Introductory Econometrics for FinanceThis 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. |
Contents
List of figures | |
optimal hedgeratio 2 6 The assumptions underlying | |
the Ftest 3 5 Sample EViews outputformultiple hypothesis tests | |
diagnostic tests 4 1 Introduction | |
the | |
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actual analysis appear application approach appropriate asset assumed assumption autocorrelation autoregressive average calculated changes chapter coefficient cointegrating conditional consider constant constructed containing correlation critical denoted dependent variable derived described determine discussed distribution dummy variables econometrics effects employed equation error estimated EViews example expected explained explanatory variables expressed Figure fitted forecasts function futures GARCH give given implied important increase intercept interest interpretation inthe Journal known lags linear matrix mean measure method negative normal Note null hypothesis observations obtained ofthe option parameters period plot positive possible predictive presented probability problem properties random regression rejected relationship researcher residuals respectively restrictions returns sample shows significant specification squares standard statistic structure suggests Suppose term thatthe unit variables variance vector volatility zero