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