Congratulations on making it this far. The content you’ve seen previously, will serve as a strong foundation of knowledge from which to build your quantitative finance career. We have a few more concepts to discuss. But before we get into the weeds, let’s take this opportunity to step back for a moment. I want to describe the series of steps, quants go through when developing trading strategies from a big picture of perspective. So you’ll be able to see, how each step can contribute to the ultimate goal of profiting from a successful trading strategy. This will help you understand the point of each school year learning and make concepts discussed in the next few videos more clear. Fundamentally, quantitative trading is the process of using statistical analysis and modeling to predict market behavior and using those predictions to make trades with the goal of profit. Like any research process understanding and predicting market behavior begins with a new idea for how the world might work. In other words, a hypothesis. A good hypothesis is the first step to making predictions about future behavior. Coming up with a good hypothesis means being brutally specific. For example, the hypothesis stocks that are discussed in the news are likely to go up is not very useful by itself, because it’s so vague that it doesn’t lead to testable predictions. In what news outlet? At what time? In what manner must the stocks we discussed and for how long will they go up? An improved hypothesis would be stocks whose company name or ticker appear in the landing page of The Wall Street Journal website will increase by price by one percent, one day following this appearance. Although it’s far from perfect, we can actually test this hypothesis by finding the tickers and checking for the change in price. So how do you come up with a good hypothesis? Well, your hypothesis should be based on your current understanding of how markets work. So the more you know about the markets, the more likely you are able to come up with a new potentially profitable idea. It can take time to build up the domain knowledge to come up with a good hypothesis in any field of study and quantitative finance is no exception. So how do you build up this domain expertise? Well, you can try to immerse yourself in the markets, observe the markets, watch financial news, read financial newspapers, read books, read blogs, and study the known strategies of famous quants and discretionary traders and investors. Attend meetings and conferences and read academic papers such as those on the Social Science Research Network. An online repository of scholarly research in the social sciences including economics and finance. But no matter who you are or what you know, if your hypothesis makes predictions that are inconsistent with the real observed data, your hypothesis is wrong. The precise manner in which it is wrong, when and how, we’ll show you how to focus your efforts to improve it.