The next alpha factor that I’d like to share with you is based on the paper titled, Expected Skewness and Momentum. Before we get into the formal definition of skewness, I’d like to give you a hypothetical example that hopefully will guide your understanding as we discuss the conditional skewness and momentum vector. Why conditional? What word do you see in the title? “And”, as a practitioner, it’s often helpful to think of the alpha factors in terms of market mechanics and or behavioral psychology. If you look at which stocks are in the news, some stocks get more of press coverage and social media posts than others. Let’s hypothesize that stocks that tend to get higher than average media attention tend to also become overpriced. What might cause that mispricing? When individual investors are flooded with news about a high flying company, there’s a natural fear of missing out or “Fomo” as the kids are calling it these days. This sets up investors for a situation referred to as attentional bias. Attentional bias is a phenomenon where people focus on some aspect at the expense of focusing on the big picture and are more likely to notice evidence that supports their prior existing beliefs. So, when a stock that is getting lots of news coverage has a high one day return in the past month, this may trigger individual investors to see this as a sign that the stock will keep going up. Their fear of missing out may kick in, so they jump in and buy as well pushing the stock further up. Since this increase may not be based on fundamentals, the market as a whole both institutional investors and individual investors may realize that the stock is over bought and sell, thus starting to push the stock price back down to earth. If this is indeed true, then the maximum one day return in a historical window can be used as a reversal factor which can also be combined with momentum to decide that the stock maybe over bought or oversold. The maximum one day return over a month is the way that we can measure skewness of returns. We’ll explain skew in the next section. Before we go to the next section though, let’s pause and talk generally about alpha factors again. Many of you might be skeptical of this approach as many newcomers to call financer. Surely in the context of this specific factor, you can think of a few occasions in recent memory where the idea behind this factor was wrong, maybe spectacularly wrong. Meaning you can surely think of ideas where a stock went up a lot and then continued going up. Alpha factors though are trying to capture a mispricing, often imperceptible to humans across one, many stocks two, on a relative basis, and three, persistent across time. We are not trying to get very high conviction in any one specific stock. As we discussed in the section about the fundamental law of active management, we can expect that our skill on any one stock will be low, even imperceptibly difficult to distinguish from noise by a human. Skill just has to be marginally better than 50-50 at the single trait level, and then, we can apply it across many stocks to get a complete alpha factor that hopefully exhibits good Sharpe ratio.