From the course: Financial Modeling and Forecasting Financial Statements

The Gap and predictable change

From the course: Financial Modeling and Forecasting Financial Statements

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The Gap and predictable change

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- Okay, I know you're a bit of a nut about sports statistics. - A nut? Well, absolutely. I love keeping track of triple doubles in basketball, OPS in baseball, and greens in regulation in golf. - Oh, doesn't that sound interesting? Okay, so, in your opinion, what's the most impressive statistical accomplishment in the history of sports? - Okay, I think it's the 1.422 OPS registered by the baseball player Barry Bonds in 2004. - Okay, but hardly any of us know what OPS is, so is there another record for which Barry Bonds is known? - Sure, he holds many batting records, including the most home runs hit in one season. That record is 73. - Okay, perfect. This illustrates an important point quite nicely. So, if you could go back in time to the end of the 2001 season, after Barry Bonds had hit his 73 home runs to set the record, what would you have predicted for the number of home runs he would hit the next season? - Okay, so, I'm standing at the end of 2001, after he's hit 73 home runs, forecasting Barry Bonds' home run total for 2002? - Exactly. Let me refine my question. Would you predict that Barry Bonds would hit more or fewer than the record 73 home runs in the next year? - Well, fewer. - Why? - Well, because of the well known statistical phenomenon called reversion to the mean. - Exactly. If you are significantly above the average value this year, you are likely to revert to a number closer to the mean in the next year. In other words, it is highly unlikely for you to set a record every year, year after year. - Okay, fascinating, but how does this relate to financial modeling and financial statement forecasting? - Okay, the same idea of reversion to the mean can be used when making financial forecasts. - Okay, I see. Now, an example is the financial statement analysis case we teach using the numbers for the Gap in 1991. - When we teach our financial statement analysis class, we like to use some old cases. - Yeah, I suppose that's because we ourselves are old. - Yeah, exactly, but we also have learned that some of these old cases actually teach some timeless lessons. - Agreed. As many of you know, the Gap is a clothing store. In 1991, the Gap was doing very well with profit margins substantially above those of other companies in its industry. - For example, the Gap had a gross profit percentage, the different between the selling price and purchase cost, of 40%. At the time, the average in the industry was just 35%. - When we teach this case, we have our students construct a forecast of the Gap's net income for the next year. One of the important factors in that forecast is the expected level of the Gap's gross profit percentage. - Well, the simple question is this. In the next year, will the Gap's gross profit percentage be higher than 40%, equal to 40%, or closer to the industry average of 35%? - Because of competitive pressures, it's unlikely for a company to significantly outperform the industry average forever. - So, in forecasting the Gap's gross profit percentage for the next year, it makes sense to use a number below 40%, a little closer to the 35% industry average, and as it turns out, in the next year, in 1992, the Gap's gross profit percentage had fallen predictably down to 37.3%. - The use of this idea of reversion to the industry mean is one consideration in constructing more accurate financial forecasts of the future. - Okay, by the way, how many home runs did Barry Bonds hit in the next year of 2002? - Good question. 46. Still pretty good, but substantially lower than his record of 73 set the year before.

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