Adjust Asset for Future Interest (Brazil)Este script foi criado para ajustar o preço de um ativo com base na taxa de juros DI11!, que reflete a expectativa do mercado para os juros futuros. O objetivo é mostrar como o valor do ativo seria influenciado se fosse diretamente ajustado pela variação dessa taxa de juros.
Como funciona?
Preço do Ativo
O script começa capturando o preço de fechamento do ativo que está sendo visualizado no gráfico. Esse é o ponto de partida para o cálculo.
Taxa de Juros DI11!
Em seguida, ele busca os valores diários da taxa DI11! no mercado. Esta taxa é uma referência de juros de curto prazo, usada para ajustes financeiros e projeções econômicas.
Fator de Ajuste
Com a taxa de juros DI11!, o script calcula um fator de ajuste simples:
Fator de Ajuste
=
1
+
DI11
100
Fator de Ajuste=1+
100
DI11
Esse fator traduz a taxa percentual em um multiplicador aplicado ao preço do ativo.
Cálculo do Ativo Ajustado
Multiplica o preço do ativo pelo fator de ajuste para obter o valor ajustado do ativo. Este cálculo mostra como o preço seria se fosse diretamente influenciado pela variação da taxa DI11!.
Exibição no Gráfico
O script plota o preço ajustado do ativo como uma linha azul no gráfico, com maior espessura para facilitar a visualização. O resultado é uma curva que reflete o impacto teórico da taxa de juros DI11! sobre o ativo.
Utilidade
Este indicador é útil para entender como as taxas de juros podem influenciar ativos financeiros de forma hipotética. Ele é especialmente interessante para analistas que desejam avaliar a relação entre o mercado de renda variável e as condições de juros no curto prazo.
This script was created to adjust the price of an asset based on the DI11! interest rate, which reflects the market's expectation for future interest rates. The goal is to show how the asset's value would be influenced if it were directly adjusted by the variation of this interest rate.
How does it work?
Asset Price
The script starts by capturing the closing price of the asset that is being viewed on the chart. This is the starting point for the calculation.
DI11! Interest Rate
The script then searches for the daily values of the DI11! rate in the market. This rate is a short-term interest reference, used for financial adjustments and economic projections.
Adjustment Factor
With the DI11! interest rate, the script calculates a simple adjustment factor:
Adjustment Factor
=
1
+
DI11
100
Adjustment Factor=1+
100
DI11
This factor translates the percentage rate into a multiplier applied to the asset's price.
Adjusted Asset Calculation
Multiplies the asset price by the adjustment factor to obtain the adjusted asset value. This calculation shows how the price would be if it were directly influenced by the variation of the DI11! rate.
Display on the Chart
The script plots the adjusted asset price as a blue line on the chart, with greater thickness for easier visualization. The result is a curve that reflects the theoretical impact of the DI11! interest rate on the asset.
Usefulness
This indicator is useful for understanding how interest rates can hypothetically influence financial assets. It is especially interesting for analysts who want to assess the relationship between the equity market and short-term interest rate conditions.
Statistics
12 Month Difference - YoY ComparisonEste script foi desenvolvido para calcular e exibir a variação percentual do preço de um ativo nos últimos 12 meses, de forma simples e visual. Ele utiliza dados históricos de preços e apresenta o resultado diretamente no gráfico, permitindo ao usuário acompanhar a relação entre o valor atual e o valor de 12 meses atrás.
O cálculo é baseado em um período de 12 meses, que equivale a 252 dias úteis no mercado financeiro. O script primeiro identifica o preço atual do ativo e o compara com o preço registrado há exatamente 252 dias úteis. A diferença entre esses dois valores é transformada em uma variação percentual, o que facilita a análise de desempenho do ativo ao longo do período.
Além disso, o script define uma cor para destacar o resultado:
Verde, se a variação percentual for positiva (indicando crescimento).
Vermelho, se a variação for negativa (indicando queda).
O valor calculado é exibido de forma prática no canto inferior direito do gráfico, como uma tabela flutuante. Essa tabela contém o texto "Relação 12M" e o valor percentual correspondente, permitindo uma leitura rápida.
Embora o resultado seja calculado para todos os momentos no gráfico, ele é mostrado apenas como uma tabela no último ponto confirmado da série histórica, ou seja, no momento mais recente com dados disponíveis. Além disso, o script inclui o valor da relação na legenda do gráfico, mas ele está oculto visualmente para evitar sobrecarregar o layout.
Esse indicador é útil para analisar rapidamente o desempenho de um ativo ao longo de um ano, ajudando investidores e analistas a entenderem tendências e mudanças no mercado.
This script was developed to calculate and display the percentage change in the price of an asset over the last 12 months, in a simple and visual way. It uses historical price data and displays the result directly on the chart, allowing the user to monitor the relationship between the current value and the value from 12 months ago.
The calculation is based on a 12-month period, which is equivalent to 252 business days in the financial market. The script first identifies the current price of the asset and compares it with the price recorded exactly 252 business days ago. The difference between these two values is transformed into a percentage change, which makes it easier to analyze the asset's performance over the period.
In addition, the script defines a color to highlight the result:
Green, if the percentage change is positive (indicating growth).
Red, if the change is negative (indicating a decline).
The calculated value is displayed conveniently in the bottom right corner of the chart, as a floating table. This table contains the text "12M Ratio" and the corresponding percentage value, allowing for quick reading.
Although the result is calculated for all points in time on the chart, it is only displayed as a table at the last confirmed point in the historical series, i.e. the most recent point in time with available data. In addition, the script includes the ratio value in the chart legend, but it is visually hidden to avoid cluttering the layout.
This indicator is useful for quickly analyzing the performance of an asset over a year, helping investors and analysts understand trends and changes in the market.
Brazil Real Interest RateEste script foi criado para calcular e exibir a Taxa de Juros Real, permitindo compreender o impacto da inflação sobre os juros nominais do mercado. Ele utiliza dois indicadores principais: a taxa de juros nominal, que reflete os juros antes de considerar a inflação, e a taxa de inflação anual, que mede o aumento dos preços em um ano.
O script funciona da seguinte forma: ele obtém diariamente os dados da taxa de juros nominal (representada pelo contrato futuro DI1) e da inflação anual (indicada pelo BRIRYY). Esses valores são processados para calcular a taxa de juros real, utilizando a fórmula de Fisher, que ajusta os juros nominais ao descontar o efeito da inflação. O resultado é uma medida mais precisa do retorno ou custo real, considerando o poder de compra.
Depois de realizar o cálculo, o script exibe a Taxa de Juros Real diretamente no gráfico, representada por uma linha verde. Isso permite acompanhar, de forma clara e visual, como a inflação e os juros afetam o cenário econômico ao longo do tempo.
This script was created to calculate and display the Real Interest Rate, allowing us to understand the impact of inflation on nominal market interest rates. It uses two main indicators: the nominal interest rate, which reflects interest rates before considering inflation, and the annual inflation rate, which measures the increase in prices over a year.
The script works as follows: it obtains daily data on the nominal interest rate (represented by the DI1 futures contract) and annual inflation (indicated by BRIRYY). These values are processed to calculate the real interest rate, using the Fisher formula, which adjusts nominal interest rates by discounting the effect of inflation. The result is a more accurate measure of real return or cost, considering purchasing power.
After performing the calculation, the script displays the Real Interest Rate directly on the graph, represented by a green line. This allows you to monitor, clearly and visually, how inflation and interest rates affect the economic scenario over time.
lib_divergenceLibrary "lib_divergence"
offers a commonly usable function to detect divergences. This will take the default RSI or other symbols / indicators / oscillators as source data.
divergence(osc, pivot_left_bars, pivot_right_bars, div_min_range, div_max_range, ref_low, ref_high, min_divergence_offset_fraction, min_divergence_offset_dev_len, min_divergence_offset_atr_mul)
Detects Divergences between Price and Oscillator action. For bullish divergences, look at trend lines between lows. For bearish divergences, look at trend lines between highs. (strong) oscillator trending, price opposing it | (medium) oscillator trending, price trend flat | (weak) price opposite trending, oscillator trend flat | (hidden) price trending, oscillator opposing it. Pivot detection is only properly done in oscillator data, reference price data is only compared at the oscillator pivot (speed optimization)
Parameters:
osc (float) : (series float) oscillator data (can be anything, even another instrument price)
pivot_left_bars (simple int) : (simple int) optional number of bars left of a confirmed pivot point, confirming it is the highest/lowest in the range before and up to the pivot (default: 5)
pivot_right_bars (simple int) : (simple int) optional number of bars right of a confirmed pivot point, confirming it is the highest/lowest in the range from and after the pivot (default: 5)
div_min_range (simple int) : (simple int) optional minimum distance to the pivot point creating a divergence (default: 5)
div_max_range (simple int) : (simple int) optional maximum amount of bars in a divergence (default: 50)
ref_low (float) : (series float) optional reference range to compare the oscillator pivot points to. (default: low)
ref_high (float) : (series float) optional reference range to compare the oscillator pivot points to. (default: high)
min_divergence_offset_fraction (simple float) : (simple float) optional scaling factor for the offset zone (xDeviation) around the last oscillator H/L detecting following equal H/Ls (default: 0.01)
min_divergence_offset_dev_len (simple int) : (simple int) optional lookback distance for the deviation detection for the offset zone around the last oscillator H/L detecting following equal H/Ls. Used as well for the ATR that does the equal H/L detection for the reference price. (default: 14)
min_divergence_offset_atr_mul (simple float) : (simple float) optional scaling factor for the offset zone (xATR) around the last price H/L detecting following equal H/Ls (default: 1)
@return A tuple of deviation flags.
