Market Myths

‘Sell in May, go away, come back on St Leger’s Day.’ 

This old stock market saying has been around for donkey’s years, the main problem with it being that not many people know when St Legers Day actually is.

St Leger’s Day this year falls on Saturday 12th September, the date of the St Leger horse race at Doncaster. 

Bankers, not banking

Bankers, not banking

The inference in the saying is that brokers and fund managers will all be on their holidays and living the high life at Ascot and Wimbledon during the summer months, so the market is likely to drift.

It is, of course, complete drivel.  The global nature of markets and the computer-driven functions of investment banks mean that the world continues to turn during the summer months.  And anyone who spent most of this summer on a 3 month jolly would be finding themselves signing on at the dole office long before St Leger’s Day.

Indeed, this year the FTSE 100 opened at 4243.7 on May 1st, but now, with just over a week to go to St Leger’s Day, finds itself over 4800, a gain of over 13%.

Looking to the US, September is notoriously the worst month of the year.  Since 1929, the S&P 500 has delivered an average performance of -1.3%, compared to an average monthly advance of +0.5%.

One explanation for this is that the US tax system encourages underperformance.  The tax year in the US ends in September, so fund managers may look to sell assets with losses to offset any gains made during the year.

This theory does have a vague air of credibility, although one could consider any number of other factors – company results are likely to be reporting on traditionally quiet periods, the hurricane season could result in compromised energy supplies, the crash after 9/11 may have an adverse effect on the long-term trend, and so on.

Ultimately, markets go up and down, and you can cherry-pick one of the many theories to justify any market behaviour in retrospect.  The key is to understand the current and future risks and issues and make a rational investment decision based on them.

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