scholarly journals Calibrating and Simulating Copula Functions in Financial Applications

2021 ◽  
Vol 7 ◽  
Author(s):  
Annalisa Di Clemente ◽  
Claudio Romano
Keyword(s):  
Financial Market ◽  
Asset Returns ◽  
Copula Function ◽  
Dependence Structure ◽  
Financial Asset ◽  
Financial Assets ◽  
Copula Functions ◽  
Financial Applications ◽  
Different Types ◽  
Financial Asset Returns

Copula functions can be utilized in financial applications to determine the dependence structure of the financial asset returns in the portfolio. Empirical evidence has proved the inadequacy of the multi-normal distribution, traditionally adopted to model the financial asset returns distribution. Copula functions can be employed in a flexible way for building efficient algorithms and to simulate a more adequate distribution of the financial assets. This paper aims to describe some simple statistical procedures currently employed to calibrate the copula functions to the financial market data. Furthermore, we present some useful methods for choosing which copula function better fits the real financial data. Also, some algorithms to simulate random variates from certain types of copula functions are illustrated. Finally, for illustration purposes, the previous procedures described are applied to two Italian equities. In particular, we show how to generate efficient Monte Carlo scenarios of equity log-returns in the bivariate case using different types of copula functions.

scholarly journals Pricing Multivariate European Equity Option Using Gaussians Mixture Distributions and EVT-Based Copulas

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Abba Mallam Hassane ◽  
Barro Diakarya ◽  
Yaméogo WendKouni ◽  
Saley Bisso
Keyword(s):  
Extreme Values ◽  
Asset Returns ◽  
Copula Function ◽  
Dependence Structure ◽  
Mixture Distributions ◽  
Equity Options ◽  
Financial Asset Returns ◽  
Equity Option ◽  
Digital Option ◽  
European Equity

In this article, we present an approach which allows taking into account the effect of extreme values in the modeling of financial asset returns and in the valorisation of associated options. Specifically, the marginal distribution of asset returns is modelled by a mixture of two Gaussian distributions. Moreover, we model the joint dependence structure of the returns using a copula function, the extremal one, which is suitable for our financial data, particularly the extreme values copulas. Applications are made on the Atos and Dassault Systems actions of the CAC40 index. Monte Carlo method is used to compute the values of some equity options such as the call on maximum, the call on minimum, the digital option, and the spreads option with the basket (Atos, Dassault systems) as underlying.

ON DEFAULT CORRELATION AND PRICING OF COLLATERALIZED DEBT OBLIGATION BY COPULA FUNCTIONS

2006 ◽  
Vol 05 (03) ◽  
pp. 483-493 ◽  
Author(s):  
PING LI ◽  
HOUSHENG CHEN ◽  
XIAOTIE DENG ◽  
SHUNMING ZHANG
Keyword(s):  
Credit Derivatives ◽  
Copula Function ◽  
Dependence Structure ◽  
Default Correlation ◽  
Specific Kind ◽  
Copula Functions ◽  
Recovery Rates ◽  
Collateralized Debt Obligation ◽  
Collateralized Debt ◽  
Debt Obligation

Default correlation is the key point for the pricing of multi-name credit derivatives. In this paper, we apply copulas to characterize the dependence structure of defaults, determine the joint default distribution, and give the price for a specific kind of multi-name credit derivative — collateralized debt obligation (CDO). We also analyze two important factors influencing the pricing of multi-name credit derivatives, recovery rates and copula function. Finally, we apply Clayton copula, in a numerical example, to simulate default times taking specific underlying recovery rates and average recovery rates, then price the tranches of a given CDO and then analyze the results.

The Volatility for Pre and Post Global Financial Crisis

2011 ◽  
Vol 2 (2) ◽  
pp. 82-95
Author(s):  
Shih-Yung Wei ◽  
Jack J. W. Yang ◽  
Jen-Tseng Chen ◽  
Wei-Chiang Samuelson Hong
Keyword(s):  
Hong Kong ◽  
Financial Crisis ◽  
Global Financial Crisis ◽  
Asset Returns ◽  
Financial Asset ◽  
Asymmetric Volatility ◽  
Empirical Results ◽  
Long Run ◽  
Short Run ◽  
Financial Asset Returns

The asymmetric volatility, temporary volatility, and permanent volatility of financial asset returns have attracted much interest in recent years. However, a consensus has not yet been reached on the causes of them for both the stocks and markets. This paper researched asymmetric volatility and short-run and long-run volatility through global financial crisis for eight Asian markets. EGARCH and CGARCH models are employed to deal with the daily return to examine the degree of asymmetric volatility (temporary volatility and permanent volatility). The authors find that after global financial crisis asymmetric volatility is lower (expect Hong Kong), and the long-run effect is more than the short-run effect. The empirical results for the short-run show that, after global financial crisis, there is significant decreasing in China and Taiwan but not in Japan; the others are significantly increasing. For the long-run, there is significant decreasing (except Thailand and Korea).

Fluctuation patterns in high-frequency financial asset returns

2008 ◽  
Vol 82 (6) ◽  
pp. 68005 ◽  
Author(s):  
T. Preis ◽  
W. Paul ◽  
J. J. Schneider
Keyword(s):  
High Frequency ◽  
Asset Returns ◽  
Financial Asset ◽  
Financial Asset Returns
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