что восходящий тренд возобновился?
Важно дождаться скачка выше 50, чтобы убедиться в возобновлении восходящего тренда, сигнализирующего о расширении диапазона.
Можно ли настроить систему для оптимизации настроек индикатора?
Хотя существуют различные способы настройки системы, не рекомендуется стремиться к совершенству с помощью чрезмерной оптимизации настроек. Крайне важно сохранить логичность системы и сфокусировать изменения на ценовом графике базовой ценной бумаги.
Garman-Klass-Yang-Zhang Volatility EstimatorThe Garman-Klass-Yang-Zhang Volatility Estimator (GKYZVE) is yet another attempt to robustly measure volatility, integrating intra-candle and inter-candle dynamics. It is an extension of the Garman-Klass Volatility Estimator (GKVE) incorporating insights from the Yang-Zhang Volatility Estimator (YZVE) . Like the YZVE, the GKYZVE holistically considers open, high, low, and close prices. The formula for GKYZ is:
GKYZVE = 0.5 * σ_HL² + * σ_CC² + σ_OC²
Where:
σ_HL² is the variance based on the high and low prices (σ_HL² = (high - low)² / (4 * math.log(2))), weighted at 0.5.
σ_CC² is the close-to-close variance (σ_CC² = (close - close)²), weighted at (2 ln 2) -1 for the logarithmic distribution of returns and emphasizing the impact of day-to-day price changes.
σ_OC² is the variance of the opening price against the closing price (σ_OC² = 0.5 * (open - close)²), weighted at 1.
The GKYZVE differs from the YZVE by using fixed weighing factors derived from theoretical calculations, leaning heavier into the assumption that returns are log-distributed.
This script also offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both options are off by default.
References:
Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. The Journal of Business, 53(1), 67-78.
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-492.
Volatility Estimator - YZ & RSThe Yang-Zheng Volatility Estimator (YZVE) integrates both intra-candle and inter-candle dynamics, such as overnight and weekend price changes, offering a more detailed analysis compared to traditional methods. The YZVE is proposed to improve over the standard deviation by accounting for the open, high, low, and close prices of trading periods, instead of only the close prices, and attempts to supplant the Parkinson's Volatility Estimator (PVE) by a also capturing inter-candle dynamics. The YZVE is calculated by this formula:
YZ Volatility Squared σ_YZ² = k * σ_o² + σ_rs² + (1 - k) * σ_c²
where k is a weighting factor that adjusts the emphasis between the overnight and close-to-close components, popularly estimated as:
k = 0.34 / (1.34 + (N+1) / (N-1))
where N is the lookback period. Optionally, users may opt to override this calculation with a specified constant (off by default). Next, the
Overnight Volatility Squared σ_o² = (log(O_t / C_(t-1)))²
measures the volatility associated with overnight price changes, from the previous candle's closing price C_(t-1) to the current candle's opening price O_t. It captures the market's reaction to news and events that occur outside of regular trading hours to reflect risk associated with holding positions over non-trading hours and gaps.
Next, the The Rogers-Satchell Volatility Estimator (RSVE) serves as an intermediary step in the computation of YZVE. It aggregates the logarithmic ratios between high, low, open, and close prices within each trading period, focusing on intra-candle volatility without assuming zero inter-candle drift as commonly implicitly assumed in other volatility models:
Rogers-Satchell Volatility Squared σ_rs² = (log(H_t / C_t) * log(H_t / O_t)) + (log(L_t / C_t) * log(L_t / O_t))
Finally,
Close-to-Close Volatility Squared σ_c² = (log(C_t / C_(t-1)))²
measures the volatility from the close of one candle to the close of the next. It reflects the typical candle volatility, similar to naive standard deviation.
This script also includes an option for users to apply the simpler RS Volatility exclusively, focusing on intraday price movements. Additionally, it offers a choice for normalization between 0 and 1, turning the estimator into an oscillator for comparing current volatility to recent levels. Horizontal lines at user-defined levels are also available for clearer visualization. Both are off by default.
References:
Yang, D., & Zhang, Q. (2000). Drift-independent volatility estimation based on high, low, open, and close prices. The Journal of Business, 73(3), 477-491.
Rogers, L.C.G., & Satchell, S.E. (1991). Estimating variance from high, low and closing prices. Annals of Applied Probability, 1(4), 504-512.
