Preview of 'Introductory Econometrics for Finance, 3rd Edition' by Chris Brooks

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Contents

12.3 12.4 12.5 12.6 12.7 12.8 12.9 12.10 12.11 12.12 12.13 12.14

The logit model Using a logit to test the pecking order hypothesis The probit model Choosing between the logit and probit models Estimation of limited dependent variable models Goodness of fit measures for linear dependent variable models Multinomial linear dependent variables The pecking order hypothesis revisited – the choice between financing methods Ordered response linear dependent variables models Are unsolicited credit ratings biased downwards? An ordered probit analysis Censored and truncated dependent variables Limited dependent variable models in EViews Appendix: The maximum likelihood estimator for logit and probit models

13 Simulation methods

13.1 13.2 13.3 13.4 13.5 13.6 13.7 13.8 13.9

Motivations Monte Carlo simulations Variance reduction techniques Bootstrapping Random number generation Disadvantages of the simulation approach to econometric or financial problem solving An example of Monte Carlo simulation in econometrics: deriving a set of critical values for a Dickey–Fuller test An example of how to simulate the price of a financial option An example of bootstrapping to calculate capital risk requirements

14 Conducting empirical research or doing a project or dissertation in finance

14.1 14.2 14.3 14.4 14.5 14.6 14.7 14.8 14.9 14.10

What is an empirical research project and what is it for? Selecting the topic Sponsored or independent research? The research proposal Working papers and literature on the internet Getting the data Choice of computer software Methodology Event studies Tests of the CAPM and the Fama–French Methodology

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Preview of 'Introductory Econometrics for Finance, 3rd Edition' by Chris Brooks by Cambridge University Press - Issuu