Applications of state space models in finance

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170 Appendix B β t β t β t 2.5 2.0 1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5 0.0 −0.5 2.0 1.5 1.0 0.5 0.0 (a) Automobiles KFMMR KFGRW 1990 1995 2000 2005 KFMMR KFGRW (c) Basics 1990 1995 2000 2005 (e) Construction KFMMR KFGRW 1990 1995 2000 2005 β t β t β t 2.0 1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5 0.0 KFMMR KFGRW (b) Banks 1990 1995 2000 2005 KFMMR KFGRW (d) Chemicals 1990 1995 2000 2005 KFMMR KFGRW (f) Financials 1990 1995 2000 2005 Figure B.3: Moving mean reverting and generalized random walk conditional betas.
Figures 171 β t β t β t 2.0 1.5 1.0 0.5 0.0 −0.5 2.0 1.5 1.0 0.5 0.0 3 2 1 0 KFMMR KFGRW (g) Food 1990 1995 2000 2005 KFMMR KFGRW (i) Industrials 1990 1995 2000 2005 KFMMR KFGRW (k) Media 1990 1995 2000 2005 β t β t β t 2.0 1.5 1.0 0.5 0.0 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5 0.0 Figure B.3 — continued KFMMR KFGRW (h) Healthcare 1990 1995 2000 2005 KFMMR KFGRW (j) Insurance 1990 1995 2000 2005 KFMMR KFGRW (l) Oil & Gas 1990 1995 2000 2005
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Sascha Mergner Applications of Stat
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erschienen im Universitätsverlag G
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Bibliographische Information der De
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Contents List of figures . . . . .
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Contents ix 4.5 Model selection and
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Contents xi 7.5 Concluding remarks
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xiv List of figures 6.14 Histograms
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Notation and conventions The outlin
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xx Used abbreviations and symbols L
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xxii Used abbreviations and symbols
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xxiv Used abbreviations and symbols
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Preface The work on this book began
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Chapter 1 Introduction “Economist
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1.2 Research objectives 3 1.2 Resea
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1.3 Organization of the thesis 5 to
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8 2 Some stylized facts of weekly s
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10 2 Some stylized facts of weekly
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18 3 Linear Gaussian state space mo
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Chapter 4 Markov regime switching M
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4.1 Basic concepts 45 R t (%) 20 10
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4.1 Basic concepts 47 probability d
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4.3 Parameter estimation 49 X 1 X 2
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4.3 Parameter estimation 51 4.3.2.1
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4.4 Forecasting and decoding 53 4.4
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4.4 Forecasting and decoding 55 mod
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Chapter 5 Conditional heteroskedast
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5.1 Autoregressive conditional hete
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5.2 Stochastic volatility 65 or the
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5.2 Stochastic volatility 67 5.2.1.
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5.2 Stochastic volatility 69 likeli
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5.2 Stochastic volatility 71 linear
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5.2 Stochastic volatility 73 3. An
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5.3 Multivariate conditional hetero
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84 6 Time-varying market beta risk
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Page 152 and 153: 120 6 Time-varying market beta risk
Page 155 and 156: Chapter 7 A Kalman filter based con
Page 157 and 158: 7.1 Factor modeling 125 uncondition
Page 159 and 160: 7.1 Factor modeling 127 predictabil
Page 161 and 162: 7.1 Factor modeling 129 usefulness,
Page 163 and 164: 7.2 Specification of a conditional
Page 165 and 166: 7.3 The risk factors 133 Table 7.1:
Page 167 and 168: 7.3 The risk factors 135 introduced
Page 169 and 170: 7.3 The risk factors 137 auxiliary
Page 171 and 172: 7.4 Empirical results 139 Table 7.4
Page 173 and 174: 7.4 Empirical results 141 are consi
Page 177 and 178: 7.4 Empirical results 145 β TS 0.4
Page 185 and 186: 7.4 Empirical results 153 cumulativ
Page 187 and 188: Chapter 8 Conclusion and outlook Th
Page 189 and 190: Conclusion and outlook 157 cannot o
Page 191 and 192: Appendix A Brief review of asset pr
Page 193 and 194: A.3 Alternative asset pricing model
Page 195 and 196: Appendix B Figures
Page 197 and 198: Figures 165 β t β t β t 2.0 1.5
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Page 209 and 210: Appendix C Tables
Page 211 and 212: Tables 179 Table C.1 — continued
Page 213 and 214: Tables 181 Table C.3: In-sample mea
Page 215 and 216: Tables 183 Table C.5: Out-of-sample
Page 217 and 218: Tables 185 Table C.7: Parameter est
Page 219 and 220: Tables 187 Table C.7 — continued
Page 221 and 222: Tables 189 Table C.8: Out-of-sample
Page 223 and 224: References Abell, J. D. and T. M. K
Page 225 and 226: References 193 Bulla, J. (2006). Ap
Page 227 and 228: References 195 Fabozzi, F. J. and J
Page 229 and 230: References 197 Harvey, A. C., E. Ru
Page 231 and 232: References 199 Lie, F., R. Brooks,
Page 233 and 234: References 201 Shephard, N. (1993).
Page 235: State space models play a key role
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Applications of state space models in finance

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