In the ever-evolving landscape of the stock market, savvy investors often seek strategies that can give them an edge. Seasonality trading strategies have attracted attention for their potential to leverage predictable patterns in stock performance. Today, we delve into an intriguing approach that zeroes in on the stock of Sherwin-Williams (SHW), a company renowned for its paints and coatings. This analysis unpacks the nuances of a monthly seasonality strategy and its compelling backtest results that could reshape the way retail investors approach the market.
Company Overview
Sherwin-Williams is a leader in the development, manufacture, and sale of coatings and related products. With a rich history dating back to 1866, the company has grown to become one of the largest paint suppliers in the world. Their product range extends from architectural paints and protective coatings to industrial marine products and automotive finishes, catering to professional, industrial, commercial, and retail customers alike.
Strategy Overview
Our focus is a monthly seasonality strategy applied to Sherwin-Williams (SHW), executed from the close of one month to the close of the next. The strategy involves taking long positions in April, May, July, and November. Spanning from January 2, 2003, to December 30, 2022, the strategy’s duration covers nearly 7,302 days, with an exposure time of approximately 34.28%, implying that the strategy is in the market for about one-third of the time.
Key Performance Indicators
The strategy exhibits an impressive Equity Final of $183,859.55 and an Equity Peak of $184,464.35. It has yielded a Return of 1,738.60%, compared to a Buy & Hold Return of 3,195.24% over the same period. Annualized returns stand at 15.69%, a testament to the strategy’s efficacy.
| Strategy | Buy and Hold | |
|---|---|---|
| Start Date | 2003-01-02 | 2003-01-02 |
| End Date | 2022-12-30 | 2022-12-30 |
| Duration | 7302 days | 7302 days |
| Exposure Time [%] | 34.28 | 99.96 |
| Equity Final [$] | 183859.55 | 343443.06 |
| Equity Peak [$] | 184464.35 | 496455.16 |
| Return [%] | 1738.6 | 3334.43 |
| Return (Ann.) [%] | 15.69 | 19.36 |
| Volatility (Ann.) [%] | 17.71 | 32.62 |
| Sharpe Ratio | 0.89 | 0.59 |
| Sortino Ratio | 1.7 | 1.06 |
| Calmar Ratio | 1.12 | 0.46 |
| Max. Drawdown [%] | -14.07 | -42.46 |
| Avg. Drawdown [%] | -2.96 | -3.25 |
| Max. Drawdown Duration | 504 days | 991 days |
| Avg. Drawdown Duration | 44 days | 28 days |
| # Trades | 60 | 1 |
| Win Rate [%] | 80.0 | 100.0 |
| Best Trade [%] | 29.54 | 3335.89 |
| Worst Trade [%] | -7.99 | 3335.89 |
| Avg. Trade [%] | 4.98 | 3335.89 |
| Max. Trade Duration | 64 days | 7300 days |
| Avg. Trade Duration | 41 days | 7300 days |
| Profit Factor | 11.31 | nan |
| Expectancy [%] | 5.16 | 3335.89 |
| SQN | 4.63 | nan |
Risk Management
Risk analysis shows an Annual Volatility of 17.71% with a Sharpe Ratio of 0.89, indicating a favorable risk-adjusted return. Maximum Drawdown is contained at -14.07%, with an Average Drawdown of -2.96%, and durations for these drawdowns average at 44 days, signaling a resilient strategy during downturns.
Trade Analysis
Over the backtest period, 60 trades were executed with an impressive 80% Win Rate. The Best Trade saw a gain of 29.54%, while the Worst Trade resulted in a loss of -7.99%. The Average Trade yielded 4.98%, with the Maximum Trade Duration at 64 days and Average Trade Duration at 41 days. A Profit Factor of 11.31 and an Expectancy of 5.16% further highlight the strategy’s potential for profitability.
Conclusion
The monthly seasonality strategy for Sherwin-Williams presents an intriguing opportunity for investors seeking to capitalize on seasonal market trends. While the strategy does not outperform the Buy & Hold approach in terms of total return, it offers a significantly lower risk profile, which might be attractive for more conservative investors. As with any strategy, it’s crucial for investors to consider their risk tolerance, investment goals, and the broader market context before implementation.
“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.”