Global Liquidity Index 10 Week LeadThis script is an extension of the Global Liquidity Index , incorporating a key modification: a 10-week lead adjustment.
The indicator values are shifted forward by 10 weeks, dynamically adapting to the chart's timeframe (daily, weekly, monthly). This adjustment plots the lead values ahead of the current time, offering a clearer visual alignment with potential future trends. The approach aligns with the theory explored and popularized by Michael Howell of CrossBorder Capital and Raoul Pal of Global Macro Investor, which suggests that Bitcoin typically lags global liquidity by approximately 8 to 12 weeks.
The Global Liquidity Index is calculated based on the following components:
Major Central Banks:
Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP) + European Central Bank (ECB) + People's Bank of China (PBC) + Bank of Japan (BOJ) + Bank of England (BOE) + Bank of Canada (BOC) + Reserve Bank of Australia (RBA) + Reserve Bank of India (RBI) + Swiss National Bank (SNB) + Central Bank of the Russian Federation (CBR) + Central Bank of Brazil (BCB) + Bank of Korea (BOK) + Reserve Bank of New Zealand (RBNZ) + Sweden's Central Bank (Riksbank) + Central Bank of Malaysia (BNM).
M2 Money Supply:
Includes M2 for the USA, Europe, China, Japan, UK, Canada, Australia, India, Switzerland, Russia, Brazil, Korea, Mexico, Indonesia, South Africa, Malaysia, and Sweden.
加密貨幣
Altcoin Exit Signal👉 This indicator is designed to help traders identify optimal times to sell altcoins during the peak of a bull market. By analyzing the historical ratio of the "OTHERS" market cap (all altcoins excluding the top 10) to Bitcoin, it signals when altcoins are nearing their cycle peaks and may be due for a decline. This is a good indicator to use for smaller altcoins outside of the top 10 by marketcap. Designed to be used on the daily timeframe.
⭐ YouTube: Money On The Move
⭐ www.youtube.com
⭐ Crypto Patreon: www.patreon.com
👉 HOW TO USE: Historically, when the white line touches or crosses the red line, it has signaled that the top of the altcoin market cycle is approaching, making it an ideal time to consider exiting altcoins before a potential decline. While the primary focus is on smaller altcoins, this tool can also be useful for larger coins by identifying trends and shifts in market dominance. The indicator uses a predefined threshold tailored for smaller altcoins as a key signal for an exit strategy.
Disclaimer: As with all indicators, past performance is not indicative of future results. Cryptocurrency trading involves significant risk and can result in the loss of your investment. This indicator should not be considered as financial advice, nor is it a recommendation to buy or sell any financial asset. Always conduct your own research and consult with a licensed financial advisor before making any investment decisions. Trading cryptocurrencies is speculative and inherently volatile, and you should only trade with money you are willing to lose.
BITCOIN BTC Neural AI Strategy by NHBprodHey everyone, here's a new trading strategy script for Bitcoin, and I’m super excited to share it with you. It’s called the "BITCOIN BTC Neural AI Strategy." It creates a neural network using RSI, MACD, and EMA which are weighted and undergo a mathematical transformation to result in a single value. Plotting the single value, and adding thresholds gives you the ability to trade. This is the strategy script, but I also have the indicator script which can be used to automate buy and sell signals directly to your phone, email, or your bot.
What It Does
RSI: Measures momentum (like, is the market pumped or tired?).
MACD: Checks if momentum is gaining or slowing (super handy for spotting moves).
EMA: Follows the big trend (like the market’s vibe over time).
Then, it smooshes all this data together and spits out a single number I call the Neural Proxy Value. If the value goes above 0.5, enter a long trade, and if it drops below -0.5, you can sell, and even short it if you'd like.
Backtest Results
Some notables:
I included slippage & I included commission.
77% net profit on a 10,000 starting account.
Hundreds of trades, and covers the maximum amount of time allowed in tradingview.
The script is ready for BITCOIN and I deploy it on the 1 hour timeframe because I feel like 1 hour bars get enough data to make solid judgements.
How to Use It
Look at the Neural Proxy line—it’s color-coded and easy to spot.
For traders who only trade long:
When the Neural Proxy line is above 0.5 = buy
When the Neural Proxy line is below -0.5 = sell
For traders who only trade short:
When the Neural Proxy line is above 0.5 = exit the short
When the Neural Proxy line is below -0.5 = enter the short
This strategy (and the pairing indicator script) is able to be used to trade long only, short only, or both long & short to maximize trade opportunities.
Crypto Sectors Performance [Daveatt]IMPORTANT
⚠️ This script must be used on the Daily timeframe only.
OVERVIEW
This indicator brings the powerful sector analysis capabilities from velo.xyz/market's
Sector Performance chart to TradingView.
It enables traders to track and compare performance across the crypto market's major sectors, providing essential insights for sector rotation strategies and market analysis.
CALCULATION METHOD
The indicator calculates performance across six key crypto sectors: DeFi, Gaming, Layer 1s, Layer 2s, AI, and Memecoins.
For each sector, it computes a rolling percentage performance by averaging the performance of multiple representative tokens.
All sector performances are rebased to 0% at the start of each period, making relative comparisons clear and intuitive.
VISUALIZATION MODES
The script features two distinct visualization methods:
Plots Mode:
Displays continuous performance lines for each sector over time, ideal for tracking relative strength trends and sector momentum. Each sector has its own color-coded line with performance values clearly marked.
Bars Mode:
Presents current sector performance as vertical bars, offering an immediate visual comparison of sector gains and losses.
The bars are color-coded and labeled with exact percentage values for precise analysis.
For the "Bars Mode", I used the box.new() function
SECTOR COMPOSITION
Each sector comprises carefully selected representative tokens:
- DeFi: AAVE, 1INCH, JUP, MKR, UNI
- Gaming: GALA, AXS, RONIN, SAND
- Layer 1: BTC, ETH, AVAX, APT, SOL, BNB, SUI
- Layer 2: ARB, OP, ZK, POL, STRK, MNT
- AI: FET, NEAR, RENDER, TAO
- Memecoins: PEPE, BONK, SHIB, DOGE, WIFU, POPCAT
PERFORMANCE TRACKING
The indicator implements a rolling window approach for performance calculations.
Starting from 0% at the beginning of each period, it tracks relative performance with positive values indicating outperformance and negative values showing underperformance.
Multiple timeframe options (1W, 1M, 3M, 6M, and 1Y) allow for both short-term and long-term analysis.
APPLICATIONS
This tool proves invaluable for:
- Sector rotation analysis
- Identifying trending sectors
- Comparing relative strength
- Gauging market sentiment
- Understanding market structure through sector performance
Thanks for reading and for the support
Daveatt
Crypto Arbitrage Scanner [CryptoSea]Crypto Arbitrage Scanner
The Crypto Arbitrage Scanner is an advanced tool designed to help traders identify arbitrage opportunities across multiple cryptocurrency exchanges. With the ability to compare prices, volumes, and differences in price, this indicator is a must-have for any trader seeking to exploit cross-exchange inefficiencies in real time.
