7 – M4 L1B 07 Risk Factors V Alpha Factors V2

In the coming series of lessons, we’ll go into detail about risk factors and alpha factors. So, what’s the difference, and why do we make this distinction? First, let’s start with how factors, whether risk factors or alpha factors, are the same. The use of factors this is based on the assumption that stocks with similar characteristics may move up or down in similar ways. For example, stocks may exhibit similar price movements if they are also within the same sector or are similar in market cap or based in the same country or have similar fundamentals. Factors represent these common characteristics such as sector, market cap, or market return or the country or book-to-market ratio. If we model the return of a stock as the sum of the contributions from risk factors and alpha factors, then we notice that each of these factors, both alpha and risk factors, contribute to the stock return. In other words, each factor is adding a little bit to the movement of the stock price. However, in practice, risk factors and alpha factors are used to accomplish different goals. We want to use factors to help us learn something about the distribution of expected future returns. Factors could be predictive of the mean of the distribution of expected returns or not. They could also help to explain a significant amount of the variance of the return distribution or not. Factors that significantly help explain the variance of the return distribution are candidates for use as risk factors. We want to find a set of risk factors that explain much of the variance of a portfolio. The reason is so that we can adjust portfolio weights to reduce that variance that’s caused by these risk factors. Reducing the movement of a portfolio that may be attributed to risk factors is how we control portfolio risk. One major risk factor is the market return from the capital asset pricing model. We saw earlier how adjusting portfolio weights to make them dollar neutral also helps to make a portfolio less sensitive to overall market movement thereby controlling risk. Factors that are significantly predictive of the mean of the return of distribution are candidates for use as alpha factors. We want to find alpha factors that are predictive of future price movements after we’ve neutralized price movements using a risk model. For example, if a factor signals that the mean of the expected return distribution is greater than zero, then this signal may indicate that the stock return will be positive in the future which also means it’s a signal to buy. One example of a former alpha factor is the market cap of a stock. Small-cap stocks tend to have higher returns compared to large cap stocks. Factors that are neither useful in explaining the variance nor predictive or the mean of the return distribution would probably not be used as either alpha or risk factors. One example would be days when there are full moons. Even though a full moon may tell you when to expect werewolves or other magical creatures to appear, it probably wouldn’t tell you much about which stocks to long or short.

%d 블로거가 이것을 좋아합니다: