Question #1

Supervised learning is a machine learning technique in which a machine is given labelled input and output data and models the output data based on the input data. In unsupervised learning, a machine is given input data in which to identify patterns and relationships, but no output data to model. Deep learning is a technique to identify patterns of increasing complexity and may use supervised or unsupervised learning. (Module 3.1, LOS 3.a) Joyce Tan manages a medium-sized investment fund at Marina Bay Advisors that specializes in international large cap equities. Over the four years that she has been portfolio manager, Tan has been invested in approximately 40 stocks at a time. Tan has used a number of methodologies to select investment opportunities from the universe of investable stocks. In some cases, Tan uses quantitative measures such as accounting ratios to find the most promising investment candidates. In other cases, her team of analysts suggest investments based on qualitative factors and various investment hypotheses. Tan begins to wonder if her team could leverage financial technology to make better decisions. Specifically, she has read about various machine learning techniques to extract useful information from large financial datasets, in order to uncover new sources of alpha.