Key Features
Multi-Exchange Price and Volume Comparison: Tracks data from multiple major cryptocurrency exchanges, including BINANCE, COINBASE, KUCOIN, and others, allowing traders to easily compare prices and volume across platforms.
Customizable Difference Metrics: Allows users to toggle between displaying price differences in percentages or absolute dollar values, depending on the preferred metric for arbitrage analysis.
Sorting and Filtering Options: Includes user-defined sorting options to order the data by Price, Volume, or Difference, helping to prioritize potential arbitrage opportunities based on the trader's chosen criteria.
Difference and Volume Thresholds: Users can specify the minimum volume and price difference thresholds, ensuring that only significant arbitrage opportunities are highlighted.
Real-Time Alerts: Built-in alert conditions notify users when arbitrage opportunities exceed their defined price difference thresholds, helping traders respond instantly to market movements.
The Crypto Arb Scanner displays a table of prices, volumes, and price differences across selected exchanges. Each exchange is listed along with the current close price, volume, and the difference in price compared to the average price across all exchanges. Highlighting is used to indicate significant differences that may present arbitrage opportunities.
In the example below, we can see a highlighted opportunity in green showing that the price is below the user inputed thresold.
How it Works
Data Collection: Gathers real-time volume and price data from various exchanges using a streamlined process, allowing for a detailed comparison.
Average Price Calculation: Computes the average price across all valid exchanges to identify where price discrepancies occur, providing a clear picture of arbitrage potential.
Sorting Mechanism: Utilizes custom sorting based on user preferences, making it easy to quickly analyze and identify key opportunities.
Dynamic Highlighting and Alerts: Price differences that exceed user-defined thresholds are highlighted, and alerts can be triggered for these arbitrage opportunities, allowing for a timely response.
Application
Arbitrage Trading: The Crypto Arb Scanner is ideal for traders looking to exploit price differences across exchanges, enabling efficient arbitrage opportunities.
Market Efficiency Analysis: Offers insights into the consistency of prices across exchanges, which can help gauge the efficiency and liquidity of the markets being traded.
Customizable Alerts: Set alerts based on price differences or volume, allowing traders to stay informed about changes without constantly monitoring the markets.
The Crypto Arbitrage Scanner is a powerful addition to any trader's toolkit, offering comprehensive features to detect arbitrage opportunities with confidence. With real-time monitoring, customizable metrics, and a user-friendly interface, this tool allows traders to make informed decisions and capitalize on inefficiencies across exchanges.
Cryptocurrency StrengthMulti-Currency Analysis: Monitor up to 19 different currencies simultaneously, including major pairs like USD, EUR, JPY, and GBP, as well as emerging market currencies such as CNY, INR, and BRL.
Customizable Display: Easily toggle the visibility of each currency and personalize their colors to suit your preferences, allowing for a tailored analysis experience.
Real-Time Strength Measurement: The indicator calculates and displays the relative strength of each currency in real-time, helping you identify potential trends and trading opportunities.
Clear Visual Representation: With color-coded lines and a dynamic legend, the indicator presents complex currency relationships in an easy-to-understand format.
Advantages
Comprehensive Market View: Gain insights into the broader forex market dynamics by analyzing multiple currencies at once.
Trend Identification: Quickly spot strong and weak currencies, aiding in the identification of potential trending pairs.
Divergence Detection: Use the indicator to identify divergences between currency strength and price action, potentially signaling reversals or continuation patterns.
Flexible Time Frames: Apply the indicator across various time frames to align with your trading strategy, from intraday to long-term analysis.
Enhanced Decision Making: Make more informed trading decisions by understanding the relative strength of currencies involved in your trades.
Unique Qualities
TSI-Based Calculations: Utilizes the True Strength Index for a more nuanced and responsive measure of currency strength compared to simple price-based indicators.
Adaptive Legend: The indicator features a dynamic legend that updates automatically based on the selected currencies, ensuring a clutter-free and relevant display.
Emerging Market Inclusion: Unlike many standard currency strength indicators, this tool includes a wide range of emerging market currencies, providing a truly global perspective.
Whether you're a seasoned forex trader or just starting out, this Currency Strength Indicator offers valuable insights that can complement your existing strategy and potentially improve your trading outcomes. Its combination of comprehensive analysis, customization options, and clear visualization makes it an essential tool for navigating the complex world of currency trading.
RSI Strategy With TP/SL - Lower TFThis Pine Script strategy integrates the Relative Strength Index (RSI) for trade signals with user-defined Take Profit (TP) and Stop Loss (SL) levels. It's designed for flexible application in different market conditions, offering long, short, or dual-direction trading.
Short Description
The strategy uses the RSI to identify overbought and oversold market conditions:
Buy signal: When RSI drops below the specified "Buy Level."
Sell signal: When RSI rises above the "Sell Level."
Additionally, it manages risk and profit targets with:
Take Profit (TP): Exits trades when the price reaches a percentage gain.
Stop Loss (SL): Exits trades to limit losses if the price falls by a certain percentage.
The strategy is versatile and includes options for visualizing performance, monthly profit/loss data, and detailed trade metrics.
How to Use
Set Parameters:
RSI Period: Default is 14. Adjust based on your analysis.
RSI Buy/Sell Levels:
Buy Level: Default is 40. Consider higher levels for conservative entries.
Sell Level: Default is 60. Lower this for earlier exits.
Take Profit (%): Set your profit target (default: 5%).
Stop Loss (%): Set your risk tolerance (default: 2%).
Trade Direction: Choose "Long Only," "Short Only," or "Both."
Interpret Signals:
Buy signals appear when RSI crosses below the buy threshold.
Sell signals appear when RSI crosses above the sell threshold.
Risk Management:
The strategy dynamically calculates TP and SL levels for each trade.
TP/SL is applied using the percentage input based on the entry price.
Monitor Performance:
Review trade statistics in the "Strategy Tester."
Use the monthly performance table to track P/L across months.
Customize Alerts:
Alerts for buy, sell, TP, and SL events can be used to automate notifications.
Key Features
Configurable RSI Settings: Adaptable to various market conditions.
Risk Management: Built-in TP and SL management.
Customizable Trade Direction: Tailored for long-only, short-only, or both directions.
Monthly P/L Table: Visualizes performance trends over time.
Alerts: Notifies when critical trade events occur.
Please do your own research before ase this to your real trading.
Crypto Wallets Profitability & Performance [LuxAlgo]The Crypto Wallets Profitability & Performance indicator provides a comprehensive view of the financial status of cryptocurrency wallets by leveraging on-chain data from IntoTheBlock. It measures the percentage of wallets profiting, losing, or breaking even based on current market prices.
Additionally, it offers performance metrics across different timeframes, enabling traders to better assess market conditions.
This information can be crucial for understanding market sentiment and making informed trading decisions.
🔶 USAGE
🔹 Wallets Profitability
This indicator is designed to help traders and analysts evaluate the profitability of cryptocurrency wallets in real-time. It aggregates data gathered from the blockchain on the number of wallets that are in profit, loss, or breaking even and presents it visually on the chart.
