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Prediction Future Asset Price which is Non-concordant with the Historical Distribution

机译:预测未来资产价格与历史分配是非协调一态的

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This paper attempts to predict the major characteristics of the future asset price which is non-concordant with the distribution estimated from the price today and the prices on a large number of previous days. The three major characteristics of the i-th non-concordant asset price are the length of the interval between the occurrence time of the previous non-concordant asset price and that of the present non-concordant asset price, the indicator which denotes that the non-concordant price is extremely small or large by its values -1 and 1 respectively, and the degree of non-concordance given by the negative logarithm of the probability of the left tail or right tail of which one of the end points is given by the observed future price. The vector of three major characteristics of the next non-concordant price is modelled to be dependent on the vectors corresponding to the present and 1-1 previous non-concordant prices via a 3-dimensional conditional distribution which is derived from a 3(1 + 1)-dimensional power-normal mixture distribution. The marginal distribution for each of the three major characteristics can then be derived from the conditional distribution. The mean of the j-th marginal distribution is an estimate of the value of the j-th characteristics of the next non-concordant price. Meanwhile, the 100(α/2) % and 100(1 - α/2) % points of the j-th marginal distribution can be used to form a prediction interval for the j-th characteristic of the next non-concordant price. The performance measures of the above estimates and prediction intervals indicate that the fitted conditional distribution is satisfactory. Thus the incorporation of the distribution of the characteristics of the next non-concordant price in the model for asset price has a good potential of yielding a more realistic model.
机译:本文试图预测未来资产价格的主要特点,这与当今价格估计的分配和大量前几天的价格是非协调一致的。第十三次非协调资产价格的三大特征是前一个非协调资产价格的发生时间与现有非协调资产价格的间隔的长度,指标表示非持卡人的价格非常小或较大,其值分别为-1和1,以及由左尾或右尾的概率的负对数给出的非协调程度,其中一个终点由其中一个结束点观察到未来的价格。下一个非协调价格的三个主要特征的向量被建模,以取决于通过从A 3(1 +的三维条件分布相对应的向量和1-1个以前的非协调价格。(1 + 1) - 二维功率正常混合分布。然后可以从条件分布中得出三个主要特征中的每一个的边缘分布。第j族边际分布的平均值是下一个非协调价格的第j-t特征的价值的估计。同时,第j-Th边缘分布的100(α/ 2)%和100(1 - α/ 2)%的点可用于形成下一个非协调价格的第j族特征的预测间隔。上述估计和预测间隔的性能测量表明,拟合条件分布是令人满意的。因此,在资产价格模型中纳入了下一个非交易价格的特征的分布具有良好的潜力,产生更现实的模型。

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