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厚尾与非对称依赖下的定汇率期权定价AI 解读

We present an approach to pricing European quanto options assuming that the underlying instruments follow a multivariate normal tempered stable (NTS) process. This allows for both fat-tailedness and asymmetric dependence between the returns on the underlying asset and the exchange rate. In an empirical application, we estimate the market and risk-neutral parameters for a quanto construction involving the Nikkei 225 index, as the underlying asset, and the Japanese yen and the…

摘要暂缺

重尾随机变量的卡方型分布AI 解读

The distribution of sums of squared random variables with heavy-tailed distributions is investigated. Considering random variables in the domain of attraction of a stable Paretian law we derive the limiting distribution as the degrees of freedom approach infinity. The finite-degrees-of-freedom behavior for stable Paretian variates is simulated. Response surface techniques are employed to compactly summarize the simulation results for a relevant range of significance levels.

摘要暂缺

估计线性动态模型的脉冲响应、阶跃响应与方差分解的渐近分布AI 解读

Formulas are derived for computing asymptotic covariance matrices of sets of impulse responses, step responses, or variance decompositions of estimated dynamic simultaneous-equations models in vector autoregressive moving-average (VARMA) form. Computed covariances would be used to test linear restrictions on sets of impulse responses, step responses, or variance decompositions. The results unify and extend previous formulas to handle any model in VARMA form, provide accurate…

利用分块 Levinson 方法计算多元 ARMA 模型的理论自协方差AI 解读

SUMMARY A closed form expression relating the theoretical autocovariances of a multivariate autoregressive moving average (ARMA) model to the ARMA parameters in terms of a system of linear equations has been presented recently. Using this result and the special Hankel plus Toeplitz structure of the coefficient matrix obtained after suitable partitioning, this paper presents a method for computing multivariate autocovariance functions that is based on a block Levinson…

多元自回归移动平均时间序列理论自协方差矩阵的计算AI 解读

SUMMARY Matrix expressions relating the theoretical autocovariances of autoregressive moving average (ARMA) processes to their parameters are derived and used to design an efficient procedure for computing autocovariance sequences of multivariate ARMA processes. The method proposed is more efficient than others suggested in the literature and, in particular, reduces the computational burden associated with exact maximum likelihood estimation of ARMA models. The closed form…

In a recent article, Garcia-Ferrer, Highfield, Palm, and Zellner (1987) used pooling techniques to forecast annual output growth rates in nine countries. Examining various model specifications, they found that, among the fixed-parameter models investigated, a third-order autoregressive (AR) model with leading indicators, AR(3)LI, produces the best forecasts overall. A reexamination using state-space methods shows that a more parsimonious fixed-parameter model, which does not…