JK - Q SuiteThis indicator is primarily for identifying pauses in Stage 2 uptrends, modelled on Qullamaggie's style of trading, but fits well with many traders including William O' Neil. or Mark Minervini.
I built this for my own purposes, and have gradually added range of tools into a single suite. My goal has also to be as clean as possible, while providing clear, actionable information.
This suite includes all of the following:
Moving averages (10, 20, 50, 200)
Coloured bars showing tightening price (blue under 75% of ADR, orange under 50% of ADR)
A 'markets' dashboard (top-right), showing the major indexes. Red if 10<20MA, or price <20MA
A 'sectors' dashboard (top-right, below markets). Red if 5<10MA, or price <10MA - see note below
Strength / Weakness information - two cells at the top, bottom-right. See below
Stock information - glanceable stock info as quick filters. The thresholds for ADR, Average volume, and Dollar Volume can be customised.
NOTE - if the 'tightening coloured candles' are not showing, the indicator needs to be at the top of the stack. Click the triple squares at the very bottom-right of the TradingView interface, and drag the indicator to the top, should work then!
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Sectors
These are based on the 11 official Sectors, tracked using index funds (XLY, XLK etc). HOWEVER, TradingView does NOT use the official 11 sectors - therefore I've done my best to match TradingViews ones to the official ones, but doesn't always work... e.g. 'Electronic Technology' is typically semiconductors, which are classes as 'Industrials', but Apple is the same sector in TV, but classed as 'Technology' using the official 11 Sectors.
If TradingView move to use the official 11 I'll update this, but for now it's a best guess and will sometimes be wrong, sorry!
Strength / Weakness information
This was an experiment in trying not to give too much back to the market! Typically the strategy would be to sell if price closes below 10MA (Weakness), however there may be large pops that can be advantageous to sell into.
The 'Strength' information (top cell, bottom-right), checks how far the price is extended above 10MA - this is customisable as a multiple of ADR. You may find that in weak markets (like now), it can be best to take profits quickly - in good markets, you could increase this as stocks make bigger or more sustained moves.
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While I'm not the best coder - and I've hacked and tried and changed different things - this has been a labour of love and essential for me.
If you have any suggestions, while I may or may not be able to implement them, I'm certainly open to ideas!
Statistics
Fusion: Machine Learning SuiteThe Fusion: Machine Learning Suite combines multiple technical analysis dimensions and harnesses the predictive power of machine learning, seamlessly integrating a diverse array of classic and novel indicators to deliver precision, adaptability, and innovation.
Features and Capabilities
Multidimensional Analysis: Fusion: MLS integrates various technical analysis dimensions to offer a more comprehensive perspective.
Machine Learning Integration: Utilizing ML algorithms, Fusion: MLS offers adaptability to market changes.
Custom Indicators: Including dimensions like "Moon Lander", "Cap Line" and "Z-Pack" the indicator expands the scope of traditional technical analysis methods.
Tailored Customization: With customization options, Fusion: MLS allows traders to configure the tool to suit their specific strategies and market focus.
In the following sections, we'll explore the features and settings of Fusion: MLS in detail, providing insights into how it can be utilized.
Major Features and Settings
The indicator consists of several core components and settings, each designed to provide specific functionalities and insights. Here's an in-depth look:
Machine Learning Component
Distance Classifier: A Strategic Approach to Market Analysis
In the world of trading and investment, the ability to classify and predict price movements is paramount. Machine learning offers powerful tools for this purpose.
The Fusion: MLS indicator among others incorporates an Approximate Nearest Neighbors (ANN)* algorithm, a machine learning classification technique, and allows the selection of various distance functions .
This flexibility sets Fusion: MLS apart from existing solutions. The available distance functions include:
Euclidean: Standard distance metric, commonly used as a default.
Chebyshev: Also known as maximum value distance.
Manhattan: Sum of absolute differences.
Minkowski: Generalized metric that includes Euclidean and Manhattan as special cases.
Mahalanobis: Measures distance between points in a correlated space.
Lorentzian: Known for its robustness to outliers and noise.
*For a deeper understanding of the Approximate Nearest Neighbors (ANN) algorithm, traders are encouraged to refer to the relevant articles that can be found in the public domain.
Alternative scoring system
Fusion: MLS also includes a custom scoring alternative based on directional price action.
"Combined: Directional" and "Alpha: Directional" scoring types represent our own directional change algorithm, simple yet effective in displaying trend direction changes early on. They are visualized by color changes when scoring becomes below or above zero.
Changes in scoring quickly reflect shifts in buyer and seller sentiment.
Traders may choose signals by Color Change in the indicator settings to get alerts when scoring color shifts, not waiting until the histogram crosses the zero level.
Application in Trading
Machine learning classification has become an integral part of modern trading, offering innovative ways to analyze and interpret financial data.
Many algorithmic trading systems leverage ML classification to automate trading decisions. By continuously learning from real-time data, these systems can adapt to changing market conditions and execute trades with increased efficiency and accuracy.
ML classification allows for the development of tailored trading strategies as traders can select specific algorithms, dimensions, and filters that align with their trading style, goals, and the particular market they are operating.
We have integrated ML classification with traditional trading tools, such as moving averages and technical indicators. This fusion creates a more robust analysis framework, combining the strengths of classical techniques with the adaptability of machine learning.
Whether used independently or in conjunction with other tools, ML classification represents a significant advancement in trading technology, opening new avenues for exploration, innovation, and success in the financial world.
ML: Weighting System
The Fusion: MLS indicator introduces a unique weighting system that allows traders to customize the influence of various technical indicators in the machine learning process. This feature is not only innovative but also provides a level of control and adaptability that sets it apart from other indicators.
Customizable Weights
The weighting system allows users to assign specific weights to different indicators such as Moon Lander, RSI, MACD, Money Flow, Bollinger Bands, Cap Line, Z-Pack, Squeeze Momentum*, and MA Crossover. These weights can be adjusted manually, providing the ability to emphasize or de-emphasize specific indicators based on the trader's strategy or market conditions.
*Note, we determined via testing that the popular "Squeeze" indicator can actually be well replicated by simply using inputs of 15 & 199 in the bedrock indicator - MACD ; while we employed the standard "Squeeze" formula (developed by J. Carter ) in Fusion: MLS, traders are hereby made aware of our research findings regarding such.
