Ready for a profitable summer? Coca-Cola will be ready, as it is the best time of the year for the company. This strategy explores a beautiful seasonal pattern that appears in KO stocks with the arrival of spring.
Inspiration
When we say summer, it means the summer period in the northern hemisphere, where the majority of the company's revenue and profits are generated.
Contrary to the name of the strategy, we will not be buying KO stocks in the summer. Instead, statistically, we can enjoy profits from a strategy where we buy stocks in March and sell them at the beginning of June. As usual, Wall Street buys much earlier and sells to the crowds of retail investors who remember on the beach that Coca-Cola is a cool company.
Key components
Exploration of the company's preparations for the summer season, which is a significant part of its business.
The strategy is based on clear dates. We completely ignore trends, news, company valuation, and the overall market situation.
Entry Rules
Entry is proceeded on the first working day of March.
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Exit Rules
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The exit occurs "On Bar Close" on June 6th or the next day if it is a day off.
Backtest 1, $ Money Management
In this variant, we invest a constant amount of $100k in each trade.
We are testing the period of the last 44 years.
Capital chart for this test:
Test results:
The average annual result was over 7%, which, when using capital for 27% of the year, gives an annualized return of approximately 26%.
*The pattern was also successfully tested on a previous period from 1962 to 1980, where the win rate was 61%, the average return was 4.95%, and the annualized return was 20.2%.
Backtest 2, % Money Management
In this backtest, we invest in the strategy with a constant 100% of the current capital (with an initial capital of $100k). This causes the value of the position to change proportionally with the increase or decrease in capital. The rest of the parameters remain unchanged.
The capital chart for this test looks as follows:
Basic statistics resulting from the test:
The maximum open drawdown is shown on the chart and was 34% during the Covid crash in 2020. Holding onto this position until June resulted in a loss of about 11% in that exceptional year. If a hypothetical stop loss of 25% was applied, the loss in that year would have been 25% instead of the actual 11%. This is a classic example of how stop losses often does not improve strategies.
Applying a percentage-based money management strategy and reinvesting all profits in the next trade resulted in a 5x increase in strategy income over the years. The total profit from the initially invested $100k amounted to $1.5M.
Additional information about the strategy
SL & TP
The strategy does not use typical stop loss and take profit levels, although they can potentially be implemented. According to our tests, for most ETF and stock strategies, SL settings worsen the results (see why). The diversification within the strategy portfolio serves as protection against the strong impact of any price changes in individual stocks on the entire portfolio. However, the company KO is considered a defensive stock and is seen as a safe haven even in turbulent times.
Market regime
The strategy has been tested in all major market regimes and has performed well in different periods, despite its simplicity.
Trading costs
The backtests include trading costs and slippage typical for the strategy, which were observed in real account tests with the Alpaca broker (detailed study). With a diversified portfolio of stocks and strategies, transaction costs can significantly impact your profit or loss, so take the time to thoroughly test and choose a broker.
Robustness
The strategy was not generated automatically or optimized automatically to fit the historical data (read why).
The main concern with seasonality strategies is the low number of trades. Seasonal patterns, by their nature, will never have a large number of trades.
Recommended instruments
The primary instrument is KO. Similar results can be achieved by using PEP stocks, which can be used interchangeably.
Pattern Day Trader
The strategy is also suitable for use on smaller accounts. The holding period is more than 68 business days, which of course does not meet the PDT requirement.
Correlation with other strategies
The strategy aligns with trends related to the spring season. It will therefore be correlated with strategies that trade during this period. The results show that KO is an exceptional instrument, supported by strong business logic, which is in our opinion worth using. Visit the correlation page.
Summary & strengths and weaknesses of the strategy
The KO Summer Rally strategy is another good example of how seasonality works not only in nature but also in financial markets.
The results speak for themselves. The backtest you see above covers 44 years, but we have also studied the previous 20 years and it worked then as well.
The strategy is very easy to implement, even manually. If you value your time, we suggest entrusting this work to simple and effective algorithms, so you don't have to worry about keeping track of deadlines, especially since by using capital precisely only for part of the year, you can use multiple systems simultaneously.
If you have doubts about whether it is worth exiting punctually or whether you should hold KO stocks for the following summer months, take a look at this result:
The main concern that can be raised about seasonality strategies is the number of transactions. Seasonal patterns, by their nature, will never have a large number of transactions. What is more important in these strategies are:
Consistency of the pattern with nature, business patterns, or consumer behavior patterns.
A representative number of years - we consider a minimum of 15-20 years.
A longer period of the pattern. We use patterns that last at least a few weeks, preferably months.
There have been many interesting scientific studies on seasonal patterns in financial markets. They confirm that seasonality can often have greater strength than trends. We enjoy studying and exploring them for you. However, we assume that patterns can evolve. That's why we review and make any necessary adjustments to our seasonal strategies once a year. The updated versions will be available to you on this website.
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What do you get in the package for this strategy:
An SQX file ready to be used on the Algocloud and StrategyQuant platforms.
Pseudocode that describes all the rules in an easy-to-understand way.
Disclaimer
The results obtained from historical data do not guarantee future outcomes. The effectiveness of a strategy can change over time. Backtesting is a tool that allows for the analysis and evaluation of an investment strategy based on historical data. Various factors, such as market changes or economic conditions, can influence the effectiveness of a strategy over time.
Investing always involves risk. This material is not investment advice. We share our experience and algorithms for educational purposes. We make efforts to ensure that our algorithms are error-free, but neither we nor the tools we use guarantee the absence of technical issues. Any decisions to use a particular strategy are made at your own risk and should be preceded by careful understanding and verification. You should always carefully consider your investment goals and risk tolerance before making investment decisions.
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