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Trading Strategies

Trading on Volatility:
Case Study # 1 - Barrick Gold

Trying to predict the market, they say, is a mug's game. It can't be done with any consistency. Nevertheless, there are those who claim to be able to predict trends and seemingly have done so with some success. Using such tools as trend lines, analysis of market breadth, Bollinger Bands, resistance points and so on, they claim to have a finger on the pulse of the market.

One such pundit is David Marantette, formerly editor and publisher of the Goldstock Newsletter. He used "cyclic analysis" in charting 30 major gold stocks and watching their performance. Although any market sector can be used, he prefered gold because it proved to be the most profitable. Based on the signals generated by the group of 30, he had his readers either 100% in or 100% out of a selected group of ten gold stocks.

His newsletter did not look at any other sector. Just gold stocks - you're in, you're out, you're in again. (He did cover gold options and silver futures for readers who can tolerate higher risk.) Since they started in 1973, their method turned $100,000 into almost $10 million. In 1998, a year in which the price of gold on December 31st was almost exactly where it was on January 1st, the Goldstock methodology generated a return of 84.8%.

In any event, I've watched some of my stocks go up and down with fairly significant swings and thought there's got to be a way to turn this volatility into profits. So I decided to study a couple for the period from June 1, 1998 to June 30, 1999. I charted their highs and lows whenever the price moved more than 10%. We started out by looking at Barrick Gold.

Date Price % Change
June 1, 1998 $26.95 n/a
June 30, 1998 $28.00 + 14.3%
Aug. 31, 1998 $20.35 - 27.3%
Oct. 7, 1998 $35.05 +72.2%
Oct. 26, 1998 $30.25 -13.6%
Nov. 5, 1998 $35.05 + 15.9%
Dec. 22, 1998 $28.70 -18.1%
Jan. 11, 1999 $32.40 +12.9%
Apr. 8, 1999 $24.35 -24.8%
May 6, 1999 $33.80 +38.8%
May 25, 1999 $24.65 -27.1%
June 30, 1999 $28.40 +15.2%

In simple terms, the table above shows that Barrick climbed 14.3% from June 1st to June 30th where it peaked. It then declined 27.3% before it started turning around again. And so on.

If we had bought shares of Barrick on June 1, 1998 and held it until June 30, 1999 we would have gained a measly 5.4%. Would we have done any better by trading Barrick? Suppose we adopted a rule of selling the stock when it declined 10% from a high and bought it back again when it increased 10% from a low? The table below outlines the trades starting with $10,000 invested. I've rounded off to the nearest whole share and whole dollar.

Date Interim Highs & Lows Trade Price Shares (after trade) Value
June 1, 1998 $26.95 $26.95 371 $10,000
June 30, 1998 $28.00 $25.20 0 $9349
Aug. 31, 1998 $20.35 $22.39 417 $9349
Oct. 7, 1998 $35.05 $31.54 0 $13,152
Oct. 26, 1998 $30.25 $33.28 395 $13,152
Nov. 5, 1998 $35.05 $31.54 0 $12,458
Dec. 22, 1998 $28.70 $31.57 395 $12,458
Jan. 11, 1999 $32.40 $29.16 0 $11,518
Apr. 8, 1999 $24.35 $26.79 430 $11,518
May 6, 1999 $33.80 $30.42 0 $13,080
May 25, 1999 $24.65 $27.12 482 $13,080
June 30, 1999 $28.40 $28.40 0 $13,689

Deducting $27 a trade for brokerage fees we are left with $13,365, a very respectable gain of 33.6% and a far sight better than the 5.4% achieved by buying and holding the stock. It's not difficult to see why David Marantette of the Goldstock Newsletter, using far more sophisticated tools to pick buy and sell points, could come up with a return of 84.8%.

Note, however, that the profitable trades only occur when the spread between a high and low is greater than 20%. In our example above, only four of the eleven spreads met that mark. But if we discount the first and last one which are arbitrary and incomplete, four of nine spreads were profitable.

If a stock fluctuates a lot but fluctuations greater than ten percent are also less than twenty percent, this will not work.

This particular example looked at a stock that ended up marginally higher after 13 months. Next we'll look at one that ended up substantially higher after 13 months and see if active trading using this formula would have improved the profits.

Case Study # 2 - Microsoft
Case Study # 3 - Tecsys Inc.
Case Study # 4 - Loewen Group
Case Study # 5 - Nortel Networks

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