Introduction - (Władysław Milo and Piotr Wdowiński) ............. 7
Part One: Principles of Modelling, Forecasting and Decision-
Making in Financial Markets
1 Flexibility and Parsimony in Multivariate Financial
Modelling: A Hybrid Bivariate DCC-SV Model (Jacek
Osiewalski and Anna Pajor) .................................. 11
1.1 Introduction ........................................... 11
1.2 Main Bayesian Models from the MSV and MGARCH Classes ... 12
1.2.1 Bivariate Stochastic Volatility
Specifications .................................. 13
1.2.1.1 The Stochastic Discount Factor Model
(SDF) ................................... 13
1.2.1.2 The JSV and TSV Models ................. 14
1.2.2 Bivariate GARCH Specifications .................. 15
1.2.2.1 The t-BEKK Model ....................... 16
1.2.2.2 The t-DCC Model ........................ 16
1.3 The Hybrid DCC-SDF Model ............................... 17
1.4 The Data and Results of Model Comparison ............... 18
1.5 Posterior Inference on Conditional Correlation
Coefficients and Volatilities .......................... 20
1.6 Concluding Remarks ..................................... 25
References .................................................. 26
2 Forecasting Stochastic Unit Root Models (Magdalena
Osińska) .................................................... 27
2.1 Introduction ........................................... 27
2.2 Stochastic Unit Root Model as a Case of Random
Coefficient Autoregressive Model ....................... 28
2.3 Testing for STUR ...................................... 32
2.4 Forecasting Procedures and Empirical Results ........... 33
2.5 Conclusions ............................................ 42
References .................................................. 42
3 Forecasting the Dependence Between Polish Financial
Returns (Ryszard Doman) ..................................... 45
3.1 Introduction ........................................... 45
3.2 Copulas and Dependence ................................. 46
3.3 Modelling the Conditional Dependence Structure by
Means of the Conditional Copulas ....................... 48
3.4 Dynamic Conditional Dependence Model ................... 50
3.5 The Data ............................................... 51
3.6 Empirical Results ...................................... 52
3.7 Conclusions ............................................ 57
References .................................................. 58
Part Two: Modelling Stock Market Returns and Volatility
4 A Note on the Market Model Specification when Stocks
Markets Are Integrated (Pawel Miłobędzki) ................... 61
4.1 Introduction ........................................... 61
4.2 Estimation of the First-Pass Regression Based on the
VEC Model .............................................. 62
4.3 Conclusion ............................................. 66
References .................................................. 67
5 The Isolation of Maximum Length Sub-periods in Which
a Stock Return Series is Exhibiting Linear and Non-Linear
Dependencies (Todea-Zoicaş Algorithm) (Alexandru Todea and
Adrian Zoicaş-Ienciu) ....................................... 69
5.1 Introduction ........................................... 69
5.2 The 'Windowed' Hinich and Patterson Methodology
(1995) and the Improved Methodology .................... 70
5.2.1 Hinich and Patterson Methodology ................ 70
5.2.2 Modified 'Windowed' Methodology ................. 72
5.3 Possible Use of the Improved Methodology ............... 73
5.4 The Data ............................................... 75
5.5 Empirical Results ...................................... 75
5.6 Conclusions ............................................ 80
Appendix .................................................... 80
References .................................................. 82
6 Using Implied Volatility to Forecast Daily Realized
Volatility of the WIG20 Index (Piotr Pluciennik) ............ 85
6.1 Introduction ........................................... 85
6.2 Parametric Volatility Models ......................... 86
6.3 Implied Volatility ..................................... 87
6.3.1 Total Implied Volatility for Class of Options ... 89
6.3.2 Algorithm to Determine Risk-Free Interest
Rate ............................................ 90
6.4 Intraday Returns and Realized Volatility ............... 90
6.5 Data ................................................... 92
6.6 Empirical Results ...................................... 93
6.7 Conclusions ............................................ 96
References .................................................. 97
Part Three: Bayesian Econometrics in Finance
7 Bayesian Analysis and Forecasting of the Conditional
Correlations Between Stock Index Returns with Multivariate
SV Models (Anna Pajor) ..................................... 101
7.1 Introduction .......................................... 101
7.2 Model Framework ....................................... 102
7.3 Trivariate VAR(l) - SV Models ......................... 103
7.3.1 The SDF Model .................................. 103
7.3.2 The BSV Model .................................. 104
7.3.3 The JSV Model .................................. 104
7.3.4 The TSV Model .................................. 105
7.4 Data Descriptions and Empirical Results ............... 107
7.4.1. Data ........................................... 107
7.4.2. Empirical Results .............................. 108
7.4.2.1 Bayesian Model Comparison ........... 108
7.4.2.2 Posterior Results for Individual
Volatilities .......................... 109
7.4.2.3 Posterior Results for the
Conditional Correlation
Coefficients .......................... 109
7.4.2.4 Forecasting Results ................... 115
7.5. Conclusions ........................................... 119
References ................................................. 120
8 Bayesian Comparison of GARCH Processes with Asymmetric
and Heavy Tailed Conditional Distributions (Mateusz
Pipień) .................................................... 123
8.1 Introduction .......................................... 123
8.2 Creating Asymmetric Distributions ..................... 125
8.3 Basic Model Framework and Competing Skewed
Conditional Distributions ............................. 128
8.4 Empirical Results ..................................... 132
8.5 Concluding Remarks .................................... 138
References ................................................. 139
9 A Bayesian Inference About Simple STUR Models with GARCH
Errors (Jacek Kwiatkowski) ................................. 141
9.1 Introduction .......................................... 141
9.2 Stochastic Unit Root Model and Inference via
Importance Sampling ................................... 142
9.3 Data and Posterior Results ............................ 147
9.4 Concluding Remarks .................................... 151
References ................................................. 151
10 Bayesian Pricing of European Call Options on the WIG20
Index (Maciej Kostrzewski) ................................. 153
10.1 Introduction .......................................... 153
10.2 Models ................................................ 153
10.3 The Bayesian Inference ................................ 154
10.4 The Comparison of the Models .......................... 157
10.5 Forecasting the WIG20 Index ........................... 158
10.6 The Pricing of the Options ............................ 159
10.7 Concluding Remarks .................................... 163
References ................................................. 163
Part Four: Econometric and Statistical Methods - Theory and
Applications
11 A Generalization of the Stability of the Equilibrium in
a Repeated Game (Ilie Parpucea) ............................ 167
11.1 Introduction .......................................... 167
11.2 The Quasi-Formal Specification of a Repeated Game
with Heterogeneous Structure .......................... 168
11.3 Conclusions ........................................... 177
References ................................................. 178
12 The Relationship between Stock Market and Economic Growth
in Developing Economies: An Econometric Analysis on
Nigeria (Mete Feridun and Tokunbo Simbowale Osinubi) ....... 179
12.1 Introduction .......................................... 179
12.2 Literature Review ..................................... 181
12.3 Empirical Results ..................................... 182
12.4 Conclusions and Policy Recommendations ................ 185
References ................................................. 186
13 Forecasting the Returns Based on the Panel Data
Estimation Methods (Ewa Majerowska) ........................ 187
13.1 Introduction .......................................... 187
13.2 Methodology ........................................... 188
13.3 Estimated Models ...................................... 190
13.4 Data .................................................. 191
13.5 Empirical Results ..................................... 192
13.6 Conclusions ........................................... 196
References ................................................. 197
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