Copy Trading Master’s Winning Strategies Review — Episode 79

Easy Copy, Smart Trade! Discover the winning strategies of our popular traders.

1. Copy Trading Master’s Introduction

User Nickname: Ray

Trader’s Profile: https://www.lbank.com/copy-trading/lead-trader/LBA3D77497

Trading Style: Short-Term Swing Trading

2. Trade Operation Recap

Opened a full-position 5x leveraged long on $TRUMP at an entry price of 15.228 USDT and closed at 15.991 USDT, achieving a single trade ROE of +25.06%. See the chart below:

3. Trade Review

3.1 Market Background

1) February 5, the ADP employment report showed that the U.S. job market remains strong. Employment increased by 183,000, significantly exceeding the expected 150,000, marking the highest level since October last year. Additionally, December’s data was revised up to 176,000. Despite a decline in job openings and slower wage growth, companies continue to hire steadily, and layoffs remain limited.

The Federal Reserve is closely monitoring the labor market to determine the pace of rate cuts. Last year’s rising unemployment led to expectations of a 1% rate cut, but the recent job market rebound has prompted Powell to describe it as “fairly stable.” Moreover, uncertainty surrounding Trump’s tariff policies adds another variable to future interest rate decisions. The market expects January non-farm payrolls to grow by 169,000, with the unemployment rate remaining at 4.1%.

The ADP report showed that the service sector experienced robust expansion, adding 190,000 jobs, while goods-producing industries lost 6,000 jobs, with manufacturing further declining by 13,000 positions.

• Trade, transportation, and utilities: +56,000
• Leisure and hospitality: +54,000
• Education and healthcare services: +20,000

ADP Chief Economist Nela Richardson noted that the job market started 2025 strong, but industry discrepancies remain significant. Consumer-driven industries continue active hiring, while business services and production sectors show sluggish growth.

2) February 7, the January U.S. non-farm payroll report showed slower job growth but sustained resilience. Payrolls increased by 143,000, below expectations, but the previous two months saw an upward revision of 100,000 jobs. The unemployment rate fell to 4.0%.

Stronger-than-expected wage growth indicates that inflationary pressures persist in the labor market.

Wall Street generally believes that, despite cooling, the job market remains stable, giving the Federal Reserve no immediate reason to cut interest rates. The likelihood of a March rate cut has decreased. Several institutions pointed out that revised job data and wage growth justify the Fed keeping interest rates unchanged.

Additionally, uncertainty regarding Trump’s policies has raised concerns, particularly regarding immigration and tariffs, which could impact the labor market. A decline in immigration could drive up wages, while tariffs could suppress job growth. The White House commented that the report indicates weaker-than-expected economic performance under Biden, underscoring the necessity of growth-oriented policies.

U.S. consumer confidence hit a seven-month low, while one-year inflation expectations reached a 15-month high,causing concerns over price stability. The February preliminary University of Michigan Consumer Sentiment Index dropped to 67.8, the lowest in seven months. It was expected to rise slightly from January’s final reading of 71.1 to 71.8.

The February one-year inflation expectation came in at 4.3%, the highest since November 2023, compared to a 3.3% forecast and 3.3% in the previous period.

The February five-year inflation expectation was 3.3%, slightly above the 3.2% forecast and previous reading.

The February University of Michigan Consumer Expectations Index dropped to 67.3, the lowest since November 2023.

U.S. one-year inflation expectations rebounded above 4%, hitting a one-month high, weakening the market’s expectations for Fed rate cuts. U.S. consumer inflation expectations for the next 12 months rose to 4.3%, the highest in 15 months. Traders now anticipate that the Fed may only cut rates once in 2025.

The S&P 500 index fell 0.4%, the Dow declined 0.25%, the Nasdaq dropped 0.81%, and the semiconductor index lost 1.26%.

The U.S. 10-year Treasury yield surged above 4.5%, hitting a daily high. During the U.S. non-farm payroll report release at 21:30 Beijing time, it briefly plunged to 4.3803% before quickly rebounding.

