ISBN: 3540251235
TITLE: Empirical
AUTHOR: Bhar/Hamori
TOC: 

1 Introduction 1
2 Basic Probability Theory and Markov Chains 5
2.1 Random Variables 5
2.2 Function of Random Variable 7
2.3 Normal Random Variable 8
2.4 Lognormal Random Variable 9
2.5 Markov Chains 10
2.6 Passage Time 14
2.7 Examples and Exercises 16
References 17
3 Estimation Techniques 19
3.1 Models, Parameters and Likelihood - An Overview 19
3.2 Maximum Likelihood Estimation and Covariance Matrix of Parameters 20
3.3 MLE Example - Classical Linear Regression 22
3.4 Dependent Observations 23
3.5 Prediction Error Decomposition 24
3.6 Serially Correlated Errors - Overview 25
3.7 Constrained Optimization and the Covariance Matrix 27
3.8 Examples and Exercises 28
References 29
4 Non-Parametric Method of Estimation 31
4.1 Background 31
4.2 Non-Parametric Approach 32
4.3 Kernel Regression 33
4.4 Illustration 1 (EViews) 35
4.5 Optimal Bandwidth Selection 36
4.6 Illustration 2 (EViews) 36
4.7 Examples and Exercises 38
References 39
5 Unit Root, Cointegration and Related Issues 41
5.1 Stationary Process 41
5.2 Unit Root 44
5.3 Dickey-Fuller Test 46
5.4 Cointegration 49
5.5 Residual-based Cointegration Test 50
5.6 Unit Root in a Regression Model 51
5.7 Application to Stock Markets 52
References 54
6 VAR Modeling 55
6.1 Stationary Process 55
6.2 Granger Causality 57
6.3 Cointegration and Error Correction 59
6.4 Johansen Test 61
6.5 LA-VAR 62
6.6 Application to Stock Prices 64
References 65
7 Time Varying Volatility Models 67
7.1 Background 67
7.2 ARCH and GARCH Models 68
7.3 TGARCH and EGARCH Models 71
7.4 Causality-in-Variante Approach 74
7.5 Information Flow between Price Change and Trading 77
Volume
References 81
8 State-Spate Models (I) 83
8.1 Background 83
8.2 Classical Regression 83
8.3 Important Time Series Processes 86
8.4 Recursive Least Squares 89
8.5 State-Spate Representation 91
8.6 Examples and Exercises 94
References 103
9 State-Spate Models (II) 105
9.1 Likelihood Function Maximization 105
9.2 EM Algorithm 108
9.3 Time Varying Parameters and Changing Conditional Variante (EViews) 111
9,4 GARCH and Stochastic Variante Model for Exchange Rate (EViews) 113
9.5 Examples and Exercises 116
References 126
10 Diserete Time Real Asset Valuation Model 127
10.1 Asset Price Basics 127
10.2 Mining Project Background 129
10.3 Example 1 130
10.4 Example 2 131
10.5 Example 3 133
10.6 Example 4 135
Appendix 138
References 140
11 Diserete Time Model of Interest Rate 141
11.1 Preliminaries of Short Rate Lattice 141
11.2 Forward Recursion for Lattice and Elementary Price 145
11.3 Matching the Current Term Structure 148
11.4 Immunization: Application of Short Rate Lattice 149
11.5 Valuing Callable Bond 152
11.6 Exercises 153
References 154
12 Global Bubbles in Stock Markets and Linkages 155
12.1 Introduction 155
12.2 Speculative Bubbles 156
12.3 Review of Key Empirical Papers 158
12.4 New Contribution 164
12.5 Global Stock Market Integration 165
12.6 Dynamic Linear Models for Bubble Solutions 167
12.7 Dynamic Linear Models for No-Bubble Solutions 172
12.8 Subset VAR for Linkages between Markets 174
12.9 Results and Discussions 175
12.10 Summary 186
References 187
13 Forward FX Market and the Risk Premium 193
13.1 Introduction 193
13.2 Alternative Approach to Model Risk Premia 195
13.3 The Proposed Model 196
13.4 State-Space Framework 201
13.5 Brief Description of Wolff/Cheung Model 204
13.6 Application of the Model and Data Description 205
13.7 Summary and Conclusions 209
Appendix 210
References 211
14 Equity Risk Premia from Derivative Prices 215
14.1 Introduction 215
14.2 The Theory behind the Modeling Framework 217
14.3 The Continuous Time State-Space Framework 220
14.4 Setting Up The Filtering Framework 223
14.5 The Data Set 228
14.6 Estimation Results 228
14.7 Summary and Conclusions 235
References 236
Index 239
About the Authors 243
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