Daily Liquidity Peaks and Troughs [ST]Daily Liquidity Peaks and Troughs
Description in English:
This indicator identifies peaks and troughs of highest liquidity on a daily timeframe by analyzing volume data. It helps traders visualize key points of high buying or selling pressure, which could indicate potential reversal or continuation areas.
Detailed Explanation:
Configuration:
Lookback Length: This input defines the period over which the highest high and lowest low are calculated. The default value is 14. This means the script will look at the past 14 bars to determine if the current high or low is a pivot point.
Volume Threshold Multiplier: This input defines the multiplier for the average volume. For example, a multiplier of 1.5 means the volume needs to be 1.5 times the average volume to be considered a significant peak or trough.
Peak Color: This input sets the color for liquidity peaks. The default color is red.
Trough Color: This input sets the color for liquidity troughs. The default color is green.
Volume Calculation:
Average Volume: The script calculates the simple moving average (SMA) of the volume over the lookback period. This helps to identify periods of significantly higher volume.
Volume Threshold: The threshold is determined by multiplying the average volume by the volume threshold multiplier. Only volumes exceeding this threshold are considered significant.
Identifying Peaks and Troughs:
Liquidity Peak: A peak is identified when the current high is the highest high over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong selling pressure.
Liquidity Trough: A trough is identified when the current low is the lowest low over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong buying pressure.
These peaks and troughs are marked on the chart with labels and shapes for easy visualization.
Plotting Peaks and Troughs:
Labels: The script uses labels to mark peaks and troughs on the chart. Peaks are marked with a red label and troughs with a green label.
Shapes: The script plots triangles above peaks and below troughs to highlight these areas visually.
Indicator Benefits:
Liquidity Identification: Helps traders identify key areas of high liquidity, indicating strong buying or selling pressure.
Visual Cues: Provides clear visual signals for potential reversal or continuation points, aiding in making informed trading decisions.
Customizable Parameters: Allows traders to adjust the lookback length and volume threshold to suit different trading strategies and market conditions.
Justification of Component Combination:
Peaks and Troughs Identification: Combining pivot points with volume analysis provides a robust method to identify significant liquidity areas. This helps in detecting potential market reversals or continuations.
Volume Analysis: Utilizing average volume and volume threshold ensures that only significant volume spikes are considered, enhancing the accuracy of identified peaks and troughs.
How Components Work Together:
The script first calculates the average volume over the specified lookback period.
It then checks each bar to see if it qualifies as a liquidity peak or trough based on the highest high, lowest low, and volume threshold.
When a peak or trough is identified, it is marked on the chart with a label and a shape, providing clear visual cues for traders.
Título: Picos e Fundos de Liquidez Diários
Descrição em Português:
Este indicador identifica picos e fundos de maior liquidez no gráfico diário, analisando os dados de volume. Ele ajuda os traders a visualizar pontos-chave de alta pressão de compra ou venda, o que pode indicar áreas potenciais de reversão ou continuação.
Explicação Detalhada:
Configuração:
Comprimento de Retrocesso: Este input define o período sobre o qual a máxima e mínima são calculadas. O valor padrão é 14. Isso significa que o script analisará os últimos 14 candles para determinar se a máxima ou mínima atual é um ponto de pivô.
Multiplicador de Limite de Volume: Este input define o multiplicador para o volume médio. Por exemplo, um multiplicador de 1.5 significa que o volume precisa ser 1.5 vezes o volume médio para ser considerado um pico ou fundo significativo.
Cor do Pico: Este input define a cor para os picos de liquidez. A cor padrão é vermelha.
Cor do Fundo: Este input define a cor para os fundos de liquidez. A cor padrão é verde.
Cálculo do Volume:
Volume Médio: O script calcula a média móvel simples (SMA) do volume ao longo do período de retrocesso. Isso ajuda a identificar períodos de volume significativamente mais alto.
Limite de Volume: O limite é determinado multiplicando o volume médio pelo multiplicador de limite de volume. Apenas volumes que excedem esse limite são considerados significativos.
Identificação de Picos e Fundos:
Pico de Liquidez: Um pico é identificado quando a máxima atual é a máxima mais alta no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de venda.
Fundo de Liquidez: Um fundo é identificado quando a mínima atual é a mínima mais baixa no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de compra.
Esses picos e fundos são marcados no gráfico com etiquetas e formas para fácil visualização.
Plotagem de Picos e Fundos:
Etiquetas: O script usa etiquetas para marcar picos e fundos no gráfico. Os picos são marcados com uma etiqueta vermelha e os fundos com uma etiqueta verde.
Formas: O script plota triângulos acima dos picos e abaixo dos fundos para destacar essas áreas visualmente.
Benefícios do Indicador:
Identificação de Liquidez: Ajuda os traders a identificar áreas-chave de alta liquidez, indicando forte pressão de compra ou venda.
Cues Visuais: Fornece sinais visuais claros para pontos potenciais de reversão ou continuação, auxiliando na tomada de decisões informadas.
Parâmetros Personalizáveis: Permite que os traders ajustem o comprimento de retrocesso e o limite de volume para se adequar a diferentes estratégias de negociação e condições de mercado.
Justificação da Combinação de Componentes:
Identificação de Picos e Fundos: A combinação de pontos de pivô com análise de volume fornece um método robusto para identificar áreas significativas de liquidez. Isso ajuda na detecção de potenciais reversões ou continuações de mercado.
Análise de Volume: Utilizar o volume médio e o limite de volume garante que apenas picos de volume significativos sejam considerados, aumentando a precisão dos picos e fundos identificados.
Como os Componentes Funcionam Juntos:
O script primeiro calcula o volume médio ao longo do período especificado de retrocesso.
Em seguida, verifica cada barra para ver se ela se qualifica como um pico ou fundo de liquidez com base
Forecasting
Enhanced Trend Arrows with Moving Average [ST]Enhanced Trend Arrows with Moving Average
Description in English:
This indicator is designed to identify market trends using a moving average and displays arrows after three consecutive closes above or below the moving average. It helps traders visualize confirmed trends and make informed decisions.
Detailed Explanation:
Configuration:
Length: Defines the period over which the moving average is calculated. The default value is 14.
MA Type: Allows choosing between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Uptrend Color: Sets the color of the arrows indicating an uptrend. The default color is green.
Downtrend Color: Sets the color of the arrows indicating a downtrend. The default color is red.