The weighting system's importance lies in its ability to provide a more nuanced and personalized analysis. By adjusting the weights of different indicators a trader focusing on momentum strategies might assign higher weights to the Squeeze Momentum and MA Crossover indicators, while a trader looking for volatility might emphasize RSI and Bollinger Bands.
The ability to customize weights adds a layer of complexity and adaptability that is rare in standard machine-learning indicators.
Custom Indicators: Moon Lander
The "Moon Lander" is not just a catchy name; it's a robust feature inspired by principles from aerospace engineering and offers a unique perspective on trading analysis. Here's a conceptual overview:
Fast EMA and Kalman Matrix
"Moon Lander" incorporates both a Fast Exponential Moving Average (EMA) and a Kalman Matrix in its design. These two elements are combined to create a histogram, providing a specific approach to data analysis.
The Kalman Matrix, or Kalman Filter, is a mathematical concept used for estimating variables that can be measured indirectly and contain noise or uncertainty. It's a standard tool in machine learning and control systems, known for its ability to provide optimal estimates based on observed data.
Kalman Filter: A Navigational Tool
The Kalman filter, an essential part of "Moon Lander," is a mathematical concept known for its applications in navigation and control systems used by NASA in the apollo program :
Guidance in Uncertainty: Just as the Kalman filter helped guide complex aerospace missions through uncertain paths, it assists traders in navigating the often unpredictable financial markets.
Filtering Noise: In trading, the Kalman filter serves to filter out market noise, allowing traders to focus on the underlying trends.
Predictive Capabilities: Its ability to predict future states makes it a valuable tool for forecasting market movements and trend directions.
Custom Indicators: Cap Line and Z-Pack
Fusion: MLS integrates our additional proprietary custom indicators that have been published on TradingView earlier:
Cap Line: Delve into the specific functionalities and applications of our proprietary "Cap Line" indicator in the published description on TradingView.
Z-Pack: Explore the analytical perspectives, focused on the z-score methodology, and custom "Z-Pack" indicator by reviewing the published description on TradingView.
Buy/Sell Signal Generation Algorithms
Fusion: MLS offers various options for generating buy/sell signals, tailored to different trading strategies and perspectives:
Fusion: Allows traders to select any number of dimensions to receive buy/sell signals from, offering customized signal generation.
ML: Utilizes the machine learning ANN distance for signal generation.
Color Change: Generates signals by selected scoring type color change.
Displayed Dimension, Alpha Dimension: Generate signals based on specific selected dimensions.
These algorithms provide flexibility in determining buy/sell signals, catering to different trading styles and market conditions.
Filters
Filters are used to refine and selectively include or exclude signals based on specific criteria. Rather than generating signals, these filters act as gatekeepers, ensuring that only the signals meeting certain conditions are considered. Here's an overview of the filters used:
Dynamic State Predictor (DSP)
The DSP employs the Kalman Matrix to evaluate existing signals by comparing the fast and slow-moving averages, both processed through the Kalman Matrix. Based on the relationship between these averages, the DSP may exclude specific signals, depending on whether they align with upward or downward trends.
Average Directional Index (ADX)
The ADX filter evaluates the strength of existing trends and filters out signals that do not meet the specified ADX threshold and length, focusing on significant market movements.
Feature Engineering: RSI
Applies a filter to the existing signals, clearing out those that do not meet the criteria for RSI overbought or oversold threshold condition.
Feature Engineering: MACD
Assesses existing signals to identify changes in the strength, direction, momentum, and duration of a trend, filtering out those that do not align with MACD trend direction.
The Visual Component
The machine learning component is an internal component. However, the indicator also offers an equally important and useful visual component. It is a graphical representation of the multiple technical analysis dimensions, that can be combined in various ways (where the name "Fusion" comes from), allowing traders to visualize the underlying data and its analysis.
Displayed Dimension: Visualization and Normalization
The Fusion: MLS indicator offers a "Displayed Dimension" feature that visualizes various dimensions as a histogram. These dimensions may include RSI, MAs, BBs, MACD, etc.
RSI Dimension on the image + ML signals
Normalization: Each dimension is normalized. If any dimension has extreme values, a Fisher transformation is applied to bring them within a reasonable range.
Combined Dimension: When selecting the "Combined" option , the normalized values of the selected dimensions are combined using techniques such as standardization, normalization, or winsorization. This flexibility enables tailored visualization and analysis.
Alpha Dimension: Enhancing Analysis
The "Alpha Dimension" feature allows traders to select an additional dimension alongside the Displayed Dimension. This facilitates a combined analysis, enhancing the depth of insights.
Theme Selection
Fusion: MLS offers various themes such as "Sailfish", "Iceberg", "Moon", "Perl", "Candy" and "Monochrome" Traders can select a theme that resonates with their preference, enhancing visual appeal. There is also a "Custom" theme available that allows the user to choose the colors of the theme.
Customizing Fusion: MLS for Various Markets and Strategies
Fusion: MLS is designed with customization in mind. Traders can tailor the indicator to suit various markets and trading strategies. Selecting specific dimensions allows it to align with individual trading goals.
Selecting Dimensions: Choose the dimensions that resonate with your trading approach, whether focusing on trend-following, momentum, or other strategies.
Adjusting Parameters: Fine-tune the parameters of each dimension, including custom ones like "Moon Lander," to suit specific market conditions.
Theme Customization: Select a theme that aligns with your visual preferences, enhancing your chart's readability and appeal.
Utilizing Research: Leverage the underlying algorithms and research, such as machine learning classification by ANN and the Kalman filter, to deepen your understanding and application of Fusion: MLS.
Alerts
The indicator includes an alerting system that notifies traders when new buy or sell signals are detected.
Disclaimer
The information provided herein is intended for informational purposes only and should not be construed as investment advice, endorsement, nor a recommendation to buy or sell any financial instruments. Fusion: MLS is a technical analysis tool, and like all tools, it should be used with caution and in conjunction with other forms of analysis.
Traders and investors are encouraged to consult with a licensed financial professional and conduct their own research before making any trading or investment decisions. Past performance of the Fusion: MLS indicator or any trading strategy does not guarantee future results, and all trading involves risk. Users of Fusion: MLS should understand the underlying algorithms and assumptions and consider their individual risk tolerance and investment goals when using this tool.
Crypto/DXY ScoringHi!
This indicator "Crypto/DXY Scoring", a multi-purpose script, consists of various comparison statistics (including an alternative RS/RSMOM model) to show the strength of a currency against the DXY.
