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Introductory Econometrics for Finance

TLDR
The third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time as discussed by the authors.
Abstract
This bestselling and thoroughly classroom-tested textbook is a complete resource for finance students. A comprehensive and illustrated discussion of the most common empirical approaches in finance prepares students for using econometrics in practice, while detailed case studies help them understand how the techniques are used in relevant financial contexts. Worked examples from the latest version of the popular statistical software EViews guide students to implement their own models and interpret results. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Building on the successful data- and problem-driven approach of previous editions, this third edition has been updated with new data, extensive examples and additional introductory material on mathematics, making the book more accessible to students encountering econometrics for the first time. A companion website, with numerous student and instructor resources, completes the learning package.

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An International Analysis of Earnings, Stock Prices and Bond Yields

TL;DR: In this paper, the authors assess the possible contemporaneous relationship between stock index prices, earnings and long-term government bond yields for a large number of countries and over a time period that spans several decades.
Posted Content

Detecting and interpreting financial stress in the euro area1

TL;DR: In this article, the authors discuss the performance of a financial stress indicator with a specific focus on the euro area, which is able to efficiently extract information from an otherwise noisy signal and provide information about the level of stress in the markets.
Journal ArticleDOI

The Asian crisis and calendar effects on stock returns in Thailand

TL;DR: The conclusion is that the inclusion of calendar effects improves the forecast accuracy.
Journal ArticleDOI

Determinants of the Adoption of Climate-Smart Agricultural Practices by Small-Scale Farming Households in King Cetshwayo District Municipality, South Africa

TL;DR: In this article, the authors argue that climate change-related education through improved extension contact and exposure to mass media can strengthen integrated farm activities that bolster farm income, and that farmer associations or groups should be given adequate attention to facilitate CSA adoption as a means to climate change mitigation and resilience.
References
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Journal ArticleDOI

A new look at the statistical model identification

TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.

Estimating the dimension of a model

TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI

The Pricing of Options and Corporate Liabilities

TL;DR: In this paper, a theoretical valuation formula for options is derived, based on the assumption that options are correctly priced in the market and it should not be possible to make sure profits by creating portfolios of long and short positions in options and their underlying stocks.
Book

Econometric Analysis of Cross Section and Panel Data

TL;DR: This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001).
Journal ArticleDOI

A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity

Halbert White
- 01 May 1980 - 
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
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