To accomplish this task, this paper combines copula modelling with time-varying parameters and pair-copula composition of multiple dependence. The bivariate analyses show an asymmetric dependence between the stock markets as well as contagion. In addition, this work proposes a method to assess the linkages and contagion between two stock markets which takes into account the effects of a third stock market. In applying this method, conditioned on the USA market, most of the evidence of contagion between the Latin American or European markets disappears, but important dependence levels still remain.

The main task of this work was to predict, for the next 15 minutes, the value‐at‐risk (VaR) of an equally weighted portfolio composed of four exchange rates against the American dollar: Japanese yen, euro, Australian dollar and Swiss franc. The dataset consists of transaction prices of each asset recorded every 15 minutes, from January 7, 2013 to December 31, 2013. For each time series, the multiplicative‐component generalized autoregressive conditional heteroskedasticity model of Engle and Sokalska (Journal of Financial Econometrics, 2012, 10, 54–83) is fitted, and the dependence among the series is modeled by a D‐vine pair‐copula. VaR predictions are estimated based on simulated observations of the fitted model following the proposal of Berg and Aas (European Journal of Finance, 2009, 15, 639–659). The proposed method presents good results in terms of out‐of‐sample intraday VaR forecasting.

No abstract

In this paper we use the conditional Value at Risk (CoVaR) and CoVaR variation (∆CoVaR) proposed by Adrian and Brunnermeier (2008 to estimate the Peruvian stock market risk (through the IGBVL) conditioned on the international financial market (given that the S&P500) and conditioned on three of the main commodities exported by Peru: copper, silver and gold. Moreover, the CoVaR measures are compared with the VaR of the IGBVL to understand the differences using conditional and unconditional risk measure estimators. The results show that both CoVaR and ∆CoVaR are useful indicators to measure the Peruvian stock market risk. Keywords: Commodities, copula, CoVaR, S&P500, VaR JEL classifications: C5, G01, G10, G18, G20, G28, G32, G38 Precio internacional de los metales y riesgo de mercado en la Bolsa de Valores de Lima RESUMENEn este trabajo utilizamos el Valor en Riesgo condicional (CoVaR) y la variación CoVaR (∆CoVaR) propuestos por Adrian and Brunnermeier (2008) para estimar el riesgo bursátil peruano (a través del IGBVL) condicionado en el mercado internacional (dado por el índice S&P500) y condicionado en tres de los principales comodities exportados por el Perú: cobre, plata y oro. Además, las medidas CoVaR son comparadas con el VaR del IGBVL para entender las diferencias al utilizar medidas de riesgo condicionales e incondicionales. Los resultados muestran que ambas medidas CoVaR and ∆CoVaR constituyen indicadores útiles para estimar el riesgo bursátil peruano.

No abstract