Seasonal Insights Simplify Buying and Selling

Timing can be as critical as the choices we make. In June 1944, as the Allies prepared to invade Normandy, their plans hinged on the weather. Group Captain James Stagg, a meteorologist, warned General Eisenhower that a storm would hit the English Channel if the invasion proceeded on June 5. Eisenhower listened, delaying the operation by a day—saving countless lives. This historical lesson shows a key principle: data-driven decisions, not gut instincts, often lead to better outcomes. Stagg’s role was key not only because of his meteorological expertise but also due to his prior experience leading an Arctic expedition and his leadership at Kew Observatory, where he oversaw the UK’s weather-forecasting efforts. His ability to synthesize complex atmospheric data and convey it clearly to military leaders proved decisive in one of history’s most critical moments.

The Power of Timing

At TradeSmith, we apply this same logic to investing. Instead of relying on intuition, we analyze recurring patterns in stock behavior—seasonality. By scanning decades of price data across thousands of stocks, we’ve identified historically reliable windows for buying and selling. These “green days” occur with remarkable consistency, offering investors a statistical edge. These patterns are not isolated to retail; they span industries, reflecting broader economic and consumer behavior cycles.

Putting It to the Test

Seasonality isn’t a new concept. Commodity traders have long tracked planting cycles, and energy markets shift with seasonal demand. What’s changed is our ability to measure these patterns precisely. Over an 18-year backtest, seasonal trades generated 857% total growth—more than double the S&P 500’s return. Even in 2007, the worst year in the test, the strategy outperformed the market. While past performance doesn’t guarantee future results, the data suggests a consistent opportunity. The foundation for this approach was built by TradeSmith CEO Keith Kaplan, a software engineer by training, who focused on data-driven analysis rather than conventional market theories. His team developed a tool that scans more than 5,000 stocks, identifying seasonal trends with an 83% historical accuracy rate—meaning the patterns appear in eight out of every 10 years. This precision allows investors to stack the odds in their favor, though it remains a tool among many rather than a standalone strategy.

However, relying solely on historical patterns carries risks. Markets evolve, and factors like economic shifts or technological disruptions can alter seasonal trends. Investors should treat seasonality as one tool among many, not a foolproof strategy. Combining it with other analyses—like fundamental or technical indicators—may provide a more robust approach. As markets grow more complex, adaptability remains key. The software’s development also highlights the importance of cross-industry validation; patterns in retail, energy, and commodities are interconnected, reflecting macroeconomic forces. For example, the January Effect, where stocks often rise in early January, and the Santa Claus Rally, a surge in December, are well-documented phenomena that the tool incorporates. Additionally, the software’s ability to pinpoint specific dates—such as Lowe’s optimal window in late August—enables investors to align trades with the most favorable conditions. These insights, combined with the 18-year backtest’s resilience even during the 2007 crisis, show the potential of seasonality as a supplementary strategy. As the tool’s free trial becomes available ahead of the Breakthrough 2026 event, investors can explore these patterns firsthand, testing their relevance in the current market environment.