Last Updated on 12 June, 2021 by Samuelsson
Both short-term traders and long-term investors use a variety of methods in a bid to beat the market. While you may be familiar with the more popular methods of analysis, such as fundamental, technical, and sentiment analysis, some savvy investors make use of seasonality patterns, which have been proven to be consistent and quite profitable. But what is seasonality in trading?
Seasonality in trading refers to any regular and predictable fluctuation or pattern in the price action of certain assets that recurs or repeats over a one-year period. It is a characteristic of the market that explains why the stock market in general and certain individual stocks tends to perform better during certain periods of the year. On the price charts, the seasonality effects are different from the long-term trend — they are specific repetitive movements around the trend line, which occur at a specific time of the year.
In this post, we will treat the topic under the following subheadings:
- What is seasonality in trading?
- Understanding seasonality in trading
- Why do seasonal patterns occur in the financial markets?
- Seasonality examples in various financial markets
- How to trade seasonal patterns: seasonality trading strategy
What is seasonality in trading?
Seasonality in trading refers to any predictable fluctuation or pattern in the price action of certain assets that recurs or repeats over a one-year period. It is a characteristic of the market that explains why the stock market in general and certain individual stocks tends to perform better during certain periods of the year.
So, you may consider any regular and predictable price fluctuation that occurs every year is seasonal. While seasonality patterns have a one-year cycle, market cycles last several years and produce the long-term trends that you see on the price charts. Seasonal patterns are specific repetitive movements around the long-term trend that occur at a specific time of the year.
The concept of seasonality can be seen in many aspects of life, especially in food production. You may ask: What is seasonality in food? Well, one of the most popular examples of seasonality is in weather, and we know that the weather determines both the planting and harvest periods. Invariably, this affects the prices of those commodities and the stocks of relevant companies.
It is not just about food-related stocks, seasonality is seen in other stocks. For example, a company that sells swimming suits will likely make more sales in the summer but may not have a lot of sales during the fall and winter months. As a result, the company’s stock may tend to perform better during the summer than in the winter season, thereby showing some summer-winter seasonality.
Seasonality patterns are seen in the broad market index as well. For example, the S&P 500 Index tends to perform better in certain months of the year than others. Some months have been shown historically to be consistently bullish and some consistently bearish. On Wall Street, you often some seasonality slangs, such as the January Effect, Sell in May, and End of Year Rally.
Because of the regularity of these seasonal patterns, some market participants study the behavior of different financial instruments at different times of the year to see how they can exploit it in their trading. Some assets tend to perform better during the summer, while others perform better during the other seasons of the year. Although seasonality patterns are quite regular and can be exploited, as with every other market pattern, it does not offer certainty. The correlation between the months or seasons of the year and the stock market performance is not a guarantee that the market would behave the same in the future!
In trading, seasonality refers to periodic fluctuations in the price action that occur regularly based on a particular season. A season, here, may mean a calendar season, such as summer or winter; it could also refer to a commercial season, such as the holiday season; or it could mean the various months of the year.
The key thing is that the patterns have a one-year cycle and are fairly consistent. But anything could be responsible for them, such as climatic conditions (colder winter, warmer summer, etc.), expected events (company reporting periods, economic news, etc.), or simply the calendar periods of the year (seasons, months, weeks). It’s considered seasonal once the pattern occurs within a one-year cycle is seasonal.
To understand seasonality in trading, we need to answer these important questions:
What is seasonal time series?
The question could also be asked this way: “What is seasonality in time series?” Well, we know from statistics that some time series exhibit cyclic variation referred to as seasonality, which you can say is the repetitive and predictable movement around the trend line. You detect it by measuring the variable of interest over small time intervals (intra-year intervals), such as days, weeks, months, or quarters.
Time series analysis provides a way to study a dataset, and as you may already know, it has four major components:
- Level: This refers to the base value for the series if it were a straight line.
- Trend: This describes the behavior of the series over time as regards its long-term direction — upward or downward.
- Seasonality: This characteristic describes the repeating patterns or cycles observed in the series.
- Noise: This refers to the variability in the observations that cannot be explained by the model.
These components combine in some way to provide the observed time series. So, they may be added together to form a model like this:
Y = levels + trends + seasonality + noise
Note that while every time series dataset has the level and noise components, the trend and seasonality components may not be present. In other words, a time series may not exhibit any visible trend or seasonal pattern. However, for any time series data sets that exhibit trends and seasonal patterns, such as security prices in the stock market, those components are the most useful features in the series because they have some predictive value.
