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Investment Thesis
Simple Dynamic Momentum
A relatively simple design to capitalize on changes in momentum in large-cap tech stocks, as well as market conditions. This is a starting submission for entry into the competition. No hyperparameter optimisation has been done - these are the first values used in backtesting.
Key Points
Momentum-Based Stock Ranking:
Annualized exponential regression slope used to sort symbols based on their momentum values, highest momentum stocks take long positions and lowest momentum stocks take short positions
Lookback Period: 90 days to rank the stocks based on momentum
Universe: Includes AAPL, MSFT, GOOGL, AMZN, META.
Adaptive Market Exposure:
Market Condition Assessment: Uses 50-day and 200-day SMAs of SPY to determine bullish or bearish conditions.
Dynamic Allocation:
Bullish Market: 99% long, 1% short.
Bearish Market: 99% long, 1% short.
Aggressively long stratergy used due to high performing nature of chosen stocks combined with high profits seen in 2024 Q1/Q2.
Risk Management:
Trailing Stop-Loss: A 17.5% moving stop-loss on all positions to limit drawdowns. This high stop loss % is used due to the relatively safe nature of the chosen stocks, and a trailing stop loss is used rather than a traditional fixed stop loss to automatically track to stocks movement (which is often upwards).
Rebalancing: Monthly adjustments.
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