Individual seasonality vs. monthly seasonality

Why do individual seasonalities deliver excellent results?

Seasonal pattern analysis is a proven approach in stock market investing. It allows investors to identify recurring patterns in the market and derive potential trading strategies from them. While single-day and monthly seasonal patterns have their own merits, there are compelling reasons why single-day seasonal patterns can deliver better performance. In this article, we will explain the advantages of this particular method.

Below we will show why using single-day seasonality (e.g., Sept 15th to Oct 25th) is better than using fixed months as an indicator.

By a single-day seasonal pattern, we mean all seasonal patterns with periods that do not start at the beginning of the month and end at the end of the month but all other periods that begin on any day of the month and end on any other day of the same or any other month, such as the period from Sept. 15 to Oct. 25.

Did you know that seasonal patterns with single dates have a much higher hit rate, and about 90% of all seasonal patterns do not run from the beginning to the end of the month?

Our evaluations and analyses have shown that approximately 90% of all seasonal patterns do not start in the first two days of the month and end in the last two days of the month.

The 10% of seasonal patterns that fit this criterion have, on average, a 25% lower hit rate than seasonal patterns with individual start and end dates.

The numbers show the potential of using individual seasonal patterns. 90% of all seasonal patterns are single periods.

And, of course, the average hit rates are much higher. This also results in a higher Sortino ratio.

The average drawdown is also much lower than with monthly patterns.

The reasons for the better performance of the individual seasonal patterns are that many recurring price developments are related to corporate earnings and share buyback programs. In particular, earnings are spread over separate days.

Example Individual Seasonal Pattern

An excellent example of an individual seasonal pattern is Microsoft stock.

Over the past 20 years, Microsoft stock has performed exceptionally well from October 11 to November 8.

Timespan: 11 Okt. to 8 Nov

Here are the key figures that the seasonal backtest shows for this period.

The backtest already shows which profits have been created by this seasonal pattern in the past.

For completeness, here is the seasonal statistics overview for the Microsoft share.

Example Monthly Seasonal Pattern

As a counterexample, let's take one of the best monthly patterns we have in our data.

November is historically one of the best months for the SPY.

Here is an overview of the monthly performance of the SPY over the last 20 years.

Let's take a closer look at November.

The seasonal pattern shows an upward trend, but as you can see from the highlighted period in the chart, there were also negative days.

The ratios are still ok, but whether you want to use them for a trading strategy is in the eye of the beholder.

The backtest shows more details and shows us that there has always been a negative performance in November. In particular, 2008 offers a negative interpretation, but we have also seen this in the example of Microsoft.

For completeness, here is the statistical overview of the seasonality of the SPY ETF.

Advantages of seasonal patterns with individual days

Finer temporal precision:

Seasonal patterns with individual days provide greater temporal accuracy than monthly patterns. The market can fluctuate wildly within a month, but investors can get more accurate information by looking at separate days within a month. This allows for more targeted identification of trading opportunities and a better timing strategy.

Consideration of events:

Looking at seasonal patterns daily allows investors to account for specific events or holidays that may affect the market. For example, quarterly reports, political announcements, or other significant events can significantly impact stock prices. Investors can better understand these events by examining performance on specific days and incorporating them into their trading strategies.

More precise volatility assessment:

Analyzing seasonal patterns with individual days allows for a more accurate assessment of market volatility. Particular days can have different volatilities, and knowing these details can benefit investors. By focusing on specific days, they can adjust their trading strategy to the individual volatility and better assess potential risks.

Flexibility and adaptability:

Single-day seasonal models offer investors greater flexibility and adaptability. They can adjust their strategy based on market conditions and individual goals. They can identify trends and patterns in real time. This allows for faster response to market fluctuations and better performance.

Effective risk minimization:

Investors can better minimize their risk by looking at seasonal patterns on individual days. They can identify potentially risky days and adjust their strategy by reducing positions or exiting the market. Investors can diversify their portfolios and minimize potential losses by analyzing market dynamics more closely.

Conclusion

Single-day seasonal patterns offer investors many advantages over monthly seasonal patterns. These patterns allow for better market performance through greater temporal precision, consideration of events, more accurate assessment of volatility, flexibility and adaptability, and effective risk mitigation. However, it is essential to note that seasonal patterns should only be one aspect of a comprehensive trading strategy. Further analysis and consideration are required to make informed investment decisions.