Breaking even line demonstrates how realized gains and losses have changed, while the profit and the loss monitor unrealized gains and losses.
The signal line helps traders by providing a smoothed average and highlighting areas relative to profiting and losing levels. This makes it easier to identify and confirm trading momentum, assess strength, and filter out market noise.
🔹 Profitability Meter
The Profitability Meter is an alternative display that visually represents the percentage of wallets that are profiting, losing, or breaking even.
🔹 Performance
The script provides a view of the financial health of cryptocurrency wallets, showing the percentage of wallets in profit, loss, or breaking even. By combining these metrics with performance data across various timeframes, traders can gain valuable insights into overall wallet performance, assess trend strength, and identify potential market reversals.
🔹 Dashboard
The dashboard presents a consolidated view of key statistics. It allows traders to quickly assess the overall financial health of wallets, monitor trend strength, and gauge market conditions.
🔶 DETAILS
🔹 The Chart Occupation Option
The chart occupation option adjusts the occupation percentage of the chart to balance the visibility of the indicator.
🔹 The Height in Performance Options
Crypto markets often experience significant volatility, leading to rapid and substantial gains or losses. Hence, plotting performance graphs on top of the chart alongside other indicators can result in a cluttered display. The height option allows you to adjust the plotting for balanced visibility, ensuring a clearer and more organized chart.
🔶 SETTINGS
The script offers a range of customizable settings to tailor the analysis to your trading needs.
Chart Occupation %: Adjust the occupation percentage of the chart to balance the visibility of the indicator.
🔹 Profiting Wallets
Profiting Percentage: Toggle to display the percentage of wallets in profit.
Smoothing: Adjust the smoothing period for the profiting percentage line.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) to overlay on the profiting percentage.
🔹 Losing Wallets
Losing Percentage: Toggle to display the percentage of wallets in loss.
Smoothing: Adjust the smoothing period for the losing percentage line.
Signal Line: Choose a signal line type (SMA, EMA, RMA, or None) to overlay on the losing percentage.
🔹 Breaking Even Wallets
Breaking-Even Percentage: Toggle to display the percentage of wallets breaking even.
Smoothing: Adjust the smoothing period for the breaking-even percentage line.
🔹 Profitability Meter
Profitability Meter: Enable or disable the meter display, set its width, and adjust the offset.
🔹 Performance
Performance Metrics: Choose the timeframe for performance metrics (Day to Date, Week to Date, etc.).
Height: Adjust the height of the chart visuals to balance the visibility of the indicator.
🔹 Dashboard
Block Profitability Stats: Toggle the display of profitability stats.
Performance Stats: Toggle the display of performance stats.
Dashboard Size and Position: Customize the size and position of the performance dashboard on the chart.
🔶 RELATED SCRIPTS
Market-Sentiment-Technicals
Multi-Chart-Widget
Kalman For Loop [BackQuant]Kalman For Loop
Introducing BackQuant's Kalman For Loop (Kalman FL) — a highly adaptive trading indicator that uses a Kalman filter to smooth price data and generate actionable long and short signals. This advanced indicator is designed to help traders identify trends, filter out market noise, and optimize their entry and exit points with precision. Let’s explore how this indicator works, its key features, and how it can enhance your trading strategies.
Core Concept: Kalman Filter
The Kalman Filter is a mathematical algorithm used to estimate the state of a system by filtering noisy data. It is widely used in areas such as control systems, signal processing, and time-series analysis. In the context of trading, a Kalman filter can be applied to price data to smooth out short-term fluctuations, providing a clearer view of the underlying trend.
Unlike moving averages, which use fixed weights to smooth data, the Kalman Filter adjusts its estimate dynamically based on the relationship between the process noise and the measurement noise. This makes the filter more adaptive to changing market conditions, providing more accurate trend detection without the lag associated with traditional smoothing techniques.
Please see the original Kalman Price Filter
In this script, the Kalman For Loop applies the Kalman filter to the price source (default set to the closing price) to generate a smoothed price series, which is then used to calculate signals.
Adaptive Smoothing with Process and Measurement Noise
Two key parameters govern the behavior of the Kalman filter:
Process Noise: This controls the extent to which the model allows for uncertainty in price changes. A lower process noise value will make the filter smoother but slower to react to price changes, while a higher value makes it more sensitive to recent price fluctuations.
Measurement Noise: This represents the uncertainty or "noise" in the observed price data. A higher measurement noise value gives the filter more leeway to ignore short-term fluctuations, focusing on the broader trend. Lowering the measurement noise makes the filter more responsive to minor changes in price.
These settings allow traders to fine-tune the Kalman filter’s sensitivity, adjusting it to match their preferred trading style or market conditions.
For-Loop Scoring Mechanism
The Kalman FL further enhances the effectiveness of the Kalman filter by using a for-loop scoring system. This mechanism evaluates the smoothed price over a range of periods (defined by the Calculation Start and Calculation End inputs), assigning a score based on whether the current filtered price is higher or lower than previous values.
Long Signals: A long signal is generated when the for-loop score surpasses the Long Threshold (default set at 20), indicating a strong upward trend. This helps traders identify potential buying opportunities.
Short Signals: A short signal is triggered when the score crosses below the Short Threshold (default set at -10), signaling a potential downtrend or selling opportunity.
These signals are plotted on the chart, giving traders a clear visual indication of when to enter long or short positions.
Customization and Visualization Options
The Kalman For Loop comes with a range of customization options to give traders full control over how the indicator operates and is displayed on the chart:
Kalman Price Source: Choose the price data used for the Kalman filter (default is the closing price), allowing you to apply the filter to other price points like open, high, or low.
Filter Order: Set the order of the Kalman filter (default is 5), controlling how far back the filter looks in its calculations.
Process and Measurement Noise: Fine-tune the sensitivity of the Kalman filter by adjusting these noise parameters.
Signal Line Width and Colors: Customize the appearance of the signal line and the colors used to indicate long and short conditions.
Threshold Lines: Toggle the display of the long and short threshold lines on the chart for better visual clarity.
The indicator also includes the option to color the candlesticks based on the current trend direction, allowing traders to quickly identify changes in market sentiment. In addition, a background color feature further highlights the overall trend by shading the background in green for long signals and red for short signals.
Trading Applications
The Kalman For Loop is a versatile tool that can be adapted to a variety of trading strategies and markets. Some of the primary use cases include:
Trend Following: The adaptive nature of the Kalman filter helps traders identify the start of new trends with greater precision. The for-loop scoring system quantifies the strength of the trend, making it easier to stay in trades for longer when the trend remains strong.
Mean Reversion: For traders looking to capitalize on short-term reversals, the Kalman filter's ability to smooth price data makes it easier to spot when price has deviated too far from its expected path, potentially signaling a reversal.
Noise Reduction: The Kalman filter excels at filtering out short-term price noise, allowing traders to focus on the broader market movements without being distracted by minor fluctuations.
Risk Management: By providing clear long and short signals based on filtered price data, the Kalman FL helps traders manage risk by entering positions only when the trend is well-defined, reducing the chances of false signals.