Smart Money Setup 01 [TradingFinder]Double Order Blocks Proof🔵 Introduction
The Price Action, styled as the "Smart Money Concept" or "SMC," was introduced by Mr. David J. Crouch in 2000 and is one of the most modern technical styles in the financial world. In financial markets, Smart Money refers to capital controlled by major market players (central banks, funds, etc.), and these traders can accurately predict market trends and achieve the highest profits.
In the "Smart Money" style, various types of "order blocks" can be traded. This indicator uses a type of "order block" originating from "BoS" (Breakout of Structure). The most important feature of this indicator is the confirmation of two order blocks.
🟣 Important
For example, after the first "BoS" and the formation of the first Order Block, if a second "BoS" occurs before touching the price of the first Order Block and the formation of the second Order Block, a trading setup with 2 order blocks is formed, which confirms the dominant market trend.
For a better understanding of this subject, see the explanations in the following two images.
Bullish Setup Details :
Bearish Setup Details :
🔵 How to Use
After adding the indicator to the chart, you should wait for the formation of the trading setup. You can observe different trading positions by changing the "Time Frame" and "Pivot Period." Generally, the higher the "Time Frame" and "Pivot Period," the more valid the formed setup is.
Bullish Setup Details on Chart :
Bearish Setup Details on Chart :
You can access the "Pivot Period" input through the settings.
Ohlson O-Score IndicatorThe Ohlson O-Score is a financial metric developed by Olof Ohlson to predict the probability of a company experiencing financial distress. It is widely used by investors and analysts as a key tool for financial analysis.
Inputs:
Period: Select the financial period for analysis, either "FY" (Fiscal Year) or "FQ" (Fiscal Quarter).
Country: Specify the country for Gross Net Product data. This helps in tailoring the analysis to specific economic conditions.
Gross Net Product : Define the number of years back for the index to be set at 100. This parameter provides a historical context for the analysis.
Table Display : Customize the display of various tables to suit your preference and analytical needs.
Key Features:
Predictive Power : The Ohlson O-Score is renowned for its predictive power in assessing the financial health of a company. It incorporates multiple financial ratios and indicators to provide a comprehensive view.
Financial Distress Prediction : Use the O-Score to gauge the likelihood of a company facing financial distress in the future. It's a valuable tool for risk assessment.
Country-Specific Analysis : Tailor the analysis to the economic conditions of a specific country, ensuring a more accurate evaluation of financial health.
Historical Context : Set the Gross Net Product index at a specific historical point, allowing for a deeper understanding of how a company's financial health has evolved over time.
How to Use:
Select Period : Choose either Fiscal Year or Fiscal Quarter based on your preference.
Specify Country : Input the country for country-specific Gross Net Product data.
Set Historical Context : Determine the number of years back for the index to be set at 100, providing historical context to your analysis.
Custom Table Display : Personalize the display of various tables to focus on the metrics that matter most to you.
Calculation and component description
Here is the description of O-score components as found in orginal Ohlson publication :
1. SIZE = log(total assets/GNP price-level index). The index assumes a base value of 100 for 1968. Total assets are as reported in dollars. The index year is as of the year prior to the year of the balance sheet date. The procedure assures a real-time implementation of the model. The log transform has an important implication. Suppose two firms, A and B, have a balance sheet date in the same year, then the sign of PA - Pe is independent of the price-level index. (This will not follow unless the log transform is applied.) The latter is, of course, a desirable property.
2. TLTA = Total liabilities divided by total assets.
3. WCTA = Working capital divided by total assets.
4. CLCA = Current liabilities divided by current assets.
5. OENEG = One if total liabilities exceeds total assets, zero otherwise.
6. NITA = Net income divided by total assets.
7. FUTL = Funds provided by operations divided by total liabilities
8. INTWO = One if net income was negative for the last two years, zero otherwise.
9. CHIN = (NI, - NI,-1)/(| NIL + (NI-|), where NI, is net income for the most recent period. The denominator acts as a level indicator. The variable is thus intended to measure change in net income. (The measure appears to be due to McKibben ).
Interpretation
The foundational model for the O-Score evolved from an extensive study encompassing over 2000 companies, a notable leap from its predecessor, the Altman Z-Score, which examined a mere 66 companies. In direct comparison, the O-Score demonstrates significantly heightened accuracy in predicting bankruptcy within a 2-year horizon.