Calculate Order Entry Units based on set Dollar ValuesFUNCTIONS
- Calculate UNITS quantity based on user's input dollar values.
- Show Units in table
USAGE
- Enter 6 usual order $ values
- Use units value in order entry
Tradingview doesn't have order entry in dollar value for most connections/exchanges so it's really tedious to calculate Units some other way every time.
This gives you the Units based on your most used order value sizes in a quick way.
Possible future updates
- Allow user settings for number of values to display
- Allow user option to set titles for each row
Note:
Tradingview really need to get off their butts and give us a real DOM panel and working dollar value order entry for all exchanges among other order entry panel updates.
I hope everyone is suggesting this to them.
QTALibrary "QTA"
This is simple library for basic Quantitative Technical Analysis for retail investors. One example of it being used can be seen here ().
calculateKellyRatio(returns)
Parameters:
returns (array) : An array of floats representing the returns from bets.
Returns: The calculated Kelly Ratio, which indicates the optimal bet size based on winning and losing probabilities.
calculateAdjustedKellyFraction(kellyRatio, riskTolerance, fedStance)
Parameters:
kellyRatio (float) : The calculated Kelly Ratio.
riskTolerance (float) : A float representing the risk tolerance level.
fedStance (string) : A string indicating the Federal Reserve's stance ("dovish", "hawkish", or neutral).
Returns: The adjusted Kelly Fraction, constrained within the bounds of .
calculateStdDev(returns)
Parameters:
returns (array) : An array of floats representing the returns.
Returns: The standard deviation of the returns, or 0 if insufficient data.
calculateMaxDrawdown(returns)
Parameters:
returns (array) : An array of floats representing the returns.
Returns: The maximum drawdown as a percentage.
calculateEV(avgWinReturn, winProb, avgLossReturn)
Parameters:
avgWinReturn (float) : The average return from winning bets.
winProb (float) : The probability of winning a bet.
avgLossReturn (float) : The average return from losing bets.
Returns: The calculated Expected Value of the bet.
calculateTailRatio(returns)
Parameters:
returns (array) : An array of floats representing the returns.
Returns: The Tail Ratio, or na if the 5th percentile is zero to avoid division by zero.
calculateSharpeRatio(avgReturn, riskFreeRate, stdDev)
Parameters:
avgReturn (float) : The average return of the investment.
riskFreeRate (float) : The risk-free rate of return.
stdDev (float) : The standard deviation of the investment's returns.
Returns: The calculated Sharpe Ratio, or na if standard deviation is zero.
calculateDownsideDeviation(returns)
Parameters:
returns (array) : An array of floats representing the returns.
Returns: The standard deviation of the downside returns, or 0 if no downside returns exist.
calculateSortinoRatio(avgReturn, downsideDeviation)
Parameters:
avgReturn (float) : The average return of the investment.
downsideDeviation (float) : The standard deviation of the downside returns.
Returns: The calculated Sortino Ratio, or na if downside deviation is zero.
calculateVaR(returns, confidenceLevel)
Parameters:
returns (array) : An array of floats representing the returns.
confidenceLevel (float) : A float representing the confidence level (e.g., 0.95 for 95% confidence).
Returns: The Value at Risk at the specified confidence level.
calculateCVaR(returns, varValue)
Parameters:
returns (array) : An array of floats representing the returns.
varValue (float) : The Value at Risk threshold.
Returns: The average Conditional Value at Risk, or na if no returns are below the threshold.
calculateExpectedPriceRange(currentPrice, ev, stdDev, confidenceLevel)
Parameters:
currentPrice (float) : The current price of the asset.
ev (float) : The expected value (in percentage terms).
stdDev (float) : The standard deviation (in percentage terms).
confidenceLevel (float) : The confidence level for the price range (e.g., 1.96 for 95% confidence).
Returns: A tuple containing the minimum and maximum expected prices.
calculateRollingStdDev(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling standard deviation of returns.
calculateRollingVariance(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling variance of returns.
calculateRollingMean(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling mean of returns.
calculateRollingCoefficientOfVariation(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling coefficient of variation of returns.
calculateRollingSumOfPercentReturns(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling sum of percent returns.
calculateRollingCumulativeProduct(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling cumulative product of returns.
calculateRollingCorrelation(priceReturns, volumeReturns, window)
Parameters:
priceReturns (array) : An array of floats representing the price returns.
volumeReturns (array) : An array of floats representing the volume returns.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling correlation.
calculateRollingPercentile(returns, window, percentile)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
percentile (int) : An integer representing the desired percentile (0-100).
Returns: An array of floats representing the rolling percentile of returns.
calculateRollingMaxMinPercentReturns(returns, window)
Parameters:
returns (array) : An array of floats representing the returns.
window (int) : An integer representing the rolling window size.
Returns: A tuple containing two arrays: rolling max and rolling min percent returns.
calculateRollingPriceToVolumeRatio(price, volData, window)
Parameters:
price (array) : An array of floats representing the price data.
volData (array) : An array of floats representing the volume data.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the rolling price-to-volume ratio.
determineMarketRegime(priceChanges)
Parameters:
priceChanges (array) : An array of floats representing the price changes.
Returns: A string indicating the market regime ("Bull", "Bear", or "Neutral").
determineVolatilityRegime(price, window)
Parameters:
price (array) : An array of floats representing the price data.
window (int) : An integer representing the rolling window size.
Returns: An array of floats representing the calculated volatility.
classifyVolatilityRegime(volatility)
Parameters:
volatility (array) : An array of floats representing the calculated volatility.
Returns: A string indicating the volatility regime ("Low" or "High").
method percentPositive(thisArray)
Returns the percentage of positive non-na values in this array.
This method calculates the percentage of positive values in the provided array, ignoring NA values.
Namespace types: array
Parameters:
thisArray (array)
_candleRange()
_PreviousCandleRange(barsback)
Parameters:
barsback (int) : An integer representing how far back you want to get a range
redCandle()
greenCandle()
_WhiteBody()
_BlackBody()
HighOpenDiff()
OpenLowDiff()
_isCloseAbovePreviousOpen(length)
Parameters:
length (int)
_isCloseBelowPrevious()
_isOpenGreaterThanPrevious()
_isOpenLessThanPrevious()
BodyHigh()
BodyLow()
_candleBody()
_BodyAvg(length)
_BodyAvg function.
Parameters:
length (simple int) : Required (recommended is 6).
_SmallBody(length)
Parameters:
length (simple int) : Length of the slow EMA
Returns: a series of bools, after checking if the candle body was less than body average.
_LongBody(length)
Parameters:
length (simple int)
bearWick()
bearWick() function.
Returns: a SERIES of FLOATS, checks if it's a blackBody(open > close), if it is, than check the difference between the high and open, else checks the difference between high and close.
bullWick()
barlength()
sumbarlength()
sumbull()
sumbear()
bull_vol()
bear_vol()
volumeFightMA()
volumeFightDelta()
weightedAVG_BullVolume()
weightedAVG_BearVolume()
VolumeFightDiff()
VolumeFightFlatFilter()
avg_bull_vol(userMA)
avg_bull_vol(int) function.
Parameters:
userMA (int)
avg_bear_vol(userMA)
avg_bear_vol(int) function.
Parameters:
userMA (int)
diff_vol(userMA)
diff_vol(int) function.
Parameters:
userMA (int)
vol_flat(userMA)
vol_flat(int) function.
Parameters:
userMA (int)
_isEngulfingBullish()
_isEngulfingBearish()
dojiup()
dojidown()
EveningStar()
MorningStar()
ShootingStar()
Hammer()
InvertedHammer()
BearishHarami()
BullishHarami()
BullishBelt()
BullishKicker()
BearishKicker()
HangingMan()
DarkCloudCover()
Watermark with dynamic variables [BM]█ OVERVIEW
This indicator allows users to add highly customizable watermark messages to their charts. Perfect for branding, annotation, or displaying dynamic chart information, this script offers advanced customization options including dynamic variables, text formatting, and flexible positioning.
█ CONCEPTS
Watermarks are overlay messages on charts. This script introduces placeholders — special keywords wrapped in % signs — that dynamically replace themselves with chart-related data. These watermarks can enhance charts with context, timestamps, or branding.
█ FEATURES
Dynamic Variables : Replace placeholders with real-time data such as bar index, timestamps, and more.
Advanced Customization : Modify text size, color, background, and alignment.
Multiple Messages : Add up to four independent messages per group, with two groups supported (A and B).
Positioning Options : Place watermarks anywhere on the chart using predefined locations.