Features
"Contrived" RS/RSMOM alternative model
Compare the strength of the crypto currency on your chart to any asset (DXY default)
Glass's ∆
Z-comparison
Hedges' g
Cliff's Delta
Z-score for log returns
RRG graph (with adjusted dimensions) Traditional RRG graph coming soon (:
Let's go over some simplified interpretations of what's shown on the chart!
The image above provides generalized interpretations for the three of the data series plotted by the indicator.
The image above further explains the other plots for the indicator!
The image above shows the final result!
Underlying Theory
"When the dollar is strong as indicated by the DXY, it usually means that investors are seeking safety in traditional assets. Bitcoin (crypto) is often considered a "risk-on" asset, meaning investors might sell BTC in favor of holding dollars, thus driving BTC prices down."
Given the complexities associated with this relationship, including its contentious implications and a variable correlation between crypto and the DXY, this theory is one within a plethora.
That said, regardless of accuracy, this indicator adheres to the theory outlined above (:
The image above shows the purpose of the red/lime columns and the corresponding red/green lines.
Should the crypto on your chart and the DXY (or comparison symbol) exhibit negative correlation, and should the performance of DXY (or comparison symbol) hold any predictive utility for the subsequent performance of the crypto on your chart, the red columns violating the red line might indicate an upcoming "dump" for the crypto on your chart.
Lime green columns violating the green line may indicator an inverse response.
Alternative Relative Rotation Graph
In its current state, the alternated dimensions for the Relative Rotation Graph cause it to function more as a "Relative Performance Graph".
Fear not; a traditional RRG graph is coming soon!
The image above shows our alternative RRG!
Interpretation
With this model, you can quickly/intuitively assess the relative performance of the display cryptos against an index of their performance.
The image above shows generalized interpretations of the model!
That's it for this indicator! Thank you for checking it out; more to come (:
TradeTrackerv2Library "TradeTrackerv2"
This library can be used to track (hypothetical) trades on the chart. Enter the Open, SL, and TP prices (or TP in R to have it calculated) and then call Trade.TrackTrade(barIndex). Keep track of your trades in an array and then simply call TradeTracker.UpdateAllTrades(close) to update all trades based on the current close price.
How to use:
1. Import the library, as always. I'm assuming the alias of "Tracker" below.
2. The Type Trade is exported, so generate a Trade object like newTrade = Tracker.Trade.new() .
3. Set the values for Open, SL, and TP. TP can be set either by price or by R, which will calculate the R based on the Open->SL range:
newTrade.priceOpen = 1.0
newTrade.priceSl = 0.5
newTrade.priceTp = 2.0
-- or in place of the third line above --
newTrade.rTp = 2
4. On each interval you want to update (whether that's per tick/close or on each bar), call trades.UpdateAllTrades(close) . This snippet assumes you have an array named trades (var trades = array.new()) .
In future updates, more customization options will be created. This is the initial prototype.
method MakeTradeLines(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method UpdateLabel(t)
Namespace types: Trade
Parameters:
t (Trade)
method MakeLabel(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method CloseTrade(t)
Namespace types: Trade
Parameters:
t (Trade)
method OpenTrade(t)
Namespace types: Trade
Parameters:
t (Trade)
method OpenCloseTrade(t, _close)
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method CalculateProfits(t, _close)
Calculates profits/losses for the Trade, given _close price
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method UpdateTrade(t, _close)
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method SetInitialValues(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method UpdateAllTrades(trades, _close)
Namespace types: Trade
Parameters:
trades (Trade )
_close (float)
method TrackTrade(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
Trade
Fields:
id (series__integer)
isOpen (series__bool)
isClosed (series__bool)
isBuy (series__bool)
priceOpen (series__float)
priceTp (series__float)
priceSl (series__float)
rTP (series__float)
profit (series__float)
r (series__float)
resultR (series__float)
lineOpen (series__line)
lineTp (series__line)
lineSl (series__line)
labelStats (series__label)
CE - 42MACRO Fixed Income and Macro This is Part 2 of 2 from the 42MACRO Recreation Series
However, there will be a bonus Indicator coming soon!
The CE - 42MACRO Fixed Income and Macro Table is a next level Macroeconomic and market analysis indicator.
It aims to provide a probabilistic insight into the market realized GRID Macro regimes,
track a multiplex of important Assets, Indices, Bonds and ETF's to derive extra market insights by showing the most important aggregates and their performance over multiple timeframes... and what that might mean for the whole market direction.
For traders and especially investors, the unique functionalities will be of high value.
Quick guide on how to use it:
docs.google.com
WARNING
By the nature of the macro regimes, the outcomes are more accurate over longer Chart Timeframes (Week to Months).
However, it is also a valuable tool to form an advanced,
market realized, short to medium term bias.
NOTE
This Indicator is intended to be used alongside the 1nd part "CE - 42MACRO Equity Factor"
for a more wholistic approach and higher accuracy.
Methodology:
The Equity Factor Table tracks specifically chosen Assets to identify their performance and add the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below Assets:
Convertibles ( AMEX:CWB )
Leveraged Loans ( AMEX:BKLN )
High Yield Credit ( AMEX:HYG )
Preferreds ( NASDAQ:PFF )
Emerging Market US$ Bonds ( NASDAQ:EMB )
Long Bond ( NASDAQ:TLT )
5-10yr Treasurys ( NASDAQ:IEF )
5-10yr TIPS ( AMEX:TIP )
0-5yr TIPS ( AMEX:STIP )
EM Local Currency Bonds ( AMEX:EMLC )
BDCs ( AMEX:BIZD )
Barclays Agg ( AMEX:AGG )
Investment Grade Credit ( AMEX:LQD )
MBS ( NASDAQ:MBB )
1-3yr Treasurys ( NASDAQ:SHY )
Bitcoin ( AMEX:BITO )
Industrial Metals ( AMEX:DBB )
Commodities ( AMEX:DBC )
Gold ( AMEX:GLD )
Equity Volatility ( AMEX:VIXM )
Interest Rate Volatility ( AMEX:PFIX )
Energy ( AMEX:USO )
Precious Metals ( AMEX:DBP )
Agriculture ( AMEX:DBA )
US Dollar ( AMEX:UUP )
Inverse US Dollar ( AMEX:UDN )
Functionalities:
Fixed Income and Macro Table
Shows relative market Asset performance
Comes with different Calculation options like RoC,
Sharpe ratio, Sortino ratio, Omega ratio and Normalization
Allows for advanced market (health) performance
Provides the calculated, realized GRID market regimes
Informs about "Risk ON" and "Risk OFF" market states
Visuals - for your best experience only use one (+ BarColoring) at a time:
You can visualize all important metrics:
- GRID regimes of the currently chosen calculation type
- Risk On/Risk Off with background colouring and additional +1/-1 values
- a smoother GRID model
- a smoother Risk On/ Risk Off metric
- Barcoloring for enabled metric of the above
If you have more suggestions, please write me
Fixed Income and Macro:
The visualisation of the relative performance of the different assets provides valuable information about the current market environment and the actual market performance.
