Trading Strategies

Trading on Volatility:
Case Study # 2 - Microsoft

In our first article we asked whether we could develop a trading strategy to improve the profitability of a particular stock by buying and selling the same stock depending on where the stock is in its trading cycle. While acknowledging that we cannot accurately predict the market, we did notice that many stocks, even blue chips, have their ups and downs. What if we sold a stock when it was off its recent high by 10% and bought back in when it was off its recent low by the same amount?

Such a strategy works, we noted, if the stock swings more than twenty percent between its peaks and valleys. But lesser swings will produce losses. We tested the method on Barrick Gold using June 1, 1998 to June 30, 1999 as our test period. The results were interesting, to say the least. Barrick bought and held for that period produced a return of 5.4%. Trading according to our formula produced a return of 33.6% after brokerage fees.

Today we're going to look at a stock that virtually doubled in price for the same period to see if trading would have boosted that return even more. The stock is Microsoft. Since Microsoft had a stock split this year, the prices are adjusted for the split. The actual price on June 1, 1998 was $83.75. Split adjusted it was $41.88. The chart below shows the highs and lows when the stock fluctuated more than 10% either way.

And the table below shows the trades made based on an initial sum of $10,000. Shares and valuations are rounded off to the nearest whole share and dollar.

You can see from the first table that Microsoft never dropped more than 20% from its recent high during the period, even with the big market correction during the year. In the end we ended up with exactly the same number of shares we started with. So with Microsoft, there would have been absolutely no advantage to trading the stock per our criteria. In fact, we end up losing $270 in brokerage fees.

However, if we are worried that even Microsoft may some day take a big fall, then our trading strategy costs us little but gives us peace of mind during corrections. Since this study was done in 1999, Microsoft did, in fact, peak at around $120 on Dec. 30th that year. After that it declined steadily and has been changing in a narrow range from $24-30 since mid-2002 (split adjusted that would be $48-60 relevant to our table above, exactly where it was in the fall of 1998).

We've looked at two different stocks now. Both were high quality, solid companies with excellent track records. With Barrick Gold, trading per our criteria turned a poor gain into a large gain. With Microsoft, the strategy did not make any difference.

The Rationale

The rationale for our trading strategy is two fold. One reason, of course, is that we want to increase our profits by taking advantage of fluctuations in the market. The second reason, and the reason why we're looking at this particular strategy, is that we want a simple method that anyone can follow. A method that does not require understanding and calculating market trends, Bollinger Bands, resistance points or any other technical stuff.

This method affords the safety of reducing downside risk to 10% of a stock's value. At the same time, if we have chosen a good solid stock, it gives us a method where we can jump back in without too much cost. If the stock in question, for example, only drops exactly 10% and then climbs again, we only lose 9% of the stock's value for having traded it.

I have since developed a portfolio using a variation of this methodology. Other criteria determine which stocks to pick in the first place. And still others determine if we should bail out of a stock for good.

After doing the first two studies, I was curious to see how the methodology would work with a stock that is on a long run slide with significant fluctuations in between. Our fourth study looks at Loewen Group during a period when it lost over 99% of its value. But first a look at another stock, Tecsys Inc.

Case Study # 1 - Barrick Gold
Case Study # 3 - Tecsys Inc.
Case Study # 4 - Loewen Group
Case Study # 5 - Nortel Networks