Investing in the stock market is often akin to understanding the rhythm of the seasons – each period comes with its own set of patterns that can either herald growth or signify a retreat. Today, we’re delving into a unique approach that leverages these seasonal trends to shape investment strategies. We’re taking a close look at the Procter & Gamble Company (PG), dissecting a decade-spanning backtest of a monthly seasonality trading strategy. Join us as we unpack the intricacies of this strategy and its performance against traditional investment approaches.
Company Overview: Procter & Gamble (PG)
Procter & Gamble, also known as P&G, is a behemoth in the consumer goods industry, boasting a vast portfolio of trusted brands that span across various categories including beauty, health care, fabric and home care, and baby, feminine, and family care. Renowned for products like Tide detergent, Pampers diapers, and Gillette razors, P&G’s offerings have become household staples globally. With its commitment to quality and innovation, Procter & Gamble consistently delivers products that touch and improve the lives of consumers around the world.
Strategy Overview
The trading strategy in focus is built upon the concept of monthly seasonality, exploiting the historical tendency of Procter & Gamble’s stock to exhibit specific patterns during certain months of the year. The backtest spans from January 2, 2003, to December 30, 2022, a duration of 7302 days. The strategy involves initiating long positions from the close of June to July, August, October, November, and December, capturing what has been identified as periods of potential strength. The exposure time to the market is 43.2% of the total duration, suggesting a disciplined approach that targets periods with higher historical returns.
Key Performance Indicators
An initial capital of $10,000 invested in this strategy would have yielded an impressive $72,036.28 by the end of the backtest, with the equity peaking slightly higher at $72,678.55. This translates to an overall return of 620.36%, surpassing the buy and hold return of 494.59%. On an annualized basis, the strategy delivered a return of 10.39%, demonstrating the potential of seasonal investment strategies to outperform more passive, long-term holdings.
| Strategy | Buy and Hold | |
|---|---|---|
| Start Date | 2003-01-02 | 2003-01-02 |
| End Date | 2022-12-30 | 2022-12-30 |
| Duration | 7302 days | 7302 days |
| Exposure Time [%] | 43.2 | 99.96 |
| Equity Final [$] | 72036.28 | 60430.68 |
| Equity Peak [$] | 72678.55 | 63838.64 |
| Return [%] | 620.36 | 504.31 |
| Return (Ann.) [%] | 10.39 | 9.42 |
| Volatility (Ann.) [%] | 12.63 | 19.8 |
| Sharpe Ratio | 0.82 | 0.48 |
| Sortino Ratio | 1.38 | 0.76 |
| Calmar Ratio | 0.54 | 0.24 |
| Max. Drawdown [%] | -19.24 | -38.95 |
| Avg. Drawdown [%] | -2.02 | -2.74 |
| Max. Drawdown Duration | 446 days | 1472 days |
| Avg. Drawdown Duration | 38 days | 36 days |
| # Trades | 40 | 1 |
| Win Rate [%] | 82.5 | 100.0 |
| Best Trade [%] | 21.73 | 505.25 |
| Worst Trade [%] | -10.69 | 505.25 |
| Avg. Trade [%] | 5.07 | 505.25 |
| Max. Trade Duration | 94 days | 7300 days |
| Avg. Trade Duration | 77 days | 7300 days |
| Profit Factor | 7.26 | nan |
| Expectancy [%] | 5.28 | 505.25 |
| SQN | 3.47 | nan |
Risk Management
Risk management is paramount in trading, and this strategy shows a calculated approach to risk with an annualized volatility of 12.63%. The Sharpe Ratio, a measure of risk-adjusted return, stands at 0.822, indicating that the excess return per unit of risk is favorable. The maximum drawdown experienced was 19.24%, with an average drawdown of just over 2%. The average drawdown duration was 38 days, with the longest lasting 446 days, providing insights into the strategy’s resilience and recovery patterns.
Trade Analysis
Throughout the backtesting period, 40 trades were executed, boasting a high win rate of 82.5%. The best trade yielded a remarkable 21.73%, while the worst saw a decline of 10.69%. The average trade resulted in a 5.07% gain, with trades typically lasting 77 days, though the longest trade duration was 94 days. The Profit Factor, which is the gross profit divided by the gross loss, stood at an impressive 7.26, and the expectancy, which estimates the average return per trade, was 5.28%.
Conclusion
The backtest results of Procter & Gamble’s monthly seasonality trading strategy present a compelling case for investors interested in time-specific market trends. While past performance is not indicative of future results, the data suggests that there can be merit in seasonal approaches to stock market investing. As always, it’s recommended that investors conduct their own research and consider their risk tolerance before adopting any new investment 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.”