3 Standard Deviation Setup on Micro 10-Year Yield FuturesIntroduction
The Micro 10-Year Yield Futures contract has caught the attention of many traders recently, as its price action reached the upper 3 standard deviation of the Bollinger Band® in the daily time frame. This rare occurrence presents a potential mean reversion setup, where the price could revert back toward its historical average.
This article explores what mean reversion is, why it matters in trading, and how the 3 standard deviation Bollinger Bands® setup may indicate an opportunity to short this market. We’ll also discuss key price levels, contract specifications, and a potential trade setup for shorting Micro 10-Year Yield Futures.
What is Mean Reversion in Trading?
Mean reversion is a trading concept based on the idea that asset prices fluctuate around a central value or mean over time. When prices move too far away from this mean, they often correct or revert back toward that average. This is particularly useful in markets that experience high volatility or extreme price movements, as those extremes tend to reverse at some point.
In simple terms, mean reversion strategies involve selling (or shorting) assets when they are significantly above their historical average, with the expectation that prices will return to normal levels. Conversely, buying when prices are significantly below the mean can also be a valid strategy.
The 3 Standard Deviation Bollinger Band® Setup
Bollinger Bands® are a popular technical indicator used to measure volatility and price extremes. The bands are plotted a certain number of standard deviations away from a moving average. The further away prices move from the average, the more extreme the movement.
Reaching the upper 3 standard deviation Bollinger Band® is a rare occurrence that suggests extreme overbought conditions. Historically, when an asset reaches this level, the likelihood of a price pullback increases, as market participants may see it as an unsustainable level. In the case of Micro 10-Year Yield Futures, the recent rally has pushed prices to this rare zone, setting the scene for a potential mean reversion.
Key Price Levels and Resistance Zones
As the Micro 10-Year Yield Futures price approaches extreme levels, there are two key resistance zones which traders should be aware of: 4.174-4.021. These levels represent areas where selling pressure might intensify, pushing prices down and aiding in the mean reversion process.
Traders looking to capitalize on this potential mean reversion setup can consider initiating short positions within this resistance range. These resistance zones act as psychological and technical barriers, providing an opportunity for traders to place their entries. Additionally, these levels help to manage risk, as they define a clear area to set stop-loss orders just above the upper resistance.
Contract Specifications and Margin Requirements
Understanding the specifications of the Micro 10-Year Yield Futures contract is crucial for traders looking to execute any trade. Here are some of the key details:
Tick Size: The minimum price fluctuation is 0.001, which equates to $1 per tick.
Margin Requirements: Margin requirements vary. Currently, the initial margin for Micro Yield Futures is around $320 per contract, making it accessible to a wide range of traders. Check with your broker for specific margin amounts.
This knowledge is essential in calculating potential profit and loss in dollar terms, as well as determining the appropriate position size based on your available margin.
Trade Setup Example
Let’s now move on to a practical trade setup based on the discussed conditions.
Entry Point: Shorting Micro 10-Year Yield Futures within the resistance range between 4.174 and 4.021.
Stop Loss: A stop should be placed just above the upper resistance, say around 4.175, to protect against further price appreciation.
Target: The target for this mean reversion trade would be around the mean of 3.750, where prices are expected to revert based on historical behavior.
Reward-to-Risk Calculation:
If a short entry is made at 4.021, with a stop at 4.175 (154 basis points risk) and a target at 3.750 (271 ticks potential gain), the reward-to-risk ratio would be approximately 1.76:1. A higher entry point closer to the upper resistance at 4.174 would significantly improve the reward-to-risk ratio, but it also increases the likelihood of missing the entry if the market reverses before reaching that level.
In dollar terms, each tick (0.001) is worth $1, so the 154-tick stop loss represents a risk of $154 loss per contract, while the potential reward of 271 ticks equates to $271 worth of gains per contract.
Risk Management Considerations
Risk management is a critical aspect of any trading strategy, especially in futures trading. While the 3 standard deviation Bollinger Band® setup provides a compelling case for mean reversion, it's essential to manage risk carefully to avoid significant losses.
Stop-Loss Orders: A well-placed stop-loss is crucial to protect against unexpected market moves. In this case, placing the stop above the resistance zone (around 4.175) ensures that risk is controlled if the market continues to rally instead of reversing.
Position Sizing: Given the volatility of futures contracts, it is important to adjust position sizes according to the trader’s risk tolerance and available margin. Overleveraging can lead to large losses if the market moves against the trade.
Moving Averages Can Shift: It’s important to remember that the moving average (the mean) can change as new data comes in. While the target is currently around 3.744, this level may adjust over time, so traders need to monitor the mean as the trade progresses (which is why we have set the target to initially be slightly higher at 3.750).
Resistances as Reinforcements: The resistance zone between 4.174 and 4.021 can act as reinforcements to the mean reversion. Traders should observe price behavior at these levels to confirm rejection signals before entering the trade.
Conclusion
In conclusion, the Micro 10-Year Yield Futures contract presents a unique trading opportunity as it has reached the rare 3 standard deviation Bollinger Band® on the daily time frame. This extreme price level indicates potential overbought conditions, making it a candidate for mean reversion back to the mean at approximately 3.750.
The trade setup involves shorting within the resistance range, with a well-defined stop and target, and offers a favorable reward-to-risk ratio. However, as always, caution is advised, and traders should manage risk effectively using stop-loss orders and appropriate position sizing.
When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com - This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies.
General Disclaimer:
The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
Meanreversion
Zero Spread Milestone: Strategic Trade in Micro Yield FuturesIntroduction
The current market scenario presents a unique potential opportunity in the yield spread between Micro 10-Year Yield Futures (10Y1!) and Micro 2-Year Yield Futures (2YY1!). This spread is reaching a critical price point of zero, likely acting as a strong resistance. Such a rare situation opens the door for a strategic trading opportunity where traders can consider shorting the Micro 10-Year Yield Futures and buying the Micro 2-Year Yield Futures.
In TradingView, this spread is visualized using the symbol 10Y1!-CBOT_MINI:2YY1!. The combination of technical indicators suggests a mean reversion trade setup, making this a compelling moment for traders to act on such a potential opportunity. The alignment of overbought signals from Bollinger Bands® and the RSI indicator further strengthens the case for a reversal, presenting an intriguing setup for informed traders.
All of this is following last Wednesday, July 31, 2024, when the FED reported their decision related to interest rates where they left them unchanged, adding further context to the current market dynamics.
Yield Futures Contract Specifications
Micro 10-Year Yield Futures (10Y1!):
Price Quotation: Quoted in yield with a minimum fluctuation of 0.001 Index points (1/10th basis point per annum).
Tick Value: Each tick is worth $1.
Margin Requirements: Approximately $320 per contract (subject to change based on market conditions).
Micro 2-Year Yield Futures (2YY1!):
Price Quotation: Quoted in yield with a minimum fluctuation of 0.001 Index points (1/10th basis point per annum).
Tick Value: Each tick is worth $1.
Margin Requirements: Approximately $330 per contract (subject to change based on market conditions).
Margin Requirements:
The margin requirements for these contracts are relatively low, making them accessible for retail traders. However, traders must ensure they maintain sufficient margin in their accounts to cover potential market movements and avoid margin calls.
Understanding Futures Spreads
What is a Futures Spread?
A futures spread is a trading strategy that involves simultaneously buying and selling two different futures contracts with the aim of profiting from the difference in their prices. This difference, known as the spread, can fluctuate based on various market factors, including interest rates, economic data, and investor sentiment. Futures spreads are often used to hedge risks, speculate on price movements, or take advantage of relative value differences between related instruments.
Advantages of Futures Spreads:
Reduced Risk: Spreads generally have lower risk compared to outright futures positions because the two legs of the spread can offset each other.
Lower Margin Requirements: Exchanges often set lower margin requirements for spread trades compared to single futures contracts because the risk is typically lower.