Timezone Support : Display timestamps in a preferred timezone with customizable formats.
█ INPUTS
The script offers comprehensive input options for customization. Each Watermark (A and B) contains identical inputs for configuration.
Watermark settings are divided into two levels:
Watermark-Level Settings
These settings apply to the entire watermark group (A/B):
Show Watermark: Toggle the visibility of the watermark group on the chart.
Position: Choose where the watermark group is displayed on the chart.
Reverse Line Order: Enable to reverse the order of the lines displayed in Watermark A.
Message-Level Settings
Each watermark contains up to four configurable messages. These messages can be independently customized with the following options:
Message Content: Enter the custom text to be displayed. You can include placeholders for dynamic data.
Text Size: Select from predefined sizes (Tiny, Small, Normal, Large, Huge) or specify a custom size.
Text Alignment and Colors:
- Adjust the alignment of the text (Left, Center, Right).
- Set text and background colors for better visibility.
Format Time: Enable time formatting for this watermark message and configure the format and timezone. The settings for each message include message content, text size, alignment, and more. Please refer to Formatting dates and times for more details on valid formatting tokens.
█ PLACEHOLDERS
Placeholders are special keywords surrounded by % signs, which the script dynamically replaces with specific chart-related data. These placeholders allow users to insert dynamic content, such as bar information or timestamps, into watermark messages.
Below is the complete list of currently available placeholders:
bar_index , barstate.isconfirmed , barstate.isfirst , barstate.ishistory , barstate.islast , barstate.islastconfirmedhistory , barstate.isnew , barstate.isrealtime , chart.is_heikinashi , chart.is_kagi , chart.is_linebreak , chart.is_pnf , chart.is_range , chart.is_renko , chart.is_standard , chart.left_visible_bar_time , chart.right_visible_bar_time , close , dayofmonth , dayofweek , dividends.future_amount , dividends.future_ex_date , dividends.future_pay_date , earnings.future_eps , earnings.future_period_end_time , earnings.future_revenue , earnings.future_time , high , hl2 , hlc3 , hlcc4 , hour , last_bar_index , last_bar_time , low , minute , month , ohlc4 , open , second , session.isfirstbar , session.isfirstbar_regular , session.islastbar , session.islastbar_regular , session.ismarket , session.ispostmarket , session.ispremarket , syminfo.basecurrency , syminfo.country , syminfo.currency , syminfo.description , syminfo.employees , syminfo.expiration_date , syminfo.industry , syminfo.main_tickerid , syminfo.mincontract , syminfo.minmove , syminfo.mintick , syminfo.pointvalue , syminfo.prefix , syminfo.pricescale , syminfo.recommendations_buy , syminfo.recommendations_buy_strong , syminfo.recommendations_date , syminfo.recommendations_hold , syminfo.recommendations_sell , syminfo.recommendations_sell_strong , syminfo.recommendations_total , syminfo.root , syminfo.sector , syminfo.session , syminfo.shareholders , syminfo.shares_outstanding_float , syminfo.shares_outstanding_total , syminfo.target_price_average , syminfo.target_price_date , syminfo.target_price_estimates , syminfo.target_price_high , syminfo.target_price_low , syminfo.target_price_median , syminfo.ticker , syminfo.tickerid , syminfo.timezone , syminfo.type , syminfo.volumetype , ta.accdist , ta.iii , ta.nvi , ta.obv , ta.pvi , ta.pvt , ta.tr , ta.vwap , ta.wad , ta.wvad , time , time_close , time_tradingday , timeframe.isdaily , timeframe.isdwm , timeframe.isintraday , timeframe.isminutes , timeframe.ismonthly , timeframe.isseconds , timeframe.isticks , timeframe.isweekly , timeframe.main_period , timeframe.multiplier , timeframe.period , timenow , volume , weekofyear , year
█ HOW TO USE
1 — Add the Script:
Apply "Watermark with dynamic variables " to your chart from the TradingView platform.
2 — Configure Inputs:
Open the script settings by clicking the gear icon next to the script's name.
Customize visibility, message content, and appearance for Watermark A and Watermark B.
3 — Utilize Placeholders:
Add placeholders like %bar_index% or %timenow% in the "Watermark - Message" fields to display dynamic data.
Empty lines in the message box are reflected on the chart, allowing you to shift text up or down.
Using in the message box translates to a new line on the chart.
4 — Preview Changes:
Adjust settings and view updates in real-time on your chart.
█ EXAMPLES
Branding
DodgyDD's charts
Debugging
█ LIMITATIONS
Only supports variables defined within the script.
Limited to four messages per watermark.
Visual alignment may vary across different chart resolutions or zoom levels.
Placeholder parsing relies on correct input formatting.
█ NOTES
This script is designed for users seeking enhanced chart annotation capabilities. It provides tools for dynamic, customizable watermarks but is not a replacement for chart objects like text labels or drawings. Please ensure placeholders are properly formatted for correct parsing.
Additionally, this script can be a valuable tool for Pine Script developers during debugging . By utilizing dynamic placeholders, developers can display real-time values of variables and chart data directly on their charts, enabling easier troubleshooting and code validation.
Supertrend StatsSupertrend with Probabilistic Stats and MA Filter
Overview: The Supertrend with Probabilistic Stats and MA Filter is a comprehensive TradingView Pine Script indicator designed to enhance trading strategies by combining the trend-detection capabilities of the Supertrend indicator with the trend-confirmation strength of Moving Averages (MA). Additionally, it offers robust statistical tracking to provide traders with valuable insights into the performance and reliability of their trading signals.
Key Features:
Supertrend Indicator Integration:
Trend Detection: Utilizes the Supertrend algorithm to identify prevailing market trends.
Buy/Sell Signals: Generates clear buy and sell signals based on trend reversals.
Customizable Parameters: Allows adjustment of ATR period and multiplier to suit different trading styles and market conditions.
Visual Aids: Plots Supertrend lines on the chart and highlights trend areas for easy visualization.
Moving Average (MA) Filter:
Trend Confirmation: Filters buy signals to occur only when the open price is above the MA and sell signals only when the open price is below the MA.
Customizable MA Types: Supports various MA types, including SMA, EMA, SMMA (RMA), WMA, and VWMA.
Flexible Configuration: Offers options to enable/disable the MA filter, select MA type, set MA length, and adjust MA source and offset.
Statistical Tracking:
Trimmed Mean Calculation: Computes trimmed means for bullish and bearish movements, removing outliers to provide a more accurate average movement.
Success Rate Metrics: Calculates the success rates (%) for both bullish and bearish signals, indicating the percentage of signals that resulted in favorable price movements.
Candle Count Analysis: Tracks the average number of candles each bullish and bearish move lasts, offering insights into the duration of trends.
Data Visualization: Presents all statistical data in a neatly formatted table on the chart, allowing for quick reference and analysis.
Customizable Statistics Table:
Text Color Customization: Provides an option to change the table text color to match personal preferences or chart aesthetics, enhancing readability.
Comprehensive Metrics: Displays key statistics such as Bullish/Bearish Averages, Counts, Success Rates, and Average Candle Counts.
Optional Pinbar Filtering:
Signal Refinement: Adds an additional layer of signal confirmation by filtering buy and sell signals based on pinbar candlestick patterns.
Adjustable Thresholds: Allows customization of the pinbar wick threshold to fine-tune signal accuracy.
Visual Enhancements:
Markers: Optionally displays markers on the first and last candles of bullish and bearish moves for better trend identification.
Highlighter: Shades the chart background to indicate current trend direction, aiding in visual trend recognition.
How It Works:
Trend Identification with Supertrend:
The indicator calculates the Supertrend based on user-defined ATR periods and multipliers.
It plots the Supertrend lines and generates buy/sell signals when the price crosses these lines, indicating a potential trend reversal.
Filtering Signals with Moving Average:
When the MA filter is enabled, the indicator ensures that buy signals are only considered valid if the candle's open price is above the selected MA, and sell signals only if the open price is below the MA.
This additional confirmation aligns trades with the broader market trend, potentially increasing signal reliability.
Statistical Analysis:
Upon triggering a buy or sell signal, the indicator records the entry price and tracks the subsequent price movements.
It calculates trimmed means to assess average movements while excluding extreme outliers.
Success rates are computed by comparing the closing price against the entry price, indicating how often signals result in favorable outcomes.
The average number of candles per move provides insight into trend duration and volatility.
Visualization and Customization:
All statistical data is presented in a table on the chart, with customizable text colors for enhanced readability.
Optional pinbar filtering and visual markers further refine and illustrate trading signals, aiding in decision-making.
Benefits to Traders:
Enhanced Signal Reliability:
By combining Supertrend with an MA filter, the indicator ensures that only signals aligning with the broader market trend are considered, potentially reducing false signals.
Data-Driven Decision Making:
The comprehensive statistical tracking offers traders insights into the performance of their signals, enabling informed adjustments to their trading strategies based on empirical data.
Trend Confirmation and Alignment:
The MA filter acts as a trend confirmation tool, ensuring that trades are placed in the direction of the prevailing trend, which can enhance the probability of successful trades.
