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.
Cryptomarket
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.
MultiSector Performance Tracker [LuxAlgo]The MultiSector Performance Tracker tool shows the overall performance of different crypto market sectors within a selected time frame, overlaid on a single chart for easy comparison.
Users can customize the time frame to suit their specific needs, whether daily, weekly, monthly, or yearly.
🔶 USAGE
The tool displays the performance of up to 6 crypto sectors within a selected time period, such as each day, week, month or year, or from the beginning of the year for any of the last 4 years.
The sectors and tickers within each sector are as follows:
Layer 1: CRYPTOCAP:ETH CRYPTOCAP:SOL CRYPTOCAP:TON
Layer 2: SEED_DONKEYDAN_MARKET_CAP:MATIC TSX:MNT AMEX:ARB
CEX: CRYPTOCAP:BNB CRYPTOCAP:OKB NYSE:BGB
DEX: CRYPTOCAP:UNI LSE:JUP CRYPTOCAP:RUNE
AI: CRYPTOCAP:NEAR GETTEX:TAO CRYPTOCAP:ICP
Ethereum Memes: CRYPTOCAP:PEPE CRYPTOCAP:SHIB CRYPTOCAP:FLOKI
Traders can compare the relative performance of a custom ticker against the sector of their choice and view the average of all sectors.
The tool is fully customizable, allowing traders to enable or disable any of the features or sectors.
🔹 Dashboard
The tool also displays the data in an ascending or descending sector performance dashboard, allowing traders to see at a glance which sectors are overperforming or underperforming.
Other dashboard features include custom ticker vs. sector comparison and sectors average, and traders can choose the location and size of the dashboard.
🔶 SETTINGS
Period: View all data by time period, daily, weekly, etc. Or view data from last year, last 2 years, etc.
Relative Performance Against: Enable/Disable relative performance comparison against a sector.
Use chart ticker: Enable the use of the chart ticker or a custom ticker for relative performance comparison.
🔹 Dashboard
Show Dashboard: Enable / disable Dashboard display.
Order: Choose between ascending and descending order.
Position: Selection of dashboard location.
Size: Selection of dashboard size.
🔹 Style
Show Sectors Labels: Enable / disable sector labels
Layer 1: Enable / disable Layer 1 sector
Layer 2: Enable / disable Layer 2 sector
CEX: Enable / disable CEX sector
DEX: Enable / disable DEX sector
AI: Enable / disable AI sector
Ethereum Memes: Enable / disable Ethereum Memes sector
Average: Enable / disable sectors average display
Custom Ticker: Enable / disable custom ticker display
SMA Fibonacci Rainbow Waves[FibonacciFlux]SMA Fibonacci Rainbow Waves
Overview
The SMA Fibonacci Rainbow Waves script is designed for traders who seek to blend simplicity with complexity in their trading strategies. By leveraging multiple Simple Moving Averages (SMAs) weighted by Fibonacci numbers, this indicator provides a nuanced view of price action, allowing traders to capture essential market dynamics while filtering out unnecessary noise.
Key Features
1. Multiple Simple Moving Averages (SMA)
- The indicator employs a series of SMAs to represent both short-term and long-term trends, providing a comprehensive view of market sentiment.
- Each SMA helps identify critical price levels that serve as support and resistance, particularly the purple Fibonacci SMA, which can be pivotal for limit entries. Traders positioned at this level can initiate stop-loss hunts at the institutional level, potentially achieving risk-reward ratios exceeding 30.
2. Fibonacci Weighting
- By applying Fibonacci principles to the SMAs, the indicator enhances adaptability to market conditions.
- This unique approach allows traders to pinpoint significant support and resistance levels within Fibonacci layers, enabling them to anticipate market movements effectively.
3. Dynamic Support and Resistance Levels
- The SMA Fibonacci Rainbow Waves indicator identifies key price levels that act as support and resistance based on Fibonacci layers.
- For instance, on the hourly chart, these levels function as reliable zones for traders to watch for potential reversals, while on the 15-minute chart, a consolidation within the rainbow pocket followed by expansion can signal lucrative trading opportunities.
4. Visual Clarity with Color Coding
- Each SMA is assigned a distinct color, making it easy to differentiate between the various levels on the chart.
- Fills between SMAs visually represent zones of confluence, enhancing the analysis of potential trading opportunities.
Signal Generation and Alerts
- The indicator generates buy and sell signals based on the interactions of the SMAs, providing clear entry and exit points.
- Customizable alerts notify traders of significant market changes, allowing for timely reactions to evolving conditions.
Benefits
1. Simplified Trading Approach
- Traders can focus on significant market trends without distraction, enhancing decision-making efficiency and reducing emotional trading.
2. Flexibility Across Timeframes
- The indicator operates effectively across multiple timeframes, allowing traders to apply its principles in various scenarios, from scalping to longer-term strategies.
3. Enhanced Market Insights
- The combination of multiple SMAs and Fibonacci weighting offers a comprehensive view of market trends, helping traders identify lucrative opportunities that may be overlooked.
4. Bridging Simplicity and Complexity
- This indicator elegantly addresses the contradictions in trading psychology, allowing traders to maintain clarity while navigating complex market dynamics.
Conclusion
The SMA Fibonacci Rainbow Waves script is an essential tool for traders seeking to streamline their analysis while effectively capturing market movements. By integrating Fibonacci principles with multiple SMAs, this indicator empowers traders to follow trends confidently. Its design makes it invaluable for both novice and experienced traders, revealing entry points often missed by traditional indicators.
Open Source Collaboration
This script is available as an open-source project on TradingView, inviting contributions from the global trading community to enhance its functionality. Collaboration ensures it remains a valuable resource for market participants.
Important Note
As with any trading tool, thorough analysis and risk management are crucial when using this indicator. Past performance does not guarantee future results, and traders should always prepare for potential market fluctuations.
The Adaptive Pairwise Momentum System [QuantraSystems]The Adaptive Pairwise Momentum System
QuantraSystems guarantees that the information created and published within this document and on the Tradingview platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.
Important Note!
The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest.
Even More Important Note!!
The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
Introduction
The Adaptive Pairwise Momentum System is not just an indicator but a comprehensive asset rotation and trend-following system. In short, it aims to find the highest performing asset from the provided range.
The system dynamically optimizes capital allocation across up to four high-performing assets, ensuring that the portfolio adapts swiftly to changing market conditions. The system logic consists of sophisticated quantitative methods, rapid momentum analysis, and robust trend filtering. The overarching goal is to ensure that the portfolio is always invested in the highest-performing asset based on dynamic market conditions, while at the same time managing risk through broader market filters and internal mechanisms like volatility and beta analysis.
Legend
System Equity Curve:
The equity curve displayed in the chart is dynamically colored based on the asset allocation at any given time. This color-coded approach allows traders to immediately identify transitions between assets and the corresponding impact on portfolio performance.
Highlighting of Current Highest Performer:
The current bar in the chart is highlighted based on the confirmed highest performing asset. This is designed to give traders advanced notice of potential shifts in allocation even before a formal position change occurs. The highlighting enables traders to prepare in real time, making it easier to manage positions without lag, particularly in fast-moving markets.
Highlighted Symbols in the Asset Table:
In the table displayed on the right hand side of the screen, the current top-performing symbol is highlighted. This clear signal at a glance provides immediate insight into which asset is currently being favored by the system. This feature enhances clarity and helps traders make informed decisions quickly, without needing to analyze the underlying data manually.
Performance Overview in Tables:
The left table provides insight into both daily and overall system performance from inception, offering traders a detailed view of short-term fluctuations and long-term growth. The right-hand table breaks down essential metrics such as Sharpe ratio, Sortino ratio, Omega ratio, and maximum drawdown for each asset, as well as for the overall system and HODL strategy.
Asset-Specific Signals:
The signals column in the table indicates whether an asset is currently held or being considered for holding based on the system's dynamic rankings. This is a critical visual aid for asset reallocation decisions, signaling when it may be appropriate to either maintain or change the asset of the portfolio.
Core Features and Methodologies
Flexibility in Asset Selection
One of the major advantages of this system is its flexibility. Users can easily modify the number and type of assets included for comparison. You can quickly input different assets and backtest their performance, allowing you to verify how well this system might fit different tokens or market conditions. This flexibility empowers users to adapt the system to a wide range of market environments and tailor it to their unique preferences.
Whole System Risk Mitigation - Macro Trend Filter
One of the features of this script is its integration of a Macro-level Trend Filter for the entire portfolio. The purpose of this filter is to ensure no capital is allocated to any token in the rotation system unless Bitcoin itself is in a positive trend. The logic here is that Bitcoin, as the cryptocurrency market leader, often sets the tone for the entire cryptocurrency market. By using Bitcoins trend direction as a barometer for overall market conditions, we create a system where capital is not allocated during unfavorable or bearish market conditions - significantly reducing exposure to downside risk.
Users have the ability to toggle this filter on and off in the input menu, with five customizable options for the trend filter, including the option to use no filter. These options are:
Nova QSM - a trend aggregate combining the Rolling VWAP, Wave Pendulum Trend, KRO Overlay, and the Pulse Profiler provides the market trend signal confirmation.
Kilonova QSM - a versatile aggregate combining the Rolling VWAP, KRO Overlay, the KRO Base, RSI Volatility Bands, NNTRSI, Regression Smoothed RSI and the RoC Suite.
Quasar QSM - an enhanced version of the original RSI Pulsar. The Quasar QSM refines the trend following approach by utilizing an aggregated methodology.
Pairwise Momentum and Strength Ranking
The backbone of this system is its ability to identify the strongest-performing asset in the selected pool, ensuring that the portfolio is always exposed to the asset showing the highest relative momentum. The system continually ranks these assets against each other and determines the highest performer by measure of past and coincident outperformance. This process occurs rapidly, allowing for swift responses to shifts in market momentum, which ensures capital is always working in the most efficient manner. The speed and precision of this reallocation strategy make the script particularly well-suited for active, momentum-driven portfolios.
Beta-Adjusted Asset Selection as a Tiebreaker
In the circumstance where two (or more) assets exhibit the same relative momentum score, the system introduces another layer of analysis. In the event of a strength ‘tie’ the system will preference maintaining the current position - that is, if the previously strongest asset is now tied, the system will still allocate to the same asset. If this is not the case, the asset with the higher beta is selected. Beta is a measure of an asset’s volatility relative to Bitcoin (BTC).
This ensures that in bullish conditions, the system favors assets with a higher potential for outsized gains due to their inherent volatility. Beta is calculated based on the Average Daily Return of each asset compared to BTC. By doing this, the system ensures that it is dynamically adjusting to risk and reward, allocating to assets with higher risk in favorable conditions and lower risk in less favorable conditions.
