Written to complement the second edition of best-selling textbook Introductory Econometrics for Finance, this book provides a comprehensive introduction to the use of the Regression Analysis of Time Series (RATS) software for modelling in finance and beyond. It provides numerous worked examples with carefully annotated code and detailed explanations of the outputs, giving readers the knowledge and confidence to use the software for their own research and to interpret their own results. A wide variety of important modelling approaches are covered, including such topics as time-series analysis and forecasting, volatility modelling, limited dependent variable and panel methods, switching models and simulations methods. The book is supported by an accompanying website containing freely downloadable data and RATS instructions.
Author(s): Chris Brooks
Edition: 1
Publisher: Cambridge University Press
Year: 2008
Language: English
Pages: 215
Tags: Финансово-экономические дисциплины;Эконометрика;
Cover......Page 1
Half-title......Page 3
Title......Page 5
Copyright......Page 6
Contents......Page 7
Figures......Page 10
Screenshots......Page 11
Preface......Page 13
About the author......Page 14
1.1 Description......Page 15
1.4 Further reading......Page 16
1.6 Opening the software......Page 17
1.7 Types of RATS files......Page 19
1.8 Reading (loading) data in RATS......Page 20
1.9 Reading in data on UK house prices......Page 22
1.11 Transformations......Page 25
1.12 Computing summary statistics......Page 26
1.13 Plots......Page 28
1.14 Comment lines......Page 31
1.17 Econometric tools available in RATS......Page 32
1.18 Outline of the remainder of this book......Page 34
2.1 Hedge ratio estimation using OLS......Page 36
2.2 Standard errors and hypothesis testing......Page 42
2.3 Estimation and hypothesis testing with the CAPM......Page 44
3.1 Conducting multiple hypothesis tests......Page 48
3.2 Multiple regression using an APT-style model......Page 50
3.3 Stepwise regression......Page 53
3.4 Constructing reports......Page 55
4 Diagnostic testing......Page 57
4.1 Testing for heteroscedasticity......Page 58
4.2 A digression on SMPL......Page 65
4.3 Using White's modified standard error estimates......Page 66
4.4 Autocorrelation and dynamic models......Page 67
4.5 Testing for non-normality......Page 71
4.6 Dummy variable construction and use......Page 72
4.7 Testing for multicollinearity......Page 76
4.8 The RESET test for functional form......Page 77
4.9.1 The Chow test......Page 79
4.9.2 The predictive failure test......Page 81
5 Formulating and estimating ARMA models......Page 85
5.1 Getting started......Page 86
5.2 Forecasting using ARMA models......Page 93
5.3 Exponential smoothing models......Page 97
6.1 Setting up a system......Page 100
6.2 A Hausman test......Page 103
6.3 VAR estimation......Page 106
6.4 Selecting the optimal lag length for a VAR......Page 110
6.5 Impulse responses and variance decompositions......Page 114
7.1 Testing for unit roots......Page 120
7.2 Testing for cointegration and modelling cointegrated variables......Page 122
7.3 Using the systems-based approach to testing for cointegration......Page 127
8.1 Estimating EWMA models......Page 134
8.2 Testing for ARCH-effects......Page 135
8.3 GARCH model estimation......Page 137
GARCH model options......Page 141
8.4 Estimating GJR and EGARCH models......Page 142
8.5 Tests for sign and size bias......Page 146
8.6 The GARCH(1,1)-M model......Page 149
8.7 Forecasting from GARCH models......Page 151
8.8 Multivariate GARCH models......Page 154
9.1 Dummy variables for seasonality......Page 159
9.2 Markov switching models......Page 163
9.3 Threshold autoregressive models......Page 167
10.1 Setting up the panel......Page 174
10.2 Estimating fixed or random effects panel models......Page 177
11 Limited dependent variable models......Page 182
11.1 Reading in the data......Page 183
11.2 The logit and probit models......Page 184
12 Simulation methods......Page 189
12.1 Simulating Dickey–Fuller critical values......Page 190
12.2 Pricing Asian options......Page 193
12.3 Simulating the price of an option using a fat-tailed process......Page 197
12.4 VAR estimation using bootstrapping......Page 200
Appendix: sources of data in this book......Page 208
References......Page 209
Index......Page 213
