Introductory Econometrics for Finance

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Cambridge University Press, May 22, 2008 - Business & Economics - 648 pages
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This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.

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I used this book for a Research Methods in Finance postgraduate paper and found it to be very concise. The explanations are in enough detail to learn the "why" as much as the "how", which is important.
A well rounded book, covers many topics, and while you wouldn't say it is easy to read (relative to a fictional novel) it is one of the easiest math books I have read.

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Boostrap is been used


A brief overview of the classical linear regression model
Further development and analysis of the classical linear
Classical linear regression model assumptions
Univariate time series modelling and forecasting
Multivariate models
Modelling volatility and correlation
Switching models
Panel data
Simulation methods
Conducting empirical research or doing a project or dissertation
Recent and future developments in the modelling
Tables of statistical distributions 616

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About the author (2008)

Chris Brooks is Professor of Finance at the ICMA Centre, University of Reading, UK, where he also obtained his PhD. He has published over 60 articles in leading academic and practitioner journals including The Journal of Business, The Journal of Banking and Finance, The Journal of Empirical Finance, The Review of Economics and Statistics and The Economic Journal. He has also acted as consultant for various banks and professional bodies in the fields of finance, econometrics and real estate.

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