Performance Metrics at a Glance:
The statistics table provides all necessary performance metrics in a single view, allowing traders to quickly assess the effectiveness of their strategy without sifting through extensive data.
Customization and Flexibility:
With options to adjust MA types, lengths, and table text colors, traders can tailor the indicator to fit their specific preferences and trading environments.
Visual Clarity and Aids:
The plotted Supertrend lines, MA line, signal markers, and highlighter enhance visual clarity, making it easier to identify trends and potential trade opportunities on the chart.
Usage Instructions:
Adding the Indicator:
Copy the Script: Select and copy the entire Pine Script provided.
Open TradingView: Navigate to TradingView and open your desired asset's chart.
Access Pine Editor: Click on the Pine Editor tab at the bottom of the TradingView interface.
Paste and Add to Chart: Paste the script into the editor and click "Add to Chart" to apply the indicator.
Configuring Settings:
Supertrend Parameters: Adjust the ATR period and multiplier to suit your trading style and the asset's volatility.
MA Filter Settings:
Enable MA Filter: Toggle "Enable MA Filter?" to ON to activate the filter.
Select MA Type: Choose from SMA, EMA, SMMA (RMA), WMA, or VWMA.
Set MA Length: Define the period for the MA calculation.
MA Source and Offset: Choose the price source (default is close) and set any desired plot offset.
Statistical Tracking:
Trimmed Mean Percentage: Set the percentage to trim outliers in mean calculations.
Show Cross Markers: Toggle to display or hide markers on the first and last candles of bullish and bearish moves.
Table Customization:
Table Text Color: Select your preferred text color for the statistics table to match your chart's theme or enhance readability.
Pinbar Filtering (Optional):
Enable Pinbar Filtering: Toggle to refine signals based on pinbar patterns.
Set Pinbar Wick Threshold: Adjust the threshold to define the characteristics of a valid pinbar.
Interpreting the Indicators:
Buy/Sell Signals: Look for labeled "BUY" and "SELL" signals on the chart that align with Supertrend reversals and MA conditions.
Statistics Table: Refer to the table located at the bottom right of the chart to assess:
Bullish/Bearish Averages: Average price movements following signals.
Counts: Total number of bullish and bearish signals.
Success Rates (%): Percentage of signals that resulted in profitable trades.
Candle Averages: Average duration of bullish and bearish moves in terms of candle counts.
Markers and Highlighter: Utilize visual markers and shaded trend areas to better understand market trends and the context of each signal.
Making Informed Decisions:
Assess Signal Performance: Use the success rates and averages to evaluate the effectiveness of your current settings and make necessary adjustments.
Adjust Parameters: Modify Supertrend and MA parameters based on observed performance and changing market conditions to optimize signal accuracy.
Combine with Other Analysis: Integrate insights from this indicator with other technical analysis tools and fundamental factors to form a holistic trading strategy.
Conclusion: The Supertrend with Probabilistic Stats and MA Filter indicator offers a powerful combination of trend detection, signal filtering, and statistical analysis. By providing detailed performance metrics and ensuring that trades align with the broader market trend, this indicator empowers traders to make more informed, data-driven decisions. Whether you're a novice seeking clarity or an experienced trader aiming to refine your strategy, this tool serves as a valuable asset in your trading toolkit.
If you have any further questions or require additional customizations, feel free to reach out!
DCA Fundamentals 1.0DCA Fundamentals 1.0
Description:
DCA Fundamentals 1.0 is an invite-only indicator designed to help traders and investors make informed decisions by analyzing key fundamental metrics of a company. It aggregates essential financial data—such as book value, earnings per share, total equity, total debt, net income, and total revenue—to provide a comprehensive overview of the stock’s intrinsic value and risk profile. By examining factors like the debt-to-equity ratio and dynamically computing Buffet’s Limit, this tool assists in identifying whether a stock may be undervalued, fairly valued, or overvalued.
Key Features:
Intrinsic Value Calculation: Estimates a stock’s intrinsic worth using a weighted combination of book value per share and EPS.
Buffet’s Limit & Margin of Safety: Adjusts intrinsic value based on the company’s debt-to-equity ratio, providing a margin of safety percentage to gauge potential investment risk.
Debt Warning: Highlights when the debt-to-equity ratio exceeds 2, signaling possible financial instability.
Data Visualization: Displays equity, debt, net income, and revenue as area plots or histograms, helping users quickly assess financial health.
Investment Status: Classifies the stock as undervalued, fairly valued, or overvalued based on current price relative to intrinsic value and Buffet’s Limit.
Dividend-to-ROE Ratio: Offers insight into dividend payout sustainability relative to the company’s return on equity.
Instructions
Fallback Data Handling:
If any financial data is unavailable, fallback values are automatically used to ensure that key calculations remain meaningful and uninterrupted.
Intrinsics & Risk Assessment:
Intrinsic Value: Computed using book value and EPS to understand the stock’s core worth.
Buffet’s Limit: Adjusted from the intrinsic value based on the debt-to-equity ratio. The resulting margin of safety helps gauge the current price’s risk level.
Debt Warning:
Debt-to-Equity Ratio > 2: Triggers a red warning, advising caution due to potentially excessive debt.
Visual Indicators:
Intrinsically Undervalued (Green Area): When price is below intrinsic value, a green shaded area suggests the stock may be undervalued, potentially presenting a buying opportunity.
Debt vs. Equity (Area Plots):
Red Area: Represents debt. A larger red area signals relatively high debt levels.
Green Area: Represents equity. A larger green area suggests stronger financial health.
Revenue & Net Income (Histograms):
Green Bars: Positive or improving fundamentals.
Red Bars: Negative or declining performance.
Investment Status:
Undervalued (Green): Price below intrinsic value.
Fairly Valued (Yellow): Price between intrinsic value and Buffet’s Limit.
Overvalued (Red): Price above intrinsic value, implying increased downside risk.
Table Display:
A convenient table summarizes key metrics at a glance, including P/E ratio, Debt-to-Equity ratio, intrinsic value, margin of safety, net income, total revenue, and the Dividend-to-ROE Ratio.
Dividend-to-ROE Ratio:
This metric provides additional context on the company’s dividend policy relative to its return on equity, aiding in evaluating dividend sustainability.
Disclaimer
Important Disclaimer:
The DCA Fundamentals 1.0 indicator is provided solely for educational and informational purposes. It is not investment advice, a recommendation, or an endorsement of any security or strategy. All calculations are based on data provided by third parties, and their accuracy or completeness is not guaranteed.
Investing and trading involve significant risks. You may lose more than your initial investment. Historical performance or indicators cannot guarantee future results. Before making any investment decisions, you should conduct thorough research, consider consulting a qualified financial professional, and implement robust risk management strategies.
By using DCA Fundamentals 1.0, you acknowledge these risks and agree that neither the creator nor any affiliated parties are responsible for any losses incurred. Use this tool at your own discretion and risk.
MOEX Aerospace & Defense IndexMOEX Aerospace & Defense Index is a financial instrument that forms an objective assessment of the capitalization of the entire aerospace and military–industrial complex of Russia, the securities of issuers of which are represented on the public stock market.
The MOEX Aerospace & Defense Index includes shares of 14 issuers of the aerospace and defense industry complex of Russia in fair shares proportional to the occupied shares of the Russian and global arms markets, as well as involvement in the Russian state defense order during wartime. The Index includes issuers from such sectors of the economy as: military aviation industry, rocket and space industry, military automotive industry and wheel products, military electronics and communications, military metallurgy and metal products.
The Index includes:
RUS:AMEZ RUS:CHKZ RUS:CHMF RUS:DZRDP RUS:ELMT RUS:IRKT RUS:KMAZ RUS:NAUK RUS:NSVZ RUS:RKKE RUS:SVAV RUS:UNAC RUS:VSMO RUS:ZVEZ
Based on historical data for the period from 2014 (the year of the beginning of the geopolitical confrontation between Russia and Ukraine), the MOEX Aerospace & Defense Index demonstrates profitability 3-4 times higher than the Russian benchmark of the stock market - the Moscow Stock Exchange Index. It makes the financial instrument the most attractive in times of geopolitical crises or military confrontations.
MOEX Aerospace & Defense Index allows you to:
1. To invest in a balanced manner in the aerospace and defense industrial complex of Russia, which produces advanced military and aerospace weapons for the needs of the Russian army and for export, which occupies 25% of the global arms market. Investing in the aerospace and military-industrial complex of Russia is especially relevant in the context of a special military operation in Ukraine, the growth of geopolitical tensions and the resulting large budget incentives for this industry from the Government of the Russian Federation.
2. To neutralize fluctuations in low-liquid and highly volatile stocks of the aerospace and military-industrial complex of Russia. The aerospace and defense industries are characterized by high volatility in stock prices, which is why the creation of a balanced index can offset price fluctuations for low-liquid shares of companies included in the index and reduce the risk for investors.
3. Politically diversify the investment portfolio. The inclusion of the MOEX Aerospace & Defense Index in the investment portfolio can reduce the risks associated with price fluctuations during geopolitical crises or military confrontations.
