V.14:8 (333-337): The S&P 500 Seasonal Day Trade by William Brower, C.T.A.

V.14:8 (333-337): The S&P 500 Seasonal Day Trade by William Brower, C.T.A.
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The S&P 500 Seasonal Day Trade by William Brower, C.T.A.

Is there a particular day of the week within a month that offers the most opportunity? Here's a trading system based on the best days of the week for trading Standard & Poor's 500 futures.

Much research has been done on seasonal trading. Originally, the concept derived from the theory that there had to be certain times of the year when it is better to buy and other times when it is better to sell. If you take a commodity and run a simulation in which you pair up all possible entry days with all possible exit days in a given year, you should be able to locate the best days to trade. If you perform this task over several years of data, it is possible some patterns will appear to identify those days with the highest probability of success for both long and short trades.

In 1994 I was present at a speech given by statistician Sheldon Knight that shed new light on this old trading strategy. Knight runs a company using statistics in processing financial data and has more than 30 years' experience in computerized analysis of stocks and futures. During the presentation in 1994, Knight reasoned that seasonal trading approaches were ineffective because commodity futures prices react to government reports and other events based on a monthly calendar, not on a yearly one. Many government reports are released not on the nth day of the calendar year, such as the fifth of every month, but on predetermined positions within a given month. For example, employment data comes out on the first Friday of every month, while money supply figures come out every Thursday. Likewise, the producer price index comes out on the second Wednesday of the month and export sales numbers are released on the fourth Thursday.

Armed with this insight, Knight forged the concept of a seasonal trading system based on the day of week in a given month. He developed the K-data timeline method, which, according to him, was almost a successful position trading system, except for the sizable drawdowns. This was later improved upon to include the influence of the actual first notice days. Recalling Knight's work in this area, I decided to use his concepts to develop trading systems.

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