It furthermore makes it possible to obtain a deeper understanding of how the interconnected market works and makes it simple to identify the actual market direction,
thus also providing all the information to derive overall market health, market strength or weakness.
Utility:
The Fixed Income and Macro Table is divided in 4 Columns which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Fixed Income/ Macro Factors:
Are the values green for a specific Column?
If so then the market reflects the corresponding GRID behavior.
Bottom 5 Fixed Income/ Macro Factors:
Are the values red for a specific Column?
If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
******
This Indicator again is based to a majority on 42MACRO's models.
I only brought them into TV and added things on top of it.
If you have questions or need a more in-depth guide DM me.
GM
Multiple Percentile Ranks (up to 5 sources at a time)This indicator is a visual percentile rank indicator that can display 1 to 5 sources at one time.
The options:
“Sources”
Choose the number of sources you would like to display. The minimum is 1, the maximum is 5.
“Label percent position”
The label for the current percentage of where the source candle ranks.
“Label position”
This displays the source/s you’ve selected, and the chosen bottom rank % and top rank %.
“Label text size”
Displays the text size of all labels.
“Display current % labels”
Switches the labels on/off only for the current percentage rank of each source.
Source options:
ATR: Average True Range
CCI: Commodity Channel Index
COG: Centre of Gravity
Close: closing price
Close Percent: close percentage from previous close
Dollar Value: volume * (high * low * close / 3)
EOM: Ease of Movement: how much volume it takes to move the price in a certain direction
OBV: On-Balance Volume
RANGE: percentage range of the close price
RSI: Relative Strength Index
RVI: Relative Vigor Index
Time Close: if you select the 1 second timeframe it will provide the gap of time between each 1 second close
Volume: each bar’s volume
Volume (MA): volume moving average
Source # where # is the number of the source. Selects the source you’d like.
Ma Length is the number of previous candles to consider when calculating the moving average of the source. Note, the “MA Length” only applies to sources that have the “(MA)” at the end of their name.
Bottom % is the bottom percentage rank of the source you’ve selected. This is a filter to display the candle line graph in red once the percentage rank is equal to the percentage you’ve chosen or below.
Top % is the top percentage rank of the source you’ve selected. This is a filter to display the candle line graph in green once the percentage rank is equal to the percentage you’ve chosen or higher.
A simple example of how to use the indicator:
Select the dropdown menu for source 1 and select volume.
As the candles populate, it will look at previous candles and assign a percentage rank of where the candles are in relation to previous candles.
*Note, the way Tradingview works is it will populate the first candle the chart was active, and continue on. So, let’s say the 3rd candle was the highest volume day. This candle will show up as 100%. If the next day, the 4th candle has an even higher volume, it will show up as 100% also, the previous candles won’t “repaint” to other values and are instead set based on when they were confirmed. So, this indicator works best when there are a lot of previous candles to compare itself to.
To use the bottom % rank filter enter a percentage such as 5%. As it comes across a candle that is 5% or less compared to previous volume candles, then the line graph will shade in red.
The same can be said for the top % rank. So, if you want to see the line graph change to green when it comes across the top 99th percentile rank of volume bars, then set the top % rank to 1% and it will give you extremely high-volume bars in green instead of blue.
COT TFF Data (S&P_500_CONSOLIDATED)Commitment of Traders - Traders in Financial Futures (Futures and Options)
Custom python script is used to create the Pinescript strings from a spreadsheet containing the dates + net positions. Data is then input manually in Pinescript (can only fit 4-5 years of data).
This data set is from the: S&P_500_CONSOLIDATED
Source: cftc.gov
COT TFF Data (VIX_FUTURES)Commitment of Traders - Traders in Financial Futures (Futures and Options)
Custom python script is used to create the Pinescript strings from a spreadsheet containing the dates + net positions. Data is then input manually in Pinescript (can only fit 4-5 years of data).
This data set is from the: VIX_FUTURES
Source: cftc.gov
dharmatech : Standard Deviation ChannelDESCRIPTION
Based on version by leojez.
Adds a 3rd standard deviation level.
Twice as fast as original version.
Refactored and simplified source code.
HOW TO USE
Load your chart
Adjust the timeframe and zoom of the chart so that the trend you're interested in is in view.
Add the indicator
Use the measuring tool to measure the number of bars from the start of the trend to the latest candle.
Open settings for the indicator.
Set the length value to the number of bars that you noted.
Value at Risk (VAR)Value at Risk (VAR) is a measure of risk metric in finance used to quantify the potential loss in the value of a portfolio of assets or a single investment in a specific time horizon, given a certain level of confidence.
For instance, lets say there is a VAR of $1000000 at the 95% confidence level in a daily time horizon period, that means that there is a 5% chance that the portfolio will decrease by more than a million within a single day.
Indicator Overview
This indicator calculates the Value at Risk (VAR) using the Variance - Covariance method. On the settings of the indicator you can also determine what significance level you want for the indicator.
Confidence level = 1 - α
α is the significance level.
Basically a 5% significance level will have a 95% Confidence level.
There is also a information tab that displays the Value at Risk (VAR), the Confidence level of the significant level you selected, and an Estimated Range. This is just an estimated range because this is based on returns which follow a normal distributions, unlike price which follows a log normal distribution. So this range will only be obeyed here and then.
Calculation method: Variance - Covariance Method
This method involves the expected return and the standard deviation (volatility). It is based on the assumption that returns follow a normal distribution. For more information on this calculation check this link out.
www.investopedia.com
Applications:
If the calculated Value at Risk (VAR) is high then, that means the risk is high and if the trader has a low risk tolerance then the trader might want to reconsider the trade.
