Analysis of Contagion in Financial Markets Based on the Gradient Measurement of the Growth in Financial Markets and Conditional Copula Functions

2013 ◽  
Author(s):  
Rafaa Siedlecki ◽  
Daniel Papla
Keyword(s):  
Financial Markets ◽  
Copula Functions ◽  
Conditional Copula ◽  
Gradient Measurement

scholarly journals Trading strategies with copulas

2013 ◽  
Vol 6 (1) ◽  
pp. 83-108 ◽  
Author(s):  
Yolanda Stander ◽  
Daniël Marais ◽  
Ilse Botha
Keyword(s):  
Confidence Level ◽  
Tail Dependence ◽  
Trading Strategy ◽  
Trading Strategies ◽  
Dependence Structure ◽  
Pairs Trading ◽  
Copula Functions ◽  
Conditional Copula ◽  
Historical Relationship ◽  
Bivariate Dependence

A new approach is proposed to identify trading opportunities in the equity market by using the information contained in the bivariate dependence structure of two equities. The relationships between the equity pairs are modelled with bivariate copulas and the fitted copula structures are utilised to identify the trading opportunities. Two trading strategies are considered that take advantage of the relative mispricing between a pair of correlated stocks and involve taking a position on the stocks when they diverge from their historical relationship. The position is then reversed when the two stocks revert to their historical relationship. Only stock-pairs with relatively high correlations are considered. The dependence structures of the chosen stock-pairs very often exhibited both upper- and lower-tail dependence, which implies that copulas with the correct characteristics should be more effective than the more traditional approaches typically applied. To identify trading opportunities, the conditional copula functions are used to derive confidence intervals for the two stocks. It is shown that the number of trading opportunities is highly dependent on the confidence level and it is argued that the chosen confidence level should take the strength of the dependence between the two stocks into account. The backtest results of the pairs-trading strategy are disappointing in that even though the strategy leads to profits in most cases, the profits are largely consumed by the trading costs. The second trading strategy entails using single stock futures and it is shown to have more potential as a statistical arbitrage approach to construct a portfolio.

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.

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
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