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ix | |
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x | |
| Acknowledgements |
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xii | |
| Preface |
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xiv | |
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Stochastic processes and financial data generating processes |
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1 | (14) |
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1 | (4) |
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Stochastic processes and their properties |
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5 | (3) |
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The behaviour of financial variables and beyond |
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8 | (7) |
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Commonly applied statistical distributions and their relevance |
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15 | (15) |
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15 | (8) |
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23 | (2) |
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25 | (3) |
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28 | (2) |
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Overview of estimation methods |
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30 | (15) |
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30 | (2) |
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32 | (1) |
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Estimation when iid is violated |
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33 | (2) |
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General residual distributions in time series and cross-section modelling |
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35 | (5) |
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40 | (5) |
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Unit roots, cointegration and other comovements in time series |
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45 | (21) |
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Unit roots and testing for unit roots |
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45 | (4) |
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49 | (2) |
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Common trends and common cycles |
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51 | (2) |
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53 | (5) |
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58 | (8) |
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Time-varying volatility models: GARCH and stochastic volatility |
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66 | (23) |
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ARCH and GARCH and their variations |
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66 | (4) |
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70 | (4) |
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74 | (1) |
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75 | (7) |
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82 | (7) |
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Shock persistence and impulse response analysis |
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89 | (24) |
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Univariate persistence measures |
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90 | (2) |
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Multivariate persistence measures |
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92 | (3) |
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Impulse response analysis and variance decomposition |
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95 | (3) |
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Non-orthogonal cross-effect impulse response analysis |
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98 | (1) |
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99 | (9) |
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108 | (5) |
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Modelling regime shifts: Markov switching models |
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113 | (18) |
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113 | (1) |
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114 | (3) |
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117 | (2) |
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Time-varying transition probabilities |
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119 | (1) |
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120 | (6) |
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126 | (5) |
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Present value models and tests for rationality and market efficiency |
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131 | (20) |
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The basic present value model and its time series characteristics |
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131 | (2) |
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133 | (3) |
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The present value model in logarithms with time-varying discount rates |
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136 | (2) |
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The VAR representation for the present value model in the log-linear form |
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138 | (1) |
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139 | (1) |
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140 | (7) |
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147 | (4) |
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State space models and the Kalman filter |
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151 | (17) |
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151 | (1) |
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152 | (1) |
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Time-varying coefficient models |
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153 | (1) |
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State space models of commonly used time series processes |
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154 | (4) |
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158 | (6) |
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164 | (4) |
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Frequency domain analysis of time series |
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168 | (30) |
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The Fourier transform and spectra |
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168 | (4) |
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Multivariate spectra, phases and coherence |
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172 | (1) |
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Frequency domain representations of commonly used time series processes |
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173 | (2) |
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Frequency domain analysis of the patterns of violation of white noise conditions |
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175 | (7) |
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182 | (12) |
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194 | (4) |
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Limited dependent variables and discrete choice models |
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198 | (28) |
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Probit and logit formulations |
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199 | (3) |
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Multinomial logit models and multinomial logistic regression |
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202 | (3) |
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205 | (2) |
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207 | (3) |
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210 | (10) |
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220 | (6) |
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Limited dependent variables and truncated and censored samples |
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226 | (23) |
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Truncated and censored data analysis |
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226 | (4) |
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230 | (3) |
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Generalisation of the Tobit model: Heckman and Cragg |
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233 | (1) |
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234 | (8) |
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242 | (7) |
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249 | (40) |
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Structure and organisation of panel data sets |
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250 | (2) |
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Fixed effects vs. random effects models |
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252 | (8) |
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260 | (4) |
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Dynamic panel data analysis |
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264 | (5) |
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269 | (9) |
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278 | (11) |
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Research tools and sources of information |
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289 | (24) |
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Financial economics and econometrics literature on the Internet |
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289 | (2) |
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Econometric software packages for financial and economic data analysis |
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291 | (3) |
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Learned societies and professional associations |
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294 | (5) |
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Organisations and institutions |
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299 | (14) |
| Index |
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313 | |
Lisainfo e-raamatute kohta