VIX Dashboard [NariCapitalTrading]Overview
This VIX Dashboard is designed to provide traders with a quick visual reference into the current volatility and trend direction of the market as measured by CBOE VIX. It uses statistical measures and indicators including Rate of Change (ROC), Average True Range (ATR), and simple moving averages (SMA) to analyze the VIX.
Components
ATR Period : The ATR Period is used to calculate the Average True Range. The default period set is 24.
Trend Period : This period is used for the Simple Moving Average (SMA) to determine the trend direction. The default is set to 48.
Speed Up/Down Thresholds : These thresholds are used to determine significant increases or decreases in the VIX’s rate of change, signaling potential market volatility spikes or drops. These are customizable in the input section.
VIX Data : The script fetches the closing price of the VIX from a specified source (CBOE:VIX) with a 60-minute interval.
Rate of Change (ROC) : The ROC measures the percentage change in price from one period to the next. The script uses a default period of 20. The period can be customized in the input section.
VIX ATR : This is the Average True Range of the VIX, indicating the daily volatility level.
Trend Direction : Determined by comparing the VIX data with its SMA, indicating if the trend is up, down, or neutral. The trend direction can be customized in the input section.
Dashboard Display : The script creates a table on the chart that dynamically updates with the VIX ROC, ATR, trend direction, and speed.
Calculations
VIX ROC : Calculated as * 100
VIX ATR : ATR is calculated using the 'atrPeriod' and is a measure of volatility.
Trend Direction : Compared against the SMA over 'trendPeriod'.
Trader Interpretation
High ROC Value : Indicates increasing volatility, which could signal a market turn or increased uncertainty.
High ATR Value : Suggests high volatility, often seen in turbulent market conditions.
Trend Direction : Helps in understanding the overall market sentiment and trend.
Speed Indicators : “Mooning” suggests rapid increase in volatility, whereas “Cratering” indicates a rapid decrease.
The interpretation of these indicators should be combined with other market analysis tools for best results.
Komut dosyalarını "市值60亿的股票" için ara
RSI Graphique and Dashboard MTFMTF RSI Indicator - User Guide
Introduction:
The MTF RSI (Multi-Timeframe Relative Strength Index) Pine Script is designed to provide traders with a comprehensive view of the RSI (Relative Strength Index) across multiple timeframes. The script includes a primary chart displaying RSI values and a dashboard summarizing RSI trends for different time intervals.
Installation:
Copy the provided Pine Script.
Open the TradingView platform.
Create a new script.
Paste the copied code into the script editor.
Save and apply the script to your chart.
Primary Chart:
The primary chart displays RSI values for the selected timeframe (5, 15, 60, 240, 1440 minutes).
different color lines represent RSI values for different timeframes.
Overbought and Oversold Levels:
Overbought levels (70) are marked in red, while oversold levels (30) are marked in blue for different timeframes.
Dashboard:
The dashboard is a quick reference for RSI trends across multiple timeframes.
Each row represents a timeframe with corresponding RSI trend information.
Arrows (▲ for bullish, ▼ for bearish) indicate the current RSI trend.
Arrow colors represent the trend: blue for bullish, red for bearish.
Settings:
Users can customize the RSI length, background color, and other parameters.
The background color of the dashboard can be adjusted for light or dark themes.
Interpretation:
Bullish Trend: ▲ arrow and blue color.
Bearish Trend: ▼ arrow and red color.
RSI values above 70 may indicate overbought conditions, while values below 30 may indicate oversold conditions.
Practical Tips:
Timeframe Selection: Consider the trend alignment across different timeframes for comprehensive market analysis.
Confirmation: Use additional indicators or technical analysis to confirm RSI signals.
Backtesting: Before applying in live trading, conduct thorough backtesting to evaluate the script's performance.
Adjustment: Modify settings according to your trading preferences and market conditions.
Disclaimer:
This script is a tool for technical analysis and should be used in conjunction with other indicators. It is not financial advice, and users should conduct their own research before making trading decisions. Adjust settings based on personal preferences and risk tolerance. Use the script responsibly and at your own risk.
Back Week For BacktestIt is Backtest Calculator For Essential and Plus plan holders, the length of available intraday data is calculated as follows: from now to 6 weeks back multiplied by timeframe(in minutes), i.e. you can go 6 weeks back on the 1-minute chart, 12 weeks back on the 2-minute chart, 30 weeks back on the 5-minute chart, 90 weeks back on the 15-minute chart and so on. The higher timeframe is selected, the more intraday data is available.
This show creates a weekday label based on the data in the plans allowed by TradingView. This show creates a weekday label based on the data in the plans allowed by TradingView. How much data is available for Bar Replay? According to the article, we can replay 6 weeks backwards for a 1-minute chart. This indicator is a label that shows how far we can go back, consisting of multiplying each minute by 6 between 1 minute and 60 minutes.
1 minute => 6 week backtest
2 minutes => 12 week backtest
.....
15 minutes => 90 week backtest
...
59 minutes => 354 week backtest
Composite RSI [KFB Quant]The Composite RSI (CRSI) is a momentum oscillator that combines 5 adjustable RSI's. It also has a Z-Score to make it easier to identify potential market extremes.
How to adjust the indicator
Inside the Length & Impact Configuration tab you can adjust the length and impact of each RSI as well as the Z-Score length specific to your needs. The default length inputs are 7, 14, 30, 60, 90 (RSI 1 - RSI 5) and the default impact is set to 1.0 for all RSI's. Default length for Z-Score is 360.
Inside the Style Configuration tab you can pick what you want to display(plot). The options are: CRSI, Z-Score, Overview Table and the individual RSI's.
Inside the Color Configuration tab you can customize the color of each plot.
How the script works
CRSI = rsi_sum / imp_sum
Z-Score = (crsi - crsi_mean) / crsi_stdev
rsi_sum = (rsi_1 -50) + (rsi_2 -50) + (rsi_3 -50) + (rsi_4 -50) + (rsi_5 -50)
imp_sum = imp_1 + imp_2 + imp_3 + imp_4 + imp_5
crsi_mean = Average of the crsi over the defined period in Z-Score Length
crsi_stdev = StDev of crsi over the defined period in Z-Score Length
This is not financial advice. Trading is risky & most traders lose money. Past performance does not guarantee future results. This indicator is for informational & educational purposes only.
SentinelsSentinels is a playful variation on combining different mean averages (MA).
A cross of 2 user-defined MA's (MA 1 & MA 2) initiates the drawing of a sentinel with tentacles, which, on its turn can provide potential support/resistance or entry/stop-loss/take profit zones.