The indicator also lets you see what the potential losses (Long and Short) of the asset can be with the confidence level of your choice.
All Candlestick Patterns on Backtest [By MUQWISHI]▋ INTRODUCTION :
The “All Candlestick Patterns on Backtest” indicator generates a table that offers a clear visualization of the historical return percentages for each candlestick pattern strategy over a specified time period. This table serves as an organized resource, serving as a launching point for in-depth research into candle formations. It may help to rectify any misconceptions surrounding candlestick patterns, refine trading approaches, and it could be foundation to make informed decisions in trading journey.
_______________________
▋ OVERVIEW:
_______________________
▋ CREDIT:
Credit to public technical “*All Candlestick Patterns*” indicator.
_______________________
▋ TABLE:
_______________________
▋ CHART:
_______________________
▋ INDICATOR SETTINGS:
#Section One: Table Setting
#Section Two: Backtest Setting
(1) Backtest Starting Period.
Note: If the datetime of the first candle on the chart is after the entreated datetime, the calculation will start from the first candle on the chart.
(2) Initial Equity ($).
(3) Leverage: Current Equity x Leverage Value.
(4) Entry Mode:
- “At Close”: Execute entry order as soon as the candle confirmed.
- “Breakout High (Low for Short)”: Stop limit buy order, entry order will be executed as soon as the next candle breakout the high of last pattern’s candle (low for short)
(5) Cancel Entry Within Bars: This option is applicable with {Entry Mode = Breakout High (Low for Short)}, to cancel the Entry Order if it's not executed within certain selected number of bars.
(6) Stoploss Range: the range refers to high of pattern - low of pattern.
(7) Risk:Reward: the calculation of risk:reward range start from entry price level. For example: A pattern triggered with range 10 points, and entry price is 100.
- For 1:1~risk:reward would the stoploss at 90 and takeprofit at 110.
- For 1:3~risk:reward would the stoploss at 90 and takeprofit at 130.
#Section Three: Technical & Candle Patterns
_______________________
▋ Comments:
This table was developed for research and educational purposes.
Candlestick patterns are almost similar as seen in “*All Candlestick Patterns*” indicator.
The table results should not be taken as a major concept to build a trading decision.
Personally, I see candlestick patterns as a means to comprehend the psychology of the market, and help to follow the price action.
Please let me know if you have any questions.
Thank you.
CE - 42MACRO Equity Factor Table This is Part 1 of 2 from the 42MACRO Recreation Series
The CE - 42MACRO Equity Factor Table is a whole toolbox packaged in a single indicator.
It aims to provide a probabilistic insight into the market realized GRID Macro Regime, use a multiplex of important Assets and Indices to form a high probability Implied Correlation expectation and allows to derive extra market insights by showing the most important aggregates and their performance over multiple timeframes... and what that might mean for the whole market direction, as well as the underlying asset.
WARNING
By the nature of the macro regimes, the outcomes are more accurate over longer Chart Timeframes (Week to Months).
However, it is also a valuable tool to form a proper,
market realized, short to medium term bias.
NOTE
This Indicator is intended to be used alongside the 2nd part "CE - 42MACRO Yield and Macro"
for a more wholistic approach and higher accuracy.
Due to coding limitations they can not be merged into one Indicator.
Methodology:
The Equity Factor Table tracks specifically chosen Assets to identify their performance and add the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below Assets, with more to come:
Dividend Compounders ( AMEX:SPHD )
Mid Caps ( AMEX:VO )
Emerging Markets ( AMEX:EEM )
Small Caps ( AMEX:IWM )
Mega Cap Growth ( NASDAQ:QQQ )
Brazil ( AMEX:EWZ )
United Kingdom ( AMEX:EWU )
Growth ( AMEX:IWF )
United States ( AMEX:SPY )
Japan ( AMEX:DXJ )
Momentum ( AMEX:MTUM )
China ( AMEX:FXI )
Low Beta ( AMEX:SPLV )
International ex-US ( NASDAQ:ACWX )
India ( AMEX:INDA )
Eurozone ( AMEX:EZU )
Quality ( AMEX:QUAL )
Size ( AMEX:OEF )
Functionalities:
1. Correlations
Takes a measure of Cross Market Correlations
2. Implied Trend
Calculates the trend for each Asset and uses the Correlation to obtain the Implied Trend for the underlying Asset
There are multiple functionalities to enhance Signal Speed and precision...
Reading a signal only over a certain threshold, otherwise being colored in gray to signal noise or unclear market behavior
Normalization of Signal
Double Normalization of Signal for more Speed... ideal for the Crypto Market
Using an additional Hull Moving Average to enhance Signal Speed
Additional simple Background coloring to get a Signal from the HMA
Barcoloring based on the Implied Correlation
3. Equity Factor Table
Shows market realized Asset performance
Provides the approximate realized GRID market regimes
Informs about "Risk ON" and "Risk OFF" market states
Now into the juicy stuff...
Visuals:
There is a variety of options to change visual settings of what is plotted and where
+ additional considerations.
Everything that is relevant in the underlying logic which can improve comprehension can be visualized with these options.
More to come
Market Correlation:
The Market Correlation Table takes the Correlation of all the Assets to the Asset on the Chart,
it furthermore uses the Normalized KAMA Oscillator by IkkeOmar to analyse the current trend of every single Asset.
(To enhance the Signal you can apply the mentioned Indicator on the relevant Assets to find your target Asset movements that you intend to capture...
and then change the length of the Indicator in here)
It then Implies a Correlation based on the Trend and the Correlation to give a probabilistically adjusted expectation for the future Chart Asset Movement.
This is strengthened by taking the average of all Implied Trends.
Thus the Correlation Table provides valuable insights about probabilistically likely Movement of the Asset over the defined time duration,
providing alpha for Traders and Investors alike.
Equity Factors:
The table provides valuable information about the current market environment (whether it's risk on or risk off),
the rough GRID models from 42MACRO and the actual market performance.
This allows you to obtain a deeper understanding of how the market works and makes it simple to identify the actual market direction,
makes it possible to derive overall market Health and shows market strength or weakness.
Utility:
The Equity Factor Table is divided in 4 Sections which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Equity Factors:
Are the values green for a specific Column?
If so then the market reflects the corresponding GRID behavior.
Bottom 5 Equity Factors:
Are the values red for a specific Column?