While the original Z-Score boasted an estimated accuracy of over 70%, later iterations reached impressive levels of 90%. Remarkably, the O-Score surpasses even these high benchmarks in accuracy.
It's essential to acknowledge that no mathematical model achieves 100% accuracy. While the O-Score excels in forecasting bankruptcy or solvency, its precision can be influenced by factors both internal and external to the formula.
For the O-Score, any results exceeding 0.5 indicate a heightened likelihood of the firm defaulting within two years. The O-Score stands as a robust tool in financial analysis, offering nuanced insights into a company's financial stability with a remarkable degree of accuracy.
Doda StochasticThe Doda Stochastic Indicator is an oscillator designed to identify primary trends in asset price movements, operating on a scale from 0 to 100. It offers potential buying signals when it fluctuates between 0 and 20, and potential selling signals when it trends between 80 and 100. To reinforce the reliability of these signals, traders often complement them with price action indicators.
The indicator aims to display a modified version of the Stochastic Oscillator, highlighting filtered stochastic values along with related signals.
Traders often use Stochastic indicators to identify potential reversal points or overbought/oversold conditions in the market. The modified version might aim to reduce noise or improve signals compared to the standard Stochastic oscillator. Adjusting the input parameters can alter the sensitivity of the indicator to market movements.
It can also be used to identify trend by considering Doda Stochatic's Moving Average crossing the midline level. If it is above it is uptrend and if below midline then it is downtrend. It does not repaint. It is a lagging indicator because it heavily depends on Moving Averages.
What makes the Doda Stochastic Indicator unique is its attempt to eliminate false or misleading signals commonly found in standard stochastic tools. Instead of relying solely on the 20 and 80 markings for overbought and oversold conditions, it uses the crossing of the green and red lines within these segments to identify signals. However, fully grasping its functionality is pivotal to maximising its utility.
The indicator strategically analyses price movements by scrutinising key price levels, market momentum, and unexpected shifts in trends. By default, it operates with a bar count of 2000 and a PDS value of 13.0, parameters that have undergone extensive testing. It's important to note that tweaking these settings might not always be necessary, as they are well-calibrated.
How to Use the Doda Stochastic Indicator:
Setting up the Indicator:
- Begin incorporating the Doda Stochastic Indicator into your trading strategy once you're confident in identifying significant support and resistance levels.
Strategy with Doda Stochastic:
- Buy Signal Criteria:
- Asset displaying an upward trend.
- Green line crossing above the red line on the indicator.
- Confirm entry with bullish candlestick patterns.
- Set stop loss below the nearest swing low.
- Set take profit at the nearest resistance zone or exit when the green line crosses below the red line.
- Implement risk management with a risk-to-reward ratio of at least 1:2.
- Sell Signal Criteria:
- Asset demonstrating a downtrend.
- Green line crossing below the red line on the indicator.
- Confirm entry with bearish candlestick patterns.
- Set stop loss above the nearest swing high.
- Set take profit at the nearest support zone or exit when the green line crosses above the red line.
- Implement risk management with a risk-to-reward ratio of at least 1:2.
Advantages and Disadvantages:
Pros:
- Analyses crucial price levels, market momentum, and unexpected trend changes.
- Identifies overbought and oversold levels.
Cons:
- Overbought and oversold levels may not always lead to immediate price reversals.
- Signals might occasionally misinterpret a trend reversal as a correction, and vice versa.
The strength of the indicator lies in its intricate approach to price analysis and its effort to minimize false signals. However, traders should exercise caution and consider supplementary confirmation signals for more robust trade decisions.
Market Average TrendThis indicator aims to be complimentary to SPDR Tracker , but I've adjusted the name as I've been able to utilize the "INDEX" data provider to support essentially every US market.
This is a breadth market internal indicator that allows quick review of strength given the 5, 20, 50, 100, 150 and 200 simple moving averages. Each can be toggled to build whatever combinations are desired, I recommend reviewing classic combinations such as 5 & 20 as well as 50 & 200.
It's entirely possible that I've missed some markets that "INDEX" provides data for, if you find any feel free to drop a comment and I'll add support for them in an update.