Leverage Relative Value: Traders can take advantage of price discrepancies between related contracts, potentially profiting from their convergence or divergence.
Yield Spread Example:
In the context of Micro 10-Year Yield Futures and Micro 2-Year Yield Futures, a yield spread trade involves buying (or shorting) one contract (10Y1! Or 2YY1!) while shorting (or buying) the other. This trade is based on the expectation that the spread between these two yields will move in a specific direction, such as narrowing or widening. The current scenario (detailed below), where the spread is reaching zero, suggests a significant resistance level, providing a unique trading opportunity for mean reversion.
Analysis Method
Technical Indicators: Bollinger Bands® and RSI
1. Bollinger Bands®:
The spread between the Micro 10-Year Yield Futures (10Y1!) and Micro 2-Year Yield Futures (2YY1!) is currently above the upper Bollinger Band on both the daily and weekly timeframes. This indicates potential overbought conditions, suggesting that a price reversal might be imminent.
2. RSI (Relative Strength Index):
The RSI is clearly overbought on the daily timeframe, signaling a possible mean reversion trade. When the RSI reaches such elevated levels, it often indicates that the current trend may be losing momentum, opening the door for a reversal.
Chart Analysis
Daily Spread Chart of 10Y1! - 2YY1!
The main article daily chart above displays the spread between 10Y1! and 2YY1!, highlighting the current position above the upper Bollinger Band. The RSI indicator also shows overbought conditions, reinforcing the potential for a mean reversion.
Weekly Spread Chart of 10Y1! - 2YY1!
The above weekly chart further confirms the spread's position above the upper Bollinger Band. This longer-term view provides additional context and supports the likelihood of a reversal.
Conclusion: Combining the insights from both Bollinger Bands® and RSI provides a compelling rationale for the trading opportunity. The spread reaching the upper Bollinger Band on multiple timeframes, along with an overbought RSI, strongly suggests that the current overextended condition is potentially unsustainable. Additionally, all of this is occurring around the key price level of zero, which can act as a significant psychological and technical resistance. This convergence of technical indicators and the critical price level points to a high probability for a potential mean reversion, making it an opportune moment to analyze shorting the Micro 10-Year Yield Futures (10Y1!) and buying the Micro 2-Year Yield Futures (2YY1!) as the spread is expected to revert towards its mean.
Trade Setup
Entry:
The strategic trade involves shorting the Micro 10-Year Yield Futures (10Y1!) and buying the Micro 2-Year Yield Futures (2YY1!) around the price point of 0. This is based on the analysis that the spread reaching zero can act as a strong resistance level.
Target:
As we expect the 20 SMA to move with each daily update, instead of targeting -0.188, we aim for a mean reversion to approximately -0.15.
Stop Loss:
Place a stop loss slightly above the recent highs of the spread. The daily ATR (Average True Range) value is 0.046, so adding this to the entry price could be a way to implement a volatility stop. This accounts for potential volatility and limits the downside risk of the trade.
Reward-to-Risk Ratio: Calculate the reward-to-risk ratio based on the entry, target, and stop loss levels. For example, if the entry is at 0.04, the target is -0.15, and the stop loss is at 0.09, the reward-to-risk ratio can be calculated as follows:
Reward: 0.19 points = $190
Risk: 0.05 = $50
Reward-to-Risk Ratio: 0.19 / 0.05 = 3.8 : 1
Importance of Risk Management
Defining Risk Management:
Risk management is crucial to limit potential losses and ensure long-term trading success. It involves identifying, analyzing, and taking proactive steps to mitigate risks associated with trading.
Using Stop Loss Orders:
Always use stop loss orders to prevent significant losses and protect capital. A stop loss order automatically exits a trade when the price reaches a predetermined level, limiting the trader's loss.
Avoiding Undefined Risk Exposure:
Clearly define your risk exposure to avoid unexpected large losses. This involves defining the right position size based on the trader’s risk management rules by setting maximum loss limits per trade and overall portfolio.
Precise Entries and Exits:
Accurate entry and exit points are essential for successful trading. Well-timed entries and exits can maximize profits and minimize losses.
Other Important Considerations:
Diversify your trades to spread risk across different assets.
Regularly review and adjust your trading strategy based on market conditions.
Stay informed about macroeconomic events and news that could impact the markets.
When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies.
General Disclaimer:
The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
Navigating Interest Rates with Micro Yield Futures Pair TradingIntroduction to Yield Futures
In the complex world of financial markets, Treasury Yield Futures offer investors a pathway to be exposed to changes in U.S. treasury yields. Among these instruments, the Micro 10-Year and Micro 2-Year Yield Futures stand out due to their granularity and accessibility. These futures contracts reflect the market's expectations for the yields of U.S. Treasury securities with corresponding maturities.
Micro 10-Year Yield Futures allow traders to express views on the longer end of the yield curve, typically influenced by factors like economic growth expectations and inflation. Conversely, Micro 2-Year Yield Futures are more sensitive to changes in the federal funds rate, making them a ideal for short-term interest rate movements.
Why Pair Trading?
Pair trading is a market-neutral strategy that involves taking offsetting positions in two closely related securities. This approach aims to capitalize on the relative price movements between the two assets, focusing on their correlation and co-integration rather than their individual price paths. In the context of Micro Treasury Yield Futures, pair trading between the 10-Year and 2-Year contracts offers a strategic advantage by exploiting the yield curve dynamics.
By simultaneously going long on Micro 10-Year Yield Futures and short on Micro 2-Year Yield Futures (or vice versa), traders can hedge against general interest rate movements while potentially profiting from changes in the yield spread between these maturities.
Analyzing the Current Market Conditions
Understanding the current market conditions is pivotal for executing a successful pair trading strategy with Micro 10-Year and Micro 2-Year Yield Futures. Currently, the interest rate environment is influenced by a complex interplay of economic recovery signals, inflation expectations, and central bank policies.
Central Bank Policies: The Federal Reserve's stance on interest rates directly affects the yield of U.S. Treasury securities. For instance, a hawkish outlook, suggesting rate hikes, can cause short-term yields to increase rapidly. Long-term yields might also rise but could be tempered by long-term inflation control measures.
Strategic Approach to Pair Trading These Futures
Trade Execution and Monitoring
To effectively implement a pair trading strategy with Micro 10-Year and Micro 2-Year Yield Futures, traders must have a solid plan for identifying entry and exit points, managing the positions, and understanding the mechanics of yield spreads. Here’s a step-by-step approach:
1. Identifying the Trade Setup
Mean Reversion Concept: In this strategy, we utilize the concept of mean reversion, which suggests that the yield spread will revert to its historical average over time. To quantify the mean, we employ a 20-period Simple Moving Average (SMA) of the spread between the Micro 10-Year and Micro 2-Year Yield Futures. This moving average serves as a benchmark to determine when the spread is significantly deviating from its typical range.
Signal Identification using the Commodity Channel Index (CCI): To further refine our entry and exit signals, the Commodity Channel Index (CCI) is employed. The CCI helps in identifying cyclical turns in the spread. This indicator is particularly useful for determining when the spread has reached a condition that is statistically overbought or oversold.
2. Trade Execution:
Going Long on One and Short on the Other: Depending on your analysis, you might go long on the Micro 10-Year Yield Futures if you anticipate the long-term rates will increase more relative to the short-term rates, or vice versa.
Position Sizing: Determine the size of each position based on the volatility of the yield spreads and your risk tolerance. It's crucial to balance the positions to ensure that the trade remains market-neutral.
Regular Review and adjustments: Regularly review the economic indicators and Fed announcements that could affect interest rates. Keep an eye on the spread for any signs that it might be moving back towards its mean or breaking out in a new trend.