The type of each MA (MA 1, MA 2 and tentacles) can be chosen from following options:
SMA
EMA
SMMA (RMA)
HullMA
WMA
VWMA
DEMA
TEMA
🔹 Examples
Fast & slow MA: HullMA, Tentacles: TEMA
Fast & slow MA: SMA, Tentacles: WMA
Fast & slow MA: WMA, Tentacles: WMA
Fast & slow MA: TEMA, Tentacles: TEMA
🔶 DETAILS
🔹 Head-Body
The head-body is formed by:
the slow MA when there is a crossunder.
the fast MA when there is a crossover.
The color of the head-body is a gradient which can be set. The color of the tentacles (non-gradient) can be set as well.
The head-body of the sentinel will be visible for maximum 60 bars after a cross has occured.
🔹 Tentacles
The length of the 'Tentacles' is calculated by taking the difference between the length of MA 1 and MA 2 , and dividing this by 6 -> diff .
The length of each tentacle is MA 1 + a multiple of diff .
The tentacles will only begin to show from 2 bars after a cross.
Each tentacle will be shown maximum x bars after the cross:
Tentacle 1: 15 bars
Tentacle 2: 20 bars
Tentacle 3: 25 bars
Tentacle 4: 30 bars
Tentacle 5: 35 bars
Tentacle 6: 40 bars
🔹 Switch lengths
By switching lengths the colors get switched too.
Note that the tentacles act differently though.
In that way, this can be an extra option to visualize the tentacles .
🔶 Happy Holidays
Merry Christmas and a Happy New Year!
ATR Range Accumulation by Standard Deviation and Volume [SS]So, this is an indicator/premise I have been experimenting with, which mixes ATR with Z-Score and Volume metrics.
What does the indicator do?
The indicator, on the lower timeframes, uses an ATR approach to determine short-term ranges. It takes the average ATR range over a designated lookback period and plots out the levels like so:
It then calculates the Z-Score for these ATR targets (shown in the chart above) and calculates, over the designated lookback period, how often price accumulates at that standard deviation level.
The indicator is essentially a hybrid of my Z-Score Support and Resistance indicator and my frequency distribution indicator. It combines both concepts into one.
You also have the option of sorting by volume accumulation. This will display the accumulation of the ranges by volume accumulation, like so:
Larger Timeframes:
If you want to see the accumulation by volume or standard deviation on the larger timeframes, you can. Simply toggle on your preferred setting:
Show Total Accumulation Breakdown:
This will break down the levels, over the lookback period, by standard deviation. This is similar to the Z-Score support and resistance indicator. It will then show you how often price accumulates at these various standard deviation levels. Here is an example on the daily timeframe using the 1D chart settings:
Inversely, you can repeat this, with the Z-Score levels, but show accumulation by volume. This will print 5 boxes, which are between +3 Standard Deviations and -3 Standard Deviations, like so:
Here we can see that 61% of volume accumulation is between -1 and 1 standard deviation.
Using it to Trade:
For swing trading, I suggest using the larger timeframe information. However, for both swing and day traders, it is also helpful to use the ATR display. You can modify the ATR display to show the levels on any timeframe by selecting which timeframe you would like to see ATR ranges for. If you are trading on the 1 or 5-minute chart, I suggest leaving the levels at no shorter than a 60-minute timeframe.
You can also use these levels on the daily for the weekly levels, etc.
The accumulation being shown will be based on the current chart timeframe. This is a function of Pinescript, but in this case, it's actually advantageous because if you are trading on the shorter timeframe, and a level has 0% recent accumulation, it's unlikely we will see that level soon or overly quickly. Intraday retracements will generally happen to areas of high accumulation.
How this indicator is different:
The difference in this indicator comes from its focus on accumulation in relation to Standard Deviation. There is one thing that is consistent among retail traders, algorithms, market makers, and funds, and that is looking at the market in terms of standard deviation. Each person, market maker, and algorithm may be slightly nuanced in how it conceptualizes standard deviation (whether it be since the inception of the ticker (or IPO), or the previous 500 days, or the previous 100 days, etc.), but the premise remains consistent. Standard Deviation is a really important, if not the most important, metric to pay attention to. Another important metric is volume. Thus, the premise is that combining volume accumulation with standard deviation should, theoretically, be telling. We can see the extent of buying at various standard deviations and whether a stock is really a buy or not.
And that's the indicator! Hope you enjoy it. Leave your comments and questions below.
Safe trades!
Mike's Crossover BotGreetings! As a newcomer to coding, I've developed a simple trading bot for experimentation purposes. However, it's important to note that this bot has not undergone rigorous testing, so please exercise caution and use it at your own risk.
Bot Overview:
The bot operates by leveraging two technical indicators: Moving Average Convergence Divergence (MACD) with 7-day and 25-day parameters, and the Relative Strength Index (RSI). These indicators help identify potential buying and selling opportunities in the market.
MACD Crossovers:
The MACD is a trend-following momentum indicator that compares short-term and long-term moving averages. In our bot, we look for crossovers between the 7-day and 25-day MACD lines. A crossover occurs when these lines intersect, suggesting a potential change in market direction.
RSI Confirmation:
To refine our signals, we incorporate the Relative Strength Index (RSI). When a MACD crossover happens, the bot checks if the RSI is below 40. If it is, a buy signal is generated, indicating a potential undervalued condition. Conversely, when the RSI is above 60 during a crossover, a sell signal is triggered, suggesting a potentially overvalued condition.
Important Considerations:
New Coder Disclaimer: This bot is designed for educational purposes, especially for those who are new to coding. It serves as a learning tool and is not intended for live trading without proper testing.
Risk Awareness: Trading always involves risks, and the bot's performance has not been thoroughly tested in live market conditions. It's crucial to exercise caution and be aware of the inherent risks associated with financial markets.
Continuous Learning: Coding and algorithmic trading are dynamic fields. As you explore this bot, consider it a starting point for learning and continuously seek to enhance your understanding and skills in coding and trading strategies.
Remember, the success of any trading strategy depends on various factors, and past performance is not indicative of future results. Always conduct thorough testing before considering any automated strategy for live trading.
Market Trend Indicator (FinnoVent)The Market Trend Indicator (FinnoVent) is a comprehensive trading tool designed to provide clear visual cues for market trends on TradingView charts. This indicator combines the principles of Exponential Moving Averages (EMAs), Bollinger Bands, the Average Directional Index (ADX), and the Relative Strength Index (RSI) to offer a nuanced view of market movements.