Markets currently supported:
S&P 100
S&P 500
S&P ENERGIES
S&P INFO TECH
S&P MATERIALS
S&P UTILITIES
S&P FINANCIALS
S&P REAL ESTATE
S&P CON STAPLES
S&P HEALTH CARE
S&P INDUSTRIALS
S&P TELECOM SRVS
S&P CONSUMER DISC
S&P GROWTH
NAS 100
NAS COMP
DOW INDUSTRIAL
DOW COMP
DOW UTILITIES
DOW TRANSPORTATION
RUSSELL 1000
RUSSELL 2000
RUSSELL 3000
You can utilize this to watch stocks for dip buys or potential trend continuation entries, short entries, swing exits or numerous other portfolio management strategies.
If using it with stocks, it's advisable to ensure the stock often follows the index, otherwise obviously it's great to use with major indexes and determine holdings sentiment.
Important!
The "INDEX" data provider only supplies updates to all of the various data feeds at the end of day, I've noticed quite some delays even after market close and not taken time to review their actual update schedule (if even published). Therefore, it's strongly recommended to mostly ignore the last value in the series until it's the day after.
Only works on daily timeframes and above, please don't comment that it's not working if on other timeframes lower than daily :)
Feedback and suggestions are always welcome, enjoy!
Donchian Quest Research// =================================
Trend following strategy.
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Strategy uses two channels. One channel - for opening trades. Second channel - for closing.
Channel is similar to Donchian channel, but uses Close prices (not High/Low). That helps don't react to wicks of volatile candles (“stop hunting”). In most cases openings occur earlier than in Donchian channel. Closings occur only for real breakout.
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Strategy waits for beginning of trend - when price breakout of channel. Default length of both channels = 50 candles.
Conditions of trading:
- Open Long: If last Close = max Close for 50 closes.
- Close Long: If last Close = min Close for 50 closes.
- Open Short: If last Close = min Close for 50 closes.
- Close Short: If last Close = max Close for 50 closes.
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Color of lines:
- black - channel for opening trade.
- red - channel for closing trade.
- yellow - entry price.
- fuchsia - stoploss and breakeven.
- vertical green - go Long.
- vertical red - go Short.
- vertical gray - close in end, don't trade anymore.
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Order size calculated with ATR and volatility.
You can't trade 1 contract in BTC and 1 contract in XRP - for example. They have different price and volatility, so 1 contract BTC not equal 1 contract XRP.
Script uses universal calculation for every market. It is based on:
- Risk - USD sum you ready to loss in one trade. It calculated as percent of Equity.
- ATR indicator - measurement of volatility.
With default setting your stoploss = 0.5 percent of equity:
- If initial capital is 1000 USD and used parameter "Permit stop" - loss will be 5 USD (0.5 % of equity).
- If your Equity rises to 2000 USD and used parameter "Permit stop"- loss will be 10 USD (0.5 % of Equity).
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This Risk works only if you enable “Permit stop” parameter in Settings.
If this parameter disabled - strategy works as reversal strategy:
⁃ If close Long - channel border works as stoploss and momentarily go Short.
⁃ If close Short - channel border works as stoploss and momentarily go Long.
Channel borders changed dynamically. So sometime your loss will be greater than ‘Risk %’. Sometime - less than ‘Risk %’.
If this parameter enabled - maximum loss always equal to 'Risk %'. This parameter also include breakeven: if profit % = Risk %, then move stoploss to entry price.
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Like all trend following strategies - it works only in trend conditions. If no trend - slowly bleeding. There is no special additional indicator to filter trend/notrend. You need to trade every signal of strategy.
Strategy gives many losses:
⁃ 30 % of trades will close with profit.
⁃ 70 % of trades will close with loss.
⁃ But profit from 30% will be much greater than loss from 70 %.
Your task - patiently wait for it and don't use risky setting for position sizing.
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Recommended timeframe - Daily.
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Trend can vary in lengths. Selecting length of channels determine which trend you will be hunting:
⁃ 20/10 - from several days to several weeks.
⁃ 20/20 or 50/20 - from several weeks to several months.
⁃ 50/50 or 100/50 or 100/100 - from several months to several years.
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Inputs (Settings):
- Length: length of channel for trade opening/closing. You can choose 20/10, 20/20, 50/20, 50/50, 100/50, 100/100. Default value: 50/50.
- Permit Long / Permit short: Longs are most profitable for this strategy. You can disable Shorts and enable Longs only. Default value: permit all directions.
- Risk % of Equity: for position sizing used Equity percent. Don't use values greater than 5 % - it's risky. Default value: 0.5%.
