Copula-GARCH模型下的两资产期权定价
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Abstract
This paper minimizes the risk of Brent oil in a multivariate portfolio, with three risk-minimizing goals: variance, parametric value-at-risk (VaR), and semiparametric value-at-risk. Brent oil is combined with five emerging ASEAN (Association of Southeast Asian Nations) stock indexes and five more developed non-ASEAN indexes. The preliminary dynamic equiciorrelation estimates indicate that the ASEAN stock indexes are less integrated and thus potentially better for diversification purposes. The Copula-GARCH模型下的两资产期权定价 portfolio results show that the ASEAN indexes are better hedges for oil in terms of minimum variance and minimum VaR. However, although the ASEAN indexes have higher extreme risk, we find that a portfolio with these indexes has slightly lower modified VaR than a portfolio with the non-ASEAN indexes. The reason is probably the higher variance and higher equicorrelation of the non-ASEAN indexes, because these Copula-GARCH模型下的两资产期权定价 inputs affect the value of the modified downside risk of a portfolio. As a complementary analysis, we put a 50 percent constraint on Brent in the portfolios, and then the portfolios with the non-ASEAN indexes have better risk-minimizing results.
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". Reliable communication protocols require that all the intended recipients of a message receive the message intact. Automatic Repeat reQuest (ARQ) techniques are used in unicast protocols, but they do not scale well to multicast protocols with large groups of receivers, since segment losses tend to b . "
to become uncorrelated thus greatly reducing the effectiveness of retransmissions. In such cases, Copula-GARCH模型下的两资产期权定价 Forward Error Correction (FEC) techniques can be used, consisting in the transmission of redundant packets (based on error correcting codes) to allow the receivers to recover from independent packet losses
by Niels Bormann, Sami Saarinen, Graeme Kelly - EUMETSAT/ECMWF Fellowship Programme Research Report 12
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, quality control procedures, and other factors introduce spatially correlated errors. The spatial structure of the error correlations is investigated based on a one-year dataset of pairs of collocations between AMVs and radiosonde observations. Assuming spatially uncorrelated sonde errors, the spatial AMV
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". We consider tests for lack of fit in ARMA models with nonindependent innovations. In this framework, the standard Box–Pierce and Ljung–Box portmanteau tests can perform poorly. Specifically, the usual text book formulas for asymptotic distributions are based on strong assumptions and should not be a . "
We consider tests for lack of fit in ARMA models with nonindependent innovations. In this framework, the standard Box–Pierce and Ljung–Box portmanteau tests can perform poorly. Specifically, the usual text book formulas for asymptotic distributions are based on strong assumptions and should not be applied without careful consideration. In this article we Copula-GARCH模型下的两资产期权定价 derive the asymptotic covariance matrix ρ̂m of a vector of autocorrelations for residuals of ARMA models under weak assumptions on the noise. The asymptotic distribution of the portmanteau statistics Copula-GARCH模型下的两资产期权定价 Copula-GARCH模型下的两资产期权定价 follows. A consistent estimator of ρ̂m, and a modification of the portmanteau tests are proposed. This allows us to construct valid asymptotic significance limits for the residual autocorrelations, and (asymptotically) valid goodness-of-fit tests, when the underlying noise process is assumed to be noncorrelated rather than independent or a martingale difference. A set of Monte Carlo experiments, and an application to the Standard & Poor 500 returns, illustrate the practical relevance of our theoretical results.