Dynamic Asset Reallocation - Opposed to Multi-Asset Fixed Intervals
One of the standout features of this system is its ability to dynamically reallocate capital. Unlike traditional portfolio allocation strategies that may rebalance between a basket of assets monthly or quarterly, this system recalculates and reallocates capital on the next bar close (if required). As soon as a new asset exhibits superior performance relative to others, the system immediately adjusts, closing the previous position and reallocating funds to the top-ranked asset.
This approach is particularly powerful in volatile markets like cryptocurrencies, where trends can shift quickly. By reallocating swiftly, the system maximizes exposure to high-performing assets while minimizing time spent in underperforming ones. Moreover, this process is entirely automated, freeing the trader from manually tracking and measuring individual token strength.
Our research has demonstrated that, from a risk-adjusted return perspective, concentration into the top-performing asset consistently outperforms broad diversification across longer time horizons. By focusing capital on the highest-performing asset, the system captures outsized returns that are not achievable through traditional diversification. However, a more risk-averse investor, or one seeking to reduce drawdowns, may prefer to move the portfolio further left along the theoretical Capital Allocation Line by incorporating a blend of cash, treasury bonds, or other yield-generating assets or even include market neutral strategies alongside the rotation system. This hybrid approach would effectively lower the overall volatility of the portfolio while still maintaining exposure to the system’s outsized returns. In theory, such an investor can reduce risk without sacrificing too much potential upside, creating a more balanced risk-return profile.
Position Changes and Fees/Slippage
Another critical and often overlooked element of this system is its ability to account for fees and slippage. Given the increased speed and frequency of allocation logic compared to the buy-and-hold strategy, it is of vital importance that the system recognises that switching between assets may incur slippage, especially in highly volatile markets. To account for this, the system integrates realistic slippage and fee estimates directly into the equity curve, simulating expected execution costs under typical market conditions and gives users a more realistic view of expected performance.
Number of Position Changes
Understanding the number of position changes in a strategy is critical to assessing its feasibility in real world trading. Frequent position changes can lead to increased costs due to slippage and fees. Monitoring the number of position changes provides insight into the system’s behavior - helping to evaluate how active the strategy is and whether it aligns with the trader's desired time input for position management.
Equity Curve and Performance Calculations
To provide a benchmark, the script also generates a Buy-and-Hold (or "HODL") equity curve that represents an equal split across the four selected assets. This allows users to easily compare the performance of the dynamic rotation system with that of a more traditional investment strategy.
The script tracks key performance metrics for both the dynamic portfolio and the HODL strategy, including:
Sharpe Ratio
The Sharpe Ratio is a key metric that evaluates a portfolio’s risk-adjusted return by comparing its ‘excess’ return to its volatility. Traditionally, the Sharpe Ratio measures returns relative to a risk-free rate. However, in our system’s calculation, we omit the risk-free rate and instead measure returns above a benchmark of 0%. This adjustment provides a more universal comparison, especially in the context of highly volatile assets like cryptocurrencies, where a traditional risk-free benchmark, such as the usual 3-month T-bills, is often irrelevant or too distant from the realities of the crypto market.
By using 0% as the baseline, we focus purely on the strategy's ability to generate raw returns in the face of market risk, which makes it easier to compare performance across different strategies or asset classes. In an environment like cryptocurrency, where volatility can be extreme, the importance of relative return against a highly volatile backdrop outweighs comparisons to a risk-free rate that bears little resemblance to the risk profile of digital assets.
Sortino Ratio
The Sortino Ratio improves upon the Sharpe Ratio by specifically targeting downside risk and leaves the upside potential untouched. In contrast to the Sharpe Ratio (which penalizes both upside and downside volatility), the Sortino Ratio focuses only on negative return deviations. This makes it a more suitable metric for evaluating strategies like the Adaptive Pairwise Momentum Strategy - that aim to minimize drawdowns without restricting upside capture. By measuring returns relative to a 0% baseline, the Sortino ratio provides a clearer assessment of how well the system generates gains while avoiding substantial losses in highly volatile markets like crypto.
Omega Ratio
The Omega Ratio is calculated as the ratio of gains to losses across all return thresholds, providing a more complete view of how the system balances upside and downside risk even compared to the Sortino Ratio. While it achieves a similar outcome to the Sortino Ratio by emphasizing the system's ability to capture gains while limiting losses, it is technically a mathematically superior method. However, we include both the Omega and Sortino ratios in our metric table, as the Sortino Ratio remains more widely recognized and commonly understood by traders and investors of all levels.
Case Study
Notes
For the sake of brevity, the Important Notes section found in the header of this text will not be rewritten. Instead, it will be highlighted that now is the perfect time to reread these notes. Reading this case study in the context of what has been mentioned above is of key importance.
As a second note, it is worth mentioning that certain market periods are referred to as either “Bull” or “Bear” markets - terms I personally find to be vague and undefinable - and therefore unfavorable. They will be used nevertheless, due to their familiarity and ease of understanding in this context. Substitute phrases could be “Macro Uptrend” or “Macro Downtrend.”
Overview
This case study provides an in-depth performance analysis of the Adaptive Pairwise Momentum System , a long-only system that dynamically allocates to outperforming assets and moves into cash during unfavorable conditions.
This backtest includes realistic assumptions for slippage and fees, applying a 0.5% cost for every position change, which includes both asset reallocation and moving to a cash position. Additionally, the system was tested using the top four cryptocurrencies by market capitalization as of the test start date of 01/01/2022 in order to minimize selection bias.
The top tokens on this date (excluding Stablecoins) were:
Bitcoin
Ethereum
Solana
BNB
This decision was made in order to avoid cherry picking assets that might have exhibited exceptional historical performance - minimizing skew in the back test. Furthermore, although this backtest focuses on these specific assets, the system is built to be flexible and adaptable, capable of being applied to a wide range of assets beyond those initially tested.
Any potential lookahead bias or repainting in the calculations has been addressed by implementing the lookback modifier for all repainting sensitive data, including asset ratios, asset scoring, and beta values. This ensures that no future information is inadvertently used in the asset allocation process.
Additionally, a fixed lookback period of one bar is used for the trend filter during allocations - meaning that the trend filter from the prior bar must be positive for an allocation to occur on the current bar. It is also important to note that all the data displayed by the indicator is based on the last confirmed (closed) bar, ensuring that the entire system is repaint-proof.
The study spans the 2022 cryptocurrency bear market through the subsequent bull market of 2023 and 2024. The stress test highlights how the system reacted to one of the most challenging market downturns in crypto history - which includes events such as:
Luna and TerraUSD crash
Three Arrows Capital liquidation
Celsius bankruptcy
Voyager Digital bankruptcy
FTX collapse
Silicon Valley + Signature + Silvergate banking collapses
Subsequent USDC deppegging
And arguably more important, 2022 was characterized by a tightening of monetary policy after the unprecedented monetary easing in response to the Covid pandemic of 2020/2021. This shift undeniably puts downward pressure on asset prices, most probably to the extent that this had a causal role to many of the above events.
By incorporating these real-world challenges, the backtest provides a more accurate and robust performance evaluation that avoids overfitting or excessive optimization for one specific market condition.
The Bear Market of 2022: Stress Test and System Resilience
During the 2022 bear market, where the overall crypto market experienced deep and consistent corrections, the Adaptive Pairwise Momentum System demonstrated its ability to mitigate downside risk effectively.
Dynamic Allocation and Cash Exposure:
The system rotated in and out of cash, as indicated by the gray period on the system equity curve. This allocation to cash during downtrending periods, specifically in late 2022, acted as the systems ‘risk-off’ exposure - the purest form of such an exposure. This prevented the system from experiencing the magnitude of drawdown suffered by the ‘Buy-and-Hold (HODL) investors.
In contrast, a passive HODL strategy would have suffered a staggering 75.32% drawdown, as it remained fully allocated to chosen assets during the market's decline. The active Pairwise Momentum system’s smaller drawdown of 54.35% demonstrates its more effective capital preservation mechanisms.
The Bull Market of 2023 and 2024: Capturing Market Upside
Following the crypto bear market, the system effectively capitalized on the recovery and subsequent bull market of 2023 and 2024.
Maximizing Market Gains:
As trends began turning bullish in early 2023, the system caught the momentum and promptly allocated capital to only the quantified highest performing asset of the time - resulting in a parabolic rise in the system's equity curve. Notably, the curve transitions from gray to purple during this period, indicating that Solana (SOL) was the top-performing asset selected by the system.
This allocation to Solana is particularly striking because, at the time, it was an asset many in the market shunned due to its association with the FTX collapse just months prior. However, this highlights a key advantage of quantitative systems like the one presented here: decisions are driven purely from objective data - free from emotional or subjective biases. Unlike human traders, who are inclined (whether consciously or subconsciously) to avoid assets that are ‘out of favor,’ this system focuses purely on price performance, often uncovering opportunities that are overlooked by discretionary based investors. This ability to make data-driven decisions ensures that the strategy is always positioned to capture the best risk-adjusted returns, even in scenarios where judgment might fail.
Minimizing Volatility and Drawdown in Uptrends
While the system captured substantial returns during the bull market it also did so with lower volatility compared to HODL. The sharpe ratio of 4.05 (versus HODL’s 3.31) reflects the system's superior risk-adjusted performance. The allocation shifts, combined with tactical periods of cash holding during minor corrections, ensured a smoother equity curve growth compared to the buy-and-hold approach.
Final Summary
The percentage returns are mentioned last for a reason - it is important to emphasize that risk-adjusted performance is paramount. In this backtest, the Pairwise Momentum system consistently outperforms due to its ability to dynamically manage risk (as seen in the superior Sharpe, Sortino and Omega ratios). With a smaller drawdown of 54.35% compared to HODL’s 75.32%, the system demonstrates its resilience during market downturns, while also capturing the highest beta on the upside during bullish phases.
The system delivered 266.26% return since the backtest start date of January 1st 2022, compared to HODL’s 10.24%, resulting in a performance delta of 256.02%
While this backtest goes some of the way to verifying the system’s feasibility, it’s important to note that past performance is not indicative of future results - especially in volatile and evolving markets like cryptocurrencies. Market behavior can shift, and in particular, if the market experiences prolonged sideways action, trend following systems such as the Adaptive Pairwise Momentum Strategy WILL face significant challenges.
RSI Pulsar [QuantraSystems]RSI Pulsar
Introduction
The RSI Pulsar is an advanced and multifaceted tool designed to cater to the varying needs of traders, from long-term swing traders to higher-frequency day traders. This indicator takes the Relative Strength Index (RSI) to new heights by combining several unique methodologies to provide clear, actionable signals across different market conditions. With its ability to analyze impulsive trend strength, volatility, and binary market direction, the RSI Pulsar offers a holistic view of the market that assists traders in identifying robust signals and rotational opportunities within a volatile market.