Alerts and Automation
To further assist traders, the Kalman For Loop includes built-in alert conditions that notify you when a long or short signal is generated. These alerts can be configured to trigger notifications, helping you stay on top of market movements without constantly monitoring the chart.
Final Thoughts
The Kalman For Loop is a powerful and adaptive trading indicator that combines the precision of the Kalman filter with a for-loop scoring mechanism to generate reliable long and short signals. Whether you’re a trend follower or a reversal trader, this indicator offers the flexibility and accuracy needed to navigate complex markets with confidence.
As always, it’s important to backtest the indicator and adjust the settings to fit your trading style and market conditions. No indicator is perfect, and the Kalman FL should be used alongside other tools and sound risk management practices for the best results.
Divergence for Many Indicators v4 Screener▋ INTRODUCTION:
The “Divergence for Many Indicators v4 Screener” is developed to provide an advanced monitoring solution for up to 24 symbols simultaneously. It efficiently collects signals from multiple symbols based on the “ Divergence for Many Indicators v4 ” and presents the output in an organized table. The table includes essential details starting with the symbol name, signal price, corresponding divergence indicator, and signal time.
_______________________
▋ CREDIT:
The divergence formula adapted from the “ Divergence for Many Indicators v4 ” script, originally created by @LonesomeTheBlue . Full credit to his work.
_______________________
▋ OVERVIEW:
The chart image can be considered an example of a recorded divergence signal that occurred in $BTCUSDT.
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▋ APPEARANCE:
The table can be displayed in three formats:
1. Full indicator name.
2. First letter of the indicator name.
3. Total number of divergences.
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▋ SIGNAL CONFIRMATION:
The table distinguishes signal confirmation by using three different colors:
1. Not-Confirmed (Orange): The signal is not confirmed yet, as the bar is still open.
2. Freshly Confirmed (Green): The signal was confirmed 1 or 2 bars ago.
3. Confirmed (Gray): The signal was confirmed 3 or more bars ago.
_______________________
▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Table location on the chart.
(2) Table’s cells size.
(3) Chart’s timezone.
(4) Sorting table.
- Signal: Sorts the table by the latest signals.
- None: Sorts the table based on the input order.
(5) Table’s colors.
(6) Signal Confirmation type color. Explained above in the SIGNAL CONFIRMATION section
Section(2): Divergence for Many Indicators v4 Settings
As seen on the Divergence for Many Indicators v4
* Explained above in the APPEARANCE section
Section(3): Symbols
(1) Enable/disable symbol in the screener.
(2) Entering a symbol.
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▋ FINAL COMMENTS:
For best performance, add the Screener indicator to an active symbol chart, such as QQQ, SPY, AAPL, BTCUSDT, ES, EURUSD, etc., and avoid mixing symbols from different market allocations.
The Divergence for Many Indicators v4 Screener indicator is not a primary tool for making trading decisions.
Dynamic Score PSAR [QuantAlgo]Dynamic Score PSAR 📈🧬
The Dynamic Score PSAR by QuantAlgo introduces an innovative approach to trend detection by utilizing a dynamic trend scoring technique in combination with the Parabolic SAR. This method goes beyond traditional trend-following indicators by evaluating market momentum through a scoring system that analyzes price behavior over a customizable window. By dynamically adjusting to evolving market conditions, this indicator provides clearer, more adaptive trend signals that help traders and investors anticipate market reversals and capitalize on momentum shifts with greater precision.
💫 Conceptual Foundation and Innovation
At the core of the Dynamic Score PSAR is the dynamic trend score system, which assesses price movements by comparing normalized PSAR values across a range of historical data points. This dynamic trend scoring technique offers a unique, probabilistic approach to trend analysis by evaluating how the current market compares to past price movements. Unlike traditional PSAR indicators that rely on static parameters, this scoring mechanism allows the indicator to adjust in real time to market fluctuations, offering traders and investors a more responsive and insightful view of trends. This innovation makes the Dynamic Score PSAR particularly effective in detecting shifts in momentum and potential reversals, even in volatile or complex market environments.
✨ Technical Composition and Calculation
The Dynamic Score PSAR is composed of several advanced components designed to provide a higher probability of detecting accurate trend shifts. The key innovation lies in the dynamic trend scoring technique, which iterates over historical PSAR values and evaluates price momentum through a dynamic scoring system. By comparing the current normalized PSAR value with previous data points over a user-defined window, the system generates a score that reflects the strength and direction of the trend. This allows for a more refined and responsive detection of trends compared to static, traditional indicators.
To enhance clarity, the PSAR values are normalized against an Exponential Moving Average (EMA), providing a standardized framework for comparison. This normalization ensures that the indicator adapts dynamically to market conditions, making it more effective in volatile markets. The smoothing process reduces noise, helping traders and investors focus on significant trend signals.
Additionally, users can adjust the length of the data window and the sensitivity thresholds for detecting uptrends and downtrends, providing flexibility for different trading and investing environments.
📈 Features and Practical Applications
Customizable Window Length: Adjust the window length to control the indicator’s sensitivity to recent price movements. This provides flexibility for short-term or long-term trend analysis.
Uptrend/Downtrend Thresholds: Set customizable thresholds for identifying uptrends and downtrends. These thresholds define when trend signals are triggered, offering adaptability to different market conditions.
Bar Coloring and Gradient Visualization: Visual cues, including color-coded bars and gradient fills, make it easier to interpret market trends and identify key moments for potential trend reversals.
Momentum Confirmation: The dynamic trend scoring system evaluates price action over time, providing a probabilistic measure of market momentum to confirm the strength and direction of a trend.
⚡️ How to Use
✅ Add the Indicator: Add the Dynamic Score PSAR to your favourites, then to your chart and adjust the PSAR settings, window length, and trend thresholds to match your preferences. Customize the sensitivity to price movements by tweaking the window length and thresholds for different market conditions.
👀 Monitor Trend Shifts: Watch for trend changes as the normalized PSAR values cross key thresholds, and use the dynamic score to confirm the strength and direction of trends. Bar coloring and background fills visually highlight key moments for trend shifts, making it easier to spot reversals.
🔔 Set Alerts: Configure alerts for significant trend crossovers and reversals, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Dynamic Score PSAR by QuantAlgo is a powerful tool that combines traditional trend-following techniques with the flexibility of a dynamic trend scoring system. This innovative approach provides clearer, more adaptive trend signals, reducing the risk of false entries and exits while helping traders and investors capture significant market moves. The ability to adjust the indicator’s sensitivity and thresholds makes it versatile across different trading and investing environments, whether you’re focused on short-term pivots or long-term trend reversals. To maximize its effectiveness, fine-tune the sensitivity settings based on current market conditions and use the visual cues to confirm trend shifts.
Ping Pong Bot StrategyOverview:
The Ping Pong Bot Strategy is designed for traders who focus on scalping and short-term opportunities using support and resistance levels. This strategy identifies potential buy entries when the price reaches a key support area and shows bullish momentum (a green bar). It aims to capitalize on small price movements with predefined risk management and take profit levels, making it suitable for active traders looking to maximize quick trades in trending or ranging markets.