As you can see, seasonality is a characteristic of a time series in which the variable shows regular and predictable changes that recur every calendar year. Since seasonal patterns are repetitive, you can use them to predict some future observations in the time series. For example, people tend to go on vacation during the December-January holiday period every year. This seasonal pattern may be used to predict the behavior of the prices of things that are commonly used during such vacations. Seasonality is an important characteristic of time series analysis, and it is generally measured by autocorrelation after subtracting the trend from the data.
Note that, in the world of trading, the variable is the price of a financial security, such as stocks, commodities, currency pairs, etc.
What’s the difference between a trend and seasonality?
The trend and seasonality are the key important components of a time series since they both provide some predictive value. However, they’re a little different from each other.
The trend refers to the linear increasing or decreasing behavior of the series over time. It indicates the direction of the series progression — whether it is going upward or downward. To show the trend more clearly, analysts try to smoothen the data. Smoothing involves some form of local averaging of data such that the components of individual observations cancel each other out, thereby showing the trend. One of the most frequently used smoothening technique is the moving average whereby the continuous average of a specified number of data is used to replace the original dataset, and when plotted would look like the picture below:
Seasonality, on the other hand, refers to the repeating patterns or cycles of behavior about the trend over time. It is generally measured by autocorrelation after subtracting the trend from the data to show something like this:
What is seasonal stock?
As we said earlier, the concept of seasonality can be seen in different things, including inventory. Also known as seasonal inventory, seasonal stock refers to the additional inventory kept in expectation of an unusually heavy seasonal demand or for promotional campaigns, which is why it may also be known as promotional stock.
Some stocks are in high demand during particular times of the year. Seasonal demand examples include Christmas, Halloween, and summer vacation shopping. So, inventory managers try to be proactive in preparing for the waxing and waning of demand during these key times so as not to run out of stock. It is not a question of how does seasonality affects demand. This rise and fall in demand are reflected in your sales during these periods, which affect the level of stock.
Since our focus is on seasonality in financial trading, let’s find out why seasonal patterns occur in the financial markets.
Why do seasonal patterns occur in the financial markets?
Knowing why seasonal patterns occur in the financial markets is perhaps one of the most interesting and controversial issues about using seasonality in making trading decisions. While some think that market seasonality could be simple coincidence, others believe that there are fundamental reasons for it.
Some of the reasons that have been suggested are as follows:
- Most human activity tends to have seasonal cycles
- People’s moods at different times of the year (i.e. holidays) affect their spending habits.
- There are always changes in the supply and demand of a financial asset
- Periods of news releases — for example, the periods in which the quarterly financial statements of companies are published — are known to attract increased interest in the financial markets
- There tends to be a surplus supply of certain commodities during the harvest period
- Demand changes during periods of severe climatic conditions (high or low temperatures, storms, etc.)
- Certain payments, including taxes, are made in specific periods of the year
Since the financial markets are made of humans with sentiments and emotions, there’s no way that these factors that affect how humans live and interact with others won’t have an impact on the financial markets.
Seasonality examples in various financial markets
Seasonality patterns are observed in the various financial markets: stocks, commodities, and Forex. Let’s take a look at some of them.
Seasonal patterns in the stock market
Some of the most popular seasonal patterns are seen in the stock markets. In the equity market, seasonality can be seen in both the broad market index and individual stocks.
Seasonality in individual stocks
Some businesses thrive at different times of the year, so the stocks of such companies tend to show some seasonal patterns in their price actions. For example, gasoline prices tend to increase in the summer when cars are used more frequently for vacations, so the stocks of oil-refining companies and hospitality firms are likely to rise during the summer periods. In places that get really hot during the summer, stocks of companies that offer air conditioning solutions may also tend to do better in summer than in other seasons.
Seasonality in the general market
In the U.S. stock market, the S&P 500 Index is used to estimate the performance of the general market. Historically, the index has been shown to perform better in certain months of the year than others. Some months have consistently had bullish or bearish returns.
The bar chart below shows the average monthly returns of the S&P 500 Index from 1964 to 2015. You can see that the market usually performs better at the beginning of the year and towards the end of the year (roughly the winter period) and does poorly from May to the end of September (the summer period). Some slogans used by Wall Street analysts to describe these seasonal patterns include:
- Sell in May and Go Away: The market tends to underperform from the month of May to the beginning of October, probably because of reduced activity in the market as many investors and traders go for summer vacations. The phrase simply indicates that it is best to sell in May and avoid the summer drawdown.
- End of the Year Rally: This is also known as the Santa Claus Rally, and it describes the fact that from October to the end of the year, the market seems to perform well. As investors come back from vacation and resume trading, the market tends to see more trading activities and better performance.
- January Effect: As investors try to offset losing stocks so that they can claim tax losses, bargain hunters move in to buy up the stocks at the beginning of the year, thereby creating a significant buying pressure that drives the market up.