Contract Specifications
To further refine our strategy, understanding the specific contract details of Micro 10-Year and Micro 2-Year Yield Futures is crucial:
Micro 10-Year Yield Futures (Symbol: 10Y1!) and Micro 2-Year Yield Futures (Symbol: 2YY1!):
Tick Value: Each tick (0.001) of movement is worth $1 per contract.
Trading Hours: Sunday to Friday, 6:00 p.m. to 5:00 p.m. (New York time) with a 60-minute break each day beginning at 5:00 p.m.
Initial Margin: Approximately $350 per contract, subject to change based on market volatility.
Pair Margin Efficiency
When trading Micro 10-Year and Micro 2-Year Yield Futures as a pair, traders can leverage margin efficiencies from reduced portfolio risk. These efficiencies lower the required capital and mitigate volatility impacts.
The two charts below illustrate the volatility contrast: the Daily ATR of the yield spread is 0.033, significantly lower than the 0.082 ATR of the Micro 10-Year alone, nearly three times higher. This lower spread volatility underlines a core advantage of pair trading—reduced market exposure and potentially smoother, more predictable returns.
Risk Management in Pair Trading Micro Yield Futures
Effective risk management is the cornerstone of any successful trading strategy, especially in pair trading where the goal is to mitigate market risks through balancing positions. Here are key risk management techniques that should be considered when pair trading Micro 10-Year and Micro 2-Year Yield Futures:
1. Setting Stop-Loss Orders:
Pre-determined Levels: Establish stop-loss levels at the outset of the trade based on historical volatility, maximum acceptable loss, and the distance from your entry point. This helps in limiting potential losses if the market moves unfavorably.
Trailing Stops: Consider using trailing stop-loss orders that move with the market price. This method locks in profits while providing protection against reversal trends.
2. Position Sizing and Leverage Control:
Balanced Exposure: Ensure that the sizes of the long and short positions are balanced to maintain a market-neutral stance. This helps in minimizing the impact of broad market movements on the pair trade.
Leverage Management: Be cautious with the use of leverage. Excessive leverage can amplify losses, especially in volatile market conditions. Always align leverage with your risk tolerance and market assessment.
3. Regular Monitoring and Adjustments:
Adaptation to Market Changes: Be flexible to adjust or close the positions based on significant changes in market conditions or when the initial trading assumptions no longer hold true.
4. Utilizing Risk Management Tools:
Risk Management Software: Set alerts on TradingView to help track the performance and risk level of your pair trades effectively.
Backtesting: Regularly backtest the strategy against historical data to ensure it remains effective under various market conditions. This can also help refine the entry and exit criteria to better handle market volatility.
Effective risk management not only preserves capital but also enhances the potential for profitability by maintaining disciplined trading practices. These strategies ensure that traders can sustain their operations and capitalize on opportunities without facing disproportionate risks.
Conclusion
Pair trading Micro 10-Year and Micro 2-Year Yield Futures offers traders a sophisticated strategy to exploit inefficiencies within the yield curve while mitigating exposure to broader market movements. This approach leverages the distinct characteristics of these two futures contracts, aiming to profit from the relative movements between long-term and short-term interest rates.
Key Takeaways:
Market Neutral Strategy: Pair trading is fundamentally a market-neutral strategy that focuses on the relative performance of two assets rather than their individual price movements. This can provide insulation against market volatility and reduce directional risk.
Importance of Strategy and Discipline: Successful pair trading requires a disciplined approach to strategy implementation, from trade setup and execution to ongoing management and exit. Adhering to a predefined strategy helps maintain focus and objectivity in trading decisions.
Dynamic Market Adaptation: The financial markets are continuously evolving, influenced by economic data, policy changes, and global events. A successful pair trader must remain adaptable, continuously analyzing market conditions and adjusting strategies as needed to align with the current economic landscape.
Comprehensive Risk Management: Effective risk management is crucial in pair trading, involving careful consideration of position sizing, stop-loss settings, and regular strategy reviews. This ensures sustainability and longevity in trading by protecting against undue losses.
By maintaining a disciplined approach and adapting to market changes, traders can harness the potential of Micro Treasury Yield Futures for strategic pair trading, balancing risk and reward effectively.
When charting futures, the data provided could be delayed. Traders working with the ticker symbols discussed in this idea may prefer to use CME Group real-time data plan on TradingView: www.tradingview.com This consideration is particularly important for shorter-term traders, whereas it may be less critical for those focused on longer-term trading strategies.
General Disclaimer:
The trade ideas presented herein are solely for illustrative purposes forming a part of a case study intended to demonstrate key principles in risk management within the context of the specific market scenarios discussed. These ideas are not to be interpreted as investment recommendations or financial advice. They do not endorse or promote any specific trading strategies, financial products, or services. The information provided is based on data believed to be reliable; however, its accuracy or completeness cannot be guaranteed. Trading in financial markets involves risks, including the potential loss of principal. Each individual should conduct their own research and consult with professional financial advisors before making any investment decisions. The author or publisher of this content bears no responsibility for any actions taken based on the information provided or for any resultant financial or other losses.
How to Trade Trends the Right WayHow to Trade Trends: A Comprehensive Guide
Trend trading is a fundamental strategy for many traders, offering the potential for significant profits if executed correctly. However, mastering trend trading requires more than just following a single indicator. In this guide, we'll explore the intricacies of trend trading and how you can enhance your strategy for better results.
1. Utilize Multiple Indicators
Relying on a single indicator to gauge market trends is like trying to understand a story by reading only one page. To get a comprehensive view of the market's direction, you should use multiple indicators. This approach can help you confirm trends and avoid false signals. Some popular indicators include moving averages, MACD (Moving Average Convergence Divergence), and RSI (Relative Strength Index). By analyzing these indicators together, you can get a clearer picture of the market's momentum and make more informed decisions.
2. Infinite Nature of Trends
One of the most important concepts in trend trading is understanding that trends, by nature, are infinite until a clear trend change is identified. This understanding shifts the focus from setting arbitrary take profits (TPs) to managing trades with dynamic stop losses (SL). Instead of trying to predict where the trend will end, adjust your stop loss to subsequent swing highs or lows. This method allows you to stay in the trade as long as the trend continues, potentially capturing larger gains.
3. The Benefit of Longer-Term Trends
While it may be tempting to trade on shorter time frames for quick profits, longer-term trends often offer more substantial rewards. A trend that exists on a daily or weekly chart is less likely to be disrupted by short-term volatility. Although these trades may require more patience, they tend to exit less frequently, allowing you to ride the trend for greater potential profits. Exiting a trend too early or trading on a system that changes signals often can result in missed opportunities and reduced profitability.
4. Strategies for Lower Timeframes
For traders who prefer lower timeframes, the high volatility can make trend trading challenging. One strategy is to use the underlying trend from a higher timeframe as a bias and apply mean reversion strategies on the lower timeframe. This approach involves entering trades at a discount during an uptrend or at a premium during a downtrend. By aligning your trades with the overall trend direction, you can improve your chances of success even in a volatile market.
Combine multiple indicators for a comprehensive analysis.
Understand the infinite nature of trends and use dynamic SL.
Focus on longer-term trends for greater profit potential.
Use mean reversion strategies on lower timeframes with an overall trend bias.
"Trade the trend until it ends."
In conclusion, trading trends is more art than science, requiring a nuanced understanding of market indicators, patience, and discipline. By using multiple indicators, adjusting your approach based on the timeframe, and managing your trades dynamically, you can enhance your trend trading strategy for better results. Remember, the key to successful trend trading is not predicting the market's every move but rather managing your trades in a way that aligns with the overall market momentum.
The Cores of Price Analysis: Trend Following vs. Mean ReversionIn the world of financial markets, predicting future price movements is akin to unlocking a treasure chest. Two of the most prominent methodologies used by traders and analysts to decipher market movements are Trend Following and Mean Reversion. Each approach offers a unique perspective on how markets behave and provides strategies for capitalizing on this behavior. In this article, we'll dive into the core concepts of these methodologies, explore how they can be implemented, and touch on basic processing techniques like smoothing and normalization, which enhance their effectiveness.
