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A quant investing strategy is an advanced mathematical model developed by industry professionals, including programmers, statisticians, and investment analysts. The purpose is to identify stocks with a higher probability of outperforming an index using a broad range of characteristics. Different models are available and may consider various factors, as we discuss in the next section below regarding different types of investing strategies. On a side note, quantitative techniques also help with asset allocation and risk management as well as aligning portfolios according to the needs of the clients. Early adopters are now investing in alternative data sources and methods to interpret large amounts of information using machine-learning models. This data, as opposed to traditional data sources, comes from web scraping which refers to collecting data from websites. Machine-learning models are a branch of artificial intelligence (AI) that allows you to compile and interpret a large volume of information to make better investment decisions. Narrowing down the scope of alternative data, historical headcount data could be one of the metrics to track. With this information, you can draw up a graph and see the changes in headcount in a company to determine its growth. Headcount data allows you to see how well a company is doing in terms of its size and hiring tendencies. A stagnant graph line might indicate that the company is standing still and not making any significant moves or expansion decisions.