How It Works:
Trend Identification with EMAs: The indicator uses two EMAs (3-period and 30-period) to identify the primary trend. An upward trend is signaled when the 3-period EMA crosses above the 30-period EMA, while a downward trend is indicated when the 3-period EMA crosses below the 30-period EMA.
Sideways Market Detection: To identify sideways trends, the indicator employs Bollinger Bands, ADX, and RSI. A sideways (or consolidating) market condition is identified when:
The price is between the middle 60% of the Bollinger Bands (avoiding the top and bottom 20%).
The ADX is below 30, indicating a lack of a strong trend.
The RSI is between 40 and 60, suggesting a neutral market momentum.
Visual Representation:
Bar Colors: The indicator colors the price bars on the chart based on the identified trend:
Green Bars: Indicate an upward trend.
Red Bars: Indicate a downward trend.
Grey Bars: Indicate a sideways or consolidating market.
How to Use:
Trend Following: Use the colored bars as a guide for trend following. Green bars suggest a potential entry for a long position, while red bars may indicate opportunities for short positions.
Sideways Market Caution: Grey bars signal a sideways market. In such conditions, traders might exercise caution and avoid trend-following strategies, as the market lacks a clear direction.
Complementary Analysis: While the Market Trend Indicator (FinnoVent) provides valuable insights, it's recommended to use it in conjunction with other forms of analysis (like fundamental analysis, other technical indicators, or price action) for comprehensive decision-making.
Suitable for: This indicator is versatile and can be applied to various timeframes and trading instruments, including stocks, forex, commodities, and indices.
Important Notes:
The indicator is designed to minimize repainting but always consider the latest data for the most accurate analysis.
Like all indicators, it is not foolproof. It works best when combined with a solid trading plan and risk management strategies.
RSI SuperstackThis script integrates three Relative Strength Index (RSI) indicators across multiple time frames, providing a comprehensive overview of oversold and overbought conditions. This holistic approach enhances the precision of entry and exit points on shorter time frames.
As a momentum indicator, the Relative Strength Index assesses a security's strength during upward and downward price movements within the specified time period.
In a broader context, an upward slope in all indicators (green, purple, and orange) signifies an increasing market momentum, suggesting a potential continuation of the upward trend.
More specifically, a collective upward slope reaching or surpassing the 40 level in all indicators serves as a buy signal. Conversely, a uniform downward slope descending to or below the 60 level in all indicators constitutes a sell signal.
The default time frames for analysis include:
- 1 Hour (1H)
- 4 Hours (4H)
- Daily (D)
It is imperative to note that this indicator should not serve as the sole determinant for initiating long or short positions. Instead, it is recommended to consider it as part of a broader analysis, incorporating factors such as trend analysis and significant support levels.
Disclaimer: The utilization of this indicator should complement a comprehensive analysis and not be solely relied upon for decision-making regarding long or short positions.
Linear Regression MTF + Bands
Multiple Time Frames (MTFs): The indicator allows you to view linear regression trends over three different time frames (TF1, TF2, TF3) simultaneously. This means a trader can observe short, medium, and long-term trends on a single chart, which is valuable for understanding overall market direction and making cross-timeframe comparisons.
Linear Regression Bands: For each time frame, the indicator calculates linear regression bands. These bands represent the expected price range based on past prices. The middle line is the linear regression line, and the upper and lower lines are set at a specified deviation from this line. Traders can use these bands to spot potential overbought or oversold conditions, or to anticipate future price movements.
History Bands: Looking at linear regression channels can be deceiving if the user does not understand the calculation. In order to see where the channel was at in history the user can display the history bands to see where price actual was in a non-repainting fashion.
Customization Options: Traders can customize various aspects of the indicator, such as whether to display each time frame, the length of the linear regression (how many past data points it considers), and the deviation for the bands. This flexibility allows traders to adapt the indicator to their specific trading style and the asset they are analyzing.
Alerts: The script includes functionality to set alerts based on the price crossing the upper or lower bands of any time frame. This feature helps traders to be notified of potential trading opportunities or risks without constantly monitoring the chart.
Examples
The 15minute linear regression is overlayed onto a 5 minute chart. We are able to see higher timeframe average and extremes. The average is the middle of the channel and the extremes are the outer edges of the bands. The bands are non-repainting meaning that is the actual value of the channel at that place in time.
Here multiple channels are shown at once. We have a linear regression for the 5, 15, and 60 minute charts. If your strategy uses those timeframes you can see the average and overbought/oversold areas without having to flip through charts.
In this example we show just the history bands. The bands could be thought of as a "don't diddle in the middle" area if your strategy is looking for reversals
You can extend the channel into the future via the various input settings.
Multi VWAP for Wick HunterCredit: honeybadgermakesfunnymoney for this Open Source Script
Published:
This is a tool that will allow you to visualize Wick Hunter's calcation of VWAP. Wick Hunter uses this calcuation for its Liqudations Bots.
There are four settings that you need to be configured to visualize your VWAP Band:
Long VWAP - The distance from current VWAP price, in %, that price must be UNDER when a liquidation event occurs to meet your you VWAP condition. The higher the value, the more price must move below the current VWAP price for it to enter a LONG position.
Short VWAP - The distance from current VWAP price, in %, that price must be ABOVE when a liquidation event occurs to meet your you VWAP condition. The higher the value, the more price must move above the current VWAP price for it to enter a SHORT position.
VWAP Timeframe - Select the timeframe you want the VWAP to be measured on.
VWAP Periods: Input the time period over which you want the VWAP to be measured over. For example, if you use "5" for this and "15" for VWAP Timeframe. The VWAP will be calculated based on the last five 15 minute candles.
You can play around with these settings using the indicator provide above. The indicator will print a triangle when the conditon for VWAP is met for a long for short trade. Play around with these settings. A few good timeframes that are popular are 5 minute, 15 minute, and one hour (60 minute). As far as periods, the most common settings are between 5 periods and 15 periods. In general the lower the timeframe and periods and closer VWAP will follow price.
MTF Breakout/RetestIntroducing the MTF (Multi Timeframe) Breakout and Retest Indicator:
This indicator is designed to enhance your trading strategy by providing a clear view of support and resistance levels across multiple timeframes. What this simply means is that you can input your levels, and be on a lower timeframe such as the 1 minute timeframe, and are able to see when your support or resistance level has a breakout
📈 Short Trade Breakout Condition:
- Definition: A short breakout occurs when a candle closes below your specified support level on any chosen timeframe.
- Confirmation: It confirms as a valid short signal when a second candle closes below the support level without retesting.
- Visual Clarity: The indicator highlights the timeframe in which this breakout has occurred.
