Financial Econometrics is simply the application of econometric tools to financial data. For many years, least squares techniques provided satisfactory tools. Stock market forecasts, efficient market tests, and even tests of portfolio models such as the CAPM and APT were essentially implemented with least squares on cleverly manipulated data sets. More recently, however, the field has developed...

requisite input, high-frequency data (HFD), and the impact of HFT on financial markets. The econometrics of HFD and trading marks a significant departure from the econometrics used when dealing with lower frequencies. In particular, ultra HFD might be randomly spaced, requiring point process techniques, while quantities such as volatility become nearly observable with HFD. At high frequency, fo...

This paper argues that time-series econometrics provides valuable tools and opens exciting research opportunities to marketing researchers. It allows marketing researchers to advance traditional modeling and estimation approaches by incorporating dynamic processes to answer new important research questions. The authors discuss the challenges facing time-series modelers in marketing, provide an ...

The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding very reliable inference, some precautions should be taken in order to ensure this. Two “Golden Rules” are formulated that, if observed, help to obtain the best the bootstrap can offer. Bootstrapping always involves setting up a bootstrap data-generating process (DGP). The main typ...

Q uantitative theory uses simple, abstract economic models together with a small amount of economic data to highlight major economic mechanisms. To illustrate the methods of quantitative theory, we review studies of the production function by Paul Douglas, Robert Solow, and Edward Prescott. Consideration of these studies takes an important research area from its earliest days through contempora...

Copulas are functions that describe the dependence between two or more random variables. This article provides a brief review of copula theory and two areas of economics in which copulas have played important roles: multivariate modeling and partial identification of parameters that depend on the joint distribution of two random variables with fixed or knownmarginal distributions.We focus on bi...

This thesis consists of three chapters that cover separate topics in econometrics. The first chapter demonstrate a negative result on the asymptotic sizes of subset AndersonRubin tests with weakly identified nuisance parameters and general covariance structure. The result of Guggenberger et al (2012) in case of homoskedasticity is shown to break down when general covariance structure is allowed...

This review is a primer for those who wish to familiarize themselves with nonparametric econometrics. Though the underlying theory for many of these methods can be daunting for some practitioners, this article will demonstrate how a range of nonparametric methods can in fact be deployed in a fairly straightforward manner. Rather than aiming for encyclopedic coverage of the field, we shall restr...

An account is given of recursive regression and Kalman filtering that gathers the important results and the ideas that lie behind them. It emphasises areas where econometricians have made contributions, including methods for handling the initial-value problem associated with nonstationary processes and algorithms for fixed-interval smoothing.

Shortly after World War II, many of the leading econometricians collaborated under the aegis of the Cowles Commission and, over the course of a few years, developed a research agenda that structured macroeconometrics for the second half of the 20th century. The central vision of this research program was simple: the development of a mathematical model of the macroeconomy with grounding in econo...