By Hongzhi Chen
An alpha has multiple definitions. The most widely used definition we use is: a computer algorithm used to predict financial instruments’ future movements. Another commonly used term is alpha value, which is the value we assign to each instrument, proportional to the money we use to invest in it. As we talk about alpha, we generally refer to the first definition. When we talk about alpha value, we refer to the second.
Before we talk more about alpha design, let’s study a simple example to get a better understanding of what an alpha looks like.
Say we have $1M capital and want to invest continually in a portfolio consisting of two stocks: Google (GOOG) and Apple (AAPL). We need to know how to allocate our capital between these two stocks. If we do a daily rebalance of our portfolio, we need to predict the next few days’ return of each stock. How do we do this?
There are a lot of things that can affect the stock prices, such as trader behavior, news, fundamental change, insider behavior, etc. To make things simple, we can deconstruct the prediction process into two steps: first, we predict stock return using a single factor like news; second, we aggregate all different predictions.
As the first step, we will need a data loader to load news. Next, we need to figure out an algorithm to turn the text news into a vector whose values are the money we want to invest in each stock. If we predict the stock price will rise, we ...