Trend Following: Surfing the Market Waves
Trend Following is based on the premise that markets move in trends over time, and these trends can be identified and followed to generate profits. The essence of trend following is to "buy high and sell higher" in a bull market, and "sell low and buy back lower" in a bear market. This method relies on the assumption that prices that have been moving in a particular direction will continue to move in that direction until the trend reverses.
How to Implement Trend Following
1. Identifying the Trend: The first step is to identify the market trend. This can be done using technical indicators such as moving averages, MACD (Moving Average Convergence Divergence), or ADX (Average Directional Index). For example, a simple strategy might involve buying when the price is above its 200-day moving average and selling when it's below.
2. Entry and Exit Points: Once a trend is identified, the next step is to determine entry and exit points. This could involve using breakout strategies, where trades are entered when the price breaks out of a consolidation pattern, or using momentum indicators to confirm trend strength before entry.
3. Risk Management: Implementing stop-loss orders and adjusting position sizes based on the volatility of the asset are crucial to managing risk in trend-following strategies.
Basic Processing Techniques
- Smoothing: To reduce market noise and make the trend more discernible, smoothing techniques such as moving averages or exponential smoothing can be applied to price data.
- Normalization: This involves scaling price data to a specific range, often to compare the relative performance of different assets or to make the data more compatible with certain technical indicators.
Mean Reversion: Betting on the Elastic Band
Contrary to trend following, Mean Reversion is based on the idea that prices tend to revert to their mean (average) over time. This methodology operates on the principle that extreme movements in price – either up or down – are likely to revert to the mean, offering profit opportunities.
How to Implement Mean Reversion
1. Identifying the Mean: The first step is to determine the mean to which the price is expected to revert. This could be a historical average price, a moving average, or another indicator that serves as a central tendency measure.
2. Identifying Extremes: The next step is to identify when prices have moved significantly away from the mean. This can be done using indicators like Bollinger Bands, RSI (Relative Strength Index), or standard deviation measures.
3. Entry and Exit Points: Trades are typically entered when prices are considered to be at an extreme deviation from the mean, betting on the reversal towards the mean. Exit points are set when prices revert to or near the mean.
Basic Processing Techniques
- Smoothing: Similar to trend following, smoothing techniques help in clarifying the mean price level by reducing the impact of short-term fluctuations.
- Normalization: Especially useful in mean reversion to standardize the deviation of price from the mean, making it easier to identify extremes across different assets or time frames.
Conclusion
Trend Following and Mean Reversion are two fundamental methodologies in financial market analysis, each with its unique perspective on market movements. By employing these strategies thoughtfully, along with processing techniques like smoothing and normalization, traders and analysts can enhance their understanding of market dynamics and improve their decision-making process. As with any investment strategy, the key to success lies in disciplined implementation, thorough backtesting, and effective risk management.
Understanding Technical IndicatorsTrading indicators are essential tools for traders and investors to analyze and interpret financial market data. These indicators, derived from mathematical calculations based on price, volume, or open interest, etc, aid in visualizing market trends, momentum, and potential reversals. They serve as an additional layer of analysis, offering a structured and objective way to understand market dynamics.
Understanding Trading Indicators
1.1 Definition : Trading indicators are graphical tools derived from price, volume, or open interest data. They help in identifying market trends, momentum, volatility, and possible trend reversals.
1.2 Types of Trading Indicators :
Trend Indicators : These indicators, such as Moving Averages (MA), Moving Average Convergence Divergence (MACD), and Ichimoku Cloud, help in determining the direction and strength of market trends.
Oscillators : Tools like the Relative Strength Index (RSI), Stochastic Oscillator, and Commodity Channel Index (CCI) measure overbought and oversold market conditions.
Volume Indicators : Indicators such as On-Balance Volume (OBV) and Volume Weighted Average Price (VWAP) use trading volume data to confirm price movements.
Volatility Indicators : These, including Bollinger Bands and Average True Range (ATR), assess the degree of price fluctuation in the market.
Utilizing Trading Indicators
2.1 Trend Following Strategy : This approach involves capitalizing on the continuation of established market trends. Indicators like the Fourier Smoothed Stochastic (FSTOCH) help detect and follow these trends, providing smoother signals and filtering market noise for more accurate decision-making.
2.2 Mean Reversion Strategy : Contrary to trend following, mean reversion strategy focuses on price corrections when they deviate significantly from historical averages. The Bollinger Bands Percentile (BBPct) is a mean reversion indicator that uses Bollinger Bands to identify potential price reversals, indicating when an asset is overbought or oversold.
Comparing Trend Following and Mean Reversion
3.1 Key Differences :
Direction : Trend following identifies and exploits established trends, whereas mean reversion focuses on price reversals.
Risk Profile : Trend following is typically higher risk due to the challenge of timing, while mean reversion is considered less risky as it banks on imminent price corrections.
Market Conditions : Trend following excels in trending markets, while mean reversion is more effective in range-bound or sideways markets.
3.2 Combining Strategies : Using both strategies together can provide a more comprehensive market view and reduce reliance on a single approach. Mean reversion indicators can confirm trend reversals identified by trend-following indicators, while the latter can help avoid premature exits in mean reversion trades.
Binary and Discrete Indicators
4.1 Binary Indicators : These indicators, like the Alpha Schaff, offer clear, binary (yes-or-no) signals. They are ideal for straightforward decision-making, indicating when to buy or sell.
4.2 Discrete Indicators : Unlike binary indicators, discrete indicators, such as the Average-True-Range, provide a range of values, offering more nuanced insights into market conditions.
The Importance of Using Both Types of Indicators
Combining binary and discrete indicators equips traders with a broader perspective on market conditions. While binary indicators provide clear entry and exit points, discrete indicators offer detailed insights into the strength of market trends and potential turning points. This combination enhances decision-making by enabling traders to cross-reference signals and identify high-probability trading opportunities.
Conclusion :
In the dynamic world of finance, trading indicators are invaluable for providing insights into market trends, momentum, and conditions. Utilizing a combination of trend following, mean reversion strategies, and both binary and discrete indicators, traders can develop a comprehensive and effective toolkit for navigating financial markets successfully.
The Fundamental Concepts of Technical IndicatorsTrading indicators are essential tools used by traders and investors to analyze price data, identify trends, and make informed decisions in financial markets. They provide valuable insights into market dynamics, helping market participants gain a competitive edge. This comprehensive explainer will delve into what trading indicators are, how they are utilized, and the differences between two prominent strategies: trend following and mean reversion. Additionally, we will explore the importance of using binary and discrete indicators together to enhance trading effectiveness.
Part 1: Understanding Trading Indicators
1.1 Definition of Trading Indicators
Trading indicators are mathematical calculations based on price, volume, or open interest data that provide graphical representations of market conditions. These calculations help traders visualize price trends, momentum, volatility, and potential reversals. Indicators serve as a supplementary layer of analysis, offering a structured and objective approach to interpreting market behavior.
1.2 Types of Trading Indicators
Trend Indicators: Identify the direction and strength of prevailing trends, such as Moving Averages (MA), Moving Average Convergence Divergence (MACD), and Ichimoku Cloud.
Oscillators: Measure overbought and oversold conditions, such as Relative Strength Index (RSI), Stochastic Oscillator, and Commodity Channel Index (CCI).
Volume Indicators: Assess trading volume to confirm price movements, like On-Balance Volume (OBV) and Volume Weighted Average Price (VWAP).
Volatility Indicators: Gauge the level of price fluctuations, including Bollinger Bands and Average True Range (ATR).