The 2-year U.S. Treasury yield climbed above 4.27%, reaching a daily high. It initially dropped from around 4.24% to below 4.16% following the non-farm payroll report release but quickly rebounded.

3.2 Trade Analysis

From February 3 to February 10, 2025, $TRUMP exhibited a downward consolidation pattern on the 4-hour K-line chart. Following a sharp decline on February 10, $TRUMP formed a long lower shadow around the Fibonacci extension level of $14.3, while the RSI showed a bullish divergence. Given these signals, a short-term long position may be considered. The trading background is illustrated in the chart below:

1) From February 8 to 9, mainstream cryptocurrencies experienced a consolidation phase, while BSC ecosystem-related tokens saw an upward surge. Among them, $TST attracted the most attention, standing out as the leading performer in this rally and driving the entire sector higher.

2) In the early hours of Monday, February 10, the market underwent a sharp decline, with ETH and other major cryptocurrencies quickly rebounding after testing the lower boundary of the ascending flag pattern. From a broader perspective, the overall structure remains intact, aligning with expectations of short-term wide-range consolidation.

At the same time, $TRUMP found support at the Fibonacci extension 0.382 level, with trading volume increasing significantly. On the 1-hour K-line chart, a long lower shadow appeared, indicating strong buying support at this level. See the chart below:

3) On the morning of February 10, the crypto market saw an overall rebound, with $TRUMP repeatedly forming lower shadows on the 15-minute chart, indicating strong buying support. Entering a long position at this level generally offers a higher probability of success, with a stop-loss set near the lower shadow and a take-profit target based on nearby resistance levels and key VPVR zones, ensuring a risk-reward ratio greater than 2.

Later, $TRUMP faced resistance near $16, showing signs of selling pressure, prompting an exit from the position. See the chart below:

3.3 Winning Strategies Summary

Mean Reversion Trading: Capturing High-Probability Opportunities Using Market Reversion

Mean Reversion Trading is a strategy based on the concept that market prices tend to revert to their historical average after deviating significantly. This approach is widely used in range-bound markets and trend retracements, with the core principle being that extreme price deviations often lead to a return to the mean. This article explores the fundamental concepts, key technical indicators, trading strategies, and risk management techniques of mean reversion trading, helping traders increase their success rate and achieve sustainable long-term profitability.

1) Fundamental Concepts of Mean Reversion Trading

Market prices do not move in a straight line; instead, they oscillate around a certain mean value. When the market experiences a short-term extreme deviation (such as a sharp rise or drop), prices typically revert to the mean over time.

Core Logic of Mean Reversion Trading:

• Short-term deviation = Opportunity: When prices stray far from their historical mean, the market may become overbought or oversold, signaling a potential reversion to the mean.
• Price movements are not random: Market fluctuations often follow statistical patterns, where metrics like mean and standard deviation help identify extreme price conditions.
• Market sentiment drives price fluctuations: Panic selling or euphoric buying often causes short-term market imbalances, followed by a return to rationality.

Mean Reversion Trading is Suitable for:

1. Range-bound markets (prices fluctuate within a defined range).
2. Retracements in trending markets (prices temporarily deviate from the mean before resuming the trend).
3. Various financial markets, including stocks, forex, and crypto markets.

2) Key Indicators for Mean Reversion Trading

To identify the degree of deviation from the mean, traders typically use the following technical indicators:

1. Moving Averages (MA)

• Simple Moving Average (SMA): Calculates the average price over a specified period, with common settings being 20-day, 50-day, and 200-day SMAs.
• Exponential Moving Average (EMA): Assigns greater weight to recent prices, making it more suitable for short-term trading.
• Trading Approach: When prices deviate significantly from the moving average, they may revert to the mean, creating potential trading opportunities.