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MOEX Aerospace & Defense Index – финансовый инструмент, формирующий объективную оценку капитализации всего аэрокосмического и оборонно-промышленного комплекса России, ценные бумаги эмитентов которого представлены на публичном рынке акций.
В MOEX Aerospace & Defense Index включены акции 14 эмитентов аэрокосмического и оборонно-промышленного комплекса России в справедливых долях, пропорциональных занимаемым долям российского и мирового рынка вооружений, а также задействования в российском гособоронзаказе в военное время. Индекс включает в себя эмитентов из таких секторов экономики, как: военная авиационная промышленность, ракетно-космическая промышленность, военная автомобильная промышленность и колесные изделия, военная электроника и связь, военная металлургия и изделия из металла.
В Индекс включены:
RUS:AMEZ RUS:CHKZ RUS:CHMF RUS:DZRDP RUS:ELMT RUS:IRKT RUS:KMAZ RUS:NAUK RUS:NSVZ RUS:RKKE RUS:SVAV RUS:UNAC RUS:VSMO RUS:ZVEZ
На исторических данных за период с 2014-го года (года начала геополитической конфронтации России и Украины) MOEX Aerospace & Defense Index демонстрирует доходность в 3-4 раза выше российского бенчмарка рынка акций – Индекса Мосбиржи, что делает финансовый инструмент наиболее привлекательным во времена геополитических кризисов или военных противостояний.
MOEX Aerospace & Defense Index позволяет:
1. Сбалансированно инвестировать в аэрокосмический и оборонно-промышленный комплекс России, производящий передовое военное и аэрокосмическое вооружение для нужд армии России и на экспорт, который занимает 25% мирового рынка вооружений. Инвестирование в аэрокосмический и оборонно-промышленный комплекс России особенно актуально в условиях специальной военной операции на Украине, росте геополитической напряженности и следующих из этого большого бюджетного стимулирования данной отрасли со стороны Правительства Российской Федерации.
2. Нивелировать колебания в низколиквидных и высоко волатильных акциях аэрокосмического и оборонно-промышленного комплекса России. Аэрокосмическая и оборонная отрасли характеризуются высокой волатильностью цен на акции, ввиду чего создание сбалансированного индекса может нивелировать колебания цен на низколиквидные акции компаний, входящих в индекс, и снизить риск для инвесторов.
3. Политически диверсифицировать инвестиционный портфель. Включение MOEX Aerospace & Defense Index в инвестиционный портфель может снизить риски, связанные с колебаниями цен во время геополитических кризисов или военных противостояний.
Up and Downwhat is "Up and Down"?
It is an indicator designed to show you in detail on the chart and warn you when there is an increase or decrease in the market at a level that you consider important.
what it does?
When the price difference between a top and bottom is greater than the level you selected (the default input is 10 percent), it indicates this along with the percentage value on the chart. Then, it indicates the start and end points with lines so that you can see the change from where to where. It shows the price's current percentage distance from the last bottom or top in the upper right corner.
it also colors the candles so you can better understand how fast the price is moving. The greener the candles, the stronger the rise, and conversely, the greater the decline, the redder the candles. Of course, if you set an alarm, it will tell you in which trading pair, in which time period, at what percentage and in which direction there is a movement.
how it does it?
It uses a moving average with a short length to find bottoms and tops. It then measures the distance from the last peak to the bottom and expresses it as a percentage. It uses momentum using the moving average as a source to paint the candles. To compress this momentum between the values 255 and 0, I used a formula that I also used in my limited fisher transform work (because the inputs in the color.rgb function take values between 0 and 255). It was a bit challenging to use the lines correctly, but with the "ta.valuewhen" function and a little experimenting, they were I made sure they were drawn correctly.
how to use it?
It is quite simple to use. First, select the minimum interval you want to receive alarms. If you make this value too high, you will not receive any alarms; if you make it too low, you will receive too many alarms. Choose the range that will benefit you most for the trading pair you are using. Then all you have to do is set an alarm. When you set an alarm, leave the note section blank and the indicator will send you the necessary information.
Mastering ATR for Smart Stop Loss and Take Profit PlacementUsing the ATR indicator to set Stop Loss and Take Profit levels provides a dynamic and flexible way to manage risk based on the volatility of the market. This method ensures that your SL and TP are always in tune with current market conditions, preventing unnecessary stop-outs while maximizing the potential for profit. The table in the script makes it easy to view your calculated levels directly on the chart, improving your trading efficiency.
If you're looking for a more automated way to manage your trades, integrating ATR-based SL and TP can be a powerful tool in your strategy.
Happy Trading!
Sangana beta tableIdeal to use this indicator in Monthly timeframe.
This indicator shows three values on a table.
First column is stocks list from a particular sector(sector selection from settings)
Second column is beta of stock. Beta can be used to check how correlated(multiplied by how volatile) the stock is with respect to market S&P500 or Nifty500.
Third column is average percentage of a stock price movement in a month from low price to high price. This is just calculated on the price. If one enters at the low of that monthly candle and exits at the high of that monthly candle, they can expect to gain that much percentage on an average that is shown in this column.
How to use this indicator : Bigger returns on a stock is expected if it swings good amount of percentage from low to high on a regular basis. Either short term or long term, investing in the stocks which high average percentage from low to high, yields better returns. However downside also gives bigger losses if stock is going down. Stay in high volatile stocks, if one is sure of upside movement.
Sorting of beta column or percentage column can be chosen on settings. Sorting is always down high to low.
This indicator is tracks stocks in S&P500 or Nifty500.
Crypto Market Cap Momentum Analyzer (AiBitcoinTrend)The Crypto Market Cap Momentum Analyzer (AiBitcoinTrend) is a robust tool designed to uncover trading opportunities by blending market cap analysis and momentum dynamics. Inspired by research-backed quantitative strategies, this indicator helps traders identify trend-following and mean-reversion setups in the cryptocurrency market by evaluating recent performance and market cap size.
This indicator classifies cryptocurrencies into market cap quintiles and ranks them based on their 2-week momentum. It then suggests potential trades—whether to go long, anticipate reversals, or simply hold—based on the crypto's market cap group and momentum trends.
👽 How the Indicator Works
👾 Market Cap Classification
The indicator categorizes cryptocurrencies into one of five market cap groups based on user-defined inputs:
Large Cap: Highest market cap tier
Upper Mid Cap: Second highest group
Mid Cap: Middle-tier market caps
Lower Mid Cap: Slightly below the mid-tier
Small Cap: Lowest market cap tier
This classification dynamically adjusts based on the provided market cap data, ensuring that you’re always working with a representative market structure.
👾 Momentum Calculation
By default, the indicator uses a 2-week momentum measure (e.g., a 14-day lookback when set to daily). It compares a cryptocurrency’s current price to its price 14 bars ago, thereby quantifying its short-term performance. Users can adjust the momentum period and rebalance period to capture shorter or longer-term trends depending on their trading style.
👾 Dynamic Ranking and Trade Suggestions
After assigning cryptos to size quintiles, the indicator sorts them by their momentum within each quintile. This two-step process results in:
Long Trade: For smaller market cap groups (Small, Lower Mid, Mid Cap) that have low (bottom-quintile) momentum, anticipating a trend continuation or breakout.
Reversal Trade: For the largest market cap group (Large Cap) that shows low momentum, expecting a mean-reversion back to equilibrium.
Hold: In scenarios where the coin’s momentum doesn’t present a strong contrarian or trend-following signal.
👽 Applications
👾 Trend-Following in Smaller Caps: Identify small or mid-cap cryptos with low momentum that might be poised for a breakout or sustained trend.
👾 Mean-Reversion in Large Caps: Pinpoint large-cap cryptocurrencies experiencing a temporary lull in performance, potentially ripe for a rebound.
👽 Why It Works in Crypto
The cryptocurrency market is heavily driven by retail investor sentiment and volatility. Research shows that:
Small-Cap Cryptos: Tend to experience higher volatility and speculative trends, making them ideal for momentum trades.
Large-Cap Cryptos: Exhibit more predictable behavior, making them suitable for mean-reversion strategies when momentum is low.
This indicator captures these dynamics to give traders a strategic edge in identifying both momentum and reversal opportunities.
👽 Indicator Settings
👾 Rebalance Period: The frequency at which momentum and trade suggestions are recalculated (Daily, Weekly, Monthly).
Shorter Periods (Daily): Fast updates, suitable for short-term trades, but more noise.
Longer Periods (Weekly/Monthly): Smoother signals, ideal for swing trading and more stable trends.
👾 Momentum Period: The lookback period for momentum calculation (default is 14 bars).
Shorter Periods: More responsive but prone to noise.
Longer Periods : Reflects broader trends, reducing sensitivity to short-term fluctuations.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Quantum ChronoRenko Dynamics Edge - Traditional### **Quantum ChronoRenko Dynamics Edge - Traditional**
**Description:**
The **Quantum ChronoRenko Dynamics Edge - Traditional** is an advanced Renko-based indicator designed for precision trading. It leverages the power of Renko charts to detect price movements, highlight critical trading signals, and dynamically track profit and risk levels. This indicator is built with modern trading strategies in mind, offering robust tools for all traders, from beginners to professionals.