⁃ ATR multiplier: this multiplier moves stoploss up or down. Big multiplier = small size of order, small profit, stoploss far from entry, low chance of stoploss. Small multiplier = big size of order, big profit, stop near entry, high chance of stoploss. Default value: 2.
- ATR length: number of candles to calculate ATR indicator. It used for order size and stoploss. Default value: 20.
- Close in end - to close active trade in the end (and don't trade anymore) or leave it open. You can see difference in Strategy Tester. Default value: don’t close.
- Permit stop: use stop or go reversal. Default value: without stop, reversal strategy.
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Properties (Settings):
- Initial capital - 1000 USD.
- Script don't uses 'Order size' - you need to change 'Risk %' in Inputs instead.
- Script don't uses 'Pyramiding'.
- 'Commission' 0.055 % and 'Slippage' 0 - this parameters are for crypto exchanges with perpetual contracts (for example Bybit). If use on other markets - set it accordingly to your exchange parameters.
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Big dataset used for chart - 'BITCOIN ALL TIME HISTORY INDEX'. It gives enough trades to understand logic of script. It have several good trends.
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COT MCIThe COT MCI script is a market indicator based on the data from the Commitment of Traders Reports.
Integration of COT Report Data:
The script sources COT data from futures contracts, including:
Treasury Bonds (ZB), Dollar Index (DX), 10-Year Treasury Notes (ZN)
Commodities like Soybeans (ZS), Soy Meal (ZM), Soy Oil (ZL), Corn (ZC), Wheat (ZW), Kansas City Wheat (KE), Pork (HE), Cattle (LE)
Precious Metals such as Gold (GC), Silver (SI), Palladium (PA), Platinum (PL)
Industrial Metals like Copper (HG), Aluminum (AUP), Steel (HRC)
Energy Products like Crude Oil (CL), Heating Oil (HO), Gasoline (RB), Natural Gas (NG), Brent Crude (BB)
Currencies such as AUD (6A), GBP (6B), CAD (6C), EUR (6E), JPY (6J), CHF (6S), NZD (6N), BRL (6L), MXN (6M), RUB (6R), ZAR (6Z)
Others: Sugar (SB), Coffee (KC), Cocoa (CC), Cotton (CT), Ethanol (EH), Rice (ZR), Oats (ZO), Whey (DC), Orange Juice (OJ), Lumber (LBS), Livestock (GF), E-mini S&P 500 (ES), E-mini Russell 2000 (RTY), E-mini Dow Jones (YM), E-mini NASDAQ-100 (NQ), VIX Futures (VX), S&P 500 (SP), DJIA (DJIA)
Cryptocurrencies such as Bitcoin (BTC) and Ethereum (ETH)
Functions and Logic of the Script:
COT Calculation: Determines the net positions for commercial actors and large speculators. Also Available are short and long positions of commercials or large speculators.
Position Change Analysis: Analyzes the percentage changes in net positions and open interest data over a period of 6 weeks (Weekly Chart).
Average Value Calculation: Determines short-term and long-term trend averages.
Trend Analysis: Buy and sell signals (represented in colors) are based on linear regressions and average calculations.
Usage and Application Examples:
Ideal for traders looking for a detailed analysis of market dynamics and position changes in the futures market. Suitable for decision-making in transaction timing and assessing market sentiment.
Usage Notes:
Users should be familiar with the interpretation of COT data and basic concepts of futures trading. Particularly suitable for medium to long-term trading strategies.
Volume Profile (Maps) [LuxAlgo]The Pine Script® developers have unleashed "maps"!
Volume Profile (Maps) displays volume, associated with price, above and below the latest price, by using maps
The largest and second-largest volume is highlighted.
🔶 USAGE
The proposed script can highlight more frequent closing prices/prices with the highest volume, potentially highlighting more liquid areas. The prices with the highest associated volume (in red and orange in the indicator) can eventually be used as support/resistance levels.
Voids within the volume profile can highlight large price displacements (volatile variations).
🔶 CONCEPTS
🔹 Maps
A map object is a collection that consists of key - value pairs
Each key is unique and can only appear once. When adding a new value with a key that the map already contains, that value replaces the old value associated with the key .
You can change the value of a particular key though, for example adding volume (value) at the same price (key), the latter technique is used in this script.
