Investors often seek patterns in the stock market to guide their trading decisions. Seasonality, the recurring tendencies of stock performance during certain times of the year, can provide intriguing opportunities for the astute investor. Today, we delve into a compelling seasonal trading strategy that has been applied to AbbVie Inc. (ABBV), a biopharmaceutical giant. With a decade of backtesting results in hand, we present a comprehensive analysis designed to illuminate the prospects and challenges of this time-based approach.
Company Overview
AbbVie Inc., a renowned name in the biopharmaceutical industry, has an impressive portfolio of products that address critical health issues across a range of medical fields. From its blockbuster immunology drugs that treat conditions like rheumatoid arthritis to its advancements in oncology, AbbVie has been at the forefront of innovation. The company’s commitment to research and development is evident in its robust pipeline, which promises to sustain its growth by continuously bringing new therapies to market. By focusing on key therapeutic areas, AbbVie not only improves patient outcomes but also enhances shareholder value over time.
Strategy Overview
The trading strategy in focus exploits monthly seasonality patterns in ABBV’s stock performance from close-to-close. It operates with the premise that certain months exhibit predictable trends that can be leveraged for profit. Specifically, the strategy involves taking long positions during the months of February, April, May, October, November, and December, and a short position in January. Spanning from January 2013 to December 2022, this strategy was active for approximately 50.64% of the time, reflecting a moderate exposure to the market.
Key Performance Indicators
The backtest results of this monthly seasonality strategy are nothing short of impressive. Starting with an initial capital of $10,000, the strategy achieved a final equity of $85,014.78, with a peak at $86,808.35. This translates to a remarkable return of 750.15%, significantly outperforming the buy and hold return of 593.42%. When annualized, the strategy’s return stands at 23.89%, showcasing its ability to consistently grow capital over the long term.
| Strategy | Buy and Hold | |
|---|---|---|
| Start Date | 2013-01-02 | 2013-01-02 |
| End Date | 2022-12-30 | 2022-12-30 |
| Duration | 3649 days | 3649 days |
| Exposure Time [%] | 50.64 | 99.92 |
| Equity Final [$] | 85014.78 | 70309.72 |
| Equity Peak [$] | 86808.35 | 73584.82 |
| Return [%] | 750.15 | 603.1 |
| Return (Ann.) [%] | 23.89 | 21.55 |
| Volatility (Ann.) [%] | 23.33 | 33.59 |
| Sharpe Ratio | 1.02 | 0.64 |
| Sortino Ratio | 1.97 | 1.12 |
| Calmar Ratio | 1.06 | 0.48 |
| Max. Drawdown [%] | -22.5 | -45.08 |
| Avg. Drawdown [%] | -3.41 | -3.82 |
| Max. Drawdown Duration | 538 days | 1043 days |
| Avg. Drawdown Duration | 36 days | 40 days |
| # Trades | 30 | 1 |
| Win Rate [%] | 83.33 | 100.0 |
| Best Trade [%] | 27.02 | 603.31 |
| Worst Trade [%] | -8.29 | 603.31 |
| Avg. Trade [%] | 7.4 | 603.31 |
| Max. Trade Duration | 94 days | 3647 days |
| Avg. Trade Duration | 61 days | 3647 days |
| Profit Factor | 16.35 | nan |
| Expectancy [%] | 7.76 | 603.31 |
| SQN | 3.09 | nan |
Risk Management
In assessing risk, we look at the volatility of the investment returns, which for this strategy was 23.33% on an annual basis. The Sharpe Ratio, a measure of risk-adjusted return, was 1.024, indicating that the strategy provided a balanced profile of risk and reward. The strategy endured a maximum drawdown of 22.50%, with an average drawdown of 3.41%. The longest drawdown lasted 538 days, while on average, drawdown periods were relatively short at 36 days.
Trade Analysis
Throughout the backtest period, the strategy executed 30 trades with an impressive win rate of 83.33%. The best trade yielded a 27.02% return, while the worst trade resulted in an 8.29% loss. The average trade provided a gain of 7.40%, with the longest trade lasting 94 days and the average trade duration being 61 days. The Profit Factor, a ratio of gross profits to gross losses, was a remarkable 16.35, and the Expectancy, the average amount earned per trade, was 7.76%.
Conclusion
The backtest results of the ABBV seasonal trading strategy paint a picture of a robust approach to equity growth that can outperform a passive buy and hold strategy. The combination of high win rate, reasonable drawdowns, and impressive profitability metrics suggests that this seasonal strategy, if executed with discipline, could be a valuable addition to a retail investor’s arsenal. As always, prospective traders should consider their risk tolerance and investment goals before adopting any new strategy.
“Make the invisible visible. My goal is to shine a light on the subtle seasonal signals in the stock market, providing investors with the insight needed to make informed decisions. By breaking down the complexities of seasonality, I strive to empower our audience with knowledge and foresight, turning data into action.”