As much as possible for each symbol. Often dating back to companies Initial Public Offerings (IPOs).

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An expected price move based on historical data that has shown similar price movements in the past. To read more on seasonal patterns please check out this other blog highlighting seasonality trading strategies

Additionally, we wrote an in-depth blog about Seasonality here: What is Seasonality in Trading?

Public companies report their earnings either quarterly or at least annually. These moments where companies share their earnings estimates, earnings per share and revenue forecasts can present very unique seasonal patterns in the data. Large portfolio managers often look to accumulate shares ahead of the released numbers while prudent risk managers and market makers look to hedge any existing exposures. These natural market dynamics create powerful seasonal tendencies and directional patterns in the data that can be observed through seasonaltrading.com’s powerful tools and watchlists.

Often seasonality presents itself in commodities or stocks that have natural operations or business dealings around certain periods of the calendar. For example, retail stocks experience spikes in sales volume, revenue and foot traffic during the holiday season while farmers and commodity producers experience seasonal harvest and planting seasons which make natural opportunities for end consumers and purchasers to hedge.

Spread trading is most common in commodity markets where deliverable future contracts have an expiration date. A trader may seek to buy the March contract and simultaneously sell the June contract. This position or difference between the two contracts is referred to as a spread. Spreads between different expirations or different commodities altogether can exhibit their own seasonal patterns and tendencies.

Spread trading is very common among professionals, commercials, and hedge funds alike. These are often less looked at by retail traders as it is often difficult to find accurate quotes of the spread itself. However, we aim to provide not only accurate pricing but seasonality insights for as many spreads as we can cover.

Swing trading usually consists of holding a position for more than a day and often a few days, weeks or even months while the trading position matures. Looking for shorter-term directional movement is often harder than long-term investing which focuses on the underlying business’s fundamentals. Seasonality and seasonal trading can often provide solid reasoning and logic as well as narrow the symbol universe for traders looking to enter profitable swing trades. Swing traders often lean on seasonality as a primary factor in their trading decisions due to the statistical nature and grounded logic behind the data.

To learn more about Swing Trading with Seasonals please check out this full guide here: Seasonal Swing Trading Guide

Seasonal trading is one of the most popular approaches to financial markets and investing with success stories dating back hundreds of years. Many commodity and stock traders observed patterns that continue to this day. The stock trader’s almanac and other published sources document the history of trading seasonals quite well. Seasonality is often overlooked due to human nature’s desire to overcomplicate things that seem to require complexity. However, many traders have shown that seasonal trading can greatly reduce the complexity while still approaching the market in a sound manner.

Stocks and Exchange Traded Funds (ETFs) demonstrate seasonal opportunities of all shapes and sizes. The retail sector of the economy undoubtedly goes through an increase in revenue, sales, and more during the holiday season. Other parts of the economy like the energy sector have seasonal fluctuations as well during weather changes. No matter the industry or sector there is usually one or more seasonal factors that can affect the stock trading. A savvy investor should always consult seasonal patterns when stock trading to avoid buying before a seasonal lull or selling before a potential seasonal uptrend.