**Key Features:**
1. **Renko-Based Signal Generation**:
- Detects **Buy Signals** when the price closes above the Renko high level.
- Detects **Sell Signals** when the price closes below the Renko low level.
- Ensures signals are non-repainting and confirmed on bar closures.
2. **Take Profit (TP) and Stop Loss (SL) Tracking**:
- Automatically calculates and plots TP and SL levels for every signal.
- Dynamic levels are displayed directly on the chart for better decision-making.
3. **Advanced Signal Management**:
- Prevents duplicate signals within the same Renko range.
- Resets signal conditions when a new Renko range is formed.
4. **Visual Enhancements**:
- Renko high and low levels are plotted with customizable colors and styles.
- TP and SL levels are marked with distinct cross shapes for clarity.
- Optional fill between Renko levels to highlight price ranges.
5. **Real-Time Alerts**:
- Generates alerts for Buy and Sell signals when a candle closes above or below the Renko levels.
- Alerts are designed to help traders react quickly to opportunities.
6. **Comprehensive Statistics**:
- Tracks the number of Buy/Sell signals.
- Calculates the number of TP and SL hits for each signal type.
- Displays detailed percentages and totals in an easy-to-read table.
**Key Benefits**:
- **Non-Repainting Logic**: Ensures stable and reliable signals based on confirmed price movements.
- **Customizability**: Flexible settings for Renko brick size, TP/SL values, and visual enhancements.
- **Professional-Level Insights**: Provides detailed statistics for tracking strategy performance.
**Use Cases**:
- Perfect for intraday and swing traders who rely on Renko charts for clear trend signals.
- Suitable for identifying key breakout opportunities and managing trades with precise TP/SL levels.
Example Usage:
For daily scalping, set the following parameters:
Brick Size: 3
Time Frame: 10 Minutes
This setup provides clean trend signals and dynamic TP/SL tracking for short-term trades.
**Why "Traditional"?**
This version uses the **Traditional Renko method**, ensuring consistent price-based calculations that align with professional trading strategies.
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**Disclaimer**:
This indicator is a tool to aid trading decisions but does not guarantee profits. Always use proper risk management.
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CandleCandle: A Comprehensive Pine Script™ Library for Candlestick Analysis
Overview
The Candle library, developed in Pine Script™, provides traders and developers with a robust toolkit for analyzing candlestick data. By offering easy access to fundamental candlestick components like open, high, low, and close prices, along with advanced derived metrics such as body-to-wick ratios, percentage calculations, and volatility analysis, this library enables detailed insights into market behavior.
This library is ideal for creating custom indicators, trading strategies, and backtesting frameworks, making it a powerful resource for any Pine Script™ developer.
Key Features
1. Core Candlestick Data
• Open : Access the opening price of the current candle.
• High : Retrieve the highest price.
• Low : Retrieve the lowest price.
• Close : Access the closing price.
2. Candle Metrics
• Full Size : Calculates the total range of the candle (high - low).
• Body Size : Computes the size of the candle’s body (open - close).
• Wick Size : Provides the combined size of the upper and lower wicks.
3. Wick and Body Ratios
• Upper Wick Size and Lower Wick Size .
• Body-to-Wick Ratio and Wick-to-Body Ratio .
4. Percentage Calculations
• Upper Wick Percentage : The proportion of the upper wick size relative to the full candle size.
• Lower Wick Percentage : The proportion of the lower wick size relative to the full candle size.
• Body Percentage and Wick Percentage relative to the candle’s range.
5. Candle Direction Analysis
• Determines if a candle is "Bullish" or "Bearish" based on its closing and opening prices.
6. Price Metrics
• Average Price : The mean of the open, high, low, and close prices.
• Midpoint Price : The midpoint between the high and low prices.
7. Volatility Measurement
• Calculates the standard deviation of the OHLC prices, providing a volatility metric for the current candle.
Code Architecture
Example Functionality
The library employs a modular structure, exporting various functions that can be used independently or in combination. For instance:
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © DevArjun
//@version=6
indicator("Candle Data", overlay = true)
import DevArjun/Candle/1 as Candle
// Body Size %
bodySize = Candle.BodySize()
// Determining the candle direction
candleDirection = Candle.CandleDirection()
// Calculating the volatility of the current candle
volatility = Candle.Volatility()
// Plotting the metrics (for demonstration)
plot(bodySize, title="Body Size", color=color.blue)
label.new(bar_index, high, candleDirection, style=label.style_circle)
Scalability
The modularity of the Candle library allows seamless integration into more extensive trading systems. Functions can be mixed and matched to suit specific analytical or strategic needs.
Use Cases
Trading Strategies
Developers can use the library to create strategies based on candle properties such as:
• Identifying long-bodied candles (momentum signals).
• Detecting wicks as potential reversal zones.
• Filtering trades based on candle ratios.
Visualization
Plotting components like body size, wick size, and directional labels helps visualize market behavior and identify patterns.
Backtesting
By incorporating volatility and ratio metrics, traders can design and test strategies on historical data, ensuring robust performance before live trading.
Education
This library is a great tool for teaching candlestick analysis and how each component contributes to market behavior.
Portfolio Highlights
Project Objective
To create a Pine Script™ library that simplifies candlestick analysis by providing comprehensive metrics and insights, empowering traders and developers with advanced tools for market analysis.
Development Challenges and Solutions
• Challenge : Achieving high precision in calculating ratios and percentages.
• Solution : Implemented robust mathematical operations and safeguarded against division-by-zero errors.
• Challenge : Ensuring modularity and scalability.
• Solution : Designed functions as independent modules, allowing flexible integration.
Impact
• Efficiency : The library reduces the time required to calculate complex candlestick metrics.
• Versatility : Supports various trading styles, from scalping to swing trading.
• Clarity : Clean code and detailed documentation ensure usability for developers of all levels.
Conclusion
The Candle library exemplifies the power of Pine Script™ in simplifying and enhancing candlestick analysis. By including this project in your portfolio, you showcase your expertise in:
• Financial data analysis.
• Pine Script™ development.
• Creating tools that solve real-world trading challenges.
This project demonstrates both technical proficiency and a keen understanding of market analysis, making it an excellent addition to your professional portfolio.
Library "Candle"
A comprehensive library to access and analyze the basic components of a candlestick, including open, high, low, close prices, and various derived metrics such as full size, body size, wick sizes, ratios, percentages, and additional analysis metrics.
Open()
Open
@description Returns the opening price of the current candle.
Returns: float - The opening price of the current candle.
High()
High
@description Returns the highest price of the current candle.
Returns: float - The highest price of the current candle.
Low()
Low
@description Returns the lowest price of the current candle.
Returns: float - The lowest price of the current candle.
Close()
Close
@description Returns the closing price of the current candle.
Returns: float - The closing price of the current candle.
FullSize()
FullSize
@description Returns the full size (range) of the current candle (high - low).
Returns: float - The full size of the current candle.
BodySize()
BodySize
@description Returns the body size of the current candle (open - close).
Returns: float - The body size of the current candle.
WickSize()
WickSize
@description Returns the size of the wicks of the current candle (full size - body size).
Returns: float - The size of the wicks of the current candle.
UpperWickSize()
UpperWickSize
@description Returns the size of the upper wick of the current candle.
Returns: float - The size of the upper wick of the current candle.
LowerWickSize()
LowerWickSize
@description Returns the size of the lower wick of the current candle.
Returns: float - The size of the lower wick of the current candle.
BodyToWickRatio()
BodyToWickRatio
@description Returns the ratio of the body size to the wick size of the current candle.
Returns: float - The body to wick ratio of the current candle.
UpperWickPercentage()
UpperWickPercentage
@description Returns the percentage of the upper wick size relative to the full size of the current candle.
Returns: float - The percentage of the upper wick size relative to the full size of the current candle.
LowerWickPercentage()
LowerWickPercentage
@description Returns the percentage of the lower wick size relative to the full size of the current candle.
Returns: float - The percentage of the lower wick size relative to the full size of the current candle.
WickToBodyRatio()
WickToBodyRatio
@description Returns the ratio of the wick size to the body size of the current candle.
Returns: float - The wick to body ratio of the current candle.
BodyPercentage()
BodyPercentage
@description Returns the percentage of the body size relative to the full size of the current candle.
Returns: float - The percentage of the body size relative to the full size of the current candle.
WickPercentage()
WickPercentage
@description Returns the percentage of the wick size relative to the full size of the current candle.
Returns: float - The percentage of the wick size relative to the full size of the current candle.
CandleDirection()
CandleDirection
@description Returns the direction of the current candle.
Returns: string - "Bullish" if the candle is bullish, "Bearish" if the candle is bearish.
AveragePrice()
AveragePrice
@description Returns the average price of the current candle (mean of open, high, low, and close).
Returns: float - The average price of the current candle.
MidpointPrice()
MidpointPrice
@description Returns the midpoint price of the current candle (mean of high and low).
Returns: float - The midpoint price of the current candle.
Volatility()
Volatility
@description Returns the standard deviation of the OHLC prices of the current candle.