Moving Average Calculation:
The moving average (MA) is calculated based on the selected type (SMA or EMA) and period. The SMA is the simple arithmetic mean of the closing prices over the specified period, while the EMA gives more weight to recent prices.
Trend Identification:
The script detects when the price crosses above (crossover) or below (crossunder) the moving average.
When a crossover occurs (price moves above the MA), it indicates a potential uptrend, and the trend variable is set to 1.
When a crossunder occurs (price moves below the MA), it indicates a potential downtrend, and the trend variable is set to -1.
The script tracks the closing price at the crossover or crossunder point using the trendPrice variable.
It also counts consecutive bars above or below the moving average to confirm the trend, using above_count for uptrend and below_count for downtrend.
Arrow Display:
The script displays an up arrow ("▲") after three consecutive closes above the moving average, indicating a confirmed uptrend.
Similarly, it displays a down arrow ("▼") after three consecutive closes below the moving average, indicating a confirmed downtrend.
The arrows are displayed at the trendPrice level to clearly indicate the point at which the trend was confirmed.
Indicator Benefits:
Trend Identification: Helps traders identify market trends using moving averages, which are widely used in technical analysis.
Visual Cues: The arrows provide clear visual signals for confirmed trends, making it easier for traders to make informed decisions.
New Features and Enhancements:
This script has been enhanced to provide more accurate trend identification by ensuring arrows are only displayed after three consecutive closes above or below the moving average.
The color customization options for uptrend and downtrend arrows have been added for better visualization.
Improved description and explanations to make the functionality and usage of the indicator clearer.
Precise ATR Stop Loss - Daily Pullbacks [ST]Precise ATR Stop Loss - Daily Pullbacks
This indicator uses ATR (Average True Range) combined with the identification of pullback lows and highs on daily charts to calculate more precise stop loss levels.
How it works:
Identification of Pullbacks:
Pullback Lows: Identifies significant low points on daily charts that can serve as support.
Pullback Highs: Identifies significant high points on daily charts that can serve as resistance.
ATR (Average True Range):
Measures market volatility and is used to adjust stop loss levels according to market conditions.
Dynamic Stop Loss:
Stop Loss for Uptrend:
When a pullback low is identified on a daily chart, the stop loss is set slightly below this point, adjusted by the ATR.
This level is shown by a green line on the chart.
Stop Loss for Downtrend:
When a pullback high is identified on a daily chart, the stop loss is set slightly above this point, adjusted by the ATR.
This level is shown by a red line on the chart.
Indicator Benefits:
Improved Precision: Uses significant pullback points on daily charts to set stops more accurately.
Dynamic Stop Loss:
Automatically adjusts stop loss levels according to market volatility, providing more effective risk management.
Título: Precise ATR Stop Loss - Daily Pullbacks
Descrição em Português:
Este indicador utiliza o ATR (Average True Range) combinado com a identificação de fundos e topos de pullback em gráficos diários para calcular níveis de stop loss mais precisos.
Como funciona:
Identificação de Pullbacks:
Fundos de Pullback: Identifica pontos de mínima significativos em gráficos diários que podem servir como suporte.
Topos de Pullback: Identifica pontos de máxima significativos em gráficos diários que podem servir como resistência.
ATR (Average True Range):
Mede a volatilidade do mercado e é utilizado para ajustar os níveis de stop loss de acordo com as condições do mercado.
Stop Loss Dinâmico:
Stop Loss para Tendência de Alta: Quando um fundo de pullback é identificado em um gráfico diário, o stop loss é colocado um pouco abaixo desse ponto, ajustado pelo ATR. Este nível é mostrado por uma linha verde no gráfico.
Stop Loss para Tendência de Baixa: Quando um topo de pullback é identificado em um gráfico diário, o stop loss é colocado um pouco acima desse ponto, ajustado pelo ATR. Este nível é mostrado por uma linha vermelha no gráfico.
Benefícios do Indicador:
Precisão Melhorada: Utiliza pontos de pullback significativos em gráficos diários para posicionar stops de forma mais precisa.
Stop Loss Dinâmico: Ajusta automaticamente os níveis de stop loss de acordo com a volatilidade do mercado, proporcionando uma gestão de risco mais eficaz.
Important Levels by Sandun Kolambage
### Pine Script Indicator: Important Levels by Sandun Kolambage
#### Description
Introducing our new pivot point and high/low indicator for TradingView! This indicator is designed to help traders identify key levels of support and resistance across different timeframes, from daily to yearly. By analyzing historical data and market trends, our indicator displays the most important pivot points and high/low levels, giving you a better understanding of market dynamics and potential trading opportunities.
Whether you're a day trader, swing trader, or long-term investor, our indicator can help you optimize your trading strategy and achieve your financial goals. Install our indicator on TradingView today and start taking advantage of these important levels!
#### Key Features
- **Daily, Weekly, Monthly, and Yearly Levels:** Automatically plots the open, high, low, and close prices for different timeframes to help traders identify significant levels.
- **Pivot Points:** Calculates and displays pivot points for weekly, monthly, and yearly timeframes, providing additional support and resistance levels.
- **Customizable Line Styles:** Offers options to customize the appearance of the lines (solid, dashed, or dotted) for better visualization.
- **Conditional Coloring:** Uses color coding to highlight the relationship between different timeframe closes, making it easy to spot important levels.
#### How It Works
1. **Daily, Weekly, Monthly, and Yearly Levels:**
- The indicator uses `request.security` to fetch and display open, high, low, and close prices for daily, weekly, monthly, and yearly timeframes.
- Lines are plotted at these key levels with colors indicating their relationship to closes of other timeframes.
2. **Pivot Points:**
- Pivot points are calculated using the formula \((High + Low + Close) / 3\).
- These pivot points are plotted on the chart and labeled clearly to indicate potential support and resistance areas.
3. **Customizable Line Styles:**
- Users can select from solid, dashed, or dotted lines to represent the key levels and pivot points for better clarity and personal preference.
4. **Conditional Coloring:**
- The indicator applies conditional coloring to the lines based on the comparison of current close prices across different timeframes. Yellow indicates lower closes, and red indicates higher closes, making it easy to identify important price levels quickly.
#### Usage Instructions
1. **Enable Key Levels:**
- Toggle the "Daily Weekly Monthly High/Low" option to display or hide the respective levels.
- Select your preferred line style (solid, dashed, dotted) for better visibility.
2. **Display Pivot Points:**
- Toggle the "Pivot" option to show or hide the weekly, monthly, and yearly pivot points on the chart.