The integration of dynamic color coding further aids in quick visual assessments, allowing traders to adapt swiftly to changing market conditions, making the RSI Pulsar an essential component in the arsenal of modern traders aiming for precision and adaptability in their trading endeavors.
Legend
The RSI Pulsar encapsulates various modes tailored to diverse trading strategies. The different modes are the:
Impulse Mode:
Focuses on strong outperformance, ideal for capturing movements in highly dynamic tokens.
Trend Following Mode:
A classical perpetual trend-following approach and provides binary long and short signal classifications ideal for medium term swing trading.
Ribbon Mode:
Offers quicker signals that are also binary in nature. Perfect for a confirmation signal when building higher frequency day trading systems.
Volatility Spectrum:
This feature projects a visual 'cloud' representing volatility, which helps traders spot emerging trends and potential breakouts or reversals.
Compressed Mode:
A condensed view that displays all signals in a clean and space-efficient manner. It provides a clear summary of market conditions, ideal for traders who prefer a simplified overview.
Methodology
The RSI Pulsar is built on a foundation of dynamic RSI analysis, where the traditional RSI is enhanced with advanced moving averages and standard deviation calculations. Each mode within the RSI Pulsar is designed to cater to specific aspects of the market's behavior, making it a versatile tool allowing traders to select different modes based on their trading style and market conditions.
Impulse Mode:
This mode identifies strong outperformance in assets, making it ideal for asset rotation systems. It uses a combination of RSI thresholds and dynamic moving averages to pinpoint when an asset is not just trending positively, but doing so with significant strength.
This is in contrast to typical usage of a base RSI, where elevated levels usually signal overbought and oversold periods. The RSI Pulsar flips this logic, where more extreme values are actually interpreted as a strong trend.
Trend Following Mode:
Here, the RSI is compared to the midline (the default is level 50, but a dynamic midline can also be set), to determine the prevailing trend. This mode simplifies the trend-following process, providing clear bullish or bearish signals based on whether the RSI is above or below the midline - whether a fixed or dynamic level.
Ribbon Mode:
This mode employs a series of calculated values derived from modified Heikin-Ashi smoothing to create a "ribbon" that smooths out price action and highlights underlying trends. The Ribbon Mode is particularly useful for traders who need quick confirmations of trend reversals or continuations.
Volatility Spectrum:
The Volatility Spectrum takes a unique approach to measuring market volatility by analyzing the size and direction of Heikin-Ashi candles. This data is used to create a volatility cloud that helps traders identify when volatility is rising, falling, or neutral - allowing them to adjust their strategies accordingly.
When the signal line breaks above the cloud, it signals increasing upwards volatility. When it breaks below it signifies increasing downwards volatility.
This can be used to help identify strengthening and weakening trends, as well as imminent volatile periods, allowing traders to position themselves and adapt their strategies accordingly. This mode also works as a great volatility filter for shorter term day trading strategies. It is incredibly sensitive to volatility divergences, and can give additional insights to larger market turning points.
Compressed Mode:
In Compressed Mode, all the signals from the various modes are displayed in a simplified format, making it easy for traders to quickly assess the market's overall condition without needing to delve into the details of each mode individually. Perfect for only viewing the exact data you need when live trading, or back testing.
Case Study I:
Utilizing ALMA Impulse Mode in High-Volatility Environments
Here, the RSI Pulsar is configured with an RSI length of 9 and an ALMA length of 2 in Impulse Mode. The chart example shows how this setup can identify significant price movements, allowing traders to enter positions early and capture substantial price moves. Despite the fast settings resulting in occasional false signals, the indicator's ability to catch and ride out major trends more than compensates, making it highly effective in volatile environments.
This configuration is suitable for traders seeking to trade quick, aggressive movements without enduring prolonged drawdowns. In Impulse Mode, the RSI Pulsar seeks strong trending zones, providing actionable signals that allow for timely entries and exits.
Case Study II:
SMMA Trend Following Mode for Ratio Analysis
The RSI Pulsar in Trend Following mode, configured with the SMMA with default length settings. This setup is ideal for analyzing longer-term trends, particularly useful in cryptocurrency pairs or ratio charts, where it’s crucial to identify robust directional moves. The chart showcases strong trends in the Solana/Ethereum pair. The RSI Pulsar’s ability to smooth out price action while remaining responsive to trend changes makes it an excellent tool for capturing extended price moves.
The image highlights how the RSI Pulsar efficiently tracks the strength of two tokens against each other, providing clear signals when one asset begins to outperform the other. Even in volatile markets, the SMMA ensures that the signals are reliable, filtering out noise and allowing traders to stay in the trend longer without being shaken out by minor corrections. This approach is particularly effective in ratio trading in order to inform a longer term swing trader of the strongest asset out of a customized pair.
Case Study III:
Monthly Analysis with RSI Pulsar in Ribbon Mode
This case study demonstrates the versatility and reliability of the RSI Pulsar in Ribbon mode, applied to a monthly chart of Bitcoin with an RSI length of 8 and a TEMA length of 14. This setup highlights the indicator’s robustness across multiple timeframes, extending even to long-term analysis. The RSI Pulsar effectively smooths out noise while capturing significant trends, as seen during Bitcoin bull markets. The Ribbon mode provides a clear visual representation of momentum shifts, making it easier for traders to identify trend continuations and reversals with confidence.
Case Study IV:
Divergences and Continuations with the Volatility Spectrum
Identifying harmony/divergences can be hit-or-miss at times, but this unique analysis method definitely has its merits at times. The RSI Pulsar, with its Volatility Spectrum feature, is used here to identify critical moments where price action either aligns with or diverges from the underlying volatility. As seen in the Bitcoin chart (using default settings), the indicator highlights areas where price trends either continue in harmony with volatility or diverge, signaling potential reversals. This method, while not always perfect, provides significant insight during key turning points in the market.
The Volatility Spectrum's visual representation of rising and falling volatility, combined with divergence and harmony analysis, enables traders to anticipate significant shifts in market dynamics. In this case, multiple divergences correctly identified early trend reversals, while periods of harmony indicated strong trend continuations. While this method requires careful interpretation, especially during complex market conditions, it offers valuable signals that can be pivotal in making informed trading decisions, especially if combined with other forms of analysis it can form a critical component of an investing system.
Trend Filtered Signals with Confidence LevelThe Trend Filtered Signals with Confidence Level is a powerful technical analysis tool designed for trend-following traders. It provides clear buy and sell signals, enhanced by a unique confidence level indicator, helping traders filter out market noise and focus on higher-probability trades. This indicator is built with advanced trend detection, volatility filtering, and volume confirmation, making it suitable for various markets such as stocks, forex, and cryptocurrencies.
Key Features:
Precise Trend Detection:
The indicator uses the Average Directional Index (ADX) to measure the strength of the trend, only generating signals when the trend is strong enough (above a user-defined threshold). This prevents false signals during sideways markets and ensures the system follows meaningful trends.
Buy and Sell Signals:
Buy signals are generated when the price crosses above the fast moving average, and the market is in a strong uptrend based on ADX and other filters. Conversely, sell signals are created when the price crosses below the fast moving average in a strong downtrend. These signals appear directly on the chart with visual markers, making them easy to spot in real-time trading.
Confidence Level for Signals:
Each buy and sell signal is given a confidence percentage, calculated from multiple factors:
The strength of the trend (ADX).
The price’s relationship to moving averages (fast MA and slow MA).
The current trading volume compared to its moving average.
The distance between the price and the moving averages, which is checked against the ATR (Average True Range).
A higher confidence percentage indicates a stronger, more reliable signal. Traders can choose to act only on signals that meet or exceed their preferred confidence level.
ATR-Based Volatility Filtering:
To avoid over-trading or receiving signals that are too close together, the ATR (Average True Range) is used as a volatility filter. This ensures that the signals are spaced out, and traders only receive alerts when the price has moved a meaningful distance, considering market volatility.
Volume Confirmation:
Volume plays a crucial role in signal accuracy. The indicator compares the current volume to its moving average, ensuring that signals are generated only when there is sufficient market participation. This feature helps traders avoid signals during low-volume or illiquid market conditions.
Exit Alerts for Trend Reversals:
The indicator doesn’t just help you enter trades; it also assists with exits. When the trend shows signs of weakening or reversing (such as price crossing back over the moving average or losing ADX strength), the indicator will issue an exit alert, helping traders lock in profits or minimize losses.
How to Use the Indicator:
Choosing Timeframes:
The Trend Filtered Signals with Confidence Level works on multiple timeframes. For intraday traders, it can be applied on 5-minute or 15-minute charts. Swing traders might prefer the 1-hour or daily timeframe to capture longer-term trends. Adjust the inputs based on the volatility of the asset you're trading and the timeframe.
Customizing Inputs:
ADX Length: Defines the length for calculating ADX. A typical setting is 14, but this can be adjusted based on how quickly or slowly you want the indicator to react to changes in trend strength.
ADX Threshold: Set this value to filter out weak trends. The default is 20, but for stronger trend signals, a threshold of 25 or 30 may be more suitable.
ATR Length & Multiplier: Used to calculate the average true range, helping to filter out signals that are too close to each other. The ATR multiplier increases the signal’s precision in volatile markets.
Fast and Slow Moving Averages: These moving averages help define the short- and long-term trend. The default fast MA is 9, and the slow MA is 21, but traders can adjust these based on their strategy.
Volume MA: Defines the length of the moving average applied to volume. A longer setting may be more appropriate for swing trading, while a shorter setting can work better for day trading.
Interpreting the Confidence Percentage:
Signals with a confidence level above 50% are generally considered reliable. However, traders can choose to filter trades based on their risk tolerance by only acting on signals above a certain confidence level (e.g., 70% or higher for conservative traders).
Use the confidence percentage as a guide to increase the likelihood of entering higher-probability trades.
Signal Alerts:
The indicator provides customizable alerts for both buy and sell signals. It also generates alerts when it's time to exit a position due to weakening trend conditions.
Alerts can be set up through TradingView’s alert system to notify you via mobile, email, or browser pop-up, so you never miss an opportunity.
Managing Entries and Exits:
Combine the buy and sell signals with the confidence level to time entries more effectively. After entering a position, keep an eye on the exit signals generated by the indicator to manage your trades.
For trend-following strategies, stay in the trade as long as the indicator shows a strong trend. When the confidence level drops significantly, or the exit alert triggers, it may be time to close the trade.
Inputs Overview:
ADX Length: Default 14, for trend strength.
ADX Threshold: Default 20, minimum trend strength for signal generation.
ATR Length & Multiplier: Adjust for volatility filtering.
Fast MA & Slow MA Lengths: Define the short-term and long-term trend.
Volume MA Length: Confirm signals with volume strength.
Minimum Signal Distance: Prevents excessive signal clustering.