Returns: float - The volatility of the current candle.
Median Deviation Suite [InvestorUnknown]The Median Deviation Suite uses a median-based baseline derived from a Double Exponential Moving Average (DEMA) and layers multiple deviation measures around it. By comparing price to these deviation-based ranges, it attempts to identify trends and potential turning points in the market. The indicator also incorporates several deviation types—Average Absolute Deviation (AAD), Median Absolute Deviation (MAD), Standard Deviation (STDEV), and Average True Range (ATR)—allowing traders to visualize different forms of volatility and dispersion. Users should calibrate the settings to suit their specific trading approach, as the default values are not optimized.
Core Components
Median of a DEMA:
The foundation of the indicator is a Median applied to the 7-day DEMA (Double Exponential Moving Average). DEMA aims to reduce lag compared to simple or exponential moving averages. By then taking a median over median_len periods of the DEMA values, the indicator creates a robust and stable central tendency line.
float dema = ta.dema(src, 7)
float median = ta.median(dema, median_len)
Multiple Deviation Measures:
Around this median, the indicator calculates several measures of dispersion:
ATR (Average True Range): A popular volatility measure.
STDEV (Standard Deviation): Measures the spread of price data from its mean.
MAD (Median Absolute Deviation): A robust measure of variability less influenced by outliers.
AAD (Average Absolute Deviation): Similar to MAD, but uses the mean absolute deviation instead of median.
Average of Deviations (avg_dev): The average of the above four measures (ATR, STDEV, MAD, AAD), providing a combined sense of volatility.
Each measure is multiplied by a user-defined multiplier (dev_mul) to scale the width of the bands.
aad = f_aad(src, dev_len, median) * dev_mul
mad = f_mad(src, dev_len, median) * dev_mul
stdev = ta.stdev(src, dev_len) * dev_mul
atr = ta.atr(dev_len) * dev_mul
avg_dev = math.avg(aad, mad, stdev, atr)
Deviation-Based Bands:
The indicator creates multiple upper and lower lines based on each deviation type. For example, using MAD:
float mad_p = median + mad // already multiplied by dev_mul
float mad_m = median - mad
Similar calculations are done for AAD, STDEV, ATR, and the average of these deviations. The indicator then determines the overall upper and lower boundaries by combining these lines:
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
This creates a layered structure of volatility envelopes. Traders can observe which layers price interacts with to gauge trend strength.
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
median_len: Affects how smooth and lagging the median of the DEMA is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
R-based Strategy Template [Daveatt]Have you ever wondered how to properly track your trading performance based on risk rather than just profits?
This template solves that problem by implementing R-multiple tracking directly in TradingView's strategy tester.
This script is a tool that you must update with your own trading entry logic.
Quick notes
Before we dive in, I want to be clear: this is a template focused on R-multiple calculation and visualization.
I'm using a basic RSI strategy with dummy values just to demonstrate how the R tracking works. The actual trading signals aren't important here - you should replace them with your own strategy logic.
R multiple logic
Let's talk about what R-multiple means in practice.
Think of R as your initial risk per trade.
For instance, if you have a $10,000 account and you're risking 1% per trade, your 1R would be $100.
A trade that makes twice your risk would be +2R ($200), while hitting your stop loss would be -1R (-$100).
This way of measuring makes it much easier to evaluate your strategy's performance regardless of account size.
Whenever the SL is hit, we lose -1R
Proof showing the strategy tester whenever the SL is hit: i.imgur.com
The magic happens in how we calculate position sizes.
The script automatically determines the right position size to risk exactly your specified percentage on each trade.
This is done through a simple but powerful calculation:
risk_amount = (strategy.equity * (risk_per_trade_percent / 100))
sl_distance = math.abs(entry_price - sl_price)
position_size = risk_amount / (sl_distance * syminfo.pointvalue)
Limitations with lower timeframe gaps
This ensures that if your stop loss gets hit, you'll lose exactly the amount you intended to risk. No more, no less.
Well, could be more or less actually ... let's assume you're trading futures on a 15-minute chart but in the 1-minute chart there is a gap ... then your 15 minute SL won't get filled and you'll likely to not lose exactly -1R
This is annoying but it can't be fixed - and that's how trading works anyway.
Features
The template gives you flexibility in how you set your stop losses. You can use fixed points, ATR-based stops, percentage-based stops, or even tick-based stops.
Regardless of which method you choose, the position sizing will automatically adjust to maintain your desired risk per trade.
To help you track performance, I've added a comprehensive statistics table in the top right corner of your chart.
It shows you everything you need to know about your strategy's performance in terms of R-multiples: how many R you've won or lost, your win rate, average R per trade, and even your longest winning and losing streaks.
Happy trading!
And remember, measuring your performance in R-multiples is one of the most classical ways to evaluate and improve your trading strategies.
Daveatt
Spread Analysis (COIN/BTC)The Spread Analysis (COIN/BTC) indicator calculates the Z-score of the price ratio between Coinbase stock ( NASDAQ:COIN ) and Bitcoin ( CRYPTOCAP:BTC ). It helps identify overbought or oversold conditions based on deviations from the historical mean of their price relationship.
Key Features:
Z-Score Calculation:
• Tracks the relative price ratio of NASDAQ:COIN to $BTC.
• Compares the current ratio to its historical average, highlighting extreme overvaluation or undervaluation.
• Buy and Sell Signals:
• Buy Signal: Triggered when the Z-score is less than -2, indicating NASDAQ:COIN may be undervalued relative to $BTC.
• Sell Signal: Triggered when the Z-score exceeds 2, suggesting NASDAQ:COIN may be overvalued relative to $BTC.
• Dynamic Z-Score Visualization:
• Blue line plots the Z-score over time.
• Dashed lines at +2 and -2 mark overbought and oversold thresholds.
• Green and red triangles highlight actionable buy and sell signals.
Use Case:
This indicator is ideal for identifying relative valuation opportunities between NASDAQ:COIN and $BTC. Use it to exploit divergences in their historical relationship and anticipate potential reversions to the mean.
Limitations:
• Best suited for range-bound markets; may produce false signals in strongly trending conditions.
• Assumes a consistent correlation between NASDAQ:COIN and CRYPTOCAP:BTC , which may break during independent price drivers like news or earnings.
Market MonitorOverview
The Market Monitor Indicator provides a customisable view of dynamic percentage changes across selected indices or sectors, calculated by comparing current and previous closing prices over the chosen timeframe.
Key Features
Choose up to 20 predefined indices or your own selected indices/stocks.
Use checkboxes to show or hide individual entries.
Monitor returns over daily, weekly, monthly, quarterly, half-yearly, or yearly timeframes
Sort by returns (descending) to quickly identify top-performing indices or alphabetically for an organised and systematic review.
Customisation
Switch between Light Mode (Blue or Green themes) and Dark Mode for visual clarity.
Adjust the table’s size, position, and location.
Customise the table title to your own choice e.g. Sectoral, Broad, Portfolio etc.
Use Cases
Use multiple instances of the script with varying timeframes to study sectoral rotation and trends.
Customise the stocks to see your portfolio returns for the day or over the past week, or longer.
TradingCharts SCTR [Bginvestor]This indicator is replicating Tradingcharts, SCTR plot. If you know, you know.
Brief description: The StockCharts Technical Rank (SCTR), conceived by technical analyst John Murphy, emerges as a pivotal tool in evaluating a stock’s technical prowess. This numerical system, colloquially known as “scooter,” gauges a stock’s strength within various groups, employing six key technical indicators across different time frames.
How to use it:
Long-term indicators (30% weight each)
-Percent above/below the 200-day exponential moving average (EMA)
-125-day rate-of-change (ROC)
Medium-term indicators (15% weight each)
-percent above/below 50-day EMA
-20-day rate-of-change
Short-term indicators (5% weight each)
-Three-day slope of percentage price oscillator histogram divided by three
-Relative strength index
How to use SCTR:
Investors select a specific group for analysis, and the SCTR assigns rankings within that group. A score of 99.99 denotes robust technical performance, while zero signals pronounced underperformance. Traders leverage this data for strategic decision-making, identifying stocks with increasing SCTR for potential buying or spotting weak stocks for potential shorting.
Credit: I've made some modifications, but credit goes to GodziBear for back engineering the averaging / scaling of the equations.
Note: Not a perfect match to TradingCharts, but very, very close.
Sector Relative Strength [Afnan]This indicator calculates and displays the relative strength (RS) of multiple sectors against a chosen benchmark. It allows you to quickly compare the performance of various sectors within any global stock market. While the default settings are configured for the Indian stock market , this tool is not limited to it; you can use it for any market by selecting the appropriate benchmark and sector indices.
📊 Key Features ⚙️
Customizable Benchmark: Select any symbol as your benchmark for relative strength calculation. The default benchmark is set to `NSE:CNX100`. This allows for global market analysis by selecting the appropriate benchmark index of any country.
Multiple Sectors: Analyze up to 23 different sector indices. The default settings include major NSE sector indices. This can be customized to any market by using the relevant sector indices of that country.
Individual Sector Control: Toggle the visibility of each sector's RS on the chart.