3. **Interpret Color Coding:**
- Yellow lines indicate levels where the close price is lower compared to a specific timeframe close.
- Red lines indicate levels where the close price is higher compared to a specific timeframe close.
- Specific colors for yearly levels and pivots are used to distinguish them clearly on the chart.
By following these guidelines, traders can effectively use this indicator to identify critical price levels and make informed trading decisions.
[SGM Return Distribution]Code Description
This Pine Script™ is designed to analyze the distribution of historical returns of a financial asset and project future confidence levels. It uses statistical techniques to estimate the probability of winning and losing as well as displaying confidence bands and distribution statistics.
User Entries
Length (252): The number of days used to calculate statistics.
Offset (20): Offset used to project future values.
Projection Days (10): Number of days projected into the future.
Smoothing Confidence Levels (10): Smoothing confidence bands.
Display Settings
Plot Distribution: Shows the distribution of returns.
Show Probabilities: Shows winning and losing probabilities.
Show Distribution Stats: Shows distribution statistics.
Show Confidence Bands: Shows confidence bands.
Show Confidence Lines: Shows confidence lines.
Calculations and Features
Distribution of Yields:
Calculates logarithmic returns and their statistics (average, volatility, skewness, kurtosis).
Projects the average and volatility over the projected number of days.
Displays the distribution of returns as a histogram.
Confidence Interval:
Uses the inv_norm function to calculate Z scores for different confidence levels.
Calculates the upper and lower bounds of the confidence bands.
Probability Display:
Calculates and displays win and loss probabilities based on the distribution of returns.
Statistics Display:
Shows key statistics such as mean, volatility, skewness and kurtosis.
Trust Bands and Lines:
Shows confidence bands and lines based on calculated confidence levels.
Mathematical Assumptions Used
Logarithmic Returns: Returns are calculated using the logarithm of prices, which is common for financial time series because it makes returns independent of price level.
Normal Distribution for Confidence Bands: Confidence interval calculations are based on the assumption that returns follow a normal distribution.
Average and Volatility Projection: Average returns and volatility are projected over a future period assuming they remain constant.
Skewness and Kurtosis: Although these measures are calculated for understanding the distribution of returns, they are not used in box projections but can provide additional information about the distribution of historical returns.
Use in Trading
Risk Estimation: Confidence bands can help estimate likely future price levels, which is crucial for determining strike levels and risk management.
Risk Management: Use confidence bands to set stop-loss and take-profit levels.
Probability Analysis: Win and loss probabilities can help assess a position's likelihood of success.
Potential Problems
Assumption of Normality for Confidence Bands: Financial returns do not always follow a normal distribution, especially in the presence of extreme events (fat tails).
Stationarity: Assuming that return statistics (average, volatility) remain constant over time can be erroneous in volatile market periods.
Limited Historical Data: Using a limited history (252 days) may not capture all possible behaviors of the asset.
Input Parameters: Results can be sensitive to the input parameters chosen (length, offset, etc.).
ToxicJ3ster - Day Trading SignalsThis Pine Script™ indicator, "ToxicJ3ster - Signals for Day Trading," is designed to assist traders in identifying key trading signals for day trading. It employs a combination of Moving Averages, RSI, Volume, ATR, ADX, Bollinger Bands, and VWAP to generate buy and sell signals. The script also incorporates multiple timeframe analysis to enhance signal accuracy. It is optimized for use on the 5-minute chart.
Purpose:
This script uniquely combines various technical indicators to create a comprehensive and reliable day trading strategy. Each indicator serves a specific purpose, and their integration is designed to provide multiple layers of confirmation for trading signals, reducing false signals and increasing trading accuracy.
1. Moving Averages: These are used to identify the overall trend direction. By calculating short and long period Moving Averages, the script can detect bullish and bearish crossovers, which are key signals for entering and exiting trades.
2. RSI Filtering: The Relative Strength Index (RSI) helps filter signals by ensuring trades are only taken in favorable market conditions. It detects overbought and oversold levels and trends within the RSI to confirm market momentum.
3. Volume and ATR Conditions: Volume and ATR multipliers are used to identify significant market activity. The script checks for volume spikes and volatility to confirm the strength of trends and avoid false signals.
4. ADX Filtering: The ADX is used to confirm the strength of a trend. By filtering out weak trends, the script focuses on strong and reliable signals, enhancing the accuracy of trade entries and exits.
5. Bollinger Bands: Bollinger Bands provide additional context for the trend and help identify potential reversal points. The script uses Bollinger Bands to avoid false signals and ensure trades are taken in trending markets.
6. Higher Timeframe Analysis: This feature ensures that signals align with broader market trends by using higher timeframe Moving Averages for trend confirmation. It adds a layer of robustness to the signals generated on the 5-minute chart.
7. VWAP Integration: VWAP is used for intraday trading signals. By calculating the VWAP and generating buy and sell signals based on its crossover with the price, the script provides additional confirmation for trade entries.
8. MACD Analysis: The MACD line, signal line, and histogram are calculated to generate additional buy/sell signals. The MACD is used to detect changes in the strength, direction, momentum, and duration of a trend.
9. Alert System: Custom alerts are integrated to notify traders of potential trading opportunities based on the signals generated by the script.
How It Works:
- Trend Detection: The script calculates short and long period Moving Averages and identifies bullish and bearish crossovers to determine the trend direction.
- Signal Filtering: RSI, Volume, ATR, and ADX are used to filter and confirm signals, ensuring trades are taken in strong and favorable market conditions.
- Multiple Timeframe Analysis: The script uses higher timeframe Moving Averages to confirm trends, aligning signals with broader market movements.
- Additional Confirmations: VWAP, MACD, and Bollinger Bands provide multiple layers of confirmation for buy and sell signals, enhancing the reliability of the trading strategy.
Usage:
- Customize the input parameters to suit your trading strategy and preferences.
- Monitor the generated signals and alerts to make informed trading decisions.
- This script is made to work best on the 5-minute chart.
Disclaimer:
This indicator is not perfect and can generate false signals. It is up to the trader to determine how they would like to proceed with their trades. Always conduct thorough research and consider seeking advice from a financial professional before making trading decisions. Use this script at your own risk.
9:30 Opening Price MarkerIndicator Name: 9:30 Opening Price Marker
Description:
The "9:30 Opening Price Marker" is a custom indicator for TradingView that highlights the opening price at 9:30 AM in the UTC-4 time zone (Eastern Daylight Time) on the chart. It helps traders and analysts easily identify and track the price level at which the market opens each day.