2. Bollinger Bands

• Bollinger Bands consist of three lines:
• Middle Band (SMA)
• Upper Band (+2 standard deviations)
• Lower Band (-2 standard deviations)
• When prices touch the upper band, the market may be overbought, increasing the likelihood of reverting to the middle band.
• When prices touch the lower band, the market may be oversold, suggesting a potential move back to the middle band.
• Trading Approach: When prices deviate significantly from the upper or lower bands, traders can look for opportunities to trade back toward the middle band.

3. Relative Strength Index (RSI)

• RSI below 30 = Market is oversold, increasing the chance of a mean reversion.
• RSI above 70 = Market is overbought, suggesting a potential return to the mean.
• Trading Approach: RSI can be used in combination with moving averages or Bollinger Bands. When RSI enters extreme levels, traders can look for mean reversion setups.

4. Fibonacci Retracement

• When prices pull back to the 0.382 or 0.618 Fibonacci retracement levels, they may resume the previous trend.
• Trading Approach: If prices stall near key retracement levels and other indicators confirm a mean reversion signal, traders can identify entry opportunities.

3) Mean Reversion Trading Strategies

The core of mean reversion trading lies in identifying opportunities where prices deviate significantly from the mean and profiting when they revert. Below are some common strategies:

1. Bollinger Bands Mean Reversion Strategy

Applicable Market: Range-bound markets (prices fluctuating within a defined range).

Strategy Logic:

• Go long when the price touches the lower Bollinger Band and RSI is below 30.
• Go short when the price touches the upper Bollinger Band and RSI is above 70.
• Take profit at the middle Bollinger Band or at the 0.382/0.618 Fibonacci retracement levels.
• Set stop-loss 2–3% outside the Bollinger Bands to prevent losses in case of extreme market movements.

2. Moving Average Reversion Strategy

Applicable Market: Trending markets (seeking pullback opportunities).

Strategy Logic:

• When the price moves significantly away from the 20-day or 50-day moving average and an overbought/oversold signal appears, look for mean reversion opportunities.
• In an uptrend, buy when the price pulls back to the 50-day moving average.
• In a downtrend, short when the price rebounds to the 50-day moving average.
• Confirm reversion signals using RSI or increased trading volume.

3. RSI Mean Reversion Strategy

Applicable Market: Range-bound markets or trend retracements.

Strategy Logic:

• Look for mean reversion signals when RSI enters the overbought (>70) or oversold (< 30) zone.
• Combine with key support/resistance levels or extreme deviations from Bollinger Bands to increase accuracy.
• Take profit when RSI recovers to around 50, and set a stop-loss 2–3% beyond the extreme level.

4. Risk Management & Position Sizing

The core risk of mean reversion trading is that the market may continue deviating in extreme conditions. Strict risk control measures are essential.

1. Set a Reasonable Stop-Loss

• Place stop-losses 2–3% outside support/resistance levels, moving averages, or Bollinger Bands.
• Avoid trading without a stop-loss to prevent excessive losses in prolonged trends.

2. Maintain a Favorable Risk-Reward Ratio

• Ensure a minimum risk-reward ratio of 1:2 or higher (e.g., if stop-loss is 2%, take-profit should be 4% or more).
• Focus on key mean reversion levels and ensure price returns to the trend before taking profit.

3. Avoid Counter-Trend Trading

• Do not blindly trade mean reversion in strong trending markets.
• If the market breaks through key support/resistance, reassess the trade opportunity.

4. Use a Scaling-In Approach

• Mean reversion can take time, so enter positions gradually to reduce risk.
• Example: If RSI drops below 30, enter a partial position first. If further oversold, add more.

5. Conclusion

Mean reversion trading identifies extreme market deviations to capture opportunities when prices revert to the mean. Indicators such as Bollinger Bands, Moving Averages, and RSI help traders find high-probability entry points. However, markets do not always revert to the mean, making strict risk management crucial.

Successful mean reversion traders continuously refine strategies, learn from experience, and adapt to different market conditions. With precise signal identification, proper position sizing, and patience in waiting for optimal entry points, traders can achieve consistent profits across various market environments.

Note: Personal opinion, for reference only. Opportunities and risks abound, always do your research before investing.

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