How It Works:
Support & Resistance Calculation:
The strategy dynamically identifies support and resistance levels using the lowest and highest price points over a user-defined period. These levels help pinpoint potential price reversal areas, guiding traders on where to enter or exit trades.
Buy Entry Criteria:
A buy signal is triggered when the closing price is at or below the support level, and the bar is green (i.e., the closing price is higher than the opening price). This ensures that entries are made when prices show signs of upward momentum after hitting support.
Risk Management:
For each trade, a stop loss is calculated based on a user-defined risk percentage, helping to protect against significant drawdowns. Additionally, a take profit level is set at a ratio relative to the risk, ensuring a disciplined approach to exit points.
0.5% Take Profit Target:
The strategy also includes a 0.5% quick take profit target, indicated by an orange arrow when reached. This feature helps traders lock in small gains rapidly, making it ideal for volatile market conditions.
Customizable Inputs:
Length: Adjusts the period for calculating support and resistance levels.
Risk-Reward Ratio: Allows traders to set the desired risk-to-reward ratio for each trade.
Risk Percentage: Defines the risk tolerance for stop loss calculations.
Take Profit Target: Enables the customization of the quick take profit target.
Ideal For:
Traders who prefer an active trading style and want to leverage support and resistance levels for precise entries and exits. This strategy is particularly useful in markets that experience frequent price bounces between support and resistance, allowing traders to "ping pong" between these levels for profitable trades.
Note:
This strategy is developed mainly for the 5-minute chart and has not been tested on longer time frames. Users should perform their own testing and adjustments if using it on different time frames.
Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
Fourier For Loop [BackQuant]Fourier For Loop
PLEASE Read the following, as understanding an indicator's functionality is essential before integrating it into a trading strategy. Knowing the core logic behind each tool allows for a sound and strategic approach to trading.
Introducing BackQuant's Fourier For Loop (FFL) — a cutting-edge trading indicator that combines Fourier transforms with a for-loop scoring mechanism. This innovative approach leverages mathematical precision to extract trends and reversals in the market, helping traders make informed decisions. Let's break down the components, rationale, and potential use-cases of this indicator.
Understanding Fourier Transform in Trading
The Fourier Transform decomposes price movements into their frequency components, allowing for a detailed analysis of cyclical behavior in the market. By transforming the price data from the time domain into the frequency domain, this indicator identifies underlying patterns that traditional methods may overlook.
In this script, Fourier transforms are applied to the specified calculation source (defaulted to HLC3). The transformation yields magnitude values that can be used to score market movements over a defined range. This scoring process helps uncover long and short signals based on relative strength and trend direction.
Why Use Fourier Transforms?
Fourier Transforms excel in identifying recurring cycles and smoothing noisy data, making them ideal for fast-paced markets where price movements may be erratic. They also provide a unique perspective on market volatility, offering traders additional insights beyond standard indicators.
Calculation Logic: For-Loop Scoring Mechanism
The For Loop Scoring mechanism compares the magnitude of each transformed point in the series, summing the results to generate a score. This score forms the backbone of the signal generation system.
Long Signals: Generated when the score surpasses the defined long threshold (default set at 40). This indicates a strong bullish trend, signaling potential upward momentum.
Short Signals: Triggered when the score crosses under the short threshold (default set at -10). This suggests a bearish trend or potential downside risk.'
Thresholds & Customization
The indicator offers customizable settings to fit various trading styles:
Calculation Periods: Control how many periods the Fourier transform covers.
Long/Short Thresholds: Adjust the sensitivity of the signals to match different timeframes or risk preferences.
Visualization Options: Traders can visualize the thresholds, change the color of bars based on trend direction, and even color the background for enhanced clarity.
Trading Applications
This Fourier For Loop indicator is designed to be versatile across various market conditions and timeframes. Some of its key use-cases include:
Cycle Detection: Fourier transforms help identify recurring patterns or cycles, giving traders a head-start on market direction.
Trend Following: The for-loop scoring system helps confirm the strength of trends, allowing traders to enter positions with greater confidence.
Risk Management: With clearly defined long and short signals, traders can manage their positions effectively, minimizing exposure to false signals.
Final Note
Incorporating this indicator into your trading strategy adds a layer of mathematical precision to traditional technical analysis. Be sure to adjust the calculation start/end points and thresholds to match your specific trading style, and remember that no indicator guarantees success. Always backtest thoroughly and integrate the Fourier For Loop into a balanced trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future .
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Adaptive Volatility-Controlled LSMA [QuantAlgo]Adaptive Volatility-Controlled LSMA by QuantAlgo 📈💫
Introducing the Adaptive Volatility-Controlled LSMA (Least Squares Moving Average) , a powerful trend-following indicator that combines trend detection with dynamic volatility adjustments. This indicator is designed to help traders and investors identify market trends while accounting for price volatility, making it suitable for a wide range of assets and timeframes. By integrating LSMA for trend analysis and Average True Range (ATR) for volatility control, this tool provides clearer signals during both trending and volatile market conditions.
💡 Core Concept and Innovation
The Adaptive Volatility-Controlled LSMA leverages the precision of the LSMA to track market trends and combines it with the sensitivity of the ATR to account for market volatility. LSMA fits a linear regression line to price data, providing a smoothed trend line that is less reactive to short-term noise. The ATR, on the other hand, dynamically adjusts the volatility bands around the LSMA, allowing the indicator to filter out false signals and respond to significant price moves. This combination provides traders with a reliable tool to identify trend shifts while managing risk in volatile markets.
📊 Technical Breakdown and Calculations
The indicator consists of the following components:
1. Least Squares Moving Average (LSMA): The LSMA calculates a linear regression line over a defined period to smooth out price fluctuations and reveal the underlying trend. It is more reactive to recent data than traditional moving averages, allowing for quicker trend detection.
2. ATR-Based Volatility Bands: The Average True Range (ATR) measures market volatility and creates upper and lower bands around the LSMA. These bands expand and contract based on market conditions, helping traders identify when price movements are significant enough to indicate a new trend.
3. Volatility Extensions: To further account for rapid market changes, the bands are extended using additional volatility measures. This ensures that trend signals are generated when price movements exceed both the standard volatility range and the extended volatility range.
⚙️ Step-by-Step Calculation:
1. LSMA Calculation: The LSMA is computed using a least squares regression method over a user-defined length. This provides a trend line that adapts to recent price movements while smoothing out noise.
2. ATR and Volatility Bands: ATR is calculated over a user-defined length and is multiplied by a factor to create upper and lower bands around the LSMA. These bands help detect when price movements are substantial enough to signal a new trend.
3. Trend Detection: The price’s relationship to the LSMA and the volatility bands is used to determine trend direction. If the price crosses above the upper volatility band, a bullish trend is detected. Conversely, a cross below the lower band indicates a bearish trend.
✅ Customizable Inputs and Features:
The Adaptive Volatility-Controlled LSMA offers a variety of customizable options to suit different trading or investing styles:
📈 Trend Settings:
1. LSMA Length: Adjust the length of the LSMA to control its sensitivity to price changes. A shorter length reacts quickly to new data, while a longer length smooths the trend line.
