Modeling financial markets using copula functions

2012 ◽  
Vol 7 (4) ◽  
pp. 291-303
Author(s):  
Patrick Persons ◽  
Mark Jadin ◽  
Jennifer Woychik
Keyword(s):  
Financial Markets ◽  
Copula Functions

scholarly journals Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Qian Liu
Keyword(s):  
Monte Carlo ◽  
Credit Risk ◽  
Financial Markets ◽  
Financial Institutions ◽  
Least Square ◽  
Copula Functions ◽  
Default Intensity ◽  
Interest Rate Swaps ◽  
Counterparty Credit Risk ◽  
Credit Valuation Adjustment

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short) as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.

scholarly journals Tail Dependence in Financial Markets: A Dynamic Copula Approach

Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 116
Author(s):  
Federico Pasquale Cortese
Keyword(s):  
Financial Markets ◽  
Value At Risk ◽  
Main Idea ◽  
Tail Dependence ◽  
Conditional Correlation ◽  
Copula Functions ◽  
Dynamic Copula ◽  
Copula Approach ◽  
Equity Indices ◽  
The Impact

This article is concerned with the study of the tail correlation among equity indices by means of dynamic copula functions. The main idea is to consider the impact of the use of copula functions in the accuracy of the model’s parameters and in the computation of Value-at-Risk (VaR). Results show that copulas provide more sophisticated results in terms of the accuracy of the forecasted VaR, in particular, if they are compared with the results obtained from Dynamic Conditional Correlation (DCC) model.

European Financial Markets and Institutions

2009 ◽  
Author(s):  
Jakob de Haan ◽  
Sander Oosterloo ◽  
Dirk Schoenmaker
Keyword(s):  
Financial Markets ◽  
Markets And Institutions

Discrete Models of Financial Markets

2009 ◽  
Author(s):  
Marek Capinski ◽  
Ekkehard Kopp
Keyword(s):  
Financial Markets ◽  
Discrete Models

Financial Markets and Institutions

2012 ◽  
Author(s):  
Jakob de Haan ◽  
Sander Oosterloo ◽  
Dirk Schoenmaker
Keyword(s):  
Financial Markets ◽  
Markets And Institutions
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