Seasonal patterns in the commodity market
Seasonality patterns are also seen in the commodity markets, including energies (crude oil, natural gas, gasoline, etc.), metals (gold, silver, copper, steel, etc.), softs (corn, rice, coffee, wheat, etc.), and livestock (pork, live cattle, etc.).There are many reasons seasonal patterns are seen in the commodity market, but the most common ones include:
- Climate change
- Consumer habits
Let’s take look at two of the most popular commodities to see the effects of seasonality in the commodity market.
WTI Crude Oil
Crude oil is probably the most traded commodity in the futures markets, and just like the stock market, the crude oil market shows some seasonality patterns. Take a look at the seasonality chart below; you can see how the price of WTI (West Texas Intermediate) crude oil has moved in each month for the 20 years that span from 1999 to December 31, 2019:
From the chart, you can make the following conclusions:
- Except for January, the first half of the year (February – June) is often characterized by a rise in WTI oil prices
- Between July and September, the WTI trades mainly in a range
- WTI oil prices usually tend to decline in the last quarter
Traders can make use of these seasonal patterns in making decisions about entering and exiting trades during the different seasons of the year.
Probably one of the most valuable commodities, gold also shows some seasonal patterns just like other financial markets. Take a look at the seasonality chart for gold below; you can see how the price of gold has moved in each month for the 20 years that span from 1999 up to December 31, 2019:
From the chart, you can make the following conclusions about seasonality patterns in the gold market:
- Historically gold is usually strong at the beginning of the year — January and February
- From March to July, gold usually trades in a range
- Gold tends to be strong in August and September
Seasonal patterns in Forex
Forex seasonality studies show that seasonal patterns are also seen in the currency markets. The USD is always paired with most of the other currencies. So, it has long been the primary driver of fluctuations in exchange rates, and the time of year sometimes plays a role in how the U.S. dollar behaves against various currencies.
Let’s look at the seasonal patterns in EUR/USD because it is the most traded currency pair in the world. In the Forex the seasonality chart below, you can see the performance of the currency pair in each month for the 20 years that span from 1999 to December 31, 2019:
From the Forex seasonality charts, you can make the following conclusions about seasonality patterns in the EUR/USD pair:
- EUR/USD is often weak around January and February
- EUR/USD traditionally declines in November and performed strongly in December
- March, April, and September seems to be a relatively good period for the currency pair
How to trade seasonal patterns: seasonality trading strategy
So far, we have shown that seasonal patterns exist in different financial markets. In the stock market, for example, both individual stocks and the broad market index (the S&P 500 Index) show seasonal patterns but note that seasonality in individual stocks can vary widely from that of the S&P 500 Index. So, you should be careful not to use the patterns in the S&P 500 Index as a basis to trade an individual stock.
Since an index is not a tradable asset, if you want to trade the seasonal patterns in the S&P 500 Index, you will have to trade an ETF that tracks the index, such as the SPDR S&P 500 ETF (SPY), iShares Core S&P 500 ETF (IVV), or Vanguard S&P 500 ETF (V00). However, you should know that, as with every other investment strategy, past performance is not always indicative of future performance when it comes to seasonal patterns.
Nonetheless, here are a few ways you can apply seasonal patterns in your trading strategy:
Use it as a market filter
Using seasonality patterns as a market filter implies that in seasonally unfavorable periods, you stay away from that market. By doing this, you may be able to reduce losses and the level of drawdown in your portfolio, while improving profitability. Let’s explain with the S&P 500 seasonality bar chart that we saw earlier.
From the S&P 500 historical average monthly returns, if you are trading SPY (SPDR S&P 500 ETF), it may appear wise to look for buying opportunities in October and try to sell in April. This way, you are trying to buy when the underlying index is known to perform when and liquidate when the index is known to underperform. So, you will be in the market during the End of the Year Rally, as well as the beginning of the next year, but sell before summer when the index doesn’t seem to do well.
But staying in the market during favorable periods and out of the markets during unfavorable periods is not the only thing you can do with seasonal patterns. In the case of individual stocks and other assets when you can trade in either direction, you can use seasonal patterns to select the securities to short and the ones to avoid. For example, you may go short on securities that are in unfavorable seasons, but when they are in a favorable season, you avoid shorting them.
Use it to determine how much leverage to take
You can use seasonal patterns to determine when to increase or decrease your leverage, depending on whether the security is in a favorable or unfavorable season. When the security is in a favorable season, you may use more leverage to increase your position size. If for any reason you don’t want to completely liquidate your position when the unfavorable season comes, you can reduce your leverage by reducing your position size.