Professor Garcia's research interest encompass informational frictions in financial markets, as well as the effect of behavioral biases in asset prices. His work is both theoretical and empirical in nature, and it has been published in leading journals such as the Journal of Finance, the Journal of Financial Economics, the Review of Financial Studies, and the Journal of Economic Theory, among others. Professor Garcia's research received the Michael Brennan award for the best paper published in the Review of Financial Studies.
Information economics, financial media, behavioral finance
FNCE 7020 - Financial Economics and Research
Studies both theoretical models at the intersection of information economics and finance, as well as natural language processing techniques, focused on financial and accounting documents.
MBAX 6250 - Derivative Securities
Fall 2018 / Fall 2019
Derivatives, like options, futures, forwards, and swaps, encompass all aspects of finance. Topics cover the characteristics, valuation, and trading strategies associated with derivatives as well as their use in risk management.
MBAX 6290 - Textual Analysis in Business
This course will discuss basic ideas around natural language processing (NLP) in research in different dismal science disciplines, from Economics to Psychology and Political Science, with a bent/focus on financial markets and accounting statements. The course is meant for graduate students as an introductory course on textual analysis, with an emphasis on methods and applications in Finance and Accounting. The language of choice for the course will be R. The course will be multilingual in that both the faculty and students can use other languages than R (python/perl/C). Recommended prerequisite: MBAC 6060 (minimum grade D-).
MSBC 5030 - Quantitative Methods
Covers foundations for statistical reasoning and statistical applications in business. Topics include graduate level treatment of descriptive statistics, probability, probability distributions, sampling theory and sampling distributions and statistical inference (estimation and hypothesis testing). Provides an introduction to regression analysis, analysis of variance, time series forecasting, decision analysis, index numbers, and nonparametric methods.