This course is concerned with the application of quantitative methods to the study of financial data. It begins by establishing the key empirical characteristics of financial data. These relate to the shape of the empirical distribution for asset returns. We then turn to an examination of the methods that are used to model these regularities. We begin with the linear regression model and discuss its application to tests of the capital asset pricing model (CAPM), the arbitrage pricing model (APT), and the forward market efficiency. We also discuss the 'spurious regression problem' which arises in financial applications. This leads to a discussion of non-stationary data and how to model long-run relationships among financial time series. We then discuss techniques of modeling time series more generally, particularly in an error correction framework. The main emphasis of the course is on applications. Students will be asked to work through a number of questions with a broad range of financial data sets.