Color-Coded Plots: Each sector's RS is plotted with a distinct color for easy identification.
Adjustable Lookback Period: Customize the lookback period for RS calculation.
Interactive Table: A sortable table displays the current RS values for all visible sectors, allowing for quick ranking.
Table Customization: Adjust the table's position, text size, and visibility.
Zero Line: A horizontal line at zero provides a reference point for RS values.
🧭 How to Use 🗺️
Add the indicator to your TradingView chart.
Select your desired benchmark symbol. The default is `NSE:CNX100`. For example, use SPY for the US market, or DAX for the German market.
Adjust the lookback period as needed.
Enable/disable the sector indices you want to analyze. The default includes major NSE sector indices like `NSE:CNXIT`, `NSE:CNXAUTO`, etc.
Customize the table's appearance as needed.
Observe the RS plots and the table to identify sectors with relative strength or weakness.
📝 Note 💡
This indicator is designed for sectorial analysis. You can use it with any market by selecting the appropriate benchmark and sector indices.
The default settings are configured for the Indian stock market with `NSE:CNX100` as the benchmark and major NSE sector indices pre-selected.
The relative strength calculation is based on the price change of the sector index compared to the benchmark over the lookback period.
Positive RS values indicate relative outperformance, while negative values indicate relative underperformance.
👨💻 Developer 🛠️
Afnan Tajuddin
Scatter Plot with Symbol or Data Source InputsDescription of setting items
Use Symbol for X Data?
Type: Checkbox (input.bool)
Explanation: Selects whether the data used for the X axis is obtained from a “symbol” or a “data source”.
If true: data for the X axis will be taken from a symbol (e.g. stock ticker).
If false: X axis data will be taken from the specified data source (e.g., closing price or volume).
Use Symbol for Y Data?
type: checkbox (input.bool)
Explanation: Selects whether the data used for the Y axis is retrieved from a “symbol” or a “data source”.
If true: Y-axis data is obtained from symbols.
If false: Data for the Y axis is obtained from the specified data source.
Select Ticker Symbol for X Data
type: symbol input (input.symbol)
description: selects the symbol to be used for the X axis (default is “AAPL”).
If “Use Symbol for X Data?” is set to true, this symbol will be used as the data for the X axis.
Select Ticker Symbol for Y Data
Type: Symbol input (input.symbol)
description: selects the symbol to be used for the Y axis (default is “GOOG”).
If “Use Symbol for Y Data?” is set to true, this symbol will be used as the data for the Y axis.
X Data Source
type: data source input (input.source)
description: specifies the data source to be used for the X axis.
Default is “close” (closing price).
Other possible values include open, high, low, volume, etc.
Y Data Source
Type: data source input (input.source)
Description: Specifies the data source to be used for the Y axis.
Default is “volume” (volume).
Other possible values include open, high, low, close, etc.
X Offset
type: integer input (input.int)
description: sets the offset value of the X axis.
This shifts the position of the X axis on the grid. The range is from -500 to 500.
Y Offset
Type: Integer input (constant)
description: offset value for y-axis.
Defaults to 0, but can be changed to adjust the Y axis position.
grid_width
type: integer input (input.int)
description: sets the width of the grid.
The default is 200. Increasing the value results in a finer grid.
grid_height
type: integer input (input.int)
description: sets the height of the grid.
Defaults to 200. Increasing the value results in a finer grid.
Frequency of updates
type: integer input (input.int)
description: set frequency of updates.
The higher the frequency of updates, the more bars will be used to calculate minimum and maximum values.
X Tick Interval
type: integer input (input.int)
description: sets the tick interval for the X axis.
The default is 10. To increase the number of ticks, decrease the value.
Y Tick Interval
Box border color
type: select color (input.color)
description: select color for grid box border
Default is blue.
Explanation of usage
To use symbol data: Set Use Symbol for X Data?
When “Use Symbol for X Data?” and “Use Symbol for Y Data?” are set to true, the data of the specified symbol is displayed on each axis. For example, you can use “AAPL” (Apple's stock price data) for the X axis and “GOOG” (Google's stock price data) for the Y axis.
To set the symbol, select the desired ticker in Select Ticker Symbol for X Data and Select Ticker Symbol for Y Data.
To use a data source: select the
You can set Use Symbol for X Data? and Use Symbol for Y Data? to false and use the data source specified in X Data Source or Y Data Source instead (e.g., closing price or volume).
Change Grid Size:.
Set the width and height of the grid with grid_width and grid_height. Larger values allow for more detailed scatter plots.
Set Tick Intervals: Set the X Tick Interval and Y Tick Interval.
Adjust X Tick Interval and Y Tick Interval to change the tick spacing on the X and Y axes.
Data Range Adjustment: Adjust the Frequency of updates to change the frequency of updates.
The Frequency of updates can be changed to control how often the data range is updated. The higher this value, the more historical data is considered and displayed.
Box Color.
Box Border Color allows you to change the color of the box border.
This script is useful for visualizing different symbols and data sources, especially to show the relationship between financial data.
Caution.
Some data may exceed the memory size, but the scale is the same, so you will know most of the locations.
*I made it myself because I could not find anything to draw a scatter plot. You can also compare more than 3 pieces of data by displaying more than one scatter plot. Here is how to do it. Set X or Y as the reference data. Set the data you want to compare to the one that is not the standard. Next, set the same indicator and set the reference to another set of data you wish to compare. Now you can compare the three sets of data. It is effective to change the color of the display box to prevent the user from not knowing which is which. Thus, you should be able to compare more than 3 pieces of data, so give it a try.
Employee Portfolio Generator [By MUQWISHI]▋ INTRODUCTION :
The “Employee Portfolio Generator” simplifies the process of building a long-term investment portfolio tailored for employees seeking to build wealth through investments rather than traditional bank savings. The tool empowers employees to set up recurring deposits at customizable intervals, enabling to make additional purchases in a list of preferred holdings, with the ability to define the purchasing investment weight for each security. The tool serves as a comprehensive solution for tracking portfolio performance, conducting research, and analyzing specific aspects of portfolio investments. The output includes an index value, a table of holdings, and chart plots, providing a deeper understanding of the portfolio's historical movements.
_______________________
▋ OVERVIEW:
● Scenario (The chart above can be taken as an example) :
Let say, in 2010, a newly employed individual committed to saving $1,000 each month. Rather than relying on a traditional savings account, chose to invest the majority of monthly savings in stable well-established stocks. Allocating 30% of monthly saving to AMEX:SPY and another 30% to NASDAQ:QQQ , recognizing these as reliable options for steady growth. Additionally, there was an admired toward innovative business models of NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:AMZN , and NASDAQ:EBAY , leading to invest 10% in each of those companies. By the end of 2024, after 15 years, the total monthly deposits amounted to $179,000, which would have been the result of traditional saving alone. However, by sticking into long term invest, the value of the portfolio assets grew, reaching nearly $900,000.
_______________________
▋ OUTPUTS:
The table can be displayed in three formats:
1. Portfolio Index Title: displays the index name at the top, and at the bottom, it shows the index value, along with the chart timeframe, e.g., daily change in points and percentage.
2. Specifications: displays the essential information on portfolio performance, including the investment date range, total deposits, free cash, returns, and assets.
3. Holdings: a list of the holding securities inside a table that contains the ticker, last price, entry price, return percentage of the portfolio's total deposits, and latest weighted percentage of the portfolio. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
4. Indication of New Deposit: An indication of a new deposit added to the portfolio for additional purchasing.
5. Chart: The portfolio's historical movements can be visualized in a plot, displayed as a bar chart, candlestick chart, or line chart, depending on the preferred format, as shown below.
_______________________
▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Naming the index.
(2) Table location on the chart and cell size.
(3) Sorting Holdings Table. By securities’ {Return(%) Portfolio, Weight(%) Portfolio, or Ticker Alphabetical} order.
(4) Choose the type of index: {Assets, Return, or Return (%)}, and the plot type for the portfolio index: {Candle, Bar, or Line}.
(5) Positive/Negative colors.
(6) Table Colors (Title, Cell, and Text).
(7) To show/hide any of selected indicator’s components.
Section(2): Recurring Deposit Settings
(1) From DateTime of starting the investment.
(2) To DateTime of ending the investment
(3) The amount of recurring deposit into portfolio and currency.
(4) The frequency of recurring deposits into the portfolio {Weekly, 2-Weeks, Monthly, Quarterly, Yearly}
(5) The Depositing Model:
● Fixed: The amount for recurring deposits remains constant throughout the entire investment period.
● Increased %: The recurring deposit amount increases at the selected frequency and percentage throughout the entire investment period.
(5B) If the user selects “ Depositing Model: Increased % ”, specify the growth model (linear or exponential) and define the rate of increase.
Section(3): Portfolio Holdings
(1) Enable a ticker in the investment portfolio.
(2) The selected deposit frequency weight for a ticker. For example, if the monthly deposit is $1,000 and the selected weight for XYZ stock is 30%, $300 will be used to purchase shares of XYZ stock.
(3) Select up to 6 tickers that the investor is interested in for long-term investment.
Please let me know if you have any questions
