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Statistics in finance - MaRDI portal

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Statistics in finance (Q1779189)

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scientific article; zbMATH DE number 2172952
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Statistics in finance
scientific article; zbMATH DE number 2172952

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    Statistics in finance (English)
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    1 June 2005
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    Contributions: -- Ole. E. Barndorff-Nielsen and Neil Shephard, Continuous Time Stochastic Volatility Modelling and Bipower Variation. p.117 -- Peter J. Brockwell (joint with Tina Marquardt), Fractionally Integrated Continuous Time ARMA Processes. p.119 -- Boris Buchmann (joint with Claudia Klüppelberg), Extremal Behaviour of Fractal Models. p.121 -- Ngai Hang CHAN, Structural Models for Credit Risk Migration. p.123 -- Claudia Czado (joint with Gernot Müller), Stochastic Volatility Models for Ordinal Valued Time Series. p.125 -- M. Deistler (joint with T. Ribarits), Data Driven Local Coordinates for Linear State Space Systems. p.128 -- Feike C. Drost, Estimation in Semi-parametric Volatility Models. p.129 -- Paul Embrechts (joint with W. Breymann and A. Dias), Modelling Dependence for High-Frequency Data in Finance. p.131 -- Vicky Fasen, Extremal Behaviour of Continuous-Time Moving Average Processes. p.132 -- Jürgen Franke (joint with Mabouba Diagne and Peter Mwita), Nonparametric Value-at-Risk Estimates p.133 -- Sylvia Frühwirth-Schnatter (joint with Helga Wagner), Gibbs Sampling for State Space Modelling of Time Series of Counts. p.135 -- X. Guo, Estimation and Change Point Detection with a Hidden Markov Model in Finance. p.137 -- M. Jacobsen (joint with M.L. Østerdal), Estimation in Discretely Observed Diffusions: Two Examples of Using Small \(\Delta\)-Optimality. p.140 -- Jan Kallsen (joint with Peter Tankov), Lévy Copulas for General Lévy Processes. p.142 -- Siem Jan Koopman (joint with Borus Jungbacker and Eugenie Hol), Forecasting Daily Variability of the S\&P 100 Stock Index Using Historical, Realised and Implied Volatility Measurements. p.143 -- Catherine Larédo (joint with Valentine Genon-Catalot), Leroux's method for General Hidden Markov Models and Stochastic Volatility Models. p.148 -- Alexander Lindner (joint with Claudia Klüppelberg and Ross Maller), A Continuous Time GARCH(1,1) Process. p.150 -- R. A. Maller, The Large-Sample Distribution of the Sharpe Ratio. p.152 -- Alexander J. McNeil (joint with Stefano Demarta), The t Copula and Related Copulas. p.156 -- Thomas Mikosch (joint with Daniel Straumann), Stable Limits for GARCH Parameter Estimation. p.157 -- Per Mykland (joint with Yacine Aït-Sahalia), The Effects of Random and Discrete Sampling when Estimating Continuous-Time Diffusions. p.160 -- Serguei Pergamenchtchikov (joint with Claudia Klüppelberg), Tail Behaviour of the Stationary Distribution of a Random Coefficient Autoregressive Model. p.161 -- Richard L. Smith, Multivariate Extremes, Max-Stable Processes and Financial Risk. p.163 -- Michael Sørensen, A Flexible Class of Stochastic Volatility Models of the Diffusion-Type. p.167 -- Vladimir Spokoiny (joint with Jörg Polzehl), Adaptive Estimation for a Varying Coefficient GARCH Model. p.169 -- Cătălin Stărică, Is GARCH(1,1) as good a model as the Nobel prize accolades would imply. 170 -- J. Michael Steele, Pricing of Contingent Claims When Prices Are Perturbed: An Elementary Example for Discussion. p.172 -- Daniel Straumann, Quasi-Maximum Likelihood Estimation and Conditional Heteroskedastic Time Series. p.174 -- Alex Szimayer (joint with Ross A. Maller and David H. Soloman), A Multinomial Approximation of American Option Prices in a Lévy\ Process Model. p.175 -- Mark Van De Vyver (joint with Ross A. Maller), The Distribution of the LR Test for a Nonlinear Latent Variable Model of Equity Returns. p.175 -- Yazhen Wang, Option Pricing and Statistics Inference for GARCH Models and Diffusions. p.179 -- Samuel Po-Shing Wong (joint with Tze Leung Lai), Valuation of American Options via Basis Functions. p.180 -- Qiwei Yao (joint with Jeremy Penzer and Mingjin Wang), Approximating Volatilities by Asymmetric Power GARCH Functions. p.180 -- Lan Zhang (joint with Per A. Mykland and Yacine Aït-Sahalia), A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High-Frequency Data. p.182
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