The Conceptual Foundations of Investing

7CAN HISTORY BE TRUSTED?

The financial media are constantly comparing current market behavior with historical periods. But what exactly can an investor learn from financial market history? That turns out to be a difficult question to answer and it depends on three key concepts: data mining, stationarity, and model specification. Although the concepts may not be familiar, there is some added good news here. All three, but particularly the first two, have applications to random events in other walks of life.

Remember that back in Chapter 1 we concluded that there cannot be any clearly demonstrable historical patterns in stock returns that can be exploited to beat the market. If there were, sophisticated investors armed with the latest computers and software would find them, exploit them, and thereby eliminate them. So if history is to provide some clues to the future performance of asset prices, those predictions cannot be simple, obvious ones. And that is where data mining, stationarity, and model specification enter the picture. Before historical data can be properly interpreted, the potential impact of all three must be considered. The best way to see why is to start with one of the most famous and controversial alleged patterns in historical stock market returns: the small firm effect.

In 1981, as part of his PhD dissertation, Rolf Banz discovered an interesting phenomenon. What he called “small stocks,” that is the stocks of companies with small market capitalization, had ...