1,721,129 research outputs found

    Currency Hedging for International Stock Portfolios: A General Approach

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    This paper tests whether hedging currency risk improves the performance of international stock portfolios. We use a generalized performance measure which allows for investor-dependencies such as different utility functions and the presence of nontraded risks. In addition we show that an auxiliary regression, similar to the Jensen regression, provides a wealth of information about the optimal portfolio holdings for investors for the non mean-variance case. This is analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean-variance case. Our empirical results show that static hedging with currency forwards does not lead to improvements in portfolio performance for a US investor that holds a stock portfolio from the G5 countries. On the other hand, hedges that are conditional on the current interest rate spread do lead to significant performance improvements. Also, when an investor has a substantial exogenous exposure to one of the currencies, currency hedging clearly improves his portfolio performance. While these results hold for investors with power utility as well as with mean-variance utility functions, the optimal hedge ratios for these investors are different.

    Currency Hedging for International Stock Portfolios

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    This paper tests whether hedging currency risk improves the performance of international stock portfolios. We use a generalized performance measure which allows for investor-dependencies such as different utility functions and the presence of nontraded risks. In addition we show that an auxiliary regression, similar to the Jensen regression, provides a wealth of information about the optimal portfolio holdings for investors for the non mean-variance case. This is analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean-variance case. Our empirical results show that static hedging with currency forwards does not lead to improvements in portfolio performance for a US investor that holds a stock portfolio from the G5 countries. On the other hand, hedges that are conditional on the current interest rate spread do lead to significant performance improvements. Also, when an investor has a substantial exogenous exposure to one of the currencies, currency hedging clearly improves his portfolio performance. While these results hold for investors with power utility as well as with mean-variance utility functions, the optimal hedge ratios for these investors are different.currency risk;forwards;hedging;international asset pricing;portfolio choice

    Testing for Spanning with Futrures Contracts and Nontraded Assets: A General Approach

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    This paper generalizes the notion of mean-variance spanning as de- ned in the seminal paper of Huberman & Kandel (1987) in three di- mensions.It is shown how regression techniques can be used to test for spanning for more general classes of utility functions, in case some as- sets are nontraded, and in case some of the assets are zero-investment securities such as futures contracts.We then implement these tech- niques to test whether a basic set of three international stock indices, the S&P 500, the FAZ (Germany), and the FTSE (UK), span a set of commodity and currency futures contracts.Depending on whether mean-variance, logarithmic, or power utility functions are considered, the hypothesis of spanning can be rejected for most futures contracts considered.If an investor has a position in a nontraded commodity, then the hypothesis of spanning can almost always be rejected for fu- tures contracts on that commodity for all utility functions considered.For currency futures this is only the case for a power utility function that re ects a preference for skewness.Finally, if we explicitly take into account net futures positions of large traders that are known to have predictive power for futures returns, the hypothesis of spanning can be rejected for most futures contracts.regression analysis;futures

    Residual-based rank specification tests for AR-GARCH type models

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    This paper derives the asymptotic distribution for a number of rank-based and classical residual specification tests in AR–GARCH type models. We consider tests for the null hypotheses of no linear and quadratic serial residual autocorrelation, residual symmetry, and no structural breaks. We also apply our method to backtesting Value-at-Risk. For these tests we show that, generally, no size correction is needed in the asymptotic test distribution when applied to AR–GARCH residuals obtained through Gaussian quasi maximum likelihood estimation. To be precise, we give exact expressions for the limiting null distribution of the test statistics applied to (standardized) residuals, and find that standard critical values often, though not always, lead to conservative tests. For this result, we give simple necessary and sufficient conditions. Simulations show that our asymptotic approximations work well for a large number of AR–GARCH models and parameter values. We also show that the rank-based tests often, though not always, have superior power properties over the classical tests, even if they are conservative. An empirical application illustrates the relevance of these tests to the AR–GARCH models for weekly stock market return indices of some major and emerging countries
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