Part 2: Utilizing Trading Indicators
2.1 Trend Following Strategy
Trend following is a popular trading strategy that capitalizes on the continuation of established trends. Traders using this approach seek to identify uptrends or downtrends and ride them for extended periods. Trend following indicators are ideally suited for identifying the direction of a trend and capturing profits during strong market movements.
Example of Trend Following Indicator: Fourier Smoothed Stochastic (FSTOCH)
(Indicators like the FSTOCH help traders reveal underlying trends in the market)
The Fourier Smoothed Stochastic is an advanced tool that utilizes the Stochastic Oscillator in combination with Fourier Transform analysis to identify and ride prevailing trends. By providing smoother signals, it helps traders stay on course with the established trend, allowing for more accurate entries and exits. Its ability to filter out market noise makes it an ideal choice for trend followers seeking a clearer view of market momentum, enabling them to capitalize on prolonged price movements.
2.2 Mean Reversion Strategy
Mean reversion is a counter-trend strategy that assumes prices will revert to their average or mean over time. Traders using this approach aim to profit from price reversals when an asset's price deviates significantly from its historical average. Mean reversion indicators are ideal for identifying overbought and oversold conditions and anticipating potential reversals.
Example of Mean Reversion Indicator: Bollinger Bands Percentile (BBPct)
(The BBPct indicator marks out price extremes which may lead to potential reversals)
The BBPct (Bollinger Bands Percent) is an indicator designed for mean reversion trading strategies. It utilizes Bollinger Bands to determine overbought and oversold conditions in the market. The indicator calculates the percentage of the current price's position within the Bollinger Bands' upper and lower boundaries. When the price is near the upper band, it suggests an overbought condition, indicating a potential mean reversion towards the lower band. Conversely, when the price is close to the lower band, it indicates an oversold condition, suggesting a possible mean reversion towards the upper band. Traders can use this information to identify potential reversal points and make informed decisions to capture price movements back towards the mean.
Part 3: Trend Following vs. Mean Reversion
3.1 Key Differences
Direction: Trend following aims to identify and ride established trends, while mean reversion seeks to capitalize on price reversals.
Risk Profile: Trend following strategies typically involve higher risk, as traders enter positions in the direction of the trend, which may be challenging to time accurately. Mean reversion strategies are often considered less risky as traders expect price reversals to occur relatively soon after significant deviations from the mean.
Market Conditions: Trend following tends to perform well in trending markets, while mean reversion thrives in ranging or sideways markets.
3.2 Combining Trend Following and Mean Reversion
While trend following and mean reversion strategies have distinct approaches, they can complement each other when used in confluence. Combining both strategies can provide a more comprehensive view of the market and reduce reliance on a single indicator. For example:
Confirming Trend Reversals: Mean reversion indicators can be used to confirm potential trend reversals identified by trend-following indicators, increasing the probability of successful entries and exits.
Managing Risk: Trend following indicators can help traders stay in trends longer and avoid premature exits when using mean reversion strategies.
Identifying Range-Bound Markets: Mean reversion strategies can be employed during periods of low volatility or when the market lacks a clear trend, while trend following indicators can be set aside until a new trend emerges.
Part 4: Binary and Discrete Indicators
4.1 Binary Indicators
(The Super Schaff gives out binary signals when it detects a potential change in trend)
Binary indicators provide straightforward, yes-or-no signals, indicating the presence or absence of a particular condition. Examples include Moving Average Crossovers and Super Schaff, which produce buy (long) or sell (short) signals when specific conditions are met.
4.2 Discrete Indicators
(The Volume-Trend Sentiment displays the overall implied sentiment based on volume and price action)
Discrete indicators generate signals based on a range of values or levels. These indicators offer more nuanced insights into market conditions, allowing traders to interpret the strength or weakness of signals. Examples include RSI and VTS.
Part 5: The Importance of Using Both
5.1 Diverse Perspectives
Combining binary and discrete indicators provides traders with diverse perspectives on market conditions. Binary indicators offer clear entry and exit signals, while discrete indicators offer a finer understanding of price trends and potential turning points.
5.2 Enhanced Decision-Making
Using both types of indicators helps traders make more informed and confident decisions. By cross-referencing binary and discrete signals, traders can filter out false signals and identify high-probability trading opportunities.
Conclusion:
Trading indicators play a vital role in modern financial markets, providing traders and investors with valuable insights into price trends, momentum, and market conditions. Trend following and mean reversion strategies offer distinct approaches to trading, each with its unique advantages and risk profiles. However, combining these strategies and utilizing both binary and discrete indicators can provide a comprehensive and powerful toolkit for traders seeking consistent success in the dynamic world of finance.
Check out the indicators mentioned in this post:
Introducing the Bars Since EMA Touch IndicatorHey there traders, Stock Justice here! Are you ready to elevate your trading game? Today, we're going to delve into an exciting indicator I call 'Bars since EMA touch', or 'BSET' for short. Buckle up, because we're about to kick your technical analysis up a notch!
The BSET, at its heart, revolves around the Exponential Moving Average, or EMA. When setting up BSET, you'll be prompted for the length of the EMA, with the default being 9. This number represents the number of bars that will be averaged to create your EMA line. A higher value smooths out the line, reducing noise but potentially delaying important signals. A lower value makes the EMA more responsive, but at the risk of responding to market noise.
BSET calculates how many bars it's been since the price last touched the EMA. A positive number indicates the number of bars since the price was last above the EMA, and a negative number shows how long it's been since the price was below the EMA.
BSET also uses the MACD and signal line to color-code these bars. Blue and red bars indicate price is above the EMA, with blue signaling an upward trend and red signaling a possible downturn if the bar number is above 3. White and green bars indicate price is below the EMA, with white signaling a downward trend and green indicating a possible upturn if the bar number is above 3.
This color-coding can be a useful tool to quickly determine whether a potential reversal is in the making or if the current trend is likely to continue. But that's not all! BSET takes it a step further by keeping track of how often price trends extend beyond certain thresholds, updating these thresholds if necessary.
These thresholds, shown as red and green lines on the histogram, indicate the 15% percentile for bull and bear trends, respectively. If more than 20% of trends exceed the current threshold, it's adjusted upwards. This gives you a historical context for how long trends usually last and can help you spot when a trend is overextended and might be due for a reversal.
BSET is an innovative tool that combines trend tracking with volatility in a unique way, helping you better understand market dynamics and make informed trading decisions. Just remember, every indicator, BSET included, is just a tool. Always use them in conjunction with other analysis methods and never risk more than you're willing to lose.
That's it for now, traders. Keep your eyes on the charts and remember: Trade safe, trade smart! This is Stock Justice, signing off!
Harnessing Gains from Mean Reversion in WTI Crude FuturesThere are three kinds of lies: lies, damn lies, and statistics. Fortunately, not always. Statistics enables investors and traders in financial and commodity markets.
In statistics, mean is also known as the average. It is a number that represents the entire data set. Mean is the sum of the data set divided by number of data points in it. For example, in a group of six men who weigh between 70kg to 80kg with an interval of two kilograms apart, the mean weight of the group is 75kg.
Previously, Mint published two case studies looking at WTI crude oil futures. a short position and a long position . Both of these case studies were centered upon the same range-bound price action of WTI futures.
Mean Reversion in Financial & Commodity Markets
In financial markets, mean refers to the average of all the data observations. For example, let's say in WTI futures, it refers to the average price of a barrel of WTI futures over the observed period.
For commodity traders, mean and reversion to the mean is a godsend.
Reversion to the mean is a consistent occurrence in finance. Especially in crude oil, ample academic research shows that crude oil prices tend to mean revert.
In other words, crude oil prices has a tendency to stray away from the mean but will eventually retrace back to the longer term average. Asset prices oscillate around the average. The bigger the diversion from the mean, the higher the probability that prices will revert to it.
Harnessing Mean Reversion in Financial Markets
An astute trader can identify the pattern embedded in the price. Such traders carefully ride the path of the asset prices to gain from it and switch their positions around when prices start to trace back.
This phenomenon has led to the development of many investing and trading strategies that involve the buying & selling assets whose prices have veered away from their historical averages.
At its core, trading the mean reversion strategy involves buying the asset whose values have fallen below the long-term average and waiting for prices to recover back up to the long-term mean before selling it.
Trading strategies are based on either taking advantage of mean reversion or momentum in the market. Markets spend greater time in consolidation mode relative to trending phases. Incorporating mean reversion in trading strategies is not only important but potentially lucrative.
For those assets, whose prices are far above the mean, the strategy would then involve selling the asset first in the hope of a price correction to the mean. When prices fall, the asset is bought back at a lower price to lock in the gain.
Mean Reversion is not Guaranteed. Take Caution.
Readers to take caution that mean reversion is not guaranteed. Unexpected highs or lows could indicate a shift in the norm. A significant price change could be structural indicating a new normal. The structural shift may provide a significant headwind or tailwind to asset prices in the longer run.
Technical Indicators to help identify Mean Reversion
This paper aims to illustrate mean reversion using WTI Crude Oil futures. Crude oil prices are known to follow Brownian motion with mean reversion, according to academic literature. WTI Crude Oil futures follow a lognormal distribution with slowly changing volatility.
Brownian motion? Lognormal distribution? Park them aside for now. Mint will cover those topics in another educational paper in near future.
Effective mean reversion involves effective timing of trade entry and exits. Trend following indicators, such as moving averages help to identify patterns. Oscillators, such as the RSI, also enable investors to identify overbought and oversold conditions. Bollinger Bands is a complementary indicator to identify mean reversion trend.
Mean Reversion in Crude Oil Prices in 2022 and 2023
WTI crude oil prices soared in the first half of 2022 as the war in Ukraine clouded supply projections after sanctions were placed on Russian oil and gas by the US and EU. This reduced the available supply pushing prices higher.
However, during second half of the year, the gloomy global economic outlook and recession risks in the US meant that demand for crude oil started to drop. Moreover, COVID outbreaks in China meant that the largest importer of Crude Oil had lesser appetite to buy.
Over the past 3 months, WTI Crude Oil has traded in a tight range between $70 to $80 a barrel. The reasons behind the range bound price action are:
At the bottom end of the range, there is strong support between $67-72 as that is the price range that the US DoE plans on purchasing oil to replenish the Strategic Petroleum Reserve.
At the top end of the range, supply outpacing demand, as well as the availability of cheap Russian oil for major consumers – China and India – limits the upside potential for oil.
Capex into new oil exploration has dropped as the world starts to shift towards alternative energy sources.
Despite the SPR currently at a 40-year low, the Biden administration continues to draw more crude from the reserves
to limit fuel price inflation in the US & keeping WTI crude prices lower.
How to be a Mean Reversion ScalperIn this video I go over how I trade with my custom mean-reversion histogram and overlay indicator, explaining the logic behind my entires and profit-taking levels. This example is taken from $SPY on the 1-minute chart, and I examine all four of the alerts that the indicator gave today. Comment below with any questions!
Heiken Ashi Algo and the Mass Effect Moving Average: Almost HereWell ladies and gentlemen I think I have created a monster and I'm really happy to call it the heiken Ashi algo and the Mass Effect moving average combination.
Don't worry I have not been leaving you hanging. It's just been very busy and I want to make sure that this thing works beautifully for you.
So what is the heiken Ashi algo oscillator?
it is an oscillator much like the original heikin-ashi RSI with a ton more features.
As you know a little while ago I came out with the CoffeeShop Crypto HARSI, Update to the original HARSI.
And as development on that oscillator continued I had to change the name to the algo because now the oscillator actually speaks to you while trading is taking place.
But as you know you should never use a single indicator by itself to enter and exit trades and understand what's happening on your chart. you should always use something as a secondary Confluence or even a tertiary confluence. Because the more confluences you have the better right?
So with that I continued development on the Mass Effect moving average and you can use them beautifully in combination.
In this video I don't want to get into the technical Aspect of all the details on how the oscillator and the moving average work but I do want to show you the parts that have been developed and what they mean.
feel free to leave your suggestions below and I will make adjustments if needed.
I'm probably going to need one more week before fully releasing both of these together and until then I'd love to communicate with you on anything to make it more fluid.
With that let's take a look at my chart and see the breakdown.
The Heiken Ashi Algo
Double Stochastic - Uses a mean regression calculation for pullback notifications but it also adds support to knowing when a trend is in full swing.
This happens when you see both stochastic ribbons touch each other while they are the same color
Green touching green is a move to the upside. It matters most When it's above or below the 50 level.
the other thing you can see here is when they touch and when they touch again as the same color is a clear sign of a Divergence.
IBXL - Inside Bar Calculation. This will be moved to the Mass Effect MA as well
Resistance / Support / are dynamic levels which change over time
Bull Key level - Are Significant price or Price action levels which almost never change over longer periods of time. when I get a key level alert I Market on my chart with a thick line and I lock it in place. These are the major areas of supply and demand Zone on your chart and you want to watch them closely when price gets near these levels
Pull Back - Helps you draw out targets to your trend lines.
Now let's talk real quick about the mass effect moving average and what it will include.
this uses a mean regression strategy so that you can swing trade- And get your confluences of when prices going to move up or down so doesn't matter if you are in an uptrend or a downtrend .
Stop lost Trend color - Is this really a stop loss line which will follow your price action and depending on its color will tell you if you should be using a stop loss of a guy or a stop loss of a sell. Obviously if it's red you should be selling and if it's green you should be buying. do not use it incorrectly. Just because it changes to Green doesn't mean you by and just because it changes to Red doesn't mean you cell. It only means you are in an area where you should be buying or selling.
The EMA's - it includes four different exponential moving averages which you can set appropriately to your style.
The VWAP - Included in this is a VWAP Moving average. Even though the VWAP is used as a moving average against the RSI in the oscillator below, I included the VWAP in the Mass Effect moving average because once you switch to a daily chart The VWAP in the oscillator disappears but you can still have it on your chart in the Mass Effect moving average. So switching to a daily chart you will still be able to see your VWAP.
The V-CROSS - This indication shows up so that you can see when the V WAP is crossing over your price level. This helps you know from point to point if you are above or below a support or resistance level and where is your price in relation to your VWAP. This will also help you notice when price is overbought or oversold.
Fractals - Show you pivot points in market structure. I use them to find exit points for trades when there is no immediate swing low or high to be seen. Usually i look further left and use one of these points to exit. But they have even more application which I'll get into in another video.
The Trend Ribbon - Is a bullish and or bearish colored ribbon to show you the trend that works in Confluence with your stop loss line which also changes from red to Green. when they are both the same color you are in a trend in that direction of up or down. The good thing about the trend ribbon is it's always seeking the same level as the VWAP and when it finally catches up to it that's when the trend usually goes flat and then reverses.
Trading strategies you may not have seen, I will share with you Many classic indicators such as MACD, RSI, EMA are basically a combination of "iron triangle" equipped by hand. The more advanced ones may be candle pattern analysis and Elliott wave theory. Today we are going to talk about trading strategies based on volatility and linear regression, as well as correlation coefficients. These indicators are easy to create in Pine, and I will be creating a volatility correlation-based indicator to publish to my public script library in the near future.
Trading strategies you may not have seen! Dry goods to share!