Conclusion:
The Trend Filtered Signals with Confidence Level indicator by Danytradehit is a comprehensive tool that not only identifies trends and trend reversals but also helps you gauge the reliability of each signal through a confidence percentage. It simplifies decision-making for traders by filtering out weak or low-probability trades, ensuring you only act on the most promising market opportunities. This indicator is highly customizable and works across various timeframes and asset classes.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
Multi-Step FlexiSuperTrend - Indicator [presentTrading]This version of the indicator is built upon the foundation of a strategy version published earlier. However, this indicator version focuses on providing visual insights and alerts for traders, rather than executing trades. This one is mostly for @thorcmt.
█ Introduction and How it is Different
The **Multi-Step FlexiSuperTrend Indicator** is a versatile tool designed to provide traders with a highly customizable and flexible approach to trend analysis. Unlike traditional supertrend indicators, which focus on a single factor or threshold, the **FlexiSuperTrend** allows users to define multiple levels of take-profit targets and incorporate different trend normalization methods.
It comes with several advanced customization features, including multi-step take profits, deviation plotting, and trend normalization, making it suitable for both novice and expert traders.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
The **Multi-Step FlexiSuperTrend** works by calculating a supertrend based on multiple factors and incorporating oscillations from trend deviations. Here’s a breakdown of how it functions:
🔶 SuperTrend Calculation
At the heart of the indicator is the SuperTrend formula, which dynamically adjusts based on price movements.
🔶 Normalization of Deviations
To enhance accuracy, the **FlexiSuperTrend** calculates multiple deviations from the trend and normalizes them.
🔶 Multi-Step Take Profit Levels
The indicator allows setting up to three take profit levels, which are displayed via price level alerts. lows traders to exit part of their position at various profit intervals.
For more detail, please check the strategy version - Multi-Step-FlexiSuperTrend-Strategy:
and 'FlexiSuperTrend-Strategy'
█ Trade Direction
The **Multi-Step FlexiSuperTrend Indicator** supports both long and short trade directions.
This flexibility allows traders to adapt to trending, volatile, or sideways markets.
█ Usage
To use the **FlexiSuperTrend Indicator**, traders can set up their preferences for the following key features:
- **Trading Direction**: Choose whether to focus on long, short, or both signals.
- **Indicator Source**: The price source to calculate the trend (e.g., close, hl2).
- **Indicator Length**: The number of periods to calculate the ATR and trend (the larger the value, the smoother the trend).
- **Starting and Increment Factor**: These adjust how reactive the trend is to price movements. The starting factor dictates how far the initial trend band is from the price, and the increment factor adjusts subsequent trend deviations.
The indicator then displays buy and sell signals on the chart, along with alerts for each take-profit level.
Local picture
█ Default Settings
The default settings of the **Multi-Step FlexiSuperTrend** are carefully designed to provide an optimal balance between sensitivity and accuracy. Let’s examine these default parameters and their effect on performance:
🔶 Indicator Length (Default: 10)
The **Indicator Length** determines the lookback period for the ATR calculation. A smaller value makes the indicator more reactive to price changes, but may generate more false signals. A longer length smooths the trend and reduces noise but may delay signals.
Effect on performance: Shorter lengths perform better in volatile markets, while longer lengths excel in trending markets.
🔶 Starting Factor (Default: 0.618)
This factor adjusts the starting distance of the SuperTrend from the current price. The smaller the starting factor, the closer the trend is to the price, making it more sensitive. Conversely, a larger factor allows more distance, reducing sensitivity but filtering out false signals.
Effect on performance: A smaller factor provides quicker signals but can lead to frequent false positives. A larger factor generates fewer but more reliable signals.
🔶 Increment Factor (Default: 0.382)
The **Increment Factor** controls how the trend bands adjust as the price moves. It increases the distance of the bands from the price with each iteration.
Effect on performance: A higher increment factor can result in wider stop-loss or trend reversal bands, allowing for longer trends to develop without frequent exits. A lower factor keeps the bands closer to the price and is more suited for shorter-term trades.
🔶 Take Profit Levels (Default: 2%, 8%, 18%)
The default take-profit levels are set at 2%, 8%, and 18%. These values represent the thresholds at which the trader can partially exit their positions. These multi-step levels are highly customizable depending on the trader’s risk tolerance and strategy.
Effect on performance: Lower take-profit levels (e.g., 2%) capture small, quick profits in volatile markets, while higher levels (8%-18%) allow for a more gradual exit in strong trends.
🔶 Normalization Method (Default: None)
The default normalization method is **None**, meaning the deviations are not normalized. However, enabling normalization (e.g., **Max-Min**) can improve the clarity of the indicator’s signals in volatile or choppy markets by smoothing out the noise.
Effect on performance: Using a normalization method can reduce the effect of extreme deviations, making signals more stable and less prone to false positives.
ATR+Order Block IndicatorThe ATR+Order Block Indicator is a unique and comprehensive tool designed to combine volatility-based analysis with key price action levels to provide traders with reliable entry and exit points. This indicator merges the Average True Range (ATR) for dynamic trailing stop calculation with order block detection to identify significant support and resistance zones on the chart. This combination offers traders a powerful blend of trend-following and price level analysis for improved trading decisions.
How the Components Work Together:
1. ATR-Based Trailing Stop:
• The Average True Range (ATR) is a widely used volatility indicator that measures the degree of price movement over a specified period. In this indicator, the ATR is used to create a trailing stop that dynamically adjusts to market conditions.
• How It Works: The ATR value is multiplied by a user-defined multiplier (ATR Multiplier) to set the distance of the trailing stop from the current price. This trailing stop moves with the price:
• If the price moves upwards, the trailing stop adjusts higher, ensuring it only moves in the direction of the trade.
• If the price moves downwards, the trailing stop adjusts lower accordingly.
• Purpose: This trailing stop helps traders manage risk by automatically adjusting to market volatility, ensuring that stops are not too tight in volatile conditions or too wide in quieter markets. It also helps lock in profits while maintaining a position in the market’s direction.
2. Order Block Detection:
• Order blocks are areas on the chart where significant buying (accumulation) or selling (distribution) has occurred. These zones often act as potential support or resistance levels due to the presence of unfilled buy or sell orders by large institutions or traders.
• How It Works: The indicator identifies the highest high (seller order block) and the lowest low (buyer order block) within a user-defined lookback period. These are plotted on the chart:
• Buyer Order Block: Represents a potential support area where buying interest is likely to reappear.
• Seller Order Block: Represents a potential resistance area where selling interest may reemerge.
• Purpose: By identifying these order blocks, traders can anticipate potential price reversals or continuations, aligning their trades with key market levels where significant buying or selling has occurred.
Justification for Combining These Components:
1. Enhanced Signal Accuracy and Context:
• The combination of ATR-based trailing stops with order block detection provides a dual-layered approach to trade decisions:
• ATR Trailing Stop offers trend-following signals based on volatility, helping traders capture market momentum.
• Order Blocks provide context to these signals by highlighting critical price levels where market participants have previously shown strong interest.
• This fusion allows traders to filter signals more effectively, ensuring trades are aligned with both market trends and key support/resistance zones.
2. Dynamic Risk Management:
• Using the ATR to set a dynamic trailing stop ensures that the stop-loss level adapts to the changing volatility of the market. When combined with order block detection, traders gain an additional layer of risk management:
• Stop Loss Placement: Traders can place stops just outside identified order blocks to protect against sudden price reversals while maintaining a tight stop aligned with current market volatility.
3. Reducing Market Noise and Avoiding False Signals:
• The indicator includes a mechanism to avoid repetitive signals, requiring a minimum gap between signals. This reduces noise and helps traders avoid multiple false entries in choppy market conditions.
• Order Blocks provide additional validation: For example, a buy signal generated near a Buyer Order Block carries more weight, as it aligns both with the ATR-based momentum and a key support area.
4. Improving Entry and Exit Strategies:
• Entry Points: The indicator generates buy (long) signals when the price crosses above the ATR trailing stop and sell (short) signals when it crosses below. These signals are enhanced by considering their proximity to order blocks, ensuring trades are initiated at strategic price levels.
• Exit Points: The ATR trailing stop provides a dynamic exit strategy, allowing trades to run while adjusting to market volatility. Traders can also use order blocks as targets or potential reversal points to exit trades.
5. Providing a Comprehensive Trading Tool:
• This indicator is unique in its integration of volatility and price level analysis, offering a well-rounded approach to trading. It combines the best of both worlds: trend-following momentum with the ATR and price action sensitivity through order blocks, making it suitable for different market conditions and trading styles.
How to Use the Indicator:
• Set the Parameters:
• Choose an ATR Period (default is 10) to define the number of bars for ATR calculation.
• Set the ATR Multiplier (default is 1.5) to adjust the sensitivity of the trailing stop.
• Define the Order Block Lookback Period (default is 20) to determine how many bars back the script will search for order blocks. Recommended 50.
• Interpret the Signals:
• BUY Signal: When the price crosses above the ATR trailing stop, indicating upward momentum. Confirm this signal by checking if it is near a Buyer Order Block.
• SELL Signal: When the price crosses below the ATR trailing stop, indicating downward momentum. Look for proximity to a Seller Order Block for added confidence.
• Monitor and Manage Trades:
• Use the ATR trailing stop for dynamic stop-loss placement.
• Watch for price action around the order blocks to make informed decisions about taking profits or cutting losses.
Conclusion:
The ATR+Order Block Indicator combines volatility and price action analysis in a unique way that offers traders a comprehensive tool for making informed trading decisions. By leveraging the strengths of both ATR-based dynamic stops and order block detection, it provides a balanced approach to trend-following and support/resistance trading, enhancing overall trading effectiveness and confidence.
Cumulative Net Money FlowDescription:
Dive into the financial depth of the markets with the "Cumulative Net Money Flow" indicator, designed to provide a comprehensive view of the monetary dynamics in trading. This tool is invaluable for traders and investors seeking to quantify the actual money entering or exiting the market over a specified period.
Features:
Value-Weighted Calculations: This indicator multiplies the trading volume by the price, offering a money flow perspective rather than just counting shares or contracts.
Custom Timeframe Adaptability: Adjust the timeframe to match your trading strategy, whether you are day trading, swing trading, or looking for longer-term trends.
Cumulative Insight: Tracks and accumulates net money flow to highlight overall market sentiment, making it easier to spot trends in capital movement.
Color-Coded Visualization: Displays positive money flow in green and negative money flow in red, providing clear, visual cues about market conditions.
Utility: "Cumulative Net Money Flow" is particularly effective in revealing the strength behind market movements. By understanding whether the money flow is predominantly buying or selling, traders can better align their strategies with market sentiment. This indicator is suited for various asset classes, including stocks, cryptocurrencies, and forex.
DEMA Adaptive DMI [BackQuant]DEMA Adaptive DMI
PLEASE Read the following, knowing what an indicator does at its core before adding it into a system is pivotal. The core concepts can allow you to include it in a logical and sound manner.