(Long conditions are same but reversed, and will be displayed in color green)
📊 Multi-Timeframe Insights:
- Scope: You can analyze support and resistance levels across various timeframes, including 5, 15, 30, and 60 minutes, while trading on a lower timeframe like 1 minute.
🎨 Dynamic Color-Coding:
- Visual Signaling: The indicator employs color-coding to visually signal breakout events. When a short breakout occurs on any timeframe the timeframe color will highlight red, and vice versa for long will highlight green. The physical line will change color based on the current timeframe you are viewing
- Real-Time Tracking: Colors reset when a level is retested, helping you track market sentiment in real-time.
🪙 Need Your Help
- I am still very much new to coding, and this code is clearly not optimized well. This code was mainly the based idea, and over the next coming months I will be working to enhance the code but I need tradingview help. If you are a coder and see a way to optimize this code please please let me know :)
EphemerisLibrary "Ephemeris"
TODO: add library description here
mercuryElements()
mercuryRates()
venusElements()
venusRates()
earthElements()
earthRates()
marsElements()
marsRates()
jupiterElements()
jupiterRates()
saturnElements()
saturnRates()
uranusElements()
uranusRates()
neptuneElements()
neptuneRates()
rev360(x)
Normalize degrees to within [0, 360)
Parameters:
x (float) : degrees to be normalized
Returns: Normalized degrees
scaleAngle(longitude, magnitude, harmonic)
Scale angle in degrees
Parameters:
longitude (float)
magnitude (float)
harmonic (int)
Returns: Scaled angle in degrees
julianCenturyInJulianDays()
Constant Julian days per century
Returns: 36525
julianEpochJ2000()
Julian date on J2000 epoch start (2000-01-01)
Returns: 2451545.0
meanObliquityForJ2000()
Mean obliquity of the ecliptic on J2000 epoch start (2000-01-01)
Returns: 23.43928
getJulianDate(Year, Month, Day, Hour, Minute)
Convert calendar date to Julian date
Parameters:
Year (int) : calendar year as integer (e.g. 2018)
Month (int) : calendar month (January = 1, December = 12)
Day (int) : calendar day of month (e.g. January valid days are 1-31)
Hour (int) : valid values 0-23
Minute (int) : valid values 0-60
julianCenturies(date, epoch_start)
Centuries since Julian Epoch 2000-01-01
Parameters:
date (float) : Julian date to conver to Julian centuries
epoch_start (float) : Julian date of epoch start (e.g. J2000 epoch = 2451545)
Returns: Julian date converted to Julian centuries
julianCenturiesSinceEpochJ2000(julianDate)
Calculate Julian centuries since epoch J2000 (2000-01-01)
Parameters:
julianDate (float) : Julian Date in days
Returns: Julian centuries since epoch J2000 (2000-01-01)
atan2(y, x)
Specialized arctan function
Parameters:
y (float) : radians
x (float) : radians
Returns: special arctan of y/x
eccAnom(ec, m_param, dp)
Compute eccentricity of the anomaly
Parameters:
ec (float) : Eccentricity of Orbit
m_param (float) : Mean Anomaly ?
dp (int) : Decimal places to round to
Returns: Eccentricity of the Anomaly
planetEphemerisCalc(TGen, planetElementId, planetRatesId)
Compute planetary ephemeris (longtude relative to Earth or Sun) on a Julian date
Parameters:
TGen (float) : Julian Date
planetElementId (float ) : All planet orbital elements in an array. This index references a specific planet's elements.
planetRatesId (float ) : All planet orbital rates in an array. This index references a specific planet's rates.
Returns: X,Y,Z ecliptic rectangular coordinates and R radius from reference body.
calculateRightAscensionAndDeclination(earthX, earthY, earthZ, planetX, planetY, planetZ)
Calculate right ascension and declination for a planet relative to Earth
Parameters:
earthX (float) : Earth X ecliptic rectangular coordinate relative to Sun
earthY (float) : Earth Y ecliptic rectangular coordinate relative to Sun
earthZ (float) : Earth Z ecliptic rectangular coordinate relative to Sun
planetX (float) : Planet X ecliptic rectangular coordinate relative to Sun
planetY (float) : Planet Y ecliptic rectangular coordinate relative to Sun
planetZ (float) : Planet Z ecliptic rectangular coordinate relative to Sun
Returns: Planet geocentric orbital radius, geocentric right ascension, and geocentric declination
mercuryHelio(T)
Compute Mercury heliocentric longitude on date
Parameters:
T (float)
Returns: Mercury heliocentric longitude on date
venusHelio(T)
Compute Venus heliocentric longitude on date
Parameters:
T (float)
Returns: Venus heliocentric longitude on date
earthHelio(T)
Compute Earth heliocentric longitude on date
Parameters:
T (float)
Returns: Earth heliocentric longitude on date
marsHelio(T)
Compute Mars heliocentric longitude on date
Parameters:
T (float)
Returns: Mars heliocentric longitude on date
jupiterHelio(T)
Compute Jupiter heliocentric longitude on date
Parameters:
T (float)
Returns: Jupiter heliocentric longitude on date
saturnHelio(T)
Compute Saturn heliocentric longitude on date
Parameters:
T (float)
Returns: Saturn heliocentric longitude on date
neptuneHelio(T)
Compute Neptune heliocentric longitude on date
Parameters:
T (float)
Returns: Neptune heliocentric longitude on date
uranusHelio(T)
Compute Uranus heliocentric longitude on date
Parameters:
T (float)
Returns: Uranus heliocentric longitude on date
sunGeo(T)
Parameters:
T (float)
mercuryGeo(T)
Parameters:
T (float)
venusGeo(T)
Parameters:
T (float)
marsGeo(T)
Parameters:
T (float)
jupiterGeo(T)
Parameters:
T (float)
saturnGeo(T)
Parameters:
T (float)
neptuneGeo(T)
Parameters:
T (float)
uranusGeo(T)
Parameters:
T (float)
moonGeo(T_JD)
Parameters:
T_JD (float)
mercuryOrbitalPeriod()
Mercury orbital period in Earth days
Returns: 87.9691
venusOrbitalPeriod()
Venus orbital period in Earth days
Returns: 224.701
earthOrbitalPeriod()
Earth orbital period in Earth days
Returns: 365.256363004
marsOrbitalPeriod()
Mars orbital period in Earth days
Returns: 686.980
jupiterOrbitalPeriod()
Jupiter orbital period in Earth days
Returns: 4332.59
saturnOrbitalPeriod()
Saturn orbital period in Earth days
Returns: 10759.22
uranusOrbitalPeriod()
Uranus orbital period in Earth days
Returns: 30688.5
neptuneOrbitalPeriod()
Neptune orbital period in Earth days
Returns: 60195.0
jupiterSaturnCompositePeriod()
jupiterNeptuneCompositePeriod()
jupiterUranusCompositePeriod()
saturnNeptuneCompositePeriod()
saturnUranusCompositePeriod()
planetSineWave(julianDateInCenturies, planetOrbitalPeriod, planetHelio)
Convert heliocentric longitude of planet into a sine wave
Parameters:
julianDateInCenturies (float)
planetOrbitalPeriod (float) : Orbital period of planet in Earth days
planetHelio (float) : Heliocentric longitude of planet in degrees
Returns: Sine of heliocentric longitude on a Julian date
NSDT Average 6This is a pretty simple concept that we were asked to put together. It uses 6 Moving Averages, and takes the average of each one, then averages them all together.
