# Financial Econometrics

This course is useful for financial investors with open positions in different financial assets (for example, stocks, exchange rates, Treasury bills, notes or bonds), and firms that hold certain positions in financial assets (for example, firms that regularly exchange between USD to GTQ, hold financial assets traded in a financial exchange, use futures contracts to manage financial risk). We study the following topics: First, related to long-run investments that possibly cover several years, we study how to optimize a portfolio of risky securities that possibly involves more than 100 assets. Second, related to long-run investments that possibly cover several years, we study how to estimate the expected return offered by a risky asset by using different factor models (for example, the Capital Asset Pricing Model, CAPM). This is useful for firm or project valuation purposes. We consider the standard case when expected return is constant over time, but we also consider an extended case for which the extended return is possibly time-varying. Related to the extended model, we study how to estimate time-varying beta parameter of stocks and correspondingly how to compute the time-varying expected return. Third, related to short-run investments that cover at most 3-4 weeks, we study how to predict price movements by using different dynamic models of financial risk (for example, the classical GARCH model). Related to this we shall undertake Monte Carlo simulations of future price trajectories in order to approximate mean return and volatility of risky assets. Fourth, we study how to estimate a potential large loss on a financial portfolio for given probability (this is named as value-at-risk, VaR). Estimation of VaR is useful for any financial investor and also for large firms (for example, commercial banks or other financial institutions) that hold significant positions in risky assets and wish to set minimum capital requirements. During the course we shall solve a large number of practical exercises (all new concepts of this course are introduced in case studies), and we will use Excel to represent the calculations. In additions, for case studies with statistical estimation and portfolio optimization we shall use the GRETL and GAUSS statistical programs. The course will be the solution of set of case studies. No preliminary knowledge on statistics or econometrics is required for this course. There will be no exam in this course. Practical work on classes is emphasized. Participants may miss up to three classes from the ten.