Multi-Factor Bottom-Up Model for Pricing Credit Derivatives

In this note we continue the study of the stress event model, a simple and intuitive dynamic model for credit risky portfolios, proposed by Duffie and Singleton (1999). The model is a bottom-up version of the multi-factor portfolio credit model proposed by Longstaff and Rajan (2008). By a novel identification of independence conditions, we are able to decompose the loss distribution into a series expansion which not only provides a clear picture of the characteristics of the loss distribution but also suggests a fast and accurate approximation for it. Our approach has three important features: (i) it is able to match the standard CDS index tranche prices and the underlying CDS spreads, (ii) the computational speed of the loss distribution is very fast, comparable to that of the Gaussian copula, (iii) the computational cost for additional factors is mild, allowing for more flexibility for calibrations and opening the possibility of studying multi-factor default dependence of a portfolio via a bottom-up approach. We demonstrate the tractability and efficiency of our approach by calibrating it to investment grade CDS index tranches.credit derivatives, CDO, bottom-up approach, multi-name, intensity-based, risk and portfolio.

A Multivariate GARCH Model with Time-Varying correlations

In this paper we propose a new multivariate GARCH model with time- varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the MLE of the varying- correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.BEKK model, constant correlation, Monte Carlo method, multivariate GARCH model, maximum likelihood estimate, varying correlation

Exchange Rate Exposure of Sectoral Returns and Volatilities: Evidence from Japanese Industrial Sectors

Most studies of exchange rate exposure of stock returns do not address three relevant aspects simultaneously. They are, namely: sensitivity of stock returns to exchange rate changes; sensitivity of volatility of stock returns to volatility of changes in foreign exchange market; and the correlation between volatilities of stock returns and exchange rate changes. In this paper, we employ a bivariate GJR-GARCH model to examine all such aspects of exchange rate exposure of sectoral indexes in Japanese industries. Based on a sample data of fourteen sectors, we find significant evidence of exposed returns and its asymmetric conditional volatility of exchange rate exposure. In addition, returns in many sectors are correlated with those of exchange rate changes. We also find support for the “averaged-out exposure and asymmetries” argument. Our findings have direct implications for practitioners in formulating investment decisions and currency hedging strategies.exchange rate exposure; asymmetric volatility spillovers; GARCH-type models; conditional correlation

Time-Varying Currency Betas: Evidence from Developed and Emerging Markets

This paper examines the conditional time-varying currency betas from five developed markets and four emerging markets. A trivariate BEKK-GARCH-in-mean model is used to estimate the timevarying conditional variance and covariance of returns of stock index, the world market portfolio and changes in bilateral exchange rate between the US dollar and the local currency of each country. It is found that currency betas are more volatile than those of the world market betas. Currency betas in emerging markets are more volatile than those in developed markets. Moreover, we find evidence of long-memory in currency betas. The usefulness of time-varying currency betas are illustrated by two applications.time-varying currency betas; multivariate GARCH-M models; international CAPM; fractionally integrated processes; stochastic dominance

Political Competitiveness

Political competitiveness – which many interpret as the degree of democracy – can be modeled as a monopolistic competition. All regimes are constrained by the threat of "entry," and thereby seek some combination of popular support and political entry barriers. This simple model predicts that many public policies are unrelated to political competitiveness, and that even unchallenged nondemocratic regimes should tax far short of their Laffer curve maximum. Economic sanctions, odious debt repudiation, and other policies designed to punish dictators can have the unintended consequences of increasing oppression and discouraging competition. Since entry barriers are a form of increasing returns, democratic countries (defined according to low entry barriers) are more likely to subdivide and nondemocratic countries are more likely to merge. These and other predictions are consistent with previous empirical findings on comparative public finance, election contests, international conflict, the size of nations, and the Lipset hypothesis. As in the private sector, the number of competitors is not necessarily a good indicator of public sector competitiveness.

Volatility Dynamics in Foreign Exchange Rates: Further Evidence from the Malaysian Ringgit and Singapore Dollar

Singapore dollar are analyzed in this paper. Our approach can simultaneously capture the empirical regularities of persistent and asymmetric effects in volatility and timevarying correlations of financial time series. Consistent with the results of Tse and Tsui (1997), there is only some weak support for asymmetric volatility in the case of the Malaysian ringgit when the two currencies are measured against the US dollar. However, there is strong evidence that depreciation shocks have a greater impact on future volatility levels compared with appreciation shocks of the same magnitude when both currencies measured against the yen. Moreover, evidence of time-varying correlation is highly significant when both currencies are measured against the yen. Regardless of the choice of the numeraire currency and the volatility models, shocks to exchange rate volatility are found to be significantly persistent.Constant correlations; Exchange rate volatility; Fractional integration; Long memory; Bivariate asymmetric GARCH; Varying correlations