Modeling Multiple Asset Returns by a Time-Varying t Copula Model

2014 ◽  
pp. 1431-1449
Author(s):  
Long Kang
Keyword(s):  
Asset Returns ◽  
Copula Model ◽  
Time Varying ◽  
T Copula

scholarly journals Research on the Dependence Structure and Risk Spillover of Internet Money Funds Based on C-Vine Copula and Time-Varying t-Copula

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huizi Ma ◽  
Lin Lin ◽  
Han Sun ◽  
Yue Qu
Keyword(s):  
Spillover Effect ◽  
Spillover Effects ◽  
Dependence Structure ◽  
Copula Model ◽  
Time Varying ◽  
Financial Products ◽  
T Copula ◽  
Dependence Relationship ◽  
Vine Copula ◽  
Risk Spillover Effects

Internet money funds (IMFs) are the most widely involved products in the Internet financial products market. This research utilized the C-vine copula model to study the risk dependence structure of IMFs and then introduces the time-varying t-copula model to analyze the risk spillover of diverse IMFs. The results show the following: (1) The risks of Internet-based IMFs, bank-based IMFs, and fund-based IMFs have obvious dependence structure, and the degree of risk dependence among different categories of IMFs is significantly different. (2) There are risk spillover effects among diverse IMFs, and their risk dependence relationship is characterized by cyclical feature. (3) The risk spillover effect among diverse IMFs is pronounced, and dynamic risk dependence between IMFs is characterized by synchronization.

Empirical comparison of skewed t-copula models for insurance and financial data

2020 ◽  
Vol 15 (4) ◽  
pp. 351-361
Author(s):  
Liwei Huang ◽  
Arkady Shemyakin
Keyword(s):  
Bayesian Estimation ◽  
Goodness Of Fit ◽  
Model Performance ◽  
Information Criteria ◽  
Stock Index ◽  
Likelihood Method ◽  
Special Importance ◽  
Copula Model ◽  
Technical Problems ◽  
T Copula

Skewed t-copulas recently became popular as a modeling tool of non-linear dependence in statistics. In this paper we consider three different versions of skewed t-copulas introduced by Demarta and McNeill; Smith, Gan and Kohn; and Azzalini and Capitanio. Each of these versions represents a generalization of the symmetric t-copula model, allowing for a different treatment of lower and upper tails. Each of them has certain advantages in mathematical construction, inferential tools and interpretability. Our objective is to apply models based on different types of skewed t-copulas to the same financial and insurance applications. We consider comovements of stock index returns and times-to-failure of related vehicle parts under the warranty period. In both cases the treatment of both lower and upper tails of the joint distributions is of a special importance. Skewed t-copula model performance is compared to the benchmark cases of Gaussian and symmetric Student t-copulas. Instruments of comparison include information criteria, goodness-of-fit and tail dependence. A special attention is paid to methods of estimation of copula parameters. Some technical problems with the implementation of maximum likelihood method and the method of moments suggest the use of Bayesian estimation. We discuss the accuracy and computational efficiency of Bayesian estimation versus MLE. Metropolis-Hastings algorithm with block updates was suggested to deal with the problem of intractability of conditionals.

scholarly journals Model for Dynamic Multiple of CPPI Strategy

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Guangyuan Xing ◽  
Yong Xue ◽  
Zongxian Feng ◽  
Xiaokang Wu
Keyword(s):  
Risk Management ◽  
Capital Market ◽  
Statistical Estimation ◽  
Composite Index ◽  
Asset Returns ◽  
Time Varying ◽  
Dynamic Setting ◽  
Asset Volatility ◽  
Value Loss ◽  
Gap Risk

Focusing on the parameter “Multiple” of CPPI strategy, this study proposes a dynamic setting model of multiple for gap risk management purpose. First, CPPI gap risk is measured as the probability that the value loss of active asset exceeds its allowed maximum drop determined by a given multiple setting. Moreover, according to the statistical estimation using SV-EVT approach, a dynamic choice of multiple is detailed as a function of time-varying asset volatility, expected loss, and the possibility of occurrence of extreme events in the active asset returns illustrated empirically on Shanghai composite index data. This study not only enriches the literature of dynamic proportion portfolio insurance, but also provides a practical reference for CPPI investors to choose a moderate risky exposure achieving gap risk management, which promotes CPPI’s application in emerging capital market.

Optimal Asset Allocation with Asymptotic Criteria

2003 ◽  
Vol 06 (06) ◽  
pp. 593-604 ◽  
Author(s):  
Slava Karguine
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Linear Functions ◽  
Time Varying ◽  
Fast Computation ◽  
Joint Moments ◽  
Numerical Example ◽  
Conditional Expectations ◽  
Wide Range ◽  
Investment Criterion

With the assumptions that asset returns follow a stochastic multi-factor process with time-varying conditional expectations and investments are linear functions of factors, we calculate asymptotic joint moments of the logarithm of investor's wealth and the factors. These formulas enable fast computation of a wide range of investment criteria. The results are illustrated by a numerical example that shows that the optimal portfolio rules are sensitive to the specification of the investment criterion.

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