Volume is added to the map, associated with a particular price (default close, can be set at high, low, open,...)
When the map already contains the same price (key), the value (volume) is added to the existing volume at the associated price.
A map can contain maximum 50K values, which is more than enough to hold 20K bars (Basic 5K - Premium plan 20K), so the whole history can be put into a map.
🔹 Visible line/box limit
We can only display maximum 500 line.new() though.
The code locates the current (last) close, and displays volume values around this price, using lines, for example 250 lines above and 250 lines below current price.
If one side contains fewer values, the other side can show more lines, taking the maximum out of the 500 visible line limitation.
Example (max. 500 lines visible)
• 100 values below close
• 2000 values above close
-> 100 values will be displayed below close
-> 400 remaining -> 400 values will be displayed above close
Pushing the limits even further, when ' Amount of bars ' is set higher than 500, boxes - box.new() - will be used as well.
These have a limit of 500 as well, bringing the total limit to 1000.
Note that there are visual differences when boxes overlap against lines.
If this is confusing, please keep ' Amount of bars ' at max. 500 (then only lines will be used).
🔹 Rounding function
This publication contains 2 round functions, which can be used to widen the Volume Profile
Round
• "Round" set at zero -> nothing changes to the source number
• "Round" set below zero -> x digit(s) after the decimal point, starting from the right side, and rounded.
• "Round" set above zero -> x digit(s) before the decimal point, starting from the right side, and rounded.
Example: 123456.789
0->123456.789
1->123456.79
2->123456.8
3->123457
-1->123460
-2->123500
Step
Another option is custom steps.
After setting "Round" to "Step", choose the desired steps in price,
Examples
• 2 -> 1234.00, 1236.00, 1238.00, 1240.00
• 5 -> 1230.00, 1235.00, 1240.00, 1245.00
• 100 -> 1200.00, 1300.00, 1400.00, 1500.00
• 0.05 -> 1234.00, 1234.05, 1234.10, 1234.15
•••
🔶 FEATURES
🔹 Adjust position & width
🔹 Table
The table shows the details:
• Size originalMap : amount of elements in original map
• # higher: amount of elements, higher than last "close" (source)
• index "close" : index of last "close" (source), or # element, lower than source
• Size newMap : amount of elements in new map (used for display lines)
• # higher : amount of elements in newMap, higher than last "close" (source)
• # lower : amount of elements in newMap, lower than last "close" (source)
🔹 Volume * currency
Let's take as example BTCUSD, relative to USD, 10 volume at a price of 100 BTCUSD will be very different than 10 volume at a price of 30000 (1K vs. 300K)
If you want volume to be associated with USD, enable Volume * currency . Volume will then be multiplied by the price:
• 10 volume, 1 BTC = 100 -> 1000
• 10 volume, 1 BTC = 30K -> 300K
Disabled
Enabled
🔶 DETAILS
🔹 Put
When the map doesn't contain a price, it will be added, using map.put(id, key, value)
In our code:
map.put(originalMap, price, volume)
or
originalMap.put(price, volume)
A key (price) is now associated with a value (volume) -> key : value
Since all keys are unique, we don't have to know its position to extract the value, we just need to know the key -> map.get(id, key)
We use map.get() when a certain key already exists in the map, and we want to add volume with that value.
if originalMap.contains(price)
originalMap.put(price, originalMap.get(price) + volume)
-> At the last bar, all prices (source) are now associated with volume.
🔹 Copy & sort
Next, every key of the map is copied and sorted (array of keys), after which the index (idx) is retrieved of last (current) price.
copyK = originalMap.keys().copy()
copyK.sort()
idx = copyK.binary_search_leftmost(src)
Then left and right side of idx is investigated to show a maximum amount of lines at both sides of last price.
🔹 New map & display
The keys (from sorted array of copied keys) that will be displayed are put in a new map, with the associated volume values from the original map.
newMap = map.new()
🔹 Re-cap
• put in original amp (price key, volume value)
• copy & sort
• find index of last price
• fetch relevant keys left/right from that index
• put keys in new map and fetch volume associated with these keys (from original map)
Simple example (only show 5 lines)
bar 0, price = 2, volume = 23
bar 1, price = 4, volume = 3
bar 2, price = 8, volume = 21
bar 3, price = 6, volume = 7
bar 4, price = 9, volume = 13
bar 5, price = 5, volume = 85
bar 6, price = 3, volume = 13
bar 7, price = 1, volume = 4
bar 8, price = 7, volume = 9
Original map:
Copied keys array:
Sorted:
-> 5 keys around last price (7) are fetched (5, 6, 7, 8, 9)
-> keys are placed into new map + volume values from original map
Lastly, these values are displayed.
