Top 10 Essential Resources for Learning Financial Econometrics. Part #2 - Introductory Econometrics

At this stage you should have a good grasp of basic probabiltiy, statistical methods and exposure to the time-series concepts used in econometrics models. The next step is to get a grounding in economics modelling and how it can be applied to large data sets such as that arising from financial markets pricing data, which is the main domain of the quantitative trader.

I really like Chris Brooks' text and I would highly recommend it for any prospective quant trader. The book begins with an extensive set of chapters on linear regression, peppered with many examples related to financial markets that are highly applicable to quantitative finance work. The chapters progress from simple linear regression to multiple regression and then discuss the importances of the assumptions of such models.

The next set of chapters concentrate on time-series analysis, including ARMA and Vector Autoregressive (VAR) models. Once again, there are plenty of examples related to quantitative finance, such as forecasting time series.

Chapter 7 discusses long-run relationships and spends time considering cointegration, a useful tool for mean-reversion algorithmic trading strategies. Chapter 8 provides the first glimpse into the world of modelling volatility including an extensive discussion on the famous Generalised Autoregressive Conditional Heteroscedastic (GARCH) model.

The book also has a chapter on Monte Carlo techniques, an area well known to long-term QuantStart readers. The main benefit of the book is that it is geared up towards students of finance, rather than those more interested in purer macroeconomic modelling.

This econometrics text by Kennedy takes a slightly different tack from that by Brooks. It concentrates far less on the financial aspect of econometrics than Brooks, instead spending a significant amount of time on discussing when assumptions to certain models can be violated. This is extremely useful as it often quite easy to apply a certain technique to a situation when the assumptions do not actually hold.

The book is not particularly heavy on mathematics (for that have a look at Greene, below) but it is far better at explanation. This is not a theorem-proof text! Its main strength is that it clearly elucidates complex econometric ideas and provides the rationale for why particular models are utilised. Other, more advanced books tend to gloss over these issues.

Although it is not as highly relevant as Brooks' book to quantitative trading, it will certainly help clarify any issues you may have with certain econometric ideas.