Financial Econometrics

Financial Econometrics

The present tentative excerpt aims to display a brief introduction to the field of financial econometrics. While financial economics has greater notoriety, empirical econometrics is significant in modeling financial series.

With globalization, the Internet community gained greater exposure. Almost unlimited knowledge has been made accessible with online resources. Prospective sources include prominent search engines’ financial sections, online encyclopedia Investopedia, government and corporate Websites to name a few. For students preparing a term essay, ESTAT and CANSIM are great databases for Canadian statistics, but the Internet STAT USA is no longer available.

Providing the findings that support financial econometric theories, employed in investment management, highlighted in this text is empirical finance. Introducing the subdiscipline, empirical finance may refer to an organizational blog, a peer reviewed journal, a college course or even a consulting and investment management corporation.

Econometricians work in the industries of finance, higher education and research, among others. Although econometricians are prevalent in a healthy economy, there are few universities who offer degrees in financial metrics; often it is merely a class. However, Master’s degrees in financial economics (MFE) or econometrics (MSc) are offered by such institutions as the prestigious Oxford University or popular University of Amsterdam, respectively.

Eighty percent of the people in the world have no food safety net. When disaster strikes – the economy gets blown, people lose a job, floods, war, conflict, bad governance, all of those things – there is nothing to fall back on. Josette Sheeran. Illustration by Megan Jorgensen (Elena)

The new actuarial science is a blend of multiple disciplines such as statistics, economics, mathematics and finance. Areas of study examples are: expected returns, volatility and price dynamics (Fan, 2008). Some models derived from the field carry theoretical as well as practical implications.

Theories and statistical and mathematical tools interact to produce the end result. For example, econometric models for trade, quotes, prices, and volumes justify the market microstructure paradigm (Engle, 2001).

In modern academia, areas of study are plentiful. The likelihood approach is common in econometric analysis; other topics of interest to econometricians are the following incidences from the literature. One account (Kitamura, 2006) focuses on parametric, semiparametric, nonparametric distributions testing and time series.  Another paper (Pagan, 1996), examines several types of financial series such as stock prices, interest rates, exchange rates omitting futures and option prices. A great source for peer-reviewed academic articles is the Journal of Financial Econometrics, an Oxford Journal reflecting current advancements in the field.

Credit risk, business and senior quantitative analysts would deal with financial econometric data, although one may prefer to look at careers in a larger pool instead. Careers in financial economics span the areas of asset management, investment and commercial banking, private equity or venture capital, management of financial institutions, corporate financial management, financial engineering, and consulting.

References:

• Engle, R. (2001). Financial econometrics – A new discipline with new methods. Journal of Econometrics, 100 (1): 53-56.
• Fan, J. (2005). A selective overview of non-parametric methods in financial econometrics. Statistical Science, 20 (4): 317-337.
• Kitamura, Y. (2006). Empirical likelihood methods in econometrics: Theory and practice. Cowles Foundation Discussion paper No. 1569. Cowles Foundation for Research in Economics, Yale University.Pagan, A. (1996). The econometrics of financial markets. Journal of Empirical Finance, 3: 15-102.