If you don't want to use 6, and only 3 for example, then just enter the same length in two of the input fields as pairs.
Example:
For 6, you could use 10, 20, 30, 40, 50, 60
For 3, you could use 10, 10, 50, 50, 100, 100
It doesn't ploy 6 MA's, it only plots one - the result of the average of an average of an average, etc..
Publishing open source so other can modify as needed.
Statistical Package for the Trading Sciences [SS]
This is SPTS.
It stands for Statistical Package for the Trading Sciences.
Its a play on SPSS (Statistical Package for the Social Sciences) by IBM (software that, prior to Pinescript, I would use on a daily basis for trading).
Let's preface this indicator first:
This isn't so much an indicator as it is a project. A passion project really.
This has been in the works for months and I still feel like its incomplete. But the plan here is to continue to add functionality to it and actually have the Pinecoding and Tradingview community contribute to it.
As a math based trader, I relied on Excel, SPSS and R constantly to plan my trades. Since learning a functional amount of Pinescript and coding a lot of what I do and what I relied on SPSS, Excel and R for, I use it perhaps maybe a few times a week.
This indicator, or package, has some of the key things I used Excel and SPSS for on a daily and weekly basis. This also adds a lot of, I would say, fairly complex math functionality to Pinescript. Because this is adding functionality not necessarily native to Pinescript, I have placed most, if not all, of the functionality into actual exportable functions. I have also set it up as a kind of library, with explanations and tips on how other coders can take these functions and implement them into other scripts.
The hope here is that other coders will take it, build upon it, improve it and hopefully share additional functionality that can be added into this package. Hence why I call it a project. Okay, let's get into an overview:
Current Functions of SPTS:
SPTS currently has the following functionality (further explanations will be offered below):
Ability to Perform a One-Tailed, Two-Tailed and Paired Sample T-Test, with corresponding P value.
Standard Pearson Correlation (with functionality to be able to calculate the Pearson Correlation between 2 arrays).
Quadratic (or Curvlinear) correlation assessments.
R squared Assessments.
Standard Linear Regression.
Multiple Regression of 2 independent variables.
Tests of Normality (with Kurtosis and Skewness) and recognition of up to 7 Different Distributions.
ARIMA Modeller (Sort of, more details below)
Okay, so let's go over each of them!
T-Tests
So traditionally, most correlation assessments on Pinescript are done with a generic Pearson Correlation using the "ta.correlation" argument. However, this is not always the best test to be used for correlations and determine effects. One approach to correlation assessments used frequently in economics is the T-Test assessment.
The t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It assesses whether the sample means are likely to have come from populations with the same mean. The test produces a t-statistic, which is then compared to a critical value from the t-distribution to determine statistical significance. Lower p-values indicate stronger evidence against the null hypothesis of equal means.
A significant t-test result, indicating the rejection of the null hypothesis, suggests that there is statistical evidence to support that there is a significant difference between the means of the two groups being compared. In practical terms, it means that the observed difference in sample means is unlikely to have occurred by random chance alone. Researchers typically interpret this as evidence that there is a real, meaningful difference between the groups being studied.
Some uses of the T-Test in finance include:
Risk Assessment: The t-test can be used to compare the risk profiles of different financial assets or portfolios. It helps investors assess whether the differences in returns or volatility are statistically significant.
Pairs Trading: Traders often apply the t-test when engaging in pairs trading, a strategy that involves trading two correlated securities. It helps determine when the price spread between the two assets is statistically significant and may revert to the mean.
Volatility Analysis: Traders and risk managers use t-tests to compare the volatility of different assets or portfolios, assessing whether one is significantly more or less volatile than another.
Market Efficiency Tests: Financial researchers use t-tests to test the Efficient Market Hypothesis by assessing whether stock price movements follow a random walk or if there are statistically significant deviations from it.
Value at Risk (VaR) Calculation: Risk managers use t-tests to calculate VaR, a measure of potential losses in a portfolio. It helps assess whether a portfolio's value is likely to fall below a certain threshold.
There are many other applications, but these are a few of the highlights. SPTS permits 3 different types of T-Test analyses, these being the One Tailed T-Test (if you want to test a single direction), two tailed T-Test (if you are unsure of which direction is significant) and a paired sample t-test.
Which T is the Right T?
Generally, a one-tailed t-test is used to determine if a sample mean is significantly greater than or less than a specified population mean, whereas a two-tailed t-test assesses if the sample mean is significantly different (either greater or less) from the population mean. In contrast, a paired sample t-test compares two sets of paired observations (e.g., before and after treatment) to assess if there's a significant difference in their means, typically used when the data points in each pair are related or dependent.
So which do you use? Well, it depends on what you want to know. As a general rule a one tailed t-test is sufficient and will help you pinpoint directionality of the relationship (that one ticker or economic indicator has a significant affect on another in a linear way).
A two tailed is more broad and looks for significance in either direction.
A paired sample t-test usually looks at identical groups to see if one group has a statistically different outcome. This is usually used in clinical trials to compare treatment interventions in identical groups. It's use in finance is somewhat limited, but it is invaluable when you want to compare equities that track the same thing (for example SPX vs SPY vs ES1!) or you want to test a hypothesis about an index and a leveraged share (for example, the relationship between FNGU and, say, MSFT or NVDA).
Statistical Significance
In general, with a t-test you would need to reference a T-Table to determine the statistical significance of the degree of Freedom and the T-Statistic.
However, because I wanted Pinescript to full fledge replace SPSS and Excel, I went ahead and threw the T-Table into an array, so that Pinescript can make the determination itself of the actual P value for a t-test, no cross referencing required :-).
Left tail (Significant):
Both tails (Significant):
Distributed throughout (insignificant):
As you can see in the images above, the t-test will also display a bell-curve analysis of where the significance falls (left tail, both tails or insignificant, distributed throughout).