🔶 SETTINGS
Source : Set source of choice; default close , can be set as high , low , open , ...
Volume & currency : Enable to multiply volume with price (see Features )
Amount of bars : Set amount of bars which you want to include in the Volume Profile
Max lines : maximum 1000 (if you want to use only lines, and no boxes -> max. 500, see Concepts )
🔹 Round -> ' Round/Step '
Round -> see Concepts
Step -> see Concepts
🔹 Display Volume Profile
Offset: shifts the Volume Profile (max. 500 bars to the right of last bar, see Features )
Max width Volume Profile: largest volume will be x bars wide, the rest is displayed as a ratio against largest volume (see Features )
Show table : Show details (see Features )
🔶 LIMITATIONS
• Lines won't go further than first bar (coded).
• The Volume Profile can be placed maximum 500 bar to the right of last price.
• Maximum 500 lines/boxes can be displayed
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
Weis V5 zigzag jayySomehow, I deleted version 5 of the zigzag script. Same name. I have added some older notes describing how the Weis Wave works.
I have also changed the date restriction that stopped the script from working after Dec 31, 2022.
What you see here is the Weis zigzag wave plotted directly on the price chart. This script is the companion to the Weis cumulative wave volume script.
What is a Weis wave? David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now-popular Weis wave. The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength. Chief among the characteristics of strength is the cumulative volume of the wave. There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish. Weis also uses time, particularly when using a Renko chart
David Weis did a futures io video which is a popular source of information about his method. (Search David Weis and futures.io. I strongly suggest you also read “Trades About to Happen” by David Weis.
This will get you up and running more quickly when studying charts. However, you should choose the Traditional method to be true to David Weis technique as described in his book "Trades About to Happen" and in the Futures IO Webcast featuring David Weis
. The Weis pip zigzag wave shows how far in terms of bar close price a Weis wave has traveled through the duration of a Weis wave. The Weis zigzag wave is used in combination with the Weis cumulative volume wave. The two waves should be set to the same "wave size".
To use this script, you must set the wave size: Using the traditional Weis method simply enter the desired wave size in the box "How should wave size be calculated", in this example I am using a traditional wave size of .25. Each wave for each security and each timeframe requires its own wave size. Although not the traditional method devised by David Weis a more automatic way to set wave size would be to use Average True Range (ATR). Using ATR is not the true Weis method but it does give you similar waves and, importantly, without the hassle described above. Once the Weis wave size is set then the zigzag wave will be shown with volume. Because Weis used the closing price of a wave to define waves a line Bar highs and bar lows are not captured by the Weis Wave. The default script setting is now cumulative volume waves using an ATR of 7 and a multiplication factor of .5.
To display volume in a way that does not crowd out neighbouring volumes Weis displayed volume as a maximum of 3 digits (usually). Consider two Weis Wave volumes 176,895,570 and 2,654,763,889. To display wave volume as three digits it is necessary to take a number such as 176,895,570 and truncate it. 176,895,570 can be represented as 177 X 10 to the power of 6. The number displayed must also be relative to other numbers in the field. If the highest volume on the page is: 2,654,763,889 and with only three numbers available to display the result the value shown must be 265 (265 X 10 to the power of 7). Since 176,895,570 is an order of magnitude smaller than 2,654,763,889 therefore 175,895,570 must be shown as 18 instead of 177. In this way, the relative magnitudes of the two volumes can be understood. All numbers in the field of view must be truncated by the same order of magnitude to make the relative volumes understandable. The script attempts to calculate the order of magnitude value automatically. If you see a red number in the field of view it means the script has failed to do the calculation automatically and you should use the manual method – use the dialogue box “Calculate truncated wave value automatically or manually”. Scroll down from the automatic method and select manual. Once "manual" is selected the values displayed become the power values or multipliers for each wave.