2. Price Source: Choose the type of price (e.g., close, high, low) that the LSMA uses to calculate trends, allowing for different interpretations of price data.
🌊 Volatility Controls:
ATR Length and Multiplier: Adjust the length and sensitivity of the ATR to control how volatility is measured. A higher ATR multiplier widens the bands, making the trend detection less sensitive, while a lower multiplier tightens the bands, increasing sensitivity.
🎨 Visualization and Alerts:
1. Bar Coloring: Customize bar colors to visually distinguish between uptrends and downtrends.
2. Volatility Bands: Enable or disable the display of volatility bands on the chart. The bands provide visual cues about trend strength and volatility thresholds.
3. Alerts: Set alerts for when the price crosses the upper or lower volatility bands, signaling potential trend changes.
📈 Practical Applications
The Adaptive Volatility-Controlled LSMA is ideal for traders and investors looking to follow trends while accounting for market volatility. Its key use cases include:
Identifying Trend Reversals: The indicator detects when price movements break through volatility bands, signaling potential trend reversals.
Filtering Market Noise: By applying ATR-based volatility filtering, the indicator helps reduce false signals caused by short-term price fluctuations.
Managing Risk: The volatility bands adjust dynamically to account for market conditions, helping traders manage risk and improve the accuracy of their trend-following strategies.
⭐️ Summary
The Adaptive Volatility-Controlled LSMA by QuantAlgo offers a robust and flexible approach to trend detection and volatility management. Its combination of LSMA and ATR creates clearer, more reliable signals, making it a valuable tool for navigating trending and volatile markets. Whether you're detecting trend shifts or filtering market noise, this indicator provides the tools you need to enhance your trading and investing strategy.
Note: The Adaptive Volatility-Controlled LSMA is a tool to enhance market analysis. It should be used in conjunction with other analytical tools and should not be relied upon as the sole basis for trading or investment decisions. No signals or indicators constitute financial advice, and past performance is not indicative of future results.
Adaptive EMA with ATR and Standard Deviation [QuantAlgo]Adaptive EMA with ATR and Standard Deviation by QuantAlgo 📈✨
Introducing the Adaptive EMA with ATR and Standard Deviation , a comprehensive trend-following indicator designed to combine the smoothness of an Exponential Moving Average (EMA) with the volatility adjustments of Average True Range (ATR) and Standard Deviation. This synergy allows traders and investors to better identify market trends while accounting for volatility, delivering clearer signals in both trending and volatile market conditions. This indicator is suitable for traders and investors seeking to balance trend detection and volatility management, offering a robust and adaptable approach across various asset classes and timeframes.
💫 Core Concept and Innovation
The Adaptive EMA with ATR and Standard Deviation brings together the trend-smoothing properties of the EMA and the volatility sensitivity of ATR and Standard Deviation. By using the EMA to track price movements over time, the indicator smooths out minor fluctuations while still providing valuable insights into overall market direction. However, market volatility can sometimes distort simple moving averages, so the ATR and Standard Deviation components dynamically adjust the trend signals, offering more nuanced insights into trend strength and reversals. This combination equips traders with a powerful tool to navigate unpredictable markets while minimizing false signals.
📊 Technical Breakdown and Calculations
The Adaptive EMA with ATR and Standard Deviation relies on three key technical components:
1. Exponential Moving Average (EMA): The EMA forms the base of the trend detection. Unlike a Simple Moving Average (SMA), the EMA gives more weight to recent price changes, allowing it to react more quickly to new data. Users can adjust the length of the EMA to make it more or less responsive to price movements.
2. Standard Deviation Bands: These bands are calculated from the standard deviation of the EMA and represent dynamic volatility thresholds. The upper and lower bands expand or contract based on recent price volatility, providing more accurate signals in both calm and volatile markets.
3. ATR-Based Volatility Filter: The Average True Range (ATR) is used to measure market volatility over a user-defined period. It helps refine the trend signals by filtering out false positives caused by minor price swings. The ATR filter ensures that the indicator only signals significant market movements.
⚙️ Step-by-Step Calculation:
1. EMA Calculation: First, the indicator calculates the EMA over a specified period based on the chosen price source (e.g., close, high, low).
2. Standard Deviation Bands: Then, it computes the standard deviation of the EMA and applies a multiplier to create upper and lower bands around the EMA. These bands adjust dynamically with the level of market volatility.
3. ATR Filtering: In addition to the standard deviation bands, the ATR is applied as a secondary filter to help refine the trend signals. This step helps eliminate signals generated by short-term price spikes or corrections, ensuring that the signals are more reliable.
4. Trend Detection: When the price crosses above the upper band, a bullish trend is identified, while a move below the lower band signals a bearish trend. The system accounts for both the standard deviation and ATR bands to generate these signals.
✅ Customizable Inputs and Features
The Adaptive EMA with ATR and Standard Deviation provides a range of customizable options to fit various trading/investing styles:
📈 Trend Settings:
1. Price Source: Choose the price type (e.g., close, high, low) to base the EMA calculation on, influencing how the trend is tracked.
2. EMA Length: Adjust the length to control how quickly the EMA reacts to price changes. A shorter length provides a more responsive EMA, while a longer period smooths out short-term fluctuations.
🌊 Volatility Controls:
1. Standard Deviation Multiplier: This parameter controls the sensitivity of the trend detection by adjusting the distance between the upper and lower bands from the EMA.
2. TR Length and Multiplier: Fine-tune the ATR settings to control how volatility is filtered, adjusting the indicator’s responsiveness during high or low volatility phases.
🎨 Visualization and Alerts:
1. Bar Coloring: Select different colors for uptrends and downtrends, providing a clear visual cue when trends change.
2. Alerts: Set up alerts to notify you when the price crosses the upper or lower bands, signaling a potential long or short trend shift. Alerts can help you stay informed without constant chart monitoring.
📈 Practical Applications
The Adaptive EMA with ATR and Standard Deviation is ideal for traders and investors looking to balance trend-following strategies with volatility management. Key uses include:
Detecting Trend Reversals: The dynamic bands help identify when the market shifts direction, providing clear signals when a trend reversal is likely.
Filtering Market Noise: By applying both Standard Deviation and ATR filtering, the indicator helps reduce false signals during periods of heightened volatility.
Volatility-Based Risk Management: The adaptability of the bands ensures that traders can manage risk more effectively by responding to shifts in volatility while keeping focus on long-term trends.
⭐️ Comprehensive Summary
The Adaptive EMA with ATR and Standard Deviation is a highly customizable indicator that provides traders with clearer signals for trend detection and volatility management. By dynamically adjusting its calculations based on market conditions, it offers a powerful tool for navigating both trending and volatile markets. Whether you're looking to detect early trend reversals or avoid false signals during periods of high volatility, this indicator gives you the flexibility and accuracy to improve your trading and investing strategies.
