The Seasonality Strategy is a systematic trading approach that selects and trades sector ETFs based on historical seasonality patterns. The strategy aims to capitalize on seasonal trends by investing in the ETF with the highest seasonality score, ensuring the score is non-negative.
Q-Score Seasonality Model
The Q-Score Seasonality Model assesses the historical performance of an asset over a specific time frame. Using 20 years of historical data, our model examines the price behavior of an asset over the next five days and assigns a score ranging from -5 to 5:
- -5: Low Seasonality. Indicates a Bearish seasonality
- 0: No Seasonality. No significant seasonal trend
- 5: High Seasonality. Indicates a Bullish seasonality
By leveraging the seasonality score, traders can anticipate potential price movements based on past performance and create advanced strategies. Our Seasonality score looks at the trend for the next 5 days. You can read more about our Q-Score in our dedicated Guide.
Asset Universe
The strategy focuses on the following ETFs:
- XLE (Energy)
- XLF (Financials)
- XLU (Utilities)
- XLI (Industrials)
- XLK (Technology)
- XLV (Healthcare)
- XLY (Consumer Discretionary)
- XLP (Consumer Staples)
- XLB (Materials)
- IYR (Real Estate)
- IYE (Energy Select)
- OIH (Oil Services)
- SMH (Semiconductors)
- IBB (Biotechnology)
Seasonality Strategy Rules
Entry Conditions:
- Identify the ETF with the highest seasonality score (must be ≥0).
- If multiple ETFs have the same score, select the one with the highest average return over the past week.
- Buy at the market open.
Exit Conditions:
- Sell at the market open the next day unless the same ETF remains the top pick (in which case, the position is held).
- If no ETFs meet the criteria, no position is taken.
Trading Costs:
- A commission of $2 per trade is applied (total of $4 per round trip).
Backtesting Period:
- January 1, 2014 – January 31, 2025
Initial Capital:
- $100,000
Performance Summary
Now let’s look at the historical backtest of this strategy and look at the performance versus the Benchmark (S&P 500 Index).
Now let’s look at some Key Metrics.
We can also look at the return distribution across years comparing this with the SPX.
- The Seasonality Strategy significantly outperforms the SPX in terms of cumulative return and CAGR, indicating strong long-term performance.
- The strategy exhibits a relatively low beta, suggesting it is not highly correlated with SPX, which can be beneficial for diversification purposes.
- The high returns in years like 2019 and 2021 showcase the effectiveness of seasonal trends in certain market environments.
And finally let’s look at the distribution of returns by month historically.
Sensitivity to Initial Capital
The strategy was tested with varying capital levels to evaluate its robustness. Larger capital allocations help mitigate the negative effects of commission costs, leading to more stable and consistent performance over time. Performance across different capital allocations is detailed below.
