Trading Strategy
Complete breakdown of the mean reversion strategy, parameters, and risk management
đ Strategy Overview
Mean Reversion v1.0
A statistical arbitrage strategy that identifies when prices deviate from their moving averages and takes positions expecting them to revert to the mean. The strategy uses EMA crossovers for trend direction and ATR for volatility-adjusted entry/exit levels.
Strategy Type
Mean Reversion
Markets
BTC, ETH, SOL
Timeframe
1 Hour
đ Technical Indicators
EMA (Exponential Moving Average)
Used to determine trend direction. When EMA20 > EMA50, the market is in an uptrend. When EMA20 < EMA50, the market is in a downtrend.
ATR (Average True Range)
Measures market volatility. All entry and exit levels are calculated relative to ATR, making the strategy adaptive to different volatility regimes.
đ¯ Entry Logic
đ LONG Entry
Trend Confirmation:
EMA Fast (20) > EMA Slow (50) â Uptrend confirmed
Pullback Detection:
Current Price < (EMA Fast - 1.5 Ã ATR)
Price has pulled back significantly from the fast EMA
No Existing Position:
Not already in a position for this market
đ SHORT Entry
Trend Confirmation:
EMA Fast (20) < EMA Slow (50) â Downtrend confirmed
Rally Detection:
Current Price > (EMA Fast + 1.5 Ã ATR)
Price has rallied significantly above the fast EMA
No Existing Position:
Not already in a position for this market
Entry Threshold Explained
The 1.5 Ã ATR threshold ensures we only enter when there's a significant deviation. In high volatility (large ATR), we need a bigger move. In low volatility (small ATR), a smaller move triggers entry. This makes the strategy adaptive.
đĒ Exit Logic
đ Stop Loss
Long Position:
Entry - 1.0 Ã ATR
Short Position:
Entry + 1.0 Ã ATR
Limits losses to ~1% of position size
đ¯ Take Profit
Long Position:
Entry + 2.0 Ã ATR
Short Position:
Entry - 2.0 Ã ATR
Targets ~2% profit on position size
âŠī¸ Mean Reversion
Price crosses back over EMA Fast
Exit when mean reversion completes, securing profit before full target
Risk-Reward Ratio
The strategy maintains a 2:1 risk-reward ratio. Stop loss at 1 ATR (~1% loss) and take profit at 2 ATR (~2% gain). This means we need a win rate above 33.3% to be profitable long-term (current backtest: 47% win rate).
đ° Position Sizing
Position Size (USD)
$100
Fixed size per trade
Max Concurrent Positions
3
One per market (BTC, ETH, SOL)
Max Exposure
$300
3% of initial capital
Leverage
1x
No leverage (spot-like)
đĄī¸ Risk Management
â ī¸ Circuit Breakers
Daily Loss Limit
If daily PnL drops below -3% of equity:
- âĸ Close all open positions immediately
- âĸ Stop opening new positions
- âĸ Auto-reset at midnight UTC
Consecutive Losses Limit
If 3 consecutive losing trades:
- âĸ Close all open positions immediately
- âĸ Stop opening new positions
- âĸ Auto-reset at midnight UTC
đ¸ Trading Costs
Commission (Maker/Taker)
0.04% per side
~$0.04 on $100 position
Slippage
0.05% average
~$0.05 on $100 position
Total cost per round-trip trade: ~$0.18 (0.18% of position). Factored into backtest results.
âī¸ Execution Details
Timing & Frequency
Execution Interval
Every 5 minutes
Candle Check
1-hour candles
Signal Generation
On new candle close
Safety Features
Idempotency
Won't duplicate trades if run multiple times
Kill Switch
Instant disable via config file
State Persistence
Atomic writes, survives restarts
đ Backtest Results (90 Days)
Period: Nov 13, 2025 - Feb 11, 2026
Return
-0.01%
Win Rate
47.06%
Max Drawdown
-0.08%
Total Trades
17
Excellent risk control: Near-flat returns with minimal drawdown demonstrate the strategy's defensive nature. With 47% win rate and 2:1 R:R, the strategy is breakeven as expected. Circuit breakers triggered correctly during testing.
â ī¸ Paper Trading Only: This strategy is running in simulation mode with no real funds at risk. All positions and results are simulated. Real trading requires explicit authorization and additional safety measures.