Features:
Timezone Conversion: The indicator converts the current time to the UTC-4 timezone (Eastern Daylight Time) to accurately determine the 9:30 AM opening price.
Visual Marker: It visually marks the opening price with a dotted line on the chart, making it prominent for quick reference.
Label: Additionally, it includes a label next to the opening price line, indicating "9:30 Opening Price", enhancing clarity and usability.
Overlay: The indicator is designed to overlay on the price chart, ensuring it doesn't clutter other technical analysis tools or indicators.
Usage:
Day-to-Day Analysis: Traders can use this indicator to quickly gauge market sentiment at the daily opening, which can influence intraday trading strategies.
Reference Point: Acts as a reference point for identifying price movements and potential trading opportunities relative to the day's opening price.
Time-Specific Insights: Provides insights into price action immediately following the market open, aiding in decision-making based on early trading activity.
Installation: Copy the provided Pine Script code into TradingView's Pine Editor, save the script as an indicator, and apply it to your chart.
Disclaimer : This indicator is intended for informational purposes only and should not be solely relied upon for trading decisions. Always consider multiple sources of information and perform thorough analysis before executing trades.
ARIMA Indicator with Optional SmoothingOverview
The ARIMA (AutoRegressive Integrated Moving Average) Indicator is a powerful tool used to forecast future price movements by combining differencing, autoregressive, and moving average components. This indicator is designed to help traders identify trends and potential reversal points by analyzing the historical price data.
Key Features
AutoRegressive Component (AR): Utilizes past values to predict future prices.
Moving Average Component (MA): Averages past price differences to smooth out noise.
Differencing: Reduces non-stationarity in the time series data.
Optional Smoothing: Applies EMA to the ARIMA output for a smoother signal.
Customizable Parameters: Allows users to adjust AR and MA orders, differencing periods, and smoothing lengths.
Concepts Underlying the Calculations
Differencing: Subtracts previous prices from current prices to remove trends and seasonality, making the data stationary.
AutoRegressive Component (AR): Predicts future prices based on a linear combination of past values.
Moving Average Component (MA): Uses past forecast errors to refine future predictions.
Exponential Moving Average (EMA): Applies more weight to recent prices, providing a smoother and more responsive signal.
How It Works
The ARIMA Indicator first calculates the differenced series to achieve stationarity. Then, it computes the simple moving average (SMA) of this differenced series. The indicator uses the AR and MA components to adjust the SMA, creating an approximation of the ARIMA model. Finally, an optional smoothing step using EMA can be applied to the ARIMA approximation to produce a smoother signal.
How Traders Can Use It
Traders can use the ARIMA Indicator to:
Identify Trends: Detect emerging trends by observing the direction of the ARIMA line.
Spot Reversals: Look for divergences between the ARIMA line and the price to identify potential reversal points.
Generate Trading Signals: Use crossovers between the ARIMA line and the price to generate buy or sell signals.
Filter Noise: Enable the optional smoothing to filter out market noise and focus on significant price movements.
Example Usage Instructions
Add the ARIMA Indicator to your chart.
Adjust the input parameters to suit your trading strategy:
Set the SMA Length (e.g., 14).
Choose the Differencing Period (e.g., 1).
Define the AR Order (p) and MA Order (q) (e.g., 1).
Configure the Smoothing Length if smoothing is desired (e.g., 5).
Enable or disable smoothing as needed.
Observe the ARIMA line (blue) and compare it to the price chart.
Use the ARIMA line to identify trends and potential reversals.
Implement trading decisions based on the ARIMA line’s behavior relative to the price.
Simple Risk-to-Reward Multiplier A simple R/R indicator that allows you to input your entry price and stop loss (in ticks). Then, your take profit levels are R-multipliers based on your stop loss. You can have up to 5 take profit levels on your chart. There is also a function to indicate if it is a long or short setup. You can also set alerts with this script, allowing you the ability not to have to stare at the charts all day.
[Suitable Hope] Crypto Upside Model 3.0The "Crypto Upside Model 3.0" indicator dynamically calculates the potential price of any cryptocurrency based on various percentages of Ethereum or Bitcoin's market capitalization.
By fetching and analyzing marketcap data from TradingView sources, it allows traders to visualize potential price targets if their chosen cryptocurrency reaches specific market dominance levels. This tool is designed for daily timeframe analysis and can be used to set informed price expectations and strategic investment goals, providing valuable insights for long-term investment planning.
Why using the Crypto Upside Model 3.0?
Strategic Planning: Helps traders and investors set realistic price targets and investment goals by visualizing potential market cap scenarios.
Informed Decision-Making: Provides a data-driven approach to understanding how a cryptocurrency might perform relative to major assets like Bitcoin and Ethereum.
Customizable Analysis: Allows users to choose different comparison assets (ETH or BTC) and visualize various market cap dominance percentages, offering tailored insights.
Daily Timeframe Focus: Ideal for swing traders and long-term investors who operate on a daily analysis timeframe, providing relevant and actionable data.
Bull Markets: Identify potential price targets if your cryptocurrency's market cap increases significantly.
Bear Markets: Assess how much value could be retained relative to major cryptocurrencies.
Strategic Entry/Exit Points: Use the visualized targets to plan entry or exit points in your trading strategy.
Comparative Advantage
Dynamic Adaptation: Unlike fixed indicators, this tool adapts to any active chart, making it versatile for multiple cryptocurrencies.
Market Cap Insights: Provides a unique perspective by linking price targets to market cap dominance, a critical factor in the crypto market.
User Instructions
Setup: Add the " Upside Model 3.0" indicator to your TradingView chart.
Configuration: Use the input settings to select the comparison cryptocurrency (ETH or BTC) and enable the desired market cap percentage plots.
Analysis: The indicator will display potential price targets based on the selected market cap percentages, providing a visual guide for setting price expectations.
Limitations
Marketcap Data Availability: The indicator relies on marketcap data from TradingView, which may not be available for all cryptocurrencies. If the data is unavailable, the indicator will not function for that asset. This tool is more likely to work with older, established cryptocurrencies, as marketcap data for newer cryptocurrencies may not yet be available.
Daily Timeframe Restriction: The indicator is designed to work exclusively on the daily timeframe, limiting its applicability for intraday trading.