Enough talk, please see the picture
1. In the linear regression in the chart, I draw the Pearson correlation coefficient with a yellow circle, which proves that 93.95% of the price falls within the standard deviation of the standard deviation band of the upper and lower 2 (you can refer to the standard deviation concept of Bollinger Band, //For a normal distribution, within one standard deviation of plus or minus is 68.2%, plus or minus two standard deviations is 95.4%, plus or minus three standard deviations is a 99.6% confidence interval//See statistics)
2. The indicator in the side graph is based on Close to Close's historical volatility percentage (great idea by @Balipour) and its SMA line, please note that the part larger than the SMA line we call "mean reversion", smaller than the SMA line part of it is called "trends",
It can be seen that the price always fluctuates during "reversion to the mean", just like the volatility reading, the volatility is large but will eventually return to its *mean*, the part below the SMA is the "trend", which proves that the current market There is a "trend", which may be left or right trading, (the direction is clearly expressed in the linear regression)
3. The above two points can see whether the current market is "trend" or "mean reversion", then continue to look at the correlation coefficient in the sub-picture indicator. I will not repeat the principle. The source of the correlation coefficient is Close (close). price), the correlation is the historical volatility, 0 is the dividing line of the correlation coefficient, above 0 is a positive correlation, below 0 is a negative correlation, under a significant positive correlation, we describe the current market as a percentage of historical volatility is "mean reversion" It is still the fluctuation of the "trend" to operate. As can be seen in the figure, in the positive correlation fluctuation, we have captured a lot of trading signals.
Finally, thanks to TV for such excellent and powerful chart analysis software
Regressive VWAP Breakout StrategyStrategy type: Breakout
Ingredients: Price, Volume, Regression
Prerequisite add-ons (free): Regressive VWAP and Strategy Visualizer
Target market: CME:BTC1! or BITSTAMP:BTCUSD
- Long Entry on Close crossing over Regressive VWAP
- Short Entry on Close crossing under Regressive VWAP
- Optional: exit when price retraces to upper band (LX) or lower band (SX)
The key to this breakout strategy is the Regressive VWAP, which weighs Price and Volume with Regression Analysis, making the slope and its bands more responsive, with a degree of mean reversion.
Below is another example, this time CME_MINI:ES1! .
Diversify your strategyThe holy grail of diversification is to find several uncorrelated asset classes all with positive returns. One problem, though, is that diversified passive investing has caused all asset classes to become more and more correlated over time. Increasingly, you see stocks, bonds, commodities, and cryptocurrencies all move together.
One approach to diversification that's increasingly popular with quants is to diversify your strategies rather than your asset classes . Long-short strategies are a popular example. Almost by definition, your short strategies will make money when your long strategies lose money, and vice versa. The challenge of making this work is that it's really hard to design short strategies with positive expected return. Since the market tends to go up over time, playing the market short is a bit like betting against the house at a casino. If you find a short strategy that actually works, that's gold right there.
Fortunately, there are some relatively uncorrelated strategies that work for long-only traders. This chart shows the Invesco "Momentum" and "Pure Value" ETFs. As you can see from the red and green arrows, the two ETFs often move in opposite directions. When one is producing positive returns, the other often isn't. Owning both can help smooth out your drawdowns and returns.
The same can be said for "mean-reversion" and "trend-following" strategies. Mean-reversion strategies involve buying assets that have made a big move downward. If you bought China stocks after their recent huge-selloff, that was a mean-reversion trade. Trend-following strategies, by contrast, involve buying assets that have made a big move upward. If you've bought oil and gas stocks in recent weeks, that was a trend-following trade. Both strategies tend to "work," but again, they're somewhat uncorrelated.
These strategies can further be broken down into short-term and long-term versions. Oil and gas is in a short-term uptrend, while the Nasdaq index is in a long-term uptrend. Facebook and Bristol-Myers Squibb are a short-term mean-reversion candidates after their recent sell-offs, while Calavo Growers and Regis Corporation are long-term mean-reversion candidates. The nice thing about using a mixture of short-term and long-term signals is that they allow you both to profit from stable market conditions and to quickly pivot at least some of your capital when market conditions change.
Using Standard Deviations As Momentum Or Mean Reverting StrategyUsing standard deviations in trading can be helpful in many way with keeping you on the right side of your trades in this video I break down how I use or would use the 1SD 2SD and 3SD based upon the percentage of time price normally traverses through each SD.
Ethereum 05/13/21, Mean Reversion studyThis is a really simple (almost too simple) way of predicting the most likely number of candles before a revisit to a certain level, presuming no outside factors increase the required sample of study. I have just tried to predict very specific candle positions and times as well as the bottom, but this is only for the extreme near future (ie, the easiest to predict), past that it becomes harder unless you reduce your precision several factors.
This is an ideal situation where there is a clear median that it has clung to, and the standard deviations are very obvious and apparent.
Note: I am only counting candle bodies, not wicks.
edit: I also made the highlight before the current hour while I was writing this it seems to agree with me so far.
EURUSD 1D MEAN REVERSION TRADING STRATEGYBest Mean Reversion Strategy:
Before we get to that point, first and foremost, let’s see what tools we need to use for this strategy.
The best mean reversion indicator that works 85% of the time is the RSI indicator.
So, you will need the RSI oscillator on your charts.
Now, there is one more important thing that needs to be done. The RSI settings must be changed from the default 14-period to 2-period RSI. So, we’re having not just any type of RSI, but a very fast RSI. Levels are 10 & 90.
The other technical indicators we’re going to deploy on the charts are:
10-period simple moving average.
200-period moving average.
Note* Another thing to keep in mind is the recommended time frame is the daily chart. Intraday charts won’t work because the fast-period RSI will generate a lot of false signals on lower time frames.
Now, let’s see how we can combine the 3 indicators into a profitable mean reversion strategy.
The first obvious question is when to buy and sell currency.
To answer this question the mean reversion trading strategy needs to satisfy 3 triggers:
The price needs to be above the 200-day EMA. This means that the overall price is in an uptrend so, we’re only going to look for buy signals in bull markets.
Second, we look for the price to below the 10-day SMA, which shows a deviation from its mean.
Last but not least, we look at the RSI to overshoot below 10, which signals that we’re in oversold territory.
Note* For sell signals use the same trading rules but in reverse.
Once all 3 conditions are satisfied we enter a trade at the open of the following day.
Once we’re in a trade we also need, we also need to know when to exit the market. This is where the 10-period simple moving average comes into play again. What we’re looking for is for the price to reverse back to the 10-period SMA strategy.
More often than not the price will overshoot to the upside and break above the 10-period SMA.
So, to fully capitalize on the entire move we use multiple take profit targets:
The first profit target is to cash half of the position once we touch the 10-period SMA.
The second portion of your position is left until we break and close above the 10-period SMA.
Based on our backtesting result, on average your trades should reach the second target within 1-3 days. The longer you keep your position open, the lower the chances of the trade to succeed. As a general rule, you should cash out of your entire position within the first 3 trading days.
Now, we have left out for last the most important part, which is managing risk.
When it comes to the protective stop loss we’re advising not to place a stop loss right away, but instead, use a time stop.
Let me explain…
Based on our backtesting results we have found that a lot of the times the market will do a false breakout below the previous day low (high) and hurt our position.
So, to avoid this scenario we have found a great trick to move around it.
Our rule is very simple:
If by the first half of the day our position shows a loss, we close that trade and call it a day.
This is a risky play but we have the edge on our side to play this kind of trick. After all, trading is a risky game and everyone needs to decide for themselves how to manage risk.
Final Words – Best Mean Reversion Strategy
In summary, the most alluring thing about mean reversion trading is the high win-loss ratio and the simplicity behind it. One thing to keep in mind is that the mean reversion strategy tends to perform poorly when the market is in a hard-mode trend. But that shouldn’t be much of a big deal since the market is ranging 75% of the time.
The key takeaways from the mean reversion trading strategy are as follow:
Mean reversion can be used with all asset classes (stocks, commodities, currencies or cryptocurrencies).
Range trading and overbought/oversold signals work the best with this method.
Adjust the RSI settings to a fast-period.
You can generate quick profits – short holding time periods.