That said, I have not included this function for the paired sample t-test because that is a bit more nuanced. But for the one and two tailed assessments, the indicator will provide you the P value.
Pearson Correlation Assessment
I don't think I need to go into too much detail on this one.
I have put in functionality to quickly calculate the Pearson Correlation of two array's, which is not currently possible with the "ta.correlation" function.
Quadratic (Curvlinear) Correlation
Not everything in life is linear, sometimes things are curved!
The Pearson Correlation is great for linear assessments, but tends to under-estimate the degree of the relationship in curved relationships. There currently is no native function to t-test for quadratic/curvlinear relationships, so I went ahead and created one.
You can see an example of how Quadratic and Pearson Correlations vary when you look at CME_MINI:ES1! against AMEX:DIA for the past 10 ish months:
Pearson Correlation:
Quadratic Correlation:
One or the other is not always the best, so it is important to check both!
R-Squared Assessments:
The R-squared value, or the square of the Pearson correlation coefficient (r), is used to measure the proportion of variance in one variable that can be explained by the linear relationship with another variable. It represents the goodness-of-fit of a linear regression model with a single predictor variable.
R-Squared is offered in 3 separate forms within this indicator. First, there is the generic R squared which is taking the square root of a Pearson Correlation assessment to assess the variance.
The next is the R-Squared which is calculated from an actual linear regression model done within the indicator.
The first is the R-Squared which is calculated from a multiple regression model done within the indicator.
Regardless of which R-Squared value you are using, the meaning is the same. R-Square assesses the variance between the variables under assessment and can offer an insight into the goodness of fit and the ability of the model to account for the degree of variance.
Here is the R Squared assessment of the SPX against the US Money Supply:
Standard Linear Regression
The indicator contains the ability to do a standard linear regression model. You can convert one ticker or economic indicator into a stock, ticker or other economic indicator. The indicator will provide you with all of the expected information from a linear regression model, including the coefficients, intercept, error assessments, correlation and R2 value.
Here is AAPL and MSFT as an example:
Multiple Regression
Oh man, this was something I really wanted in Pinescript, and now we have it!
I have created a function for multiple regression, which, if you export the function, will permit you to perform multiple regression on any variables available in Pinescript!
Using this functionality in the indicator, you will need to select 2, dependent variables and a single independent variable.
Here is an example of multiple regression for NASDAQ:AAPL using NASDAQ:MSFT and NASDAQ:NVDA :
And an example of SPX using the US Money Supply (M2) and AMEX:GLD :
Tests of Normality:
Many indicators perform a lot of functions on the assumption of normality, yet there are no indicators that actually test that assumption!
So, I have inputted a function to assess for normality. It uses the Kurtosis and Skewness to determine up to 7 different distribution types and it will explain the implication of the distribution. Here is an example of SP:SPX on the Monthly Perspective since 2010:
And NYSE:BA since the 60s:
And NVDA since 2015:
ARIMA Modeller
Okay, so let me disclose, this isn't a full fledge ARIMA modeller. I took some shortcuts.
True ARIMA modelling would involve decomposing the seasonality from the trend. I omitted this step for simplicity sake. Instead, you can select between using an EMA or SMA based approach, and it will perform an autogressive type analysis on the EMA or SMA.
I have tested it on lookback with results provided by SPSS and this actually works better than SPSS' ARIMA function. So I am actually kind of impressed.
You will need to input your parameters for the ARIMA model, I usually would do a 14, 21 and 50 day EMA of the close price, and it will forecast out that range over the length of the EMA.
So for example, if you select the EMA 50 on the daily, it will plot out the forecast for the next 50 days based on an autoregressive model created on the EMA 50. Here is how it looks on AMEX:SPY :
You can also elect to plot the upper and lower confidence bands:
Closing Remarks
So that is the indicator/package.
I do hope to continue expanding its functionality, but as of now, it does already have quite a lot of functionality.
I really hope you enjoy it and find it helpful. This. Has. Taken. AGES! No joke. Between referencing my old statistics textbooks, trying to remember how to calculate some of these things, and wanting to throw my computer against the wall because of errors in the code, this was a task, that's for sure. So I really hope you find some usefulness in it all and enjoy the ability to be able to do functions that previously could really only be done in external software.
As always, leave your comments, suggestions and feedback below!
Take care!
TMA MTFThis indicator plots three different Triple Moving Averages (TMAs) for two different time frames on a price chart:
Middle TMA Line: This is the main TMA line, calculated based on a user-defined number of past bars. It's represented by a solid line on the chart.
Upper TMA Line: This line is calculated by adding a certain multiple of the Average True Range (ATR) to the main TMA line. It helps identify potential resistance levels and is plotted as a solid line.
Lower TMA Line: Similar to the upper line, this line is calculated by subtracting a multiple of the ATR from the main TMA line. It helps identify potential support levels and is also plotted as a solid line.
Additionally, you have the option to overlay these TMA lines on a higher timeframe (HTF) if desired. When you enable this feature, it plots the same three TMA lines but calculated using data from a higher timeframe, which can provide additional context for your trading decisions.
The indicator uses different colors for the TMA lines based on their relationships:
Green: The middle TMA line is above the higher timeframe middle TMA line, suggesting a potential bullish (upward) trend.
Red: The middle TMA line is below the higher timeframe middle TMA line, suggesting a potential bearish (downward) trend.
In addition, it plots the upper and lower TMA lines in shades of purple and maroon, respectively, on the higher timeframe for reference.
Overall, this indicator helps traders identify potential areas of support and resistance and assess the trend direction by comparing the TMA lines of different timeframes.
Variable:
TMA_Period:
This input variable allows you to specify the number of past bars that are used to calculate the main Triple Moving Average (TMA) line. A larger value will result in a smoother TMA line, while a smaller value will make it more responsive to recent price changes.
ATR_Period:
This input variable determines the number of past bars used to calculate the Average True Range (ATR). The ATR is a measure of price volatility. A longer ATR period considers a broader range of price movement, while a shorter period reacts more quickly to recent volatility.
ATR_Multiplier:
This input allows you to set a multiplier for the ATR on the current timeframe. The ATR value is multiplied by this factor to calculate the upper and lower TMA lines. A higher multiplier will result in wider TMA bands, while a lower multiplier will make them narrower.
ATR_Multiplier_HTF:
Similar to ATR_Multiplier, this input sets a multiplier for the ATR on a higher timeframe (HTF). It affects the width of the HTF TMA bands.