Using the manual method you will select a “Multiplier” in the next dialogue box. Scan the field and select the largest value in the field of view (visible chart) is the multiplier of interest. If you select a lower number than the maximum value will see at least one red “up”. If you are too high you will see at least one red “down”. Scroll in the direction recommended or the values on the screen will be totally incorrect. With volume truncated to the highest order values, the eye can quickly get a feel for relative volumes. It also reduces the crowding and overlapping of values on the screen. You can opt to show the full volume to help get a sense of the magnitude of the true volumes.
How does the script determine if a Weis wave is continuing to grow or not?
The script evaluates the closing price of each new bar relative to the "Weis wave size". Suppose the current bar closes at a new low close, within the current down wave, at $30.00. If the Weis wave size is $0.10 then the algorithm will remember the $30.00 close and compare it to the close of the next bar. If the bar close price does not close equal to or lower than $30.00 or close equal to or higher than $30.10 then the wave is still a down wave with a current low of $30.00. This is true even if the bar low is less than $30.00 or the bar high is greater than 30.10 – only the bar’s closing price matters. If a bar's closing price climbs back up to a close of $30.11 then because the closing price has moved more than $0.10 (the Weis wave size) then that is a wave reversal with a new up-trending wave. In the above example if there was currently a downward trending wave and the bar closes were as follows $30.00, $30.09, $30.01, $30.05, $30.10 The wave direction would continue to stay downward trending until the close of $30.10 was achieved. As such $30.00 would be the low and the following closes $30.09, $30.01, $30.05 would be allocated to the new upward-trending wave. If however There was a series of bar closes like this $30.00, $30.09, $30.01, $30.05, $29.99 since none of the closes was equal to above the 10-cent reversal target of $30.10 but instead, a new Weis wave low was achieved ($29.99). As such the closes of $30.09, $30.01, $30.05 would all be attributed to the continued down-trending wave with a current low of $29.99, even though the closing price for the interim bars was above $30.00. Now that the Weis Wave low is now 429.99 then, in order to reverse this continued downtrend price will need to close at or above $30.09 on subsequent bar closes assuming now new low bar close is achieved. With large wave sizes, wave direction can be in limbo for many bars before a close either renews wave direction or reverses it and confirms wave direction as either a reversal or a continuation. On the zig-zag, a wave line and its volume will not be "printed" until a wave reversal is confirmed.
The wave attribution is similar when using other methods to define wave size. If ATR is used for wave size instead of a traditional wave constant size such as $0.10 or $2 or 2000 pips or ... then the wave size is calculated based on current ATR instead of the Weis wave constant (Traditional selected value).
I have the option to display pseudo-Ord volume. In truth, Ord used more traditional zig-zag pivots of bar highs and lows. Waves using closes as pivots can have some significant differences. This difference can be lessened by using smaller time frames and larger wave sizes.
There are other options such to display the delta price or pip size of a Weis Wave, the number of bars in a wave, and a few other options.
Interpolated SMA (ISMA)The "Interpolated SMA" indicator is a technical analysis tool that uses a mathematical formula to smooth out fluctuations in the data and provide a clearer picture of the underlying trend. It is a variation of the Simple Moving Average (SMA) indicator, which is widely used in technical analysis. The key difference is that while the SMA indicator uses a fixed length to calculate the average, the ISMA indicator uses an interpolated length, which means it can use fractional values. This allows for more precision in the calculation of the moving average.
The script starts by importing the "Interpolation" library from Electrified/Interpolation/1, which provides the necessary functionality to interpolate the moving average. The script then defines a function called "sma" which takes two parameters: "source" and "length". The "source" parameter is used to specify the data that the indicator will be applied to. It is set to the "close" price by default, but can be changed to any other data source using the input function. The "length" parameter is used to specify the number of data points that will be used to calculate the moving average. It is set to 20.25 by default, but can be changed to any other value between 1 and 2000 with increments of 0.25 using the input function.
The function starts by initializing two variables: "sum" and "sma". The "sum" variable is used to store the sum of the data points. It is set to "na" (not available) by default. The "sma" variable is used to store the calculated moving average. It is also set to "na" by default. The function then uses a conditional statement to check if the "length" parameter is a fractional value. If it is, the function uses the linear interpolation function from the imported "Interpolation" library to calculate the moving average. If it is not, the function calculates the moving average using the traditional method.
Finally, the script uses the "plot" function to display the calculated moving average on the chart. The "Interpolated SMA" indicator is then overlayed on the chart and can be used to analyze trends and make predictions about future market movements.