Note: The Adaptive EMA with ATR and Standard Deviation is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
H-Infinity Volatility Filter [QuantAlgo]Introducing the H-Infinity Volatility Filter by QuantAlgo 📈💫
Enhance your trading/investing strategy with the H-Infinity Volatility Filter , a powerful tool designed to filter out market noise and identify clear trend signals in volatile conditions. By applying an advanced H∞ filtering process, this indicator assists traders and investors in navigating uncertain market conditions with improved clarity and precision.
🌟 Key Features:
🛠 Customizable Noise Parameters: Adjust worst-case noise and disturbance settings to tailor the filter to various market conditions. This flexibility helps you adapt the indicator to handle different levels of market volatility and disruptions.
⚡️ Dynamic Trend Detection: The filter identifies uptrends and downtrends based on the filtered price data, allowing you to quickly spot potential shifts in the market direction.
🎨 Color-Coded Visuals: Easily differentiate between bullish and bearish trends with customizable color settings. The indicator colors the chart’s candles according to the detected trend for immediate clarity.
🔔 Custom Alerts: Set alerts for trend changes, so you’re instantly informed when the market transitions from bullish to bearish or vice versa. Stay updated without constantly monitoring the charts.
📈 How to Use:
✅ Add the Indicator: Add the H-Infinity Volatility Filter to your favourites and apply it to your chart. Customize the noise and disturbance parameters to match the volatility of the asset you are trading/investing. This allows you to optimize the filter for your specific strategy.
👀 Monitor Trend Shifts: Watch for clear visual signals as the filter detects uptrends or downtrends. The color-coded candles and line plots help you quickly assess market conditions and potential reversals.
🔔 Set Alerts: Configure alerts to notify you when the trend changes, allowing you to react quickly to potential market shifts without needing to manually track price movements.
🌟 How It Works and Academic Background:
The H-Infinity Volatility Filter is built on the foundations of H∞ (H-infinity) control theory , a mathematical framework originating from the field of engineering and control systems. Developed in the 1980s by notable engineers such as George Zames and John C. Doyle , this theory was designed to help systems perform optimally under uncertain and noisy conditions. H∞ control focuses on minimizing the worst-case effects of disturbances and noise, making it a powerful tool for managing uncertainty in complex environments.
In financial markets, where unpredictable price fluctuations and noise often obscure meaningful trends, this same concept can be applied to price data to filter out short-term volatility. The H-Infinity Volatility Filter adopts this approach, allowing traders and investors to better identify potential trends by reducing the impact of random price movements. Instead of focusing on precise market predictions, the filter increases the probability of highlighting significant trends by smoothing out market noise.
This indicator works by processing historical price data through an H∞ filter that continuously adjusts based on worst-case noise levels and disturbances. By considering several past states, it estimates the current price trend while accounting for potential external disruptions that might influence price behavior. Parameters like "worst-case noise" and "disturbance" are user-configurable, allowing traders to adapt the filter to different market conditions. For example, in highly volatile markets, these parameters can be adjusted to manage larger price swings, while in more stable markets, they can be fine-tuned for smoother trend detection.
The H-Infinity Volatility Filter also incorporates a dynamic trend detection system that classifies price movements as bullish or bearish. It uses color-coded candles and plots—green for bullish trends and red for bearish trends—to provide clear visual cues for market direction. This helps traders and investors quickly interpret the trend and act on potential signals. While the indicator doesn’t guarantee accuracy in trend prediction, it significantly reduces the likelihood of false signals by focusing on meaningful price changes rather than random fluctuations.
How It Can Be Applied to Trading/Investing:
By applying the principles of H∞ control theory to financial markets, the H-Infinity Volatility Filter provides traders and investors with a sophisticated tool that manages uncertainty more effectively. Its design makes it suitable for use in a wide range of markets—whether in fast-moving, volatile environments or calmer conditions.
The indicator is versatile and can be used in both short-term trading and medium to long-term investing strategies. Traders can tune the filter to align with their specific risk tolerance, asset class, and market conditions, making it an ideal tool for reducing the effects of market noise while increasing the probability of detecting reliable trend signals.
For investors, the filter can help in identifying medium to long-term trends by filtering out short-term price swings and focusing on the broader market direction. Whether applied to stocks, forex, commodities, or cryptocurrencies, the H-Infinity Volatility Filter helps traders and investors interpret market behavior with more confidence by offering a more refined view of price movements through its noise reduction techniques.
Disclaimer:
The H-Infinity Volatility Filter is designed to assist in market analysis by filtering out noise and volatility. It should not be used as the sole tool for making trading or investment decisions. Always incorporate other forms of analysis and risk management strategies. No statements or signals from this indicator or us should be considered financial advice. Past performance is not indicative of future results.
Adaptive VWAP [QuantAlgo]Introducing the Adaptive VWAP by QuantAlgo 📈🧬
Enhance your trading and investing strategies with the Adaptive VWAP , a versatile tool designed to provide dynamic insights into market trends and price behavior. This indicator offers a flexible approach to VWAP calculations by allowing users to adapt it based on lookback periods or fixed timeframes, making it suitable for a wide range of market conditions.
🌟 Key Features:
🛠 Customizable VWAP Settings: Choose between an adaptive VWAP that adjusts based on a rolling lookback period, or switch to a fixed timeframe (e.g., daily, weekly, monthly) for a more structured approach. Adjust the VWAP to suit your trading or investing style.
💫 Dynamic Bands and ATR Filter: Configurable deviation bands with multipliers allow you to visualize price movement around VWAP, while an ATR-based noise filter helps reduce false signals during periods of market fluctuation.
🎨 Trend Visualization: Color-coded trend identification helps you easily spot uptrends and downtrends based on VWAP positioning. The indicator fills the areas between the bands for clearer visual representation of price volatility and trend strength.
🔔 Custom Alerts: Set up alerts for when price crosses above or below the VWAP, signaling potential uptrend or downtrend opportunities. Stay informed without needing to monitor the charts constantly.
✍️ How to Use:
✅ Add the Indicator: Add the Adaptive VWAP to your favourites and apply to your chart. Choose between adaptive or timeframe-based VWAP calculation, adjust the lookback period, and configure the deviation bands to your preferred settings.
👀 Monitor Bands and Trends: Watch for price interaction with the VWAP and its deviation bands. The color-coded signals and band fills help identify potential trend shifts or price extremes.
🔔 Set Alerts: Configure alerts for uptrend and downtrend signals based on price crossing the VWAP, so you’re always informed of significant market movements.
⚙️ How It Works:
The Adaptive VWAP adjusts its calculation based on the user’s chosen configuration, allowing for a flexible approach to market analysis. The adaptive setting uses a rolling lookback period to continuously adjust the VWAP, while the fixed timeframe option anchors VWAP to key timeframes like daily, weekly, or monthly periods. This flexibility enables traders and investors to use the tool in various market environments.
Deviation bands, calculated with customizable multipliers, provide a clear visual of how far the price has moved from the VWAP, helping you gauge potential overbought or oversold conditions. To reduce false signals, an ATR-based filter can be applied, ensuring that only significant price movements trigger trend confirmations.
The tool also includes a fast exponential smoothing function for the VWAP, helping smooth out price fluctuations without sacrificing responsiveness. Trend confirmation is reinforced by the number of bars that price stays above or below the VWAP, ensuring a more consistent trend identification process.