Conceptual Foundation and Innovation
The DEMA Adaptive DMI blends the Double Exponential Moving Average (DEMA) with the Directional Movement Index (DMI) to offer a unique approach to trend-following. By applying DEMA to the high and low prices, this indicator refines the traditional DMI calculation, enhancing its responsiveness to price changes. This results in a more adaptive and timely measure of market trends and momentum, providing traders with a more refined tool for capturing directional movements in the market.
Technical Composition and Calculation
At its core, the DEMA Adaptive DMI calculates the DEMA for both the high and low prices over a user-defined period. This dual application of DEMA serves to smooth out price fluctuations while retaining sensitivity to market movements. The DMI is then derived from the changes in these DEMA values, producing a set of plus and minus directional indicators that reflect the prevailing trend. Additionally, an Average Directional Index (ADX) is computed to measure the strength of the trend, with the entire process being dynamically adjusted based on the DEMA calculations.
DEMA Application:
The DEMA is applied to both high and low prices to reduce lag and provide a smoother representation of price action.
Directional Movement Calculation: The DMI is calculated using the smoothed price changes, resulting in plus and minus indicators that accurately reflect market trends.
ADX Calculation:
The ADX is computed to quantify the strength of the trend, offering traders insight into whether the market is trending strongly or is in a phase of consolidation.
Features and User Inputs The DEMA Adaptive DMI offers a range of customizable options to suit different trading styles and market conditions:
DEMA Calculation Period: Users can set the period for the DEMA calculation, allowing for adjustments based on the desired sensitivity.
DMI Length: The length of the DMI calculation can be adjusted, providing flexibility in how trends are measured.
ADX Smoothing Period: The smoothing period for the ADX can be customized to fine-tune the trend strength measurement.
Divergence Detection: Optional divergence detection features allow traders to spot potential reversals based on the DMI and price action.
Visualization options include static high and low levels to mark extreme DMI thresholds, the ability to color bars according to trend direction, and background hues to highlight overbought and oversold conditions.
Practical Applications
The DEMA Adaptive DMI is particularly effective in markets where trend strength and direction are crucial for successful trading. Traders can leverage this indicator to:
Identify Trend Reversals:
Detect potential trend reversals by monitoring the DMI and ADX in conjunction with divergence signals.
Trend Confirmation:
Use the DEMA-based DMI to confirm the strength and direction of a trend, aiding in the timing of entries and exits.
Strategic Positioning:
The indicator's responsiveness allows traders to position themselves effectively in fast-moving markets, reducing the risk of late entries or exits.
Advantages and Strategic Value
By integrating the DEMA with the DMI, this indicator provides a more adaptive and timely measure of market trends. The reduced lag from the DEMA ensures that traders receive signals that are closely aligned with current market conditions, while the dynamic DMI calculation offers a more accurate representation of trend direction and strength. This makes the DEMA Adaptive DMI a valuable tool for traders looking to enhance their trend-following strategies with a focus on precision and adaptability.
Summary and Usage Tips
The DEMA Adaptive DMI is a sophisticated trend-following indicator that combines the benefits of DEMA and DMI into a single, powerful tool. Traders are encouraged to incorporate this indicator into their trading systems for a more nuanced and responsive approach to trend detection and confirmation. Whether used for identifying trend reversals, confirming trend strength, or strategically positioning in the market, the DEMA Adaptive DMI offers a versatile and reliable solution for trend-following strategies.
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
Atlantean Bitcoin Weekly Market Condition - Top/Bottom BTC Overview:
The "Atlantean Bitcoin Weekly Market Condition Detector - Top/Bottom BTC" is a specialized TradingView indicator designed to identify significant turning points in the Bitcoin market on a weekly basis. By analyzing long-term and short-term moving averages across two distinct resolutions, this indicator provides traders with valuable insights into potential market bottoms and tops, as well as the initiation of bull markets.
Key Features:
Market Bottom Detection: The script uses a combination of a simple moving average (SMA) and an exponential moving average (EMA) calculated over long and short periods to identify potential market bottoms. When these conditions are met, the script signals a "Market Bottom" label on the chart, indicating a possible buying opportunity.
Bull Market Start Indicator: When the short-term EMA crosses above the long-term SMA, it signals the beginning of a bull market. This is marked by a "Bull Market Start" label on the chart, helping traders to prepare for potential market upswings.
Market Top Detection: The script identifies potential market tops by analyzing the crossunder of long and short-term moving averages. A "Market Top" label is plotted, suggesting a potential selling point.
Customizable Moving Averages Display: Users can choose to display the moving averages used for detecting market tops and bottoms, providing additional insights into market conditions.
How It Works: The indicator operates by monitoring the interactions between the specified moving averages:
Market Bottom: Detected when the long-term SMA (adjusted by a factor of 0.745) crosses over the short-term EMA.
Bull Market Start: Detected when the short-term EMA crosses above the long-term SMA.
Market Top: Detected when the long-term SMA (adjusted by a factor of 2) crosses under the short-term SMA.
These conditions are highlighted on the chart, allowing traders to visualize significant market events and make informed decisions.
Intended Use: This indicator is best used on weekly Bitcoin charts. It’s designed to provide long-term market insights rather than short-term trading signals. Traders can use this tool to identify strategic entry and exit points during major market cycles. The optional display of moving averages can further enhance understanding of market dynamics.
Originality and Utility: Unlike many other indicators, this script not only highlights traditional market tops and bottoms but also identifies the aggressive start of bull markets, offering a comprehensive view of market conditions. The unique combination of adjusted moving averages makes this script a valuable tool for long-term Bitcoin traders.
Disclaimer: The signals provided by this indicator are based on historical data and mathematical calculations. They do not guarantee future market performance. Traders should use this tool as part of a broader trading strategy and consider other factors before making trading decisions. Not financial advice.
Happy Trading!
By Atlantean
VS Dynamic Candle Replicator ProThe "VS Dynamic Candle Replicator Pro" is a powerful and flexible Pine Script™ indicator designed for traders who want to gain a better understanding of price action by replicating key candle movements across various timeframes. This indicator allows users to project the Open, High, Low, and Close of any candle from a selected timeframe onto the current chart, making it easy to compare candle dynamics, anticipate future price movements, and identify potential reversal or continuation points.
By visually projecting past candles from any timeframe and adjusting their properties such as color, size, and offset, traders can gain unique insights into market conditions. Whether you are a day trader or a swing trader, this tool offers an innovative way to visualize price patterns and make informed decisions.
Indicator Description:
The VS Dynamic Candle Replicator Pro dynamically replicates a selected timeframe's candle and overlays it on your current chart. This enables you to visually monitor how past candle characteristics influence the present market behavior.
This indicator is equipped with two main components:
Dynamic Candle Replicator:
This feature allows users to project a candle from a chosen timeframe onto the current chart. You can choose the candle’s position, appearance, and even toggle the visualization on or off. For example, you can project a daily candle onto a 15-minute chart and compare how intraday movements correspond to the daily range.
Previous Daily Candle Projection:
Users can also choose to display the previous daily candle (or any other timeframe) directly on the chart. This helps to see the momentum carried from the previous day and its impact on today’s price action.
Both of these components feature full customization of candle width, line width, and colors. Additionally, the indicator labels key price levels—Open, High, Low, and Close—so traders can clearly identify critical support and resistance levels.
Features & Settings:
1. Timeframe Selection:
Timeframe: Choose which timeframe’s candle you want to replicate. Options include anything from intraday periods (like 1 minute) to daily, weekly, or even monthly candles. This flexibility allows traders to seamlessly shift between different market perspectives.
2. Candle Offset & Sizing:
Offset (bars to the right): Control how many bars the replicated candle is shifted to the right. This is useful for visual clarity, allowing you to isolate the replicated candle from the current price action.
Candle Width & Line Width: Adjust the visual thickness of the candle body and the wicks for better visibility.
3. Candle Color Customization:
Bullish/Bearish Colors: Choose distinct colors for bullish and bearish candles. This visual cue makes it easier to distinguish market trends at a glance.
4. Projected Levels (Lines & Labels):
Dynamic labels and lines mark the Open, High, Low, and Close levels of the replicated candle. These are also fully customizable in terms of color, line style, and label positioning.
5. Vertical Offset:
Adjust the vertical positioning of labels for the price levels to prevent overlapping and ensure clarity on the chart.
6. Toggle Features:
Show or hide both the dynamic replicator candle and the previous daily candle at any time to declutter the chart when needed.
How to Use the VS Dynamic Candle Replicator Pro:
Select the Desired Timeframe:
Begin by choosing the timeframe for the candle you want to replicate. For example, if you want to observe the behavior of a daily candle on a 5-minute chart, set the timeframe to "1D".
Set the Offset and Size:
Customize the position of the replicated candle by adjusting the "Offset (bars to the right)" input. This ensures the replicated candle does not interfere with the current price action. You can also adjust the size of the candle body and wicks for optimal visibility.
Customize Colors:
Choose your preferred colors for bullish and bearish candles to quickly recognize the market sentiment represented by the replicated candle. This is particularly helpful for distinguishing between periods of upward and downward momentum.
Enable or Disable Features:
You can toggle the display of the dynamic replicator candle and the previous daily candle depending on what you want to focus on. This flexibility is useful for decluttering your chart when you need to focus on specific price patterns.
Observe Key Levels:
The indicator will project lines and labels marking the Open, High, Low, and Close of the selected timeframe candle. These key levels act as crucial support and resistance zones and provide insights into potential price reactions.
Monitor Price Action Around Replicated Candles:
Use the replicated candle as a reference to compare the current price action. This can be a helpful tool in identifying trends, spotting reversals, or confirming price breakouts.
Applications:
Day Trading: Overlay higher timeframe candles (such as daily or 4-hour candles) on shorter timeframes (e.g., 5-minute or 15-minute charts) to better understand the broader context and key levels.
Swing Trading: Visualize how daily or weekly candles align with intraday movements to make more informed decisions on trend continuations or reversals.
Key Level Identification: The projected Open, High, Low, and Close levels serve as important reference points for support and resistance, helping traders execute more precise entries and exits.
Conclusion:
The VS Dynamic Candle Replicator Pro is an innovative tool designed for traders who want to enhance their market analysis by comparing past and present price action in a visually intuitive manner. Its high level of customization and ease of use make it a valuable asset for traders of all experience levels. Whether you are looking to improve your understanding of market dynamics or refine your trading strategy, this indicator provides the necessary tools to gain a clearer perspective on price movements.
Embrace a smarter way of analyzing the market with the VS Dynamic Candle Replicator Pro and take your trading to the next level!