TF_1:
This input variable lets you choose the desired higher timeframe (HTF) for the indicator. You can select from various timeframes, including 1 minute, 5 minutes, 15 minutes, 30 minutes, 60 minutes, 240 minutes (4 hours), daily (D), weekly (W), monthly (M), or choose "Auto" to let the script automatically determine the HTF based on the current timeframe.
src:
This input allows you to choose the price source used for calculations. By default, it's set to 'close,' which means the closing prices of each bar are used. You can change this to other price sources like 'open,' 'high,' 'low,' or 'ohlc4' (a combination of open, high, low, and close prices).
ma_type:
This input lets you select the type of moving average used in the calculations. You have three options: Weighted Moving Average (WMA), Double Weighted Moving Average (DWMA), and Triple Weighted Moving Average (TWMA).
Plot_TMA_HTF_Midline:
If set to 'true,' it will plot the middle TMA line of the higher timeframe (HTF) on the chart. If set to 'false,' the HTF middle TMA line will not be displayed.
RSI Trend Detector PSAR BasedRSI Trend Detector is based on the Direction of PSAR. This indicator helps the easy detection of Trend Direction and Sideways Movement of Price. It was difficult to determine the RSI Trend Direction in a basic RSI indicator. one cannot decide the exact entry point where to enter.
RSI Trend Detector helps with the direction of trend using PSAR direction which is almost instant direction changing indicator with Zero Lag. The color of the RSI changes immediately based on PSAR direction. One can determine the trend whether its in UP / Down or Sideways.
One can easily detect Pullback and entry points using this indicator.
The basic working can be interpreted with a normal default RSI, The only additional feature is the direction of trend using a SAR signal.
Oversold Zone is below 30
Overbought Zone is above 70
how ever RSI above 50 is treated a UP trend and Below 50 as Down Trend.
when RSI is between 40 and 60 price must be considered as Sideways. One can easily interpret the TREND.
Yellow Line = RSI Moving Average
RED and Green Line= RSI
Grey Zone = Sideways
Horizontal line = RSI level 50
Settings can be changed as required.
RSI Line:
RSI Above 50 up trend and Entry when color is green
RSI Below 50 down trend and Entry when color is Red
RSI in Grey Zone is sideways, wait for a breakout
RSI above 50 and color is red then its a pullback in uptrend
RSI below 50 and color is green then its a pullback in downtrend
ALERTS:
Up signal and Down Signal are provided when ever RSI crosses RSIMA
Up Signal: RSI crosses RSI Moving Average upwards
Down Signal: RSI crosses RSI Moving Average Downwards
Hope the Tradingview community likes this.
Number of Bars CheatSheetA regular trading day on the New York Stock Exchange (NYSE) consists of two main sessions: the Opening Auction and the Closing Auction, separated by a continuous trading session. Here's a breakdown of the trading day:
1. **Pre-Opening Session**: This session starts at 4:00 AM Eastern Time (ET) and lasts until 9:30 AM ET. During this time, there is limited trading activity, and orders can be entered and canceled. However, most of the trading activity doesn't occur until the regular trading session begins.
2. **Regular Trading Session**: The regular trading session on the NYSE starts at 9:30 AM ET and lasts until 4:00 PM ET. This is the primary trading session where the majority of price bars are formed.
3. **Closing Auction**: After the regular trading session ends at 4:00 PM ET, there is a closing auction period that typically lasts until 4:10 PM ET. During this time, there is a final price discovery process where orders are matched to determine the closing price for each security.
So, during the regular trading session, which is the main focus for most traders and investors, there are a total of 6.5 hours of trading. Trading occurs continuously during this time, with price bars being formed based on the time frame you're looking at. The most common time frames for price bars are one minute, five minutes, 15 minutes, 30 minutes, and one hour, among others. Therefore, the number of price bars in a regular trading day on the NYSE will depend on the time frame you are using for your analysis. For example, if you are using one-minute bars, there will be 6.5 x 60 = 390 price bars in a regular trading day.
Bursa Malaysia Index SeriesBursa Malaysia Index Series. The index computation is as follows:-
Current aggregate Market Capitalisation/Base Aggregate Market Capitalisation x 100.
The Bursa Malaysia Index Series is calculated and disseminated on a real-time basis at 60-second intervals during Bursa’s trading hours.
External Indicator Analysis Overlay | Buy/Sell | HTF Heikin-AshiThis chart overlay offers multiple candlestick display options. The Regular (Japanese) and the Heikin-Ashi candles are well known. The Mari-Ashi (or Renko) option is something special as it should be timeframe independent, so that sideways action should be represented in one candle. That is difficult to realize as an overlay on the normal candlestick structure, but perhaps the chosen implementation is useful nonetheless. The Velocity option is experimental and is designed to show if the price has accelerated too much in a trend direction. In this case, the highs and lows do not reflect the actual highs and lows, but indicate the overshooting velocity. The opening of the candle also depends on the inherent velocity, but the close of the candle is always the actual close. Anyway, it doesn't look very useful, but the option is there.
All options can be applied to higher timeframes. A usable setting is obtained by disabling only the body of the TradingView candles in regular mode and enabling this overlay.
A large part of this overlay consists of buy/sell indication settings. For activation it is necessary to select an external source. For example the “Relative Bi-Directional Volatility Range”, specifically the Trend Shift Signal (TSS). This signal switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish. It will be automatically detected without specifying the Indication Type. Alternatively, the Volatility Moving Average (VMA) would meet the requirements for the Indication Type “Buy = positive | Sell = negative”. The Moving Average Convergence Divergence (MACD) also fulfills these conditions. Another example is to use any Moving Average with the Indication Type “Buy = rising | Sell = falling”. In the chart above the Hull Moving Average (HMA) is used. In addition, it is possible to reverse the signal, so that positive signals become negative and vice versa. The signals will be labeled as Buy or Sell on the chart.
The user can analyze whether the provided signals are good or bad indications for going long or short or simply for rebalancing a portfolio. Therefore, it is possible to set a starting point for the analysis and choose a weighting for the investments from 0% to 100% of the portfolio. To avoid sleepless nights, a very reliable (and conservative) setting seems to be Rebalancing with 50% (very similar to the well-known 60/40 portfolio). The calculation results are shown in a table.
As a small addition there is the possibility to label the peaks by setting the distance between the highs/lows. This will make the quality of the buy and sell signals even more clear.
Short Term IndeXThe Short-Term Index (STIX) is a simple market indicator designed to assess short-term overbought or oversold conditions in the stock market. Leveraging a combination of advancing and declining issues, STIX provides valuable insights into market sentiment and potential reversals. To enhance its interpretability and reveal the underlying trend with greater clarity, STIX has been refined through a Heiken-Ashi transformation, ensuring a smoother representation of market dynamics.