Disclaimer:
The Adaptive VWAP is designed to enhance your market analysis but should not be relied upon as the sole basis for trading or investing decisions. Always combine it with other analytical tools and practices. No statements or signals from this indicator constitute financial advice. Past performance is not indicative of future results.
Volatility-Adjusted DEMA Supertrend [QuantAlgo]Introducing the Volatility-Adjusted DEMA Supertrend by QuantAlgo 📈💫
Take your trading and investing strategies to the next level with the Volatility-Adjusted DEMA Supertrend , a dynamic tool designed to adapt to market volatility and provide clear, actionable trend signals. This innovative indicator is ideal for both traders and investors looking for a more responsive approach to market trends, helping you capture potential shifts with greater precision.
🌟 Key Features:
🛠 Customizable Trend Settings: Adjust the period for trend calculation and fine-tune the sensitivity to price movements. This flexibility allows you to tailor the Supertrend to your unique trading or investing strategy, whether you're focusing on shorter or longer timeframes.
📊 Volatility-Responsive Multiplier: The Supertrend dynamically adjusts its sensitivity based on real-time market volatility. This could help filter out noise in calmer markets and provide more accurate signals during periods of heightened volatility.
✨ Trend-Based Color-Coding: Visualize bullish and bearish trends with ease. The indicator paints candles and plots trend lines with distinct colors based on the current market direction, offering quick, clear insights into potential opportunities.
🔔 Custom Alerts: Set up alerts for key trend shifts to ensure you're notified of significant market changes. These alerts would allow you to act swiftly, potentially capturing opportunities without needing to constantly monitor the charts.
📈 How to Use:
✅ Add the Indicator: Add the Volatility-Adjusted DEMA Supertrend to your chart. Customize the trend period, volatility settings, and price source to match your trading or investing style. This ensures the indicator aligns with your market strategy.
👀 Monitor Trend Shifts: Watch the color-coded trend lines and candles as they dynamically shift based on real-time market conditions. These visual cues help you spot potential trend reversals and confirm your entries and exits with greater confidence.
🔔 Set Alerts: Configure alerts for key trend shifts, allowing you to stay informed of potential market reversals or continuation patterns, even when you're not actively watching the market.
⚙️ How It Works:
The Volatility-Adjusted DEMA Supertrend is designed to adapt to changes in market conditions, making it highly responsive to price volatility. The indicator calculates a trend line based on price and volatility, dynamically adjusting it to reflect recent market behavior. When the market experiences higher volatility, the trend line becomes more flexible, potentially allowing for greater sensitivity to rapid price movements. Conversely, during periods of low volatility, the indicator tightens its range, helping to reduce noise and avoid false signals.
The indicator includes a volatility-responsive multiplier, which further enhances its adaptability to market conditions. This means the trend direction would always be based on the latest market data, potentially helping you stay ahead of shifts or continuation trends. The Supertrend's visual color-coding simplifies the process of identifying bullish or bearish trends, while customizable alerts ensure you can stay on top of significant changes in market direction.
This tool is versatile and could be applied across various markets and timeframes, making it a valuable addition for both traders and investors. Whether you’re trading in fast-moving markets or focusing on longer-term investments, the Volatility-Adjusted DEMA Supertrend could help you remain aligned with the current market environment.
Disclaimer:
This indicator is designed to enhance your analysis by providing trend information, but it should not be used as the sole basis for making trading or investing decisions. Always combine it with other forms of analysis and risk management practices. No statements or claims aim to be financial advice, and no signals from us or our indicators should be interpreted as such. Past performance is not indicative of future results.
Dynamic Volume RSI (DVRSI) [QuantAlgo]Introducing the Dynamic Volume RSI (DVRSI) by QuantAlgo 📈✨
Elevate your trading and investing strategies with the Dynamic Volume RSI (DVRSI) , a powerful tool designed to provide clear insights into market momentum and trend shifts. This indicator is ideal for traders and investors who want to stay ahead of the curve by using volume-responsive calculations and adaptive smoothing techniques to enhance signal clarity and reliability.
🌟 Key Features:
🛠 Customizable RSI Settings: Tailor the indicator to your strategy by adjusting the RSI length and price source. Whether you’re focused on short-term trades or long-term investments, DVRSI adapts to your needs.
🌊 Adaptive Smoothing: Enable adaptive smoothing to filter out market noise and ensure cleaner signals in volatile or choppy market conditions.
🎨 Dynamic Color-Coding: Easily identify bullish and bearish trends with color-coded candles and RSI plots, offering clear visual cues to track market direction.
⚖️ Volume-Responsive Adjustments: The DVRSI reacts to volume changes, giving greater significance to high-volume price moves and improving the accuracy of trend detection.
🔔 Custom Alerts: Stay informed with alerts for key RSI crossovers and trend changes, allowing you to act quickly on emerging opportunities.
📈 How to Use:
✅ Add the Indicator: Set up the DVRSI by adding it to your chart and customizing the RSI length, price source, and smoothing options to fit your specific strategy.
👀 Monitor Visual Cues: Watch for trend shifts through the color-coded plot and candles, signaling changes in momentum as the RSI crosses key levels.
🔔 Set Alerts: Configure alerts for critical RSI crossovers, such as the 50 line, ensuring you stay on top of potential market reversals and opportunities.
🔍 How It Works:
The Dynamic Volume RSI (DVRSI) is a unique indicator designed to provide more accurate and responsive signals by incorporating both price movement and volume sensitivity into the RSI framework. It begins by calculating the traditional RSI values based on a user-defined length and price source, but unlike standard RSI tools, the DVRSI applies volume-weighted adjustments to reflect the strength of market participation.
The indicator dynamically adjusts its sensitivity by factoring in volume to the RSI calculation, which means that price moves backed by higher volumes carry more weight, making the signal more reliable. This method helps identify stronger trends and reduces the risk of false signals in low-volume environments. To further enhance accuracy, the DVRSI offers an adaptive smoothing option that allows users to reduce noise during periods of market volatility. This adaptive smoothing function responds to market conditions, providing a cleaner signal by reducing erratic movements or price spikes that could lead to misleading signals.
Additionally, the DVRSI uses dynamic color-coding to visually represent the strength of bullish or bearish trends. The candles and RSI plots change color based on the RSI values crossing critical thresholds, such as the 50 level, offering an intuitive way to recognize trend shifts. Traders can also configure alerts for specific RSI crossovers (e.g., above 50 or below 40), ensuring that they stay informed of potential trend reversals and significant market shifts in real-time.
The combination of volume sensitivity, adaptive smoothing, and dynamic trend visualization makes the DVRSI a robust and versatile tool for traders and investors looking to fine-tune their market analysis. By incorporating both price and volume data, this indicator delivers more precise signals, helping users make informed decisions with greater confidence.
Disclaimer:
The Dynamic Volume RSI is designed to enhance your market analysis but should not be used as a sole decision-making tool. Always consider multiple factors before making any trading or investment decisions. Past performance is not indicative of future results.
Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
