Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be c...Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be constructed by the mixed linear model approaches for experimental data with sampling errors within populations or with some missing values.Unweighted pair-group method ( UPGM ) is suggested as fusion method. Sampling variances of estimated dissimilarity coefficient can be obtained by the jackknife procedure.A one-tail t-test is applicable for detecting significance of dissimilarity of populaions within specific group.Unbiasedness and efficiency for estimation of dissimilarity coefficients are proved by Monte Carolo simulations.Worked example from cotton yield data is given for demonstration of the use of these cluster methods.展开更多
Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon a...Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon and solve the ‘volatility smile dilemma’.This paper combines the variance gamma model with the least squares Monte Carlo simulation method to empirically analyze the Everbright convertible bond based on its high activity in the Chinese market.In this paper,the predicted price and the actual price are compared,and the applicability of the variance gamma model in the Chinese convertible bond market is analyzed.Empirical results show that the fitting price predicted by the variance gamma model is consistent with the actual price trend,indicating that the method is applicable to the Chinese convertible bond market.展开更多
文摘Two mixed linear models are proposed for grouping populations by a dissimilarity coefficent which has two parameters for squared difference of marginal mean and variance component of interaction.Cluster trees can be constructed by the mixed linear model approaches for experimental data with sampling errors within populations or with some missing values.Unweighted pair-group method ( UPGM ) is suggested as fusion method. Sampling variances of estimated dissimilarity coefficient can be obtained by the jackknife procedure.A one-tail t-test is applicable for detecting significance of dissimilarity of populaions within specific group.Unbiasedness and efficiency for estimation of dissimilarity coefficients are proved by Monte Carolo simulations.Worked example from cotton yield data is given for demonstration of the use of these cluster methods.
文摘Due to the‘spike and tail’ phenomenon of asset returns,the applicability of the Black-Scholes model for pricing convertible bonds has been questioned,and the variance gamma model can cope well with this phenomenon and solve the ‘volatility smile dilemma’.This paper combines the variance gamma model with the least squares Monte Carlo simulation method to empirically analyze the Everbright convertible bond based on its high activity in the Chinese market.In this paper,the predicted price and the actual price are compared,and the applicability of the variance gamma model in the Chinese convertible bond market is analyzed.Empirical results show that the fitting price predicted by the variance gamma model is consistent with the actual price trend,indicating that the method is applicable to the Chinese convertible bond market.