If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
This whole Indicator, as well as the second part, is based to a majority on 42MACRO's models.
I only brought them into TV and added things on top of it.
If you have questions or need a more in-depth guide DM me.
Will make a guide to all functionalities if necessity becomes apparent.
GM
EMA Screener with Day BreakoutsThe present script is aimed at screening number of stocks as per user input with respect to Daily Exponential Moving Average. Default is set at 200 DEMA, it can be changed by the user from settings menu as per user's preference.
The EMA cell illuminates to Green if Day's Open < EMA
The EMA cell illuminates to Purple if Day's Open > EMA
EMU cell shows the price as, EMA * EMA Price Multiplier (i.e. range below EMA, customizable from settings by user)
EMU cell illuminates to light Green when Price > EMU (i.e. the price is in range of EMA, For example suppose EMA value is 1000 and EMA Price Multiplier is 0.95 then the EMU cell value will be 950 as soon as the price crosses above 950 the EMU cell will get illuminated)
EMD cell shows the price as, EMA * EMA Price Multiplier (i.e. range above EMA, customizable from settings by user)
EMD cell illuminates to red when Price < EMD (i.e. the price is in range of EMA, For example suppose EMA value is 1000 and EMA Price Multiplier is 1.05 then the EMD cell value will be 1050 as soon as the price crosses below 1050 the EMD cell will get illuminated)
The DBO (Day Break Out) cell illuminates to Blue when the current price is near Day's high.
--Dr. Vats
Disclaimer: Only for studying price movement ideas, trading is not advised.
Earnings_MFCThe Earnings_MFC indicator displays statistical information of the price movement of the selected asset as follows:
TAGS: Label on each "earning day" with information on the movement that the price has made from the close of the day before the announcement to:
the opening of the next day (Close to Open - GAP)
the close of the next day (Close to Close - CTC)
HISTOGRAM: Histogram of the times the price has moved in each price band (number of configurable bands).
Each movement has been taken and represented in histogram format, so that visually you can see the number of times the price has exceeded a certain value. Within each band is numbered the number of times the price has reached that area
The histogram has two overlapping data:
....+ A main histogram (red/green stripes)
....+ A secondary histogram (black stripes)
....+ This is so that you can configure which data to see in each one: the GAP movement data or the CTC movement data
The maximum and minimum movement has been indicated (for the main histogram)
It has been indicated, both for positive and negative movements, which is their first (gray) and second (red/green) standard deviation (for the main histogram)
TABLE: A table is included with the following information (you can hide this table):
Summary of statistical data:
....+ Number of samples
....+ Maximum UP movement and average (for both CAP and CTC)
....+ Maximum DOWN movement and average (for both CAP and CTC)
....+ Maximum movement UP or DOWN and average (both for CAP and CTC)
List of all past Earnings (according to the history available in the chart) with their movements
HOW TO USE:
For Options traders it can come in handy to position themselves with Sell PUTs / Sell CALLs / Spreads or Iron Condors. Considering the probabilities of the movement (taking into account that past movements do not ensure future movements), this indicator can help in the decision making for sell strikes.
REMARKS:
Use only in Daily timeframe
Depending on the history of the asset (whether the user is PRO or not FREE) there will be more data
[SS] Linear ModelerHello everyone,
This is the linear modeler indicator.
It is a statistical based indicator that provides a likely price target and range based on a linear regression time series analysis.
To represent it visually, all the indicator does is it represents a linear regression channel and actually plots out the range at various points based on the current trend (see the chart below):
The indicator will perform the same assessment, but give you a working range and timeline for targets.
As well, the indicator will back-test the range and variables to see how it is performing and how reliable the results are likely to be.
General Functions:
In the chart above you can see all the various parameters and functions.
The indicator will display the most likely target (MLT) to be expected within the next pre-determined timeframe (by candles).
So for the first target, the indicator is saying within the next 10 candles, BA's MLT is 221.46 and based on BT results the reliability of this assessment is around 46%.
The indicator will also display the anticipated range at each designated timeframe.
In the chart above, we can see that at 20 candles, the likely range that BA should be trading in is 204 and 238 with a reliability of around 62% based on previous performance.
Plot Functions:
As this is performing a linear time series projection, you can have the indicator plot the projected ranges. Simply go to the settings menu and select the desired forecast length:
This will plot out the desired range and result over the specified time period. Here is an example of BA plotted over the next 50 candles on the hourly:
You can technically use this as an SMA/EMA type indicator, just keep in mind it may be a bit slower than a traditional EMA and SMA indicator, as it is processing a lot of data and plotting out forecasted data as opposed to an SMA or EMA.
If you wish to use it as an EMA or SMA, you can unselect the "Display Chart" Function to hide the table, and you can also select the "Plot Label" function. This will display the current projection analytics directly on your plotted line so you don't need to reference the table at all:
Tips on use:
I use this on the larger and smaller timeframes. On all timeframes, I will look to targets that display 90% to 100% in the BT results.
Bear in mind, this does not mean that we will 100% of the time hit this target, these targets can fail, it just means that there is a higher confidence of hitting this target than other, less reliable targets.
I will plot these targets out if they fall within the implied range of the timeframe I am looking at and will act on them according to the price action.
This is a great indicator to use in combination with other range based indicators. If you use the implied range from options to help guide your trading, you can see which targets are likely to be hit based on the current trend that fall within that implied range.
You can also assess the strength of the trends at various points in time and have an actionable range with a reliability reading at various points in time.
That is pretty much the bulk of the indicator.
Hopefully you find it helpful and useful.
As always, leave your questions and suggestions below.
Thanks for reading and checking it out!
Guassian Distribution Forecast [prediction intervals]The Indicator
The Indicator combines volatility and frequency distributions to forecast an area of possible price expansion with an approximate confidence interval / level and level of significance (significance level).
The Script Formula
Additional comments
To alter the models forecasting precision to reflect a given confidence interval, e.g the 90% confidence level (C.L.), use the 1.64 multiplier (toggle value in "Standard normal distribution sd" setting), to use a specific C.L., e.g. the 85th percentile either search for this on google, or calculate it yourself using a Standard Normal Distribution Probability table. Additionaly volatility may be changed by toggling the lookback period setting, this can be thought of as widening the distribution tails.
The look forward parameter is currently fixed at 20, this is because it does not currently work correctly with higher integers, I will try resolve this problem and any other bugs as soon as possible
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.