A trading tip – use a time stop instead of a price stop.
Thank you for reading!
Mean Reversion Trading Strategy with a Sneaky Secret.
In this guide, you’ll learn a mean reversion trading strategy with some trading secrets that will assist you to limit the downside. The first part of the guide will highlight what is mean reversion trading, while in the second part we’ll reveal the mean reversion strategy and how you can fine-tune it to fit your personality.
If this is your first time on our website, our team at Trading Strategy Guides welcomes you. Make sure you hit the subscribe button, so you get your Free Trading Strategy every week directly into your email box.
The mean reversion trading systems are more appealing to a lot of traders because it tends to have a higher win rate as opposed to the trend following strategies. Even when the markets are in well-established trends, mean reversion happens quite often.
So, there are more opportunities to profit from mean reversion trading.
Let’s kick the ball rolling and start with the basic by first explaining what is mean reversion in trading and then we’re going to reveal 5 trading principles that can be used with the mean reversion strategy.
Table of Contents
1 What is Mean Reversion Trading?
2 How Mean Reversion Trading Works?
3 Why the Mean Reversion Strategy Works?
4 Mean Reversion Trading Strategy
5 Final Words – Best Mean Reversion Strategy
What is Mean Reversion Trading?
Put it simply; mean reversion trading assumes that over time the prices of any asset (stock, commodity, FX currency or cryptocurrency) in time will revert back to the mean or average price.
In other words, reversion to the mean trading comes down to the old saying:
“What goes up must come down.”
The mean reversion theory is at the foundation of many trading strategies that involve buying and selling of those asset class prices that have deviated from their historical averages. The idea is that in the long-term prices will return back to their previous average prices and normal pattern.
Example of mean reversion trading strategies includes:
Reversals.
Pullback trading.
Retracement.
Range trading system.
Overbought and oversold strategies.
Our best mean reversion strategy is to trade those price ranges that occur after a severe price markup or markdown. In this case, reversion to the mean implies trading around the middle of the range as our average price.
In essence, mean reversion is playing around a central value be it the middle of the range, or a moving average, or however you wish to express it.
The reversion to mean trading system tends to produce a higher win rate in those instances where we can notice extreme changes in the price.
We can measure extreme price changes relative to the time frame used.
Obviously, there is also a probability that the price will not revert back to its mean. This can indicate that there is a real shift in the market sentiment and we’re in a new paradigm.
Now that we know what is mean reversion trading, let’s see how the mean reversion regression works.
How Mean Reversion Trading Works?
With mean reversion, we’re looking to trade against the heard.
A lot of the times when you’re doing mean reversion trading, you’ll be quick in-and-out of a trade. That’s why day trading mean reversion strategy works better.
There are other different ways to trade with the mean reversion strategy, including:
Price stretch from a simple moving average strategy.
A break outside the Bollinger Bands strategy and a return back to the mean.
A test of support and resistance strategy while the price is consolidating.
The linear regression is clearly slopping upwards and it’s acting as a magnet to the price. Each time the price deviates from the average price line it snaps back to it outlining the reversion to the mean concept.
The main advantages of the mean reversion strategy include:
Effective exit strategy – the take profit target is always the average price.
High win rate – the shorter the mean reversion time frame used the higher the win rate.
Good risk-adjusted returns.
All trading strategies have their own pros and cons.
The biggest flaw is that once you’re in a trade you’ll often see first a loss before you see a profit.
The main components of the mean reversion strategy should include:
1. Entry signal after the price has moved away from its average price. You can simply calculate how far away percentage-wise are from the mean or use an ATR strategy multiple declines or simply use a volume oscillator to gauge oversold/overbought readings.
2. Exit signal gives you a way out once you get into a trade.
3. Broad market timing.
Why the Mean Reversion Strategy Works?
Mean reversion is a key element part of how all financial markets work.
Mean reversion happens because the prices have a tendency to overshoot and undershoot their intrinsic value. These “price anomalies” happens because the impact of new information that hits the market takes time to be digested by the market.
The market participants will take some time to understand the new information as the information is filtered slowly. Additionally, it takes time for the market to establish a fair value.
Secondly, mean reversion trading also works because prices also move based on collective emotions.
What this means for traders is that the price tends to overshoot to the downside a bit more than they overshoot to the upside. This is true because fear tends to be a bigger emotion than greed.
Let’s put the puzzle pieces together and construct our reversion to the mean trading strategy.
Scalping Forex Pairs After US Market CloseI'm sharing a strategy I've used for many years, that is scalping certain forex pairs after the US market closes and before the Asian markets open. During this time there isn't any economic news released so prices have a tendency to oscillate and don't trend which is a perfect environment to use the Buy Sell Bands for a mean reversion strategy.
Technical Trading Option 2: Mean ReversionHello friends,
In the last post, I mentioned the first major technical trading strategy that is available to you, in this I will cover the second and finish this two-part short series of posts.
The moving average is a very simple, but very versatile and useful tool. Averages are just kind of an amazing mathematical beauty in themselves, you can do a lot with them. You can calculate the center of mass using integrals that sum infinitely many terms and divide by infinity. You can quicky sum numbers using them: consider summing the first 100 integers. (1 + 100)/2 = 50.5. This is the average value of each term in the sequence, if you multiply it by the number of terms, you get the sum of the series: 50.5*100 = 5050. You can check this is the sum for yourself. Gauss famously used this technique. Averages are fundamental to integration which is a key part of all of the physics that makes the universe possible.
The moving average of finance is no less graceful or majestic. The markets tend to obey them again and again following unwritten, unknowable laws. To get to the point: as we saw in the last entry, the moving average can be used to identify a trend, but it can also be used as a tool for mean reversion. That such a simple technique can be used profitably is a beautiful thing. I could write an article about why you should keep everything as simple as possible, but not today.
In bitcoin, as you can see, the 200 moving average seems to be part of the technical structure that has caused us to bounce 200% off of it. If you had been watching this long term moving average, it would have worked out pretty well for you. But Shkreli, I hear you say, Bitcoin has only been trading for hardly over 200 weeks, there's not enough data here to suggest it is significant. Yes, that's true. I leave it to you to see if it is relevant in other markets. I'm just here to try to get you thinking about strategy (maybe even inspire you to put it into code so that you can be automated, ask me if you're interested about that..)
The RSI below it is also a very common tool used by the mean reversion trader. The idea is that it tells you by some magical formula that a market is oversold or overbought. In bitcoin, really on any timeframe, it seems that mean reversion is kind of a terrible idea on the short side, but on the long side, it works pretty well as you can see with the weekly RSI data. I've selected the weekly here because it is very important. I didn't want to do two posts of daily charts. I think I am one of the few traders I see who seems not to care at all about short term movements. I believe this gives me a clarity that most do not have. I don't have to worry as much and can just stick to the plan much easier. If you know about the sharpe ratio, you know that optimally you want to be trading very often (quantitatively, probably not manually) but I've always been willing to forgo optimal returns in theory to do what felt right for me. (I am not trying to personally trade anymore - I am moving to quantitative so this doesn't necessarily reflect what I do today, but it's how I cut my teeth in the markets. In reality I am looking to place tens of thousands of trades a year on some strategies)
As is suggested in the name, mean reversion is based on the assumption that prices are going to sometimes perform above average and sometimes below average. You want to be long when they are below average and short when they are above average in simplest terms.
Thus concludes the second main strategy in the technical trader's toolkit. Now that I've narrowed your focus and maybe clarified what you already knew, what are you going to take away from this? How are you going to trade going forward? What do you think is going to make money?
I wish you all the best of luck in your trading endeavors. Always backtest your strategies and be as methodical as you can be.
YoungShkreli
My next post will likely be focused on some element of trading that isn't about seeking alpha, but instead about execution, risk, modelling or something else. I'm not sure, but too much attention is given to TA and setups and this is a mistake.