Calculation and Methodology:
stix = ta.ema(adv / (adv + dec) * 100, len)
STIX is calculated by dividing the difference between the sum of advancing issues (ADV) by the total number of issues traded (ADV + DEC). This quotient is multiplied by 100 to express the result as a percentage. The STIX index ranges from 0 to 100, where extreme values indicate potential overbought (mainly above 60) or oversold (mainly below 40) market conditions.
Heiken-Ashi Transformation:
By applying a Heiken-Ashi transformation to STIX, the indicator gains improved visual clarity and noise reduction. This transformation enhances the ability to identify trend shifts and potential reversal points, making it an even more valuable tool for traders and investors.
Utility and Use Cases:
-The Short-Term Index (STIX) offers a range of practical applications-
1. Overbought/Oversold Conditions: STIX provides a clear indication of short-term overbought or oversold conditions, helping traders anticipate potential market reversals.
2. Reversal Points: STIX can help pinpoint potential reversal points in short-term market trends, providing traders with opportunities to enter or exit positions.
3. Trend Analysis: By observing STIX values over time, traders can assess the strength and sustainability of short-term trends, aiding in trend-following strategies.
The Short-Term Index (STIX), enhanced by its Heiken-Ashi transformation, equips traders and investors with a tool for assessing short-term market conditions, confirming price movements, and identifying potential reversal points. Its robust methodology and refined presentation contribute to a more comprehensive understanding of short-term market dynamics, enabling traders to make well-informed trading decisions.
See Also:
- Other Market Breadth Indicators-
HighLowBox+220MAs[libHTF]HighLowBox+220MAs
This is a sample script of libHTF to use HTF values without request.security().
import nazomobile/libHTFwoRS/1
HTF candles are calculated internally using 'GMT+3' from current TF candles by libHTF .
To calcurate Higher TF candles, please display many past bars at first.
The advantage and disadvantage is that the data can be generated at the current TF granularity.
Although the signal can be displayed more sensitively, plots such as MAs are not smooth.
In this script, assigned ➊,➋,➌,➍ for htf1,htf2,htf3,htf4.
HTF candles
Draw candles for HTF1-4 on the right edge of the chart. 2 candles for each HTF.
They are updated with every current TF bar update.
Left edge of HTF candles is located at the x-postion latest bar_index + offset.
DMI HTF
ADX/+DI/DI arrows(8lines) are shown each timeframes range.
Current TF's is located at left side of the HighLowBox.
HTF's are located at HighLowBox of HTF candles.
The top of HighLowBox is 100, The bottom of HighLowBox is 0.
HighLowBox HTF
Enclose in a square high and low range in each timeframe.
Shows price range and duration of each box.
In current timeframe, shows Fibonacci Scale inside(23.6%, 38.2%, 50.0%, 61.8%, 76.4%)/outside of each box.
Outside(161.8%,261.8,361.8%) would be shown as next target, if break top/bottom of each box.
In HTF, shows Fibonacci Level of the current price at latest box only.
Boxes:
1 for current timeframe.
4 for higher timeframes.(Steps of timeframe: 5, 15, 60, 240, D, W, M, 3M, 6M, Y)
HighLowBox TrendLine
Draw TrendLine for each HighLow Range. TrendLine is drawn between high and return high(or low and return low) of each HighLowBox.
Style of TrendLine is same as each HighLowBox.
HighLowBox RSI
RSI Signals are shown at the bottom(RSI<=30) or the top(RSI>=70) of HighLowBox in each timeframe.
RSI Signal is color coded by RSI9 and RSI14 in each timeframe.(current TF: ●, HTF1-4: ➊➋➌➍)
In case of RSI<=30, Location: bottom of the HighLowBox
white: only RSI9 is <=30
aqua: RSI9&RSI14; <=30 and RSI9RSI14
green: only RSI14 <=30
In case of RSI>=70, Location: top of the HighLowBox
white: only RSI9 is >=70
yellow: RSI9&RSI14; >=70 and RSI9>RSI14
orange: RSI9&RSI14; >=70 and RSI9=70
blue/green and orange/red could be a oversold/overbought sign.
20/200 MAs
Shows 20 and 200 MAs in each TFs(tfChart and 4 Higher).
TFs:
current TF
HTF1-4
MAs:
20SMA
20EMA
200SMA
200EMA
Indicator Based Market Exposure (IBME)The Indicator Based Market Exposure (IBME) system was created by Big Wave Chartist as a way to navigate the markets using a confluence of three different signals to determine when the "internals" of the market are in your favor and how heavily invested to be at any point. The idea of the system is also to flash warning signs when the market internals are beginning to deteriorate so as to take a defensive stance. Of course this system can be strictly adhered to, or it can be incorporated into a more discretionary style of trading, and be combined with progressive exposure into (and out of) the market as positions gain (or lose) traction.
The IBME displays a straightforward action signal based on the combination of the 3 separate signals:
Green 🟢 Full size-longs permitted
Yellow 🟡 Pilot positions permitted
Red 🔴 No longs allowed
So let's get into the signals used:
McClellan Summation Index
Net New Highs/Lows
Net New Highs Crossover
McClellan Summation Index (MSI)
The McClellan Summation Index is a long-term version of the McClellan Oscillator, which is a market breadth indicator based on stock advances and declines. Interpretation is similar to that of the McClellan Oscillator, except that it is more suited to intermediate to major trends and related reversals. The McClellan Summation Index can be calculated as the sum of all the daily values of the McClellan Oscillator. This is used along with the 10-sma to watch for a crossover indicating an uptrend or downtrend beginning.
Net New Highs/Lows
This is the net number of stocks making 52-week highs or lows. For instance, if there are 60 new 52-week highs and 20 new 52-week lows, the net number will be 40 net new 52 week highs. This signal is particularly useful in gauging breadth.
Net New Highs Crossover
This is the description of NNHC from the original separate version of this indicator created by HikoStory: "Net New Highs can guide you to increase or decrease your exposure based on the current market health. They are calculated by subtracting the new highs from the new lows, based on all stocks of the...NASDAQ. A positive value shows that the market is doing good, since more stocks are making new highs compared to new lows. A negative value shows that the market is doing bad, since more stocks are making new lows compared to new highs. Combined with a moving average you can see crossovers that can warn you early when there is a change in the current market health."
The default index for the IBME is the Nasdaq.
The IBME is meant to be used on a daily time frame chart, therefore the signal will only show on a daily time frame chart.
Display options include:
Show/hide individual signals
Table background/font color
Table size/placement