Multi-Step FlexiSuperTrend - Strategy [presentTrading]At the heart of this endeavor is a passion for continuous improvement in the art of trading
█ Introduction and How it is Different
The "Multi-Step FlexiSuperTrend - Strategy " is an advanced trading strategy that integrates the well-known SuperTrend indicator with a nuanced and dynamic approach to market trend analysis. Unlike conventional SuperTrend strategies that rely on static thresholds and fixed parameters, this strategy introduces multi-step take profit mechanisms that allow traders to capitalize on varying market conditions in a more controlled and systematic manner.
What sets this strategy apart is its ability to dynamically adjust to market volatility through the use of an incremental factor applied to the SuperTrend calculation. This adjustment ensures that the strategy remains responsive to both minor and major market shifts, providing a more accurate signal for entries and exits. Additionally, the integration of multi-step take profit levels offers traders the flexibility to scale out of positions, locking in profits progressively as the market moves in their favor.
BTC 6hr Long/Short Performance
█ Strategy, How it Works: Detailed Explanation
The Multi-Step FlexiSuperTrend strategy operates on the foundation of the SuperTrend indicator, but with several enhancements that make it more adaptable to varying market conditions. The key components of this strategy include the SuperTrend Polyfactor Oscillator, a dynamic normalization process, and multi-step take profit levels.
🔶 SuperTrend Polyfactor Oscillator
The SuperTrend Polyfactor Oscillator is the heart of this strategy. It is calculated by applying a series of SuperTrend calculations with varying factors, starting from a defined "Starting Factor" and incrementing by a specified "Increment Factor." The indicator length and the chosen price source (e.g., HLC3, HL2) are inputs to the oscillator.
The SuperTrend formula typically calculates an upper and lower band based on the average true range (ATR) and a multiplier (the factor). These bands determine the trend direction. In the FlexiSuperTrend strategy, the oscillator is enhanced by iteratively applying the SuperTrend calculation across different factors. The iterative process allows the strategy to capture both minor and significant trend changes.
For each iteration (indexed by `i`), the following calculations are performed:
1. ATR Calculation: The Average True Range (ATR) is calculated over the specified `indicatorLength`:
ATR_i = ATR(indicatorLength)
2. Upper and Lower Bands Calculation: The upper and lower bands are calculated using the ATR and the current factor:
Upper Band_i = hl2 + (ATR_i * Factor_i)
Lower Band_i = hl2 - (ATR_i * Factor_i)
Here, `Factor_i` starts from `startingFactor` and is incremented by `incrementFactor` in each iteration.
3. Trend Determination: The trend is determined by comparing the indicator source with the upper and lower bands:
Trend_i = 1 (uptrend) if IndicatorSource > Upper Band_i
Trend_i = 0 (downtrend) if IndicatorSource < Lower Band_i
Otherwise, the trend remains unchanged from the previous value.
4. Output Calculation: The output of each iteration is determined based on the trend:
Output_i = Lower Band_i if Trend_i = 1
Output_i = Upper Band_i if Trend_i = 0
This process is repeated for each iteration (from 0 to 19), creating a series of outputs that reflect different levels of trend sensitivity.
Local
🔶 Normalization Process
To make the oscillator values comparable across different market conditions, the deviations between the indicator source and the SuperTrend outputs are normalized. The normalization method can be one of the following:
1. Max-Min Normalization: The deviations are normalized based on the range of the deviations:
Normalized Value_i = (Deviation_i - Min Deviation) / (Max Deviation - Min Deviation)
2. Absolute Sum Normalization: The deviations are normalized based on the sum of absolute deviations:
Normalized Value_i = Deviation_i / Sum of Absolute Deviations
This normalization ensures that the oscillator values are within a consistent range, facilitating more reliable trend analysis.
For more details:
🔶 Multi-Step Take Profit Mechanism
One of the unique features of this strategy is the multi-step take profit mechanism. This allows traders to lock in profits at multiple levels as the market moves in their favor. The strategy uses three take profit levels, each defined as a percentage increase (for long trades) or decrease (for short trades) from the entry price.
1. First Take Profit Level: Calculated as a percentage increase/decrease from the entry price:
TP_Level1 = Entry Price * (1 + tp_level1 / 100) for long trades
TP_Level1 = Entry Price * (1 - tp_level1 / 100) for short trades
The strategy exits a portion of the position (defined by `tp_percent1`) when this level is reached.
2. Second Take Profit Level: Similar to the first level, but with a higher percentage:
TP_Level2 = Entry Price * (1 + tp_level2 / 100) for long trades
TP_Level2 = Entry Price * (1 - tp_level2 / 100) for short trades
The strategy exits another portion of the position (`tp_percent2`) at this level.
3. Third Take Profit Level: The final take profit level:
TP_Level3 = Entry Price * (1 + tp_level3 / 100) for long trades
TP_Level3 = Entry Price * (1 - tp_level3 / 100) for short trades
The remaining portion of the position (`tp_percent3`) is exited at this level.
This multi-step approach provides a balance between securing profits and allowing the remaining position to benefit from continued favorable market movement.
█ Trade Direction
The strategy allows traders to specify the trade direction through the `tradeDirection` input. The options are:
1. Both: The strategy will take both long and short positions based on the entry signals.
2. Long: The strategy will only take long positions.
3. Short: The strategy will only take short positions.
This flexibility enables traders to tailor the strategy to their market outlook or current trend analysis.
█ Usage
To use the Multi-Step FlexiSuperTrend strategy, traders need to set the input parameters according to their trading style and market conditions. The strategy is designed for versatility, allowing for various market environments, including trending and ranging markets.
Traders can also adjust the multi-step take profit levels and percentages to match their risk management and profit-taking preferences. For example, in highly volatile markets, traders might set wider take profit levels with smaller percentages at each level to capture larger price movements.
The normalization method and the incremental factor can be fine-tuned to adjust the sensitivity of the SuperTrend Polyfactor Oscillator, making the strategy more responsive to minor market shifts or more focused on significant trends.
█ Default Settings
The default settings of the strategy are carefully chosen to provide a balanced approach between risk management and profit potential. Here is a breakdown of the default settings and their effects on performance:
1. Indicator Length (10): This parameter controls the lookback period for the ATR calculation. A shorter length makes the strategy more sensitive to recent price movements, potentially generating more signals. A longer length smooths out the ATR, reducing sensitivity but filtering out noise.
2. Starting Factor (0.618): This is the initial multiplier used in the SuperTrend calculation. A lower starting factor makes the SuperTrend bands closer to the price, generating more frequent trend changes. A higher starting factor places the bands further away, filtering out minor fluctuations.
3. Increment Factor (0.382): This parameter controls how much the factor increases with each iteration of the SuperTrend calculation. A smaller increment factor results in more gradual changes in sensitivity, while a larger increment factor creates a wider range of sensitivity across the iterations.
4. Normalization Method (None): The default is no normalization, meaning the raw deviations are used. Normalization methods like Max-Min or Absolute Sum can make the deviations more consistent across different market conditions, improving the reliability of the oscillator.
5. Take Profit Levels (2%, 8%, 18%): These levels define the thresholds for exiting portions of the position. Lower levels (e.g., 2%) capture smaller profits quickly, while higher levels (e.g., 18%) allow positions to run longer for more significant gains.
6. Take Profit Percentages (30%, 20%, 15%): These percentages determine how much of the position is exited at each take profit level. A higher percentage at the first level locks in more profit early, reducing exposure to market reversals. Lower percentages at higher levels allow for a portion of the position to benefit from extended trends.
Market Structure Based Stop LossMarket Structure Based Dynamic Stop Loss
Introduction
The Market Structure Based Stop Loss indicator is a strategic tool for traders designed to be useful in both rigorous backtesting and live testing, by providing an objective, “guess-free” stop loss level. This indicator dynamically plots suggested stop loss levels based on market structure, and the concepts of “interim lows/highs.”
It provides a robust framework for managing risk in both long and short positions. By leveraging historical price movements and real time market dynamics, this indicator helps traders identify quantitatively consistent risk levels while optimizing trade returns.
Legend
This indicator utilizes various inputs to customize its functionality, including "Stop Loss Sensitivity" and "Wick Depth," which dictate how closely the stop loss levels hug the price's highs and lows. The stop loss levels are plotted as lines on the trading chart, providing clear visual cues for position management. As seen in the chart below, this indicator dynamically plots stop loss levels for both long and short positions at every point in time.
A “Stop Loss Table” is also included, in order to enhance precision trading and increase backtesting accuracy. It is customizable in both size and positioning.
Case Study
Methodology
The methodology behind this indicator focuses on the precision placement of stop losses using market structure as a guide. It calculates stop losses by identifying the "lowest close" and the corresponding "lowest low" for long setups, and inversely for short setups. By adjusting the sensitivity settings, traders can tweak the indicator's responsiveness to price changes, ensuring that the stop losses are set with a balance between tight risk control and enough room to avoid premature exits due to market noise. The indicator's ability to adapt to different trading styles and time frames makes it an essential tool for traders aiming for efficiency and effectiveness in their risk management strategies.
An important point to make is the fact that the stop loss levels are always placed within the wicks. This is important to avoid what can be described as a “floating stop loss”. A stop loss placed outside of a wick is susceptible to an outsized degree of slippage. This is because traders always cluster their stop losses at high/low wicks, and a stop loss placed outside of this level will inevitably be caught in a low liquidity cascade or “wash-out.” When price approaches a cluster of stop losses, it is highly probable that you will be stopped out anyway, so it is prudent to attempt to be the trader who gets stopped out first in order to avoid high slippage, and losses above what you originally intended.
// For long positions: stop-loss is slightly inside the lowest wick
float dynamic_SL_Long = lowestClose - (lowestClose - lowestLow) * (1 - WickDepth)
// For short positions: stop-loss is slightly inside the highest wick
float dynamic_SL_Short = highestClose + (highestHigh - highestClose) * (1 - WickDepth)
The percentage depth of the wick in which the stop loss is placed is customisable with the “Wick Depth” variable, in order to customize stop loss strategies around the liquidity of the market a trader is executing their orders in.
PUMP IndicatorsPUMP Indicator Description
★ Supported Markets and Assets
The PUMP indicator is a versatile tool that can be effectively applied to various markets and assets, including:
▶ Korean Stocks: KOSPI, KOSDAQ, etc.
▶ U.S. Stocks: NYSE, NASDAQ, etc.
▶ Cryptocurrencies: Major cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), etc.
▶ Futures: Major futures contracts like gold, silver, crude oil, etc.
▶ ETFs: SPY, QQQ, etc.
★ Indicator Description
The PUMP indicator is designed to analyze price divergence and volatility.
It is provided with minimal representation on the chart, allowing users to use it in conjunction with other indicators, such as classical RSI, TRIX, CCI, ADX, BWI, Bollinger Bands, etc.
Everything displayed on the chart can be turned on or off in the options, allowing users to customize their setup.
The PUMP indicator is based on the concept of the MACD indicator, which calculates the difference between the leading line and the lagging line to generate signals.