Assumptions of Market Dynamics: The calculations assume a direct correlation between market dominance and price, which may not account for other market dynamics and external factors influencing prices.
Data Accuracy: The accuracy of the indicator depends on the reliability of the data provided by TradingView, which may sometimes experience delays or inaccuracies.
Currently available cryptocurrencies: Bitcoin, Ethereum, Solana, Binance Coin, Cardano, Ripple, Polkadot, Avalanche, Chainlink, Litecoin, Dogecoin, Terra, Uniswap, VeChain, Stellar, Internet Computer, Hedera, Filecoin, Monero, Aave, TRON, NEAR Protocol, Compound, Maker,... For all compatible cryptocurrencies, please consult CRYPTOCAP's documentation.
Final notes
Although various sources ask a payment or user data for similar kind of private indicators, this one is entirely free and open source. "Uncanny" isn't it? I hope this indicator will provide you value. Feel free to leave a message if you have any questions or constructive feedback.
Examples of how I use this indicator
When using ETH's historical price as a reference compared to Bitcoin's marketcap, we can notice that price generally has been held between the +-30% and 50% lines of BTC's marketcap. If history is repeating again, we can expect major resistances around the 50% looking ahead into the future. This for me would be a great area to potentially reduce my ETH spot position.
When using SOL's historical price action, we can notice that the 15% line of ETH's marketcap has been a top in the previous cycle. Today SOL (July 2024), is back at this level. Could this be a top again or could price break this 15% level and head perhaps towards 30% which currently sits around $260? Time will tell.
These are 2 simple example of how I interpret the data. I'm keen to hear what other findings with other pairs you can find.
Sector Analysis This indicator offers a straightforward yet effective way to analyze and compare the performance of various sectors within the market. By normalizing and plotting sector-specific data as lines on the chart, it enables users to quickly assess sector rotations, relative strength, and potential shifts in market dynamics. The sector labels further enhance usability by clearly identifying each line’s corresponding sector, facilitating easy interpretation and analysis.
Risk Radar ProThe "Risk Radar Pro" indicator is a sophisticated tool designed to help investors and traders assess the risk and performance of their investments over a specified period. This presentation will explain each component of the indicator, how to interpret the results, and the advantages compared to traditional metrics.
The "Risk Radar Pro" indicator includes several key metrics:
● Beta
● Maximum Drawdown
● Compound Annual Growth Rate (CAGR)
● Annualized Volatility
● Dynamic Sharpe Ratio
● Dynamic Sortino Ratio
Each of these metrics is dynamically calculated using data from the entire selected period, providing a more adaptive and accurate measure of performance and risk.
1. Start Date
● Description: The date from which the calculations begin.
● Interpretation: This allows the user to set a specific period for analysis, ensuring that all metrics reflect the performance from this point onward.
2. Beta
● Description: Beta measures the volatility or systematic risk of the instrument relative to a reference index (e.g., SPY).
● Interpretation: A beta of 1 indicates that the instrument moves with the market. A beta greater than 1 indicates more volatility than the market, while a beta less than 1 indicates less volatility.
● Advantages: Unlike classic beta, which typically uses fixed historical intervals, this dynamic beta adjusts to market changes over the entire selected period, providing a more responsive measure.
3. Maximum Drawdown
● Description: The maximum observed loss from a peak to a trough before a new peak is achieved.
● Interpretation: This shows the largest single drop in value during the specified period. It is a critical measure of downside risk.
● Advantages: By tracking the maximum drawdown dynamically, the indicator can provide timely alerts when significant losses occur, allowing for better risk management.
4. Annualized Performance
● Description: The mean annual growth rate of the investment over the specified period.
● Interpretation: The Annualized Performance represents the smoothed annual rate at which the investment would have grown if it had grown at a steady rate.
● Advantages: This dynamic calculation reflects the actual long-term growth trend of the investment rather than relying on a fixed time frame.
5. Annualized Volatility
● Description: Measures the degree of variation in the instrument's returns over time, expressed as a percentage.
● Interpretation: Higher volatility indicates greater risk, as the investment's returns fluctuate more.
● Advantages: Annualized volatility calculated over the entire selected period provides a more accurate measure of risk, as it includes all market conditions encountered during that time.
6. Dynamic Sharpe Ratio
● Description: Measures the risk-adjusted return of an investment relative to its volatility.
● Choice of Risk-Free Rate Ticker: Users can select a ticker symbol to represent the risk-free rate in Sharpe ratio calculations. The default option is US03M, representing the 3-month US Treasury bill.
● Interpretation: A higher Sharpe ratio indicates better risk-adjusted returns. This ratio accounts for the risk-free rate to provide a comparison with risk-free investments.
● Advantages: By using returns and volatility over the entire period, the dynamic Sharpe ratio adjusts to changes in market conditions, offering a more accurate measure than traditional static calculations.
7. Dynamic Sortino Ratio
● Description: Similar to the Sharpe ratio, but focuses only on downside risk.
Interpretation: A higher Sortino ratio indicates better risk-adjusted returns, focusing solely on negative returns, which are more relevant to risk-averse investors.
● Choice of Risk-Free Rate Ticker: Similarly, users can choose a ticker symbol for the risk-free rate in Sortino ratio calculations. By default, this is also set to US03M.
● Advantages: This ratio's dynamic calculation considering the downside deviation over the entire period provides a more accurate measure of risk-adjusted returns in volatile markets.
Comparison with Basic Metrics
● Static vs. Dynamic Calculations: Traditional metrics often use fixed historical intervals, which may not reflect current market conditions. The dynamic calculations in "Risk Radar Pro" adjust to market changes, providing more relevant and timely information.
● Comprehensive Risk Assessment: By including metrics like maximum drawdown, Sharpe ratio, and Sortino ratio, the indicator provides a holistic view of both upside potential and downside risk.
● User Customization: Users can customize the start date, reference index, risk-free rate, and table position, tailoring the indicator to their specific needs and preferences.
Conclusion
The "Risk Radar Pro" indicator is a powerful tool for investors and traders looking to assess and manage risk more effectively. By providing dynamic, comprehensive metrics, it offers a significant advantage over traditional static calculations, ensuring that users have the most accurate and relevant information to make informed decisions.
The "Risk Radar Pro" indicator provides analytical tools and metrics for informational purposes only. It is not intended as financial advice. Users should conduct their own research and consider their individual risk tolerance and investment objectives before making any investment decisions based on the indicator's outputs. Trading and investing involve risks, including the risk of loss. Past performance is not indicative of future results.
