Financial Econometrics Workshop

TOOLS & TECHNIQUES: Quantitative Analysis Track

2 DAY WORKSHOP
(Workshop is not being offered at this time)

Qualifies for CPD and 14 CPE Credits

INTRODUCTION

Statistical modeling of financial data is challenging. The problems range from access to high quality data to the biases inherent to financial information. This workshop focuses on some of the common approaches to modeling financial data; both cross-sectional and time-series problems are analyzed. This intensive and highly interactive course includes the latest practical and theoretical developments in financial time series and offers practical case studies and interactive modeling exercises to reinforce both the various concepts and the relationship among these concepts.We strongly encourage delegates to ask questions to maximize benefit and, as such, times may vary during the day from the printed schedule. There will be adequate time allocated for refreshment breaks, lunch and for delegates to network and discuss the issues being addressed.

Who should attend?

This intensive and interactive training course is designed for practitioners with an understanding of statistical principles, who want to deepen their understanding of the particular problems encountered in financial econometrics. The course benefits both commercial and investment bankers, treasury and investment professionals, and market and credit analysts.

What will you get out of this course?

• Gain a better understanding of the complexities in modeling cross-sectional financial data as well as some of the standard models for financial time series

• Develop a structural approach in determining and controlling for the common characteristics of financial data

• Learn to evaluate the different approaches used in cross-sectional modeling

• Develop skills to analyze complex relationships between returns and factors

• Explore the use of ARIMA models for describing financial time series, including risk factors

• Understand the strengths and weaknesses of various GARCH model specifications

• Learn to model equilibrium relationships using Vector Autoregressive (VAR) and Vector Error Correction Models (VECM)

The course uses OxMetrics, an object-oriented matrix language. The language is capable running C++ and GAUSS scripts. Programming in this language is easy and there are several freely available software libraries that extended the capabilities of this language and software. Both the language and the software are very intuitive and no previous exposure to or experience in Ox is required. To learn more about Ox, www.oxmetrics.com provides a wealth of information.

COURSE OVERVIEW AND OUTLINE

For this highly interactive course, all delegates are strongly recommended to attend the workshop with a laptop computer loaded with Microsoft Excel with Visual Basic and Excel Solver Add-ins. There will be several interactive group sessions to work on real-life cases.

Regression application in finance – univariate case

• Basic properties of financial time series

• Capital asset pricing model

• INTERACTIVE GROUP SESSION: Descriptive statistics of financial time series

• INTERACTIVE GROUP SESSION: OLS estimate of CAPM models

Regression application in finance – multivariate case

• Multifactor models in finance

• From OLS through WLS to GLS and ML

• Extending the capital asset pricing model

• INTERACTIVE GROUP SESSION: Replicating Fama-French using different models

Cross-sectional analysis and Fama-MacBeth betas

• GLS and SUR

• Panel data, fixed and random effects, and Fama-Macbeth estimation

• INTERACTIVE GROUP SESSION: Replicating Fama-French with panel data estimation and the Fama-MacBeth procedure

ARIMA models

• AR and MA models and the Box-Jenkins procedure

• Model estimation and diagnostic checking

• ARIMA and fARIMA, ARfIMA model

• Forecasting using ARIMA

• INTERACTIVE GROUP SESSION: Estimating time series using AR, MA, ARIMA, and ARfIMA procedures

Cointegration

• Unit roots and cointegration

• Granger causality

• INTERACTIVE GROUP SESSION: Testing time series for cointegrating relationships

• INTERACTIVE GROUP SESSION: Estimating fundamental asset values using cointegration

GARCH models

• Comparing different univariate GARCH models, I-GARCH, GARCH-M, E-GARCH, T-GARCH, HYGARCH, fIGARCH

• INTERACTIVE GROUP SESSION: Choosing the “right” model for different types of series

Vector autoregressive models

• Stationary VAR models and VARMA models, dynamic VAR models

• INTERACTIVE GROUP SESSION: Estimating commodity prices using VAR

• INTERACTIVE GROUP SESSION: Estimating long-term equity returns

Vector error correction models

• VECM and VAR

• Exploring Granger causality

• Impulse response in VECM models

• INTERACTIVE GROUP SESSION: Estimating long-run equilibrium relationships in asset prices