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| 文件名: Copulae in Mathematical and Quantitative Finance.pdf | |
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听多元统计老师说，copula在金融领域的应用非常广泛，特地找来！！
书名叫Copulae in Mathematical and Quantitative Finance论坛上已有本书，我看了一下，略贵，这里免费分享 The notion of copula provides an efficient way to describe the interrelationships of random variables and offers a great flexibility in building multivariate stochastic models. Since its discovery in the early 1950s, copulas have contributed to understand better the various facets of stochastic dependence and have allowed to break away from the standard assumptions (like multivariate Gaussian distribution), which generally underestimate theprobability of joint extreme risks. Nowadays, copula-based dependence models are rapidly gaining considerable popularity in several fields and are becoming indispensable tools not only in finance, insurance, risk management and econometrics but also in biostatistics, hydrology or machine learning. For example, they are widely used for the modelling of market, credit and operational risk, as well as for the aggregation of risks and portfolio selection. Moreover, such a large interest in the applications of copulas has spurred researchers and scientists in investigating and developing new theoretical methods and tools for handling randomness and uncertainty in practical situations. The workshop “Copulae in Mathematicaland Quantitative Finance”, which took place in Cracow (Poland) on 10th–11th July 2012, has represented a good opportunity for intensive exchange of ideas about recent developments and achievements that can contribute to the general development of the field. The talks presented at this event have focused on several interesting theoretical problems as well as empirical applications. In order to make all these contributions available to a larger audience, we have prepared this volume collecting both surveys giving an up-to-date account of some aspects of copula models and extended versions of talks presented at the workshop in Cracow. Our special thanks go to the authors fortheir willingness to contribute to this volume and to our colleagues whose contribution as reviewers was essential in the preparation of the volume. The professional work of the scientific and organizing committees was greatly appreciated, as well as the support of the co-sponsors of this conference. Finally, we are indebted to our publisher Springer, in particular to Alice Blanck for her assistance in the editorial process. Bolzano, Italy Fabrizio Durante Berlin, Germany Wolfgang Karl H¨ ardle Warszawa, Poland Piotr Jaworski January 2013 1 A Convolution-Based Autoregressive Process........................... 1 Umberto Cherubini and Fabio Gobbi 2 Selection of Vine Copulas.................................................. 17 Claudia Czado, Eike Christian Brechmann, and Lutz Gruber 3 Copulas in Machine Learning............................................. 39 Gal Elidan 4 An Overview of the Goodness-of-Fit Test Problem for Copulas....... 61 Jean-David Fermanian 5 Assessing and Modeling Asymmetry in Bivariate Continuous Data............................................................ 91 Christian Genest and Johanna G. Neˇ slehov′ a 6 Modeling Time-Varying Dependencies Between Positive-Valued High-Frequency Time Series........................... 115 Nikolaus Hautsch, Ostap Okhrin, and Alexander Ristig 7 The Limiting Properties of Copulas Under Univariate Conditioning................................................................ 129 Piotr Jaworski 8 Singular Mixture Copulas................................................. 165 Dominic Lauterbach and Dietmar Pfeifer 9 Toward a Copula Theory for Multivariate Regular Variation........ 177 Haijun Li 10 CIID Frailty Models and Implied Copulas.............................. 201 Jan-Frederik Mai, Matthias Scherer, and Rudi Zagst 11 Copula-Based Models for Multivariate Discrete Response Data...... 231 Aristidis K. Nikoloulopoulos ix x Contents 12 Vector Generalized Linear Models: A Gaussian Copula Approach.................................................................... 251 Peter X.-K. Song, Mingyao Li, and Peng Zhang 13 Application of Bernstein Copulas to the Pricing of Multi-Asset Derivatives................................................. 277 Bertrand Tavin Index............................................................................... 289 [hide][/hide] |
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