The great availability of financial data requires appropriate statistical techniques for their analysis. Often financial variables are measured sequentially in discrete time and the resulting data are commonly called financial time series (e.g. the prices of a financial asset measured over a certain period).
This module introduces various graphical methods to represent these data, starting from financial charts for single assets and then considering more complex plots. Although very important, graphical methods are not sufficient to extract all the necessary information and some analytics are also necessary. Therefore, the lectures illustrate how to fit a variety of statistical models to financial data in order to forecast prices of financial assets and other financial variables.
We cover the main theoretical and methodological aspects, illustrated with exercises and examples. Computations are done using the (free) software R. We mainly consider two important practical applications: the development of financial trading strategies for single assets and the development of portfolio management strategies for multiple assets.