In some alpha factor papers that we’ll discuss in the next lesson, the academic research discusses findings that are specific to one direction or one tail end of a particular attribute. A practitioner’s approach is to think about extending the interpretation of the academic conclusion, so that it can be more readily applied to general situations. For example, in an alpha factor that we’ll discuss, the curvature of a stock’s price path over time has some predictive value of its future expected performance. Even though the paper itself doesn’t discuss linear trajectories, a practitioner would want to find some meaningful hypothesis about straight lines and how they compare to convex or concave functions. In other words, when a straight line is compared to a convex curve, the line is relatively more concave than the convex curve. By thinking how an academic finding can be applied more broadly to a full range of a particular attribute, a practitioner has a better chance of creating an alpha factor that can more generally be applied to the entire stock universe.