CNN Fear and Greed IndexThe “CNN Fear and Greed Index” indicator in this context is designed to gauge market sentiment based on a combination of several fundamental indicators. Here’s a breakdown of how this indicator works and what it represents:
Components of the Indicator:
1. Stock Price Momentum:
• Calculates the momentum of the S&P 500 index relative to its 125-day moving average. Momentum is essentially the rate of acceleration or deceleration of price movements over time.
2. Stock Price Strength:
• Measures the breadth of the market by comparing the number of stocks hitting 52-week highs versus lows. This provides insights into the overall strength or weakness of the market trend.
3. Stock Price Breadth:
• Evaluates the volume of shares trading on the rise versus the falling volume. Higher volume on rising days suggests positive market breadth, while higher volume on declining days indicates negative breadth.
4. Put and Call Options Ratio (Put/Call Ratio):
• This ratio indicates the sentiment of investors in the options market. A higher put/call ratio typically signals increased bearish sentiment (more puts relative to calls) and vice versa.
5. Market Volatility (VIX):
• Also known as the “fear gauge,” the VIX measures the expected volatility in the market over the next 30 days. Higher VIX values indicate higher expected volatility and often correlate with increased fear or uncertainty in the market.
6. Safe Haven Demand:
• Compares the returns of stocks (represented by S&P 500) versus safer investments like 10-year Treasury bonds. Higher returns on bonds relative to stocks suggest a flight to safety or risk aversion.
7. Junk Bond Demand:
• Measures the spread between yields on high-yield (junk) bonds and investment-grade bonds. Widening spreads may indicate increasing risk aversion as investors demand higher yields for riskier bonds.
Normalization and Weighting:
• Normalization: Each component is normalized to a scale of 0 to 100 using a function that adjusts the range based on historical highs and lows of the respective indicator.
• Weighting: The user can adjust the relative importance (weight) of each component using input parameters. This customization allows for different interpretations of market sentiment based on which factors are considered more influential.
Fear and Greed Index Calculation:
• The Fear and Greed Index is calculated as a weighted average of all normalized components. This index provides a single numerical value that summarizes the overall sentiment of the market based on the selected indicators.
Usage:
• Visualization: The indicator plots the Fear and Greed Index and its components on the chart. This allows traders and analysts to visually assess the sentiment trends over time.
• Analysis: Changes in the Fear and Greed Index can signal shifts in market sentiment. For example, a rising index may indicate increasing greed and potential overbought conditions, while a falling index may suggest increasing fear and potential oversold conditions.
• Customization: Traders can customize the indicator by adjusting the weights assigned to each component based on their trading strategies and market insights.
By integrating multiple fundamental indicators into a single index, the “CNN Fear and Greed Index” provides a comprehensive snapshot of market sentiment, helping traders make informed decisions about market entry, exit, and risk management strategies.
Fourier Extrapolation of PriceOverview
The "Fourier Extrapolation of Price" indicator utilizes Fourier Transform methods to analyze and predict future price movements based on historical data. By decomposing price series into their frequency components, this indicator provides a forecast of future price trends, making it a powerful tool for traders seeking advanced analytical techniques.
Key Features
Fourier Transform Analysis: Applies Discrete Fourier Transform (DFT) to the price series to identify frequency components.
Price Prediction: Forecasts future prices based on the dominant frequencies detected in the historical data.
Customizable Parameters: Allows users to set the length of historical data for analysis and the forecast period.
Visual Representation: Plots historical and forecasted prices for easy comparison.
How It Works
The indicator first normalizes the price series by subtracting the mean. It then applies the Discrete Fourier Transform (DFT) to the normalized data, extracting the real and imaginary parts. The magnitude and phase of these components are used to forecast future prices through an inverse DFT. Finally, the forecasted prices are denormalized and plotted alongside the historical prices on the chart.
Usage Instructions
Configure Parameters: Set the length of the historical data (DFT Length) and the forecast period (Forecast Length) to suit your analysis.
Apply to Chart: Add the indicator to your chart to start the analysis. Note that the computation may take a minute to complete due to the complexity of the Fourier Transform.
Analyze Results: Review the plotted forecasted prices (in red) alongside the historical prices (in blue) to identify potential future trends.
Trading Decisions: Use the forecasted price trends to inform your trading decisions, such as identifying potential entry and exit points based on predicted market movements.
Note : Due to the computational complexity of the Fourier Transform, the prediction may take a minute to load. Please be patient as the indicator processes the data to provide accurate forecasts.
This indicator is useful for traders who:
Advanced Analysis: Seek advanced mathematical techniques for market analysis.
Trend Prediction: Want to forecast future price movements based on historical data.
Customizable Analysis: Prefer customizable parameters for tailored analysis.
Visual Insights: Appreciate visual representation of historical and forecasted prices for better decision-making.
Gap Trend Lines by @eyemaginativeSummary:
The "Gap Trend Lines" script is designed to identify and visualize gaps between the close of one candle and the opening of the next on a TradingView chart. It draws extended trend lines to visually connect these gaps, helping traders to identify significant price movements between consecutive candles.
Functionality:
Indicator Setup:
The script is set as an overlay indicator on the main chart.
It includes settings for maximum line and label counts, ensuring efficient performance.
Parameter Customization:
Gap Threshold: Defines the minimum gap size considered significant.
Line Colors: Allows customization of colors for small and large gaps.
Line Thickness and Style: Provides options to adjust the thickness and style (solid, dotted, dashed) of the trend lines.
Drawing Extended Trend Lines:
For each bar (candlestick) on the chart, the script checks if there is a gap between the previous candle's close and the current candle's open.
If a gap is detected (i.e., close != open), it determines the size of the gap.
Depending on the size relative to the defined threshold, it selects the appropriate color (small or large gap).
It then draws an extended trend line that starts from the close of the previous candle (bar_index , close ) and extends to the open of the current candle (bar_index, open).
The trend line is drawn with the specified thickness, color, and style.
Dynamic Line Attribute Changes:
The script includes a function (changeLineAttributes()) that periodically changes the color and style of the trend lines.
By default, it changes the color every 4 hours (adjustable), alternating between green and the original color.
Enhanced Functionality:
Handles both small and large gaps with different visual cues (colors).
Supports extended trend lines that span both past and future directions (extend=extend.both), ensuring visibility across the entire chart.
Usage:
Traders can use the "Gap Trend Lines" script to:
Identify and analyze gaps between candlesticks.
Visualize significant price movements or breaks in continuity.
Customize the appearance of trend lines for better clarity and analysis.
By utilizing this script, traders can gain insights into price gap dynamics directly on TradingView charts, aiding in decision-making and strategy development.
Exponential Grid [Phi, Pi, Euler]If you disagree with one of the EMH principles that price is too random, then by definition you must agree that historic price has deterministic function to a scenario ahead.
I personally believe that constants like phi, pi and e can mimic exponential growth of the price.
In this script, first grid is based on the Lowest price multiplied with self fraction of the constant.
For example:
If you are familiar with fib ratio 1.272, then you must know that it is 1.618 to the power of 0.5.
With default settings of exponent step 0.25
First grid = Lowest price x phi^0.25
Second grid = Lowest price x phi^0.25x2
Third grid = Lowest price x phi^0.25x3 and so on
The script will automatically find the lowest price and update the grid values.
Or you can set up your custom Lowest price manually if you feel like the All Time Low level loses its relevance value after long period.
There are 64 grids including Lowest price level. And it wasn't by a chance. Pine Script has a limitation of max 64 plots. Number of grids shown in the chart depends on the highest price. Once price breaks above ATH a couple of next grids will be plotted automatically. In most cases if everything is plotted, the chart appears squeezed and you'll need to zoom in to see it. Therefore, I adjusted it relatively to the scale of the chart for the comfort.
In some cases 64 plots aren't enough to cover the whole chart. For example, let's take a look at NVIDIA chart:
Since the price has started with 0.0333, it is way too small to cover all with default settings.
We are left with 2 choices:
Either Enable "Round"
OR increase Exponent Step (from 0.25 to 0.5 in the particular example below)
If you set constant to pi or e which is a bigger number than phi, expect the gaps to be bigger. To reduce it to a more gradual way of expansion you can decrease Exponent Step.
Earnings Beat IndicatorThis indicator seeks to predict whether a stock will beat or miss earnings by forecasting revenues, and subsequently net income, using linear regression. The y-values of this regression are revenues and the x-axis is an economic series of your choosing. Double-click the status line (the words "US" and "GDP") to change economic datasets. The full list of economic datasets available in TradingView is in the Help Center.
Instructions:
1. Double-click on the status line (the fields "US" and "GDP"). The inputs tab will pop up.
2. Type in the country and data codes for the economic datasets you believe have the highest correlation with revenues and net margins respectively.
3. Check the correlation coefficient between financial data and economic data by interpreting the white and gray numbers on the status line - white for the correlation coefficient between revenues and your chosen economic dataset, and gray for the correlation coefficient between net margins and your chosen economic dataset. These numbers should be as close to +1 or -1 as possible.
4. Interpret the results - the blue number indicates whether revenues will beat estimates and the green number indicates whether earnings will beat estimates. A 1 for both outputs indicates a double beat, a 1 and a 0 indicates a revenue beat but not an earnings beat, a 0 and a 1 indicates an earnings beat but not a revenue beat, and a 0 and a 0 indicates a double miss.
- DickZhones
COT-NocTradingIndicator Description:
Commitments of Traders (COT) Data Indicator
The Commitments of Traders (COT) Data Indicator on TradingView provides insights into market sentiment based on the weekly CFTC (Commodity Futures Trading Commission) reports. It plots three key lines derived from this data, offering valuable information for traders seeking to understand positioning trends among large speculators, commercial hedgers, and small traders.
Lines Plotted:
Commercials: Reflects positions held by commercial entities engaged in the production or sale of the underlying commodity. Their positions often act as a hedge against physical market exposure.
Non Commercials: Represents positions held by large speculators, typically hedge funds and large financial institutions, who often take more significant positions based on their market outlook.
Retail Traders: Shows positions held by small traders, including individual retail traders and smaller institutional players, providing insights into the broader retail sentiment.
Labeling:
Each line is accompanied by a label to clearly identify its corresponding group, enhancing clarity and ease of interpretation for traders analyzing the indicator.
Usage:
Trend Confirmation: Monitor the positioning of commercial and non commercial relative to retail traders to confirm trends and potential reversals.
Sentiment Analysis: Assess shifts in market sentiment based on changes in positioning across different trader categories.
Trading Signals: Use crossovers, divergences, and extreme positioning relative to historical data to generate potential trading signals.
This indicator is valuable for traders looking to incorporate institutional positioning data into their trading strategies, offering a deeper understanding of market dynamics beyond price action alone.
ADX and SADX, SDIThe indicator aims to analyze and visualize the Average Directional Index (ADX) and its smoothed versions, along with directional indicators (DI) to help traders identify trend strength and potential buy/sell signals.
Indicator Settings:
The indicator is named "ADX and SADX, SDI" and is set to display prices with a precision of 2 decimal places.
Users can customize the ADX smoothing length, DI length, ADX smoothing period, and DI smoothing period through input variables.
Directional Movement (DM) Calculation:
The function dirmov calculates the positive and negative directional movements (DM) and the smoothed values of the positive directional index (DI+) and negative directional index (DI-).
This is done using the average true range (ATR) to normalize the DM values.
Average Directional Index (ADX) Calculation:
The function adx calculates the ADX, which measures the strength of a trend.
It uses the DI+ and DI- values to compute the ADX value.
Smoothed ADX and DI Calculation:
The ADX values are further smoothed using a simple moving average (SMA).
The DI difference is also smoothed and used to determine the trend direction.
Buy and Sell Signals:
A buy signal is generated when the DI+ crosses above DI- and the smoothed DI difference is increasing.
A sell signal is generated when the DI- crosses above DI+ and the smoothed DI difference is decreasing.
Plotting:
The ADX, smoothed ADX, smoothed DI difference (SPM), DI+, and DI- values are plotted on the chart.
Horizontal lines are drawn to indicate threshold levels (e.g., level 22).
Background and bar colors change based on buy (lime) and sell (maroon) signals to visually indicate these conditions.
Purpose of the Code:
This Pine Script code is used to create a custom indicator on TradingView that helps traders identify the strength and direction of a trend. The Average Directional Index (ADX) is used to measure trend strength, while the Directional Indicators (DI+ and DI-) are used to determine the direction of the trend. The smoothed versions of these indicators (SADX and SDI) provide additional confirmation and smoothing to reduce noise and false signals. Traders can use the buy and sell signals generated by this indicator to make informed trading decisions based on the trend strength and direction.
Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Median Analyst ConsensusThe Median Analyst Consensus Indicator provides an unbiased, easy-to-interpret view of market sentiment by leveraging TradingView's comprehensive financial data library. This tool displays the median 12-month price target and the percentage difference from the current price directly on your charts.
Key Features
1. Accurate Market Sentiment: By consolidating analyst ratings and price targets from multiple reputable sources like Bloomberg, Refinitiv (formerly Thomson Reuters), S&P Capital IQ, and Morningstar, this indicator displays the median analyst consensus. Using the median ensures outlier ratings don't skew the overall sentiment, providing a more robust representation.
2. Simplicity at a Glance: View the median 12-month price target and percentage difference from the current price directly on your chart. No need to juggle multiple reports - key insights are surfaced within your normal trading workflow.
3. Data-Driven Transparency: If no analyst data is available for a particular asset, the indicator will not display, ensuring you only see reliable information. The number of contributing analysts is also shown for context.
Why the Median?
The median is favored over the mean to minimize the impact of outlier ratings that could distort the consensus view. By taking the middle value across all analyst projections, the median provides a more stable, outlier-resistant measure of market sentiment.
Powered by TradingView Data
This indicator taps into TradingView's financial data library, which aggregates analyst ratings, estimates, and recommendations from leading institutional data providers. TradingView sources this data from firms like FactSet, Bloomberg, Refinitiv, S&P Capital IQ, and Morningstar, ensuring a comprehensive and trusted view of analyst sentiment.
The library provides variables like:
syminfo.recommendations_buy
syminfo.recommendations_sell
syminfo.target_price_median
syminfo.recommendations_buy_strong
syminfo.recommendations_sell_strong
The indicator calculates and displays the median of these analyst inputs.
Usage
The indicator displays:
The median 12-month price target across analysts
The percentage difference between the price target and current price
The number of contributing analyst estimates
If no analyst data is available, the indicator does not display, ensuring full transparency.
The Median Analyst Consensus Indicator provides an unbiased, easy-to-interpret view of market sentiment by leveraging TradingView's comprehensive financial data library. This tool offers a new perspective on potential trade opportunities directly on your charts.
Disclaimer
While the data is sourced from reputable providers, analyst forecasts should not be construed as investment recommendations. This indicator aims to synthesize market opinions, but investment decisions are solely your responsibility. As with any analytical tool, you should conduct your own research and risk assessments before executing any trades.
ΔYoY(Economics)Year over year indicator which will benchmark the most recent data vs 1 year lookback; Will automate the lookback for quarterly and monthly data based on timeframe selected (3M for quarterly, 1M for monthly). Tradingview will aggregate weekly data into a monthly data point. SMA applied to get the average over some x period.
Ln(close)Natural log indicator for normalizing data. SMA applied so you can take the average of that normalization factor. Personally use it for US economic data where the value is very large (GDI, Fed Balance Sheet, USM2 etc.) and the year over year delta is not pertinent (USM2) or not available (GDI.. although I did make an indicator to get YoY :D). Any additional ideas leave a comment and I'll take a look.
Nasan Moving Average with ForecastThe "Nasan Moving Average with Forecast" indicator is a technical analysis forecasting tool that combines the principles of historical data analysis and random walk theory. It calculates a customized moving average (Nasan Moving Average) by integrating price data and statistical measures and projects future price points by generating forecast values within calculated volatility bounds, creating a dynamic and insightful visualization of potential market movements. This indicator to blend past market behavior with probabilistic future trends to enhance forecasting.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
forecast_points: Number of points to forecast (default 30).
m: Multiplier for standard deviation (default 2.5).
bl: Block length for calculating max/min values (default 100).
use_calculated_max_min: Boolean to decide whether to use calculated max/min values.
Nasan Moving Average Calculation:
Calculates the simple moving average (mean) and standard deviation (sd) of the typical price (hlc3).
Computes intermediate variables (a, b, c, etc.) based on log transformation and cumulative sum.
Applies weighted moving averages (wma) to these intermediate variables to smooth them and derive the final value c6.
Plots c6 as the Nasan Moving Average if the bar is confirmed. To learn more see Nasan Moving Average.
Forecast Points Calculation:
Calculates maximum (max_val) and minimum (min_val) values for the forecast, either using a fixed value or based on standard deviation and a multiplier.
Initializes an array to store forecast values and creates polyline objects for plotting.
If the current bar is one of the last three bars and confirmed:
Clears and reinitializes the polyline.
Initializes the first forecast value from the cumulative sum c.
Generates subsequent forecast values using a random value within the range .
Updates the forecast array and plots the forecast points as an orange curved polyline.
Plotting Max/Min Values:
Plots max_val and min_val as green and red lines, respectively, to indicate the bounds of the forecast range.
Components of the Forecasting Model
Historical Dependence:
Nasan Moving Average Calculation: The script calculates a custom moving average (c6) that incorporates historical price data (hlc3), standard deviations (sd), and weighted moving averages (wma). This part of the code processes historical data to create a smoothed representation of the price trend.
Max/Min Value Calculation: The maximum (max_val) and minimum (min_val) values for the forecast can be calculated based on the historical standard deviation of a transformed variable b over a block length (bl). This introduces historical volatility into the bounds for the forecast.
Random Walk Model:
Random Value Generation: Within the forecast points calculation, a random value (random_val) is generated for each forecast point within the range . This random value introduces stochasticity into the model, characteristic of a random walk process.
Cumulative Sum for Forecasting: The script uses a cumulative sum (prev_f + random_val) to generate the next forecast point (next_f). This is a typical approach in random walk models where each new point is based on the previous point plus some random noise.
Explanation of the Forecast Model
Random Walk Characteristics: Each new forecast point is generated by adding a random value to the previous point, making the model a random walk with drift, where the drift is influenced by historical correction factors (c1, c4).
Historical and Statistical Dependence: The bounds of the random values and the initial conditions are derived from historical data, ensuring that the forecast respects historical volatility and trends.
The forecasting model in the script is a hybrid approach: It uses a random walk to generate future points, characterized by adding random values to the previous forecasted value.
The historical and statistical dependence is incorporated through initial conditions, scaling factors, and bounds derived from historical price data and its statistical properties.
This combination ensures that the forecasts are not purely stochastic but are grounded in historical price behavior, making the model more robust and potentially more accurate in reflecting market conditions.