Dynamic Liquidity Map [Kioseff Trading]Hello!
Just a quick/fun project here: "Dynamic Heatmap".
This script draws a volume delta or open interest delta heatmap for the asset on your chart.
The adjective "Dynamic" is used for two reasons (:
1: Self-Adjusting Lower Timeframe Data
The script requests ~10 lower timeframe volume and open interest data sets.
When using the fixed range feature the script will, beginning at the start time, check the ~10 requested lower timeframes to see which of the lower timeframes has available data.
The script will always use the lowest timeframe available during the calculation period. As time continues, the script will continue to check if new lower timeframe data (lower than the currently used lowest timeframe) is available. This process repeats until bar time is close enough to the current time that 1-minute data can be retrieved.
The image above exemplifies the process.
Incrementally lower timeframe data will be used as it becomes available.
1: Fixed range capabilities
The script features a "fixed range" tool, where you can manually set a start time (or drag & drop a bar on the chart) to determine the interval the heatmap covers.
From the start date, the script will calculate the calculate the sub-intervals necessary to draw a rows x columns heatmap. Consequently, setting the start time further back will draw a heat map with larger rows x columns, whereas, a start time closer to the current bar time will draw a more "precise" heatmap with smaller rows x columns.
Additionally, the heatmap can be calculated using open interest data.
The image above shows the heatmap displaying open interest delta.
The image above shows alternative settings for the heatmap.
Delta values have been hidden alongside grid border colors. These settings can be replicated to achieve a more "traditional" feel for the heatmap.
Thanks for checking this out!
Session High Low TimestampDescription: Displays the timestamp of the session's high/low. Useful for finding a pattern to day dips/spikes.
Note: Most useful for ETH (extended hours timeframe)
Volume SuperTrend AI (Expo)█ Overview
The Volume SuperTrend AI is an advanced technical indicator used to predict trends in price movements by utilizing a combination of traditional SuperTrend calculation and AI techniques, particularly the k-nearest neighbors (KNN) algorithm.
The Volume SuperTrend AI is designed to provide traders with insights into potential market trends, using both volume-weighted moving averages (VWMA) and the k-nearest neighbors (KNN) algorithm. By combining these approaches, the indicator aims to offer more precise predictions of price trends, offering bullish and bearish signals.
█ How It Works
Volume Analysis: By utilizing volume-weighted moving averages (VWMA), the Volume SuperTrend AI emphasizes the importance of trading volume in the trend direction, allowing it to respond more accurately to market dynamics.
Artificial Intelligence Integration - k-Nearest Neighbors (k-NN) Algorithm: The k-NN algorithm is employed to intelligently examine historical data points, measuring distances between current parameters and previous data. The nearest neighbors are utilized to create predictive modeling, thus adapting to intricate market patterns.
█ How to use
Trend Identification
The Volume SuperTrend AI indicator considers not only price movement but also trading volume, introducing an extra dimension to trend analysis. By integrating volume data, the indicator offers a more nuanced and robust understanding of market trends. When trends are supported by high trading volumes, they tend to be more stable and reliable. In practice, a green line displayed beneath the price typically suggests an upward trend, reflecting a bullish market sentiment. Conversely, a red line positioned above the price signals a downward trend, indicative of bearish conditions.
Trend Continuation signals
The AI algorithm is the fundamental component in the coloring of the Volume SuperTrend. This integration serves as a means of predicting the trend while preserving the inherent characteristics of the SuperTrend. By maintaining these essential features, the AI-enhanced Volume SuperTrend allows traders to more accurately identify and capitalize on trend continuation signals.
TrailingStop
The Volume SuperTrend AI indicator serves as a dynamic trailing stop loss, adjusting with both price movement and trading volume. This approach protects profits while allowing the trade room to grow, taking into account volume for a more nuanced response to market changes.
█ Settings
AI Settings:
Neighbors (k):
This setting controls the number of nearest neighbors to consider in the k-Nearest Neighbors (k-NN) algorithm. By adjusting this parameter, you can directly influence the sensitivity of the model to local fluctuations in the data. A lower value of k may lead to predictions that closely follow short-term trends but may be prone to noise. A higher value of k can provide more stable predictions, considering the broader context of market trends, but might lag in responsiveness.
Data (n):
This setting refers to the number of data points to consider in the model. It allows the user to define the size of the dataset that will be analyzed. A larger value of n may provide more comprehensive insights by considering a wider historical context but can increase computational complexity. A smaller value of n focuses on more recent data, possibly providing quicker insights but might overlook longer-term trends.
AI Trend Settings:
Price Trend & Prediction Trend:
These settings allow you to adjust the lengths of the weighted moving averages that are used to calculate both the price trend and the prediction trend. Shorter lengths make the trends more responsive to recent price changes, capturing quick market movements. Longer lengths smooth out the trends, filtering out noise, and highlighting more persistent market directions.
AI Trend Signals:
This toggle option enables or disables the trend signals generated by the AI. Activating this function may assist traders in identifying key trend shifts and opportunities for entry or exit. Disabling it may be preferred when focusing on other aspects of the analysis.
Super Trend Settings:
Length:
This setting determines the length of the SuperTrend, affecting how it reacts to price changes. A shorter length will produce a more sensitive SuperTrend, reacting quickly to price fluctuations. A longer length will create a smoother SuperTrend, reducing false alarms but potentially lagging behind real market changes.
Factor:
This parameter is the multiplier for the Average True Range (ATR) in SuperTrend calculation. By adjusting the factor, you can control the distance of the SuperTrend from the price. A higher factor makes the SuperTrend further from the price, giving more room for price movement but possibly missing shorter-term signals. A lower factor brings the SuperTrend closer to the price, making it more reactive but possibly more prone to false signals.
Moving Average Source:
This setting lets you choose the type of moving average used for the SuperTrend calculation, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), etc.
Different types of moving averages provide various characteristics to the SuperTrend, enabling customization to align with individual trading strategies and market conditions.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Seasonal - Trading Day of MonthIndicator Description: Historical Comparative Price Analysis
The Historical Comparative Price Analysis indicator serves as a comprehensive tool for evaluating price changes over distinct trading periods. By configuring the date settings, the indicator captures the percentage change data for each individual day or month, facilitating a clear historical perspective. Each year is represented in a separate row, allowing for a side-by-side presentation of corresponding data for the same trading day or week.