GOOD, UP, and CR signals predict price increases.
DOWN and BAD signals predict price decreases.
WARN emphasizes that the buy position is not certain, regardless of price increases or decreases.
Therefore, the PUMP indicator is good to use with other indicators. It visually displays divergence and volatility signals along with the MACD movements below, and users can receive alerts for movements in their interested stocks using the alarm function.
It can be used as an indicator for viewing buy and sell signals, as well as predicting the price flow.
▶ (Drawback) Unlike typical TRIX, RSI, TRIX, CCI, ADX, BWI indicators, which are implemented in a new lower window, the PUMP indicator displays both signals and the leading and lagging lines simultaneously, so it is not implemented in a new window, meaning the baseline may vary depending on the daily chart appearance.
★ The PUMP indicator consists of the following components:
▶ PUMP Indicator Leading and Lagging Lines
PUMP t: Leading line (yellow)
PUMP p: Lagging line (blue)
The MACD displayed at the bottom of the chart calculates the divergence between the PUMP t leading line and the PUMP p lagging line.
▶ EA Formula
The core calculation of the PUMP indicator is as follows:
EA (Exponential Average): 100 * (eavg1 / eavg2)
Where eavg1 is the short-term EMA, and eavg2 is the long-term EMA.
It calculates the divergence of the index.
▶ The PUMP indicator is a fixed indicator (cannot be arbitrarily modified).
▶ Highlights: The method of calculating the interval or number of uses is an important part of the index calculation and is therefore private.
★ Signal Description
The PUMP indicator provides a total of six major signals:
▶ UP Signal: Occurs when the divergence between the MACD PUMP t leading line and PUMP p lagging line narrows, and the divergence of the exponential moving average widens compared to before.
▶ DOWN Signal: Occurs when the MACD PUMP t leading line crosses above the PUMP p lagging line.
▶ GOOD Signal: Represents an UP signal with added volume.
(The GOOD signal is not necessarily better than the UP signal. If a GOOD signal appears in a stock that has sufficiently fallen in price, it helps understand that a rebound has started. Therefore, the GOOD signal is made to find a rebound in stocks that have continuously declined, rather than finding signals in consistently rising prices.)
▶ BAD Signal: Occurs when the PUMP t leading line crosses above the 0 baseline, indicating a potential sell signal.
▶ WARN Signal: A warning signal occurring at high levels, indicating that buying is not recommended (regardless of buy or sell).
▶ CR Signal: Occurs in all sections where the PUMP t leading line crosses below the PUMP p lagging line.
★ Lower MACD Horizontal Baseline
The PUMP indicator provides three horizontal baselines from the MACD indicator for additional analysis:
▶ Pump H
▶ PUMP M
▶ PUMP L
It visually provides the divergence of the lower MACD indicator for rising and falling changes, with the default set to 0, and users can change the numbers in the options as needed.
★ Moving Averages
The PUMP indicator provides three basic moving averages:
▶ Buzz 7: 7-day moving average
▶ Buzz 26: 26-day moving average
▶ Buzz 120: 120-day moving average
The number of moving averages is fixed, but users can use them in conjunction with the moving averages provided by TradingView as needed.
★ Alert Function
Using the Alert function of TradingView, you can set alerts for various signals generated by the PUMP indicator.
▶ GOOD Signal Alert
▶ UP Signal Alert
▶ CR Signal Alert
▶ DOWN Signal Alert
▶ BAD Signal Alert
▶ WARN Signal Alert
★ Usage
1. The PUMP indicator is not focused on buy and sell signals but calculates the current price movement and divergence and is designed to express it through MACD leading and lagging lines and signals.
2. The PUMP indicator can be used alone or in conjunction with other indicators for technical analysis.
3. You can analyze buy and sell using the signals of the PUMP indicator along with fundamental analysis, such as news, issues, national policies, company profits, and sales increases.
4. The MACD leading and lagging lines at the bottom of the chart move inversely to the price, ensuring that the PUMP indicator does not interfere when used with other indicators.
5. You can receive real-time alerts using the alarm function.
Below, we attach pictures to help users understand.
============================================
PUMP 인디케이터 설명(한글)
★ 지원되는 시장 및 자산
PUMP 표시기는 다음과 같은 다양한 시장 및 자산에 효과적으로 적용할 수 있는 다용도 도구입니다:
▶ 한국주식: KOSPI, KOSDAQ 등.
▶ 미국주식: NYSE, NASDAQ 등.
▶ 암호화폐: 비트코인(BTC), 이더리움(ETH) 등 주요 암호화폐.
▶ 선물 : 금, 은, 원유 등 주요 선물 계약.
▶ 상장지수펀드(ETF) : SPY, QQQ 등.
★ 지표 설명
PUMP 지표는 가격 이격과 변동성을 분석하도록 설계되었습니다.
사용자가 만든 지표 또는 고전 RSI, TRIX, CCI, ADX, BWI, Bollinger Bands 등과 함께 사용할 수 있게 차트에 최소한의 표현으로 제공됩니다.
그리고 차트에 표현되는 모든 것들을 옵션에서 on / off 가능하게 하였기에 사용자가 커스텀 할 수 있게 하였습니다.
PUMP 지표 신호를 생성하기 위해 선행 라인과 후행 라인 간의 차이를 계산하는 MACD 지표의 개념을 기반으로 합니다.
GOOD, UP, CR 신호는 가격 상승을 예측합니다.
DOWN, BAD 신호는 가격 하락을 예측합니다.
WARN은 가격 상승과 하락에 관계없이, 매수 자리는 확실히 아님을 강조한 신호입니다.
그러므로 PUMP 지표는 다른 지표와 함께 사용하기 좋고, 이격과 변동성을 신호와 하단 MACD 움직임을 눈으로 볼 수 있으며, 알람 기능을 활용하여 관심 있는 종목의 움직임을 알람으로 받아 볼 수 있는 지표입니다.
매수와 매도를 보는 지표로 사용할 수 있으며, 가격의 흐름을 예상하는 지표로 사용할 수 있습니다.
▶ (단점) 보통의 TRIX, RSI, TRIX, CCI, ADX, BWI 지표들은 하단의 새로운 창에서 구현됩니다. 하지만 PUMP 지표는 신호와 하단 선행과 후행을 동시에 표현하기 때문에 새로운 창에서 구현되지 않기에 기준 축이 일봉의 모습에 따라 달라질 수 있습니다.
★ PUMP 지표는 다음과 같은 구성요소로 구성됩니다
▶ PUMP 지표 선행과 후행
PUMP t : 선행라인 (노란색)
PUMP p : 후행라인 (파란색)
차트 하단에 나타나는 MACD는 PUMP t선행라인과 PUMP p 후행라인의 이격도를 계산합니다.
▶ EA공식
PUMP 지표의 핵심 계산식은 다음과 같습니다:
EA(지수평균): 100 * (eavg1 / eavg2)
여기서 eavg1은 단기 EMA이고 eavg2는 장기 EMA입니다.
지수의 이격도를 계산합니다.
▶ PUMP 지표는 고정 지표입니다. (임의 수정 불가)
▶ 강조 : 이격의 계산법이나 사용하는 숫자는 지표 계산의 중요한 부분이므로 비공개입니다.
★ 신호 설명
PUMP 표시등은 총 6개의 주요 신호를 제공합니다:
▶ UP 신호: MACD PUMP t 선행과 PUMP p 후행의 이격이 줄어들 때, 지수 이동 평균의 이격도가 이전 보다 넓어지면 발생합니다.
▶ DOWN 신호: MACD PUMP t 선행이 PUMP p 후행을 상향 교차할 때 발생합니다.
▶ GOOD 신호: 거래량이 추가된 UP 신호를 나타냅니다.
(GOOD 신호가 UP 신호보다 좋다기 보다, 충분히 가격 하락한 종목에서 GOOD 신호가 나온다면 반등이 시작되는 것을 이해할 수 있게 만든 지표입니다. 그러므로 GOOD 신호는 가격이 꾸준히 상승하는 곳에서 신호를 찾기보다, 지속 하락하다 반등을 찾는 신호로 만들었습니다.)
▶ BAD 신호: PUMP t 선행이 0 기준선 이상으로 교차할 때 발생하며, 이는 잠재적인 판매 신호를 나타냅니다.
▶ 경고 신호: 높은 수준에서 발생하는 경고 신호로, 매수가 권장되지 않음을 나타냅니다(매수, 매도와 무관함).
▶ CR 신호: PUMP t 선행 라인이 PUMP p 후행 라인 아래로 교차하는 모든 구간에서 발생합니다.
★ 하단 MACD 가로 기준선
PUMP 표시기는 추가 분석을 위해 MACD 지표에서 3가지 가로 기준을 제공합니다:
▶ pump H
▶ PUMP M
▶ PUMP L
하단의 MACD 지표의 이격도를 상승 및 하강의 변화를 시각적으로 기준을 만들 수 있게 제공하며, 기본은 0으로 제공하고, 사용자의 필요에 따라 옵션에서 숫자를 변경할 수 있게 하였습니다.
★ 이동 평균
PUMP 표시기는 세 가지 기본 이동 평균을 제공 합니다:
▶ Buzz 7: 7일 이동 평균
▶ Buzz 26: 26일 이동 평균
▶ Buzz 120 : 120일 이동 평균
이동 평균의 수는 고정되어 있지만, 사용자는 필요에 따라 TradingView에서 제공하는 이동 평균과 함께 사용할 수 있습니다.
★ 알림 기능
TradingView의 Alert 기능을 사용하여 PUMP 지표 생성되는 다양한 신호에 대한 Alert를 설정할 수 있습니다.
▶ GOOD 신호 알림
▶ UP 신호 알림
▶ CR 신호 알림
▶ DOWN 신호 알림
▶ BAD 신호 알림
▶ WARN 신호 알림
★ 사용법
1.PUMP 지표는 매수와 매도에 중점을 둔 지표가 아니며 현재 가격의 움직임과 이격도를 계산하며 MACD 선행과 후행 그리고 신호로 표현하기 위해 만들어진 지표입니다.
2. PUMP 지표는 단일로 사용할 수 있고, 또는 다른 지표와 함께 기술적분석으로 사용할 수 있습니다.
3. 뉴스와 이슈, 국가의 정책, 회사의 이익, 매출의 상승 등 기본적분석과 함께 PUMP 지표의 신호를 이용하여 매수와 매도 분석을 할 수 있습니다.
4. 차트 하단의 MACD 선행과 후행은 가격의 움직임을 반대로 움직이며, 가격과 반대로 움직이게 함으로써 다른 지표와 함께 사용하였을 때, PUMP 지표가 방해가 되지 않게 하였습니다.
5. 알람을 사용하여 실시간으로 알람을 받아 보실 수 있습니다.
아래 사진을 첨부하여 사용자 이해를 돕습니다.