Within the "Summary" row, the indicator calculates the average change for each selected trading day within a specified time frame. This calculation, rooted in Larry Williams' concept, considers trading days rather than calendar days. The "Summary" row provides a quick insight into whether the current price change exceeds or falls short of the average change within the chosen time frame.
The indicator's final row presents a comprehensive overview, including the maximum and minimum average changes. It showcases the closing price from the first column of the 10th row, aiding in distinguishing between the last trading day of the month and the first trading day, which varies due to different market opening times.
To enhance visual analysis, the indicator attempts to display the price average of the chosen time frame as a reference line on the chart. The maximum and minimum values are added or subtracted from the reference line to create an average price channel. The color of the candlesticks dynamically changes to indicate whether the current price change is above or below the average.
For optimal results, we recommend selecting the previous year's data and the current month's data from the 1st to the 31st day. In weekly charts, multiple months can be selected to provide a broader perspective on price trends.
Enhance your trading insights with the Historical Comparative Price Analysis indicator, and gain a deeper understanding of how current price changes relate to historical averages.
Note: This description is intended for educational and informational purposes and is not intended as financial advice. Always conduct your research and analysis before making trading decisions.
Symbol Searcher [EmuMoon]Introducing the EmuMoon 'Symbol Searcher'. Your go-to tool for quickly comparing and discovering the best coins/symbols to trade.
With this nifty tool, you can easily search and compare 40+ different coins/symbols simultaneously to find the most volatile ones, while also identifying coins that are already correlated to the ones you're trading. That way, you can diversify your portfolio and avoid putting all your eggs in one basket.🧺🐣
The Symbol Searcher lets you sort by volatility, correlation and weighted combinations of both. You can even input your own coins/symbols to see how they stack up. It's a fun way to explore the crypto/trading market and find new opportunities.
You can also add the 'Symbol Searcher' to the chart multiple times to display even more symbols. This works excellent with the other DCA Tools that are Advanced!
Features
The EmuMoon 'Symbol Searcher' has a number of features, including:
• Optimal Coin Selection - The 'Top Picks' Table automatically populates with coins/symbols exhibiting the most desirable values that are well suited to trading.
• 'Sort By' Drop-Down - Explore a wide range of sorting options to discover coins/symbols that align with your target goals and preferences.
• Lookback Duration - Small or broad, you can specify the quantity of bars/candles that are used when performing internal calculations.
• Customisable View - Choose the Quantity of Pairs to Compare and also separately choose the Quantity of Pairs to Display.
• Real-Time Data - Receive up-to-the-minute data on coins/symbols, pick any time frame interval to make informed and timely choices.
• Quick & Easy - You can search, compare and analyse a wide range of coins with speed and convenience and no complex setup.
• Default Pairs - Carefully selected from Binance USDT Spot, the top 40 pairs with a 'Maximum Supply' based on the highest statistics at the time of creating. Add your own at any time.
• Connectivity - Use on the go, on any device. Settings menu and display tables have been optimized to look great on Mobile as well as PC, Browser, App, Laptop, Mobile, Tablet etc.
• Fast Loading - Streamlined array/table structure means enhanced script compile times, significantly improving script compiling times and timeout errors.
Settings
• Show Main Table - Show or hide the main coin selection table.
• Display X Pairs - Choose how many pairs to display.
• Compare X Pairs - Choose how many pairs to compare.
• Lookback - Choose the quantity of bars/candles to be used for the Correlation and Volatility calculations.
• Sort By - Choose how the main table is sorted.
• Show Top Picks Table - Show or hide the Top Picks Table.
• + Corr X Vol - Choose the quantity of High Correlation + High Volatility coins to show on the Top Picks Table.
• - Corr X Vol - Choose the quantity of Low Correlation + High Volatility coins to show on the Top Picks Table.
• o Corr X Vol - Choose the quantity of Neutral Correlation + High Volatility coins to show on the Top Picks Table.
• Symbol Input 1 - To check for correlation, the script utilizes coin slot number 1 as a reference, comparing it against all the coins numbered 2~40.
• Symbol Inputs 2~40 - Customize the coin inputs (2~40) according to your preference.
• Table Position - Adjust location of table plotted on chart. You can also add the 'Symbol Searcher' to the chart multiple times to display even more symbols. 🎉
• Info & Help - Some great information about the script and its features
• Text Size - Whether you are on PC, App, or Tablet, you can adjust the view to fit your device.
Usage
While statistics provide valuable insights, they should not be solely relied upon as an indicator of future results. This script serves as a tool traders can utilise to help gain an overview of the market landscape, and quickly compare and identify potential opportunities, enhancing their decision-making process. To use the indicator, simply input your chosen coins/symbols or use the defaults, select the quantity you want to compare, choose a sorting option, you can also generate a Top Picks list based on the highest performing values by using the +/-/o Corr X Vol quantity selections.
Clownpumps Higher/Lower Close Analysis (HLCA) IndicatorThe Clownpumps Higher/Lower Close Analysis" (HLCA) indicator offers a visual breakdown of the weekly behavior of a market, illustrating how often it closes higher or lower than its opening price. This comprehensive tool assists traders and analysts in pinpointing recurrent patterns that pertain to specific weekdays, forming a solid basis for a systematic trading strategy.
Features and Interpretation:
Color-Coded Analysis: The HLCA uses two intuitive colors to depict the daily trend:
Green: Indicates that, on average, the market closes higher than its opening price more frequently on that day.
Red: Highlights days when the market generally closes lower than its opening price.
Identifying Recurrent Patterns: Using the HLCA can reveal if a specific weekday consistently sees an asset closing higher or lower. For example, a consistent bullish sentiment on Mondays for a particular stock becomes easily observable.
Comparative Analysis: Deploying the HLCA across a range of assets can uncover trends that are either sector-wide or unique to individual stocks or cryptocurrencies.
Strategic Entry & Exit Points: Knowledge of which days an asset generally closes higher can guide traders in timing their market entries and exits.
Complementary to Other Tools: While the HLCA is a robust tool in itself, its true potential is unlocked when used in tandem with other market indicators. Pairing the daily closing patterns with volume data, for instance, can shed light on the strength of the observed trends.
Cautionary Notes:
Past behavior doesn't predict future performance. Always remember that correlation doesn't guarantee causation, especially when external market-shifting events come into play.
It's recommended to backtest any insights on historical data before committing to live trades.