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UP신호는 이격을
▶ The UP signal indicates horizontal divergence.
CR신호는 선행이 후행을 아래로 돌파
▶ The CR signal indicates vertical divergence when the leading line crosses below the lagging line.
WARN 신호를 확인
▶ Check the WARN signal.
BAD와 DOWN 신호
▶ BAD and DOWN signals.
PUMP 지표의 기준 3개
3 criteria for PUMP indicators
따로 그림을 그리지 않은 차트
▶ A chart without separate drawings.
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다른 지표와 + 조합
+ Combination with other indicators
[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.
CryptoLibrary "Crypto"
This Library includes functions related to crytocurrencies and their blockchain
btcBlockReward(t)
Delivers the BTC block reward for a specific date/time
Parameters:
t (int) : Time of the current candle
Returns: blockRewardBtc
ATH/ATL Tracker [LuxAlgo]The ATH/ATL Tracker effectively displays changes made between new All-Time Highs (ATH)/All-Time Lows (ATL) and their previous respective values, over the entire history of available data.
The indicator shows a histogram of the change between a new ATH/ATL and its respective preceding ATH/ATL. A tooltip showing the price made during a new ATH/ATL alongside its date is included.
🔶 USAGE
By tracking the change between new ATHs/ATLs and older ATHs/ATLs, traders can gain insight into market sentiment, breadth, and rotation.
If many stocks are consistently setting new ATHs and the number of new ATHs is increasing relative to old ATHs, it could indicate broad market participation in a rally. If only a few stocks are reaching new ATHs or the number is declining, it might signal that the market's upward momentum is decreasing.
A significant increase in new ATHs suggests optimism and willingness among investors to buy at higher prices, which could be considered a positive sentiment. On the other hand, a decrease or lack of new ATHs might indicate caution or pessimism.
By observing the sectors where stocks are consistently setting new ATHs, users can identify which sectors are leading the market. Sectors with few or no new ATHs may be losing momentum and could be identified as lagging behind the overall market sentiment.
🔶 DETAILS
The indicator's main display is a histogram-style readout that displays the change in price from older ATH/ATLs to Newer/Current ATH/ATLs. This change is determined by the distance that the current values have overtaken the previous values, resulting in the displayed data.
The largest changes in ATH/ATLs from the ticker's history will appear as the largest bars in the display.
The most recent bars (depending on the selected display setting) will always represent the current ATH or ATL values.
When determining ATH & ATL values, it is important to filter out insignificant highs and lows that may happen constantly when exploring higher and lower prices. To combat this, the indicator looks to a higher timeframe than your chart's timeframe in order to determine these more significant ATHs & ATLs.
For Example: If a user was on a 1-minute chart and 5 highs-new highs occur across 5 adjacent bars, this has the potential to show up as 5 new ATHs. When looking at a higher timeframe, 5 minutes, only the highest of the 5 bars will indicate a new ATH. To assist with this, the indicator will display warnings in the dashboard when a suboptimal timeframe is selected as input.
🔹 Dashboard
The dashboard displays averages from the ATH/ATL data to aid in the anticipation and expectations for new ATH/ATLs.
The average duration is an average of the time between each new ATH/ATL, in this indicator it is calculated in "Days" to provide a more comprehensive understanding.
The average change is the average of all change data displayed in the histogram.
🔶 SETTINGS
Duration: The designated higher timeframe to use for filtering out insignificant ATHs & ATLs.
Order: The display order for the ATH/ATL Bars, Options are to display in chronological (oldest to newest) or reverse chronological order (newest to oldest).
Bar Width: Sets the width for each ATH/ATL bar.
Bar Spacing: Sets the # of empty bars in between each ATH/ATL bar.
Dashboard Settings: Parameters for the dashboard's size and location on the chart.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
Bitcoin Futures vs. Spot Tri-Frame - Strategy [presentTrading]Prove idea with a backtest is always true for trading.
I developed and open-sourced it as an educational material for crypto traders to understand that the futures and spot spread may be effective but not be as effective as they might think. It serves as an indicator of sentiment rather than a reliable predictor of market trends over certain periods. It is better suited for specific trading environments, which require further research.
█ Introduction and How it is Different
The "Bitcoin Futures vs. Spot Tri-Frame Strategy" utilizes three different timeframes to calculate the Z-Score of the spread between BTC futures and spot prices on Binance and OKX exchanges. The strategy executes long or short trades based on composite Z-Score conditions across the three timeframes.
The spread refers to the difference in price between BTC futures and BTC spot prices, calculated by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges.
BTCUSD 1D L/S Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Spread
The spread is the difference in price between BTC futures and BTC spot prices. The strategy calculates the spread by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges. This spread serves as the primary metric for identifying trading opportunities.
Spread = Weighted Average Futures Price - Weighted Average Spot Price
🔶 Z-Score Calculation
The Z-Score measures how many standard deviations the current spread is from its historical mean. This is calculated for each timeframe as follows:
Spread Mean_tf = SMA(Spread_tf, longTermSMA)
Spread StdDev_tf = STDEV(Spread_tf, longTermSMA)
Z-Score_tf = (Spread_tf - Spread Mean_tf) / Spread StdDev_tf
Local performance
🔶 Composite Entry Conditions
The strategy triggers long and short entries based on composite Z-Score conditions across all three timeframes:
- Long Condition: All three Z-Scores must be greater than the long entry threshold.
Long Condition = (Z-Score_tf1 > zScoreLongEntryThreshold) and (Z-Score_tf2 > zScoreLongEntryThreshold) and (Z-Score_tf3 > zScoreLongEntryThreshold)
- Short Condition: All three Z-Scores must be less than the short entry threshold.
Short Condition = (Z-Score_tf1 < zScoreShortEntryThreshold) and (Z-Score_tf2 < zScoreShortEntryThreshold) and (Z-Score_tf3 < zScoreShortEntryThreshold)
█ Trade Direction
The strategy allows the user to specify the trading direction:
- Long: Only long trades are executed.
- Short: Only short trades are executed.
- Both: Both long and short trades are executed based on the Z-Score conditions.
█ Usage
The strategy can be applied to BTC or Crypto trading on major exchanges like Binance and OKX. By leveraging discrepancies between futures and spot prices, traders can exploit market inefficiencies. This strategy is suitable for traders who prefer a statistical approach and want to diversify their timeframes to validate signals.
█ Default Settings
- Input TF 1 (60 minutes): Sets the first timeframe for Z-Score calculation.
- Input TF 2 (120 minutes): Sets the second timeframe for Z-Score calculation.
- Input TF 3 (180 minutes): Sets the third timeframe for Z-Score calculation.
- Long Entry Z-Score Threshold (3): Defines the threshold above which a long trade is triggered.
- Short Entry Z-Score Threshold (-3): Defines the threshold below which a short trade is triggered.
- Long-Term SMA Period (100): The period used to calculate the simple moving average for the spread.
- Use Hold Days (true): Enables holding trades for a specified number of days.
- Hold Days (5): Number of days to hold the trade before exiting.
- TPSL Condition (None): Defines the conditions for taking profit and stop loss.
- Take Profit (%) (30.0): The percentage at which the trade will take profit.
- Stop Loss (%) (20.0): The percentage at which the trade will stop loss.
By fine-tuning these settings, traders can optimize the strategy to suit their risk tolerance and trading style, enhancing overall performance.
Multi ETH Rolling APY Calculator [presentTrading]This one is for SEC paves way for Ethereum ETFs in boost for crypto!
█ Introduction and How it is Different
The "Multi ETH Rolling APY Calculator" is a sophisticated Pine Script tool designed to analyze the annualized difference between Ethereum (ETH) spot and futures prices. This tool is essential for identifying arbitrage opportunities and assessing market sentiment, offering traders invaluable insights into market dynamics. By calculating the premium or discount of futures contracts relative to the spot price and annualizing this figure based on the time until each contract's expiration, the Multi ETH Rolling APY Calculator provides a clear view of potential profit margins and market trends.
Unlike traditional trading indicators that focus solely on price movements or technical patterns, this calculator delves deeper into the futures market, providing a dual-purpose tool. It not only helps in spotting arbitrage opportunities but also serves as a gauge for the emotional state of the market, thereby offering a more comprehensive analysis of market conditions. This dual functionality sets it apart, making it a must-have for traders looking to navigate the volatile cryptocurrency trading landscape effectively.
Historical backtesting has revealed that Bitcoin's Rolling APY can serve as a robust indicator of market sentiment:
- Below 0%: Often indicates panic or 'end-of-world' scenarios.
- 0-5%: Signifies extreme market fear.
- 5-10%: Reflects a calm market environment.
- 10-15%: Suggests a moderately warm market.
- 15-20%: Indicates an overheated market.
- **Above 20%: Signals FOMO (fear of missing out).
█ Strategy, How it Works: Detailed Explanation
The Multi ETH Rolling APY Calculator employs a systematic approach to derive its insights. The process is broken down into several steps, each contributing to the overall analysis:
🔶 Data Fetching: The script first fetches the necessary data, including the closing prices of Ethereum's spot market and selected futures contracts. These futures contracts are typically set to expire at different dates, providing a broad perspective on market expectations over time.
🔶 Time and Expiration: The tool takes into account the current time and the expiration dates of the futures contracts. This helps in calculating the number of days remaining until each contract's expiration.
🔶 Premium Calculations: The premium or discount of each futures contract relative to the spot price is computed. This is done by subtracting the spot price from the futures price and then dividing the result by the spot price. This calculation gives a percentage that represents the premium or discount.
🔶 Annualized Percentage Yield (APY) Calculations: The calculated premium or discount is then annualized based on the number of days remaining until the contract's expiration. This involves multiplying the premium or discount by the factor (365 / days remaining) to annualize the figure. If the user chooses not to annualize the numbers, this step is skipped.
🔶 Plotting Results: The annualized yields are then plotted on a chart, allowing traders to visualize the potential returns from different futures contracts. The plots are color-coded for easy differentiation and quick analysis.
By following this structured approach, the Multi ETH Rolling APY Calculator provides traders with clear, actionable insights into market dynamics and potential arbitrage opportunities.
█ Trade Direction
While this tool does not provide direct trading signals, it informs traders about potential arbitrage opportunities and the prevailing market sentiment. Traders can leverage this data to make strategic decisions, aligning long or short positions with the anticipated market movements and arbitrage conditions.
█ Usage
By inputting specific parameters related to their market analysis, traders can monitor discrepancies in Bitcoin’s pricing across different timelines, which is especially beneficial for those involved in derivatives trading, arbitrage, and sentiment analysis.
█ Default Settings
- Resolution: Controls the frequency of data (default is daily).
- Show numbers in annual: Determines whether APY is displayed on an annual basis.
- Base Symbol and Future Symbols: Specify the spot and futures markets for analysis.
