修正Ornstein Uhlenbeck过程以纳入投机对金融市场波动的影响

Hendrietha Joan Hendricks, J. Ongala, D. Ntirampeba
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引用次数: 0

摘要

摘要:金融市场参与者经常根据手头的某些信息推测市场的行为。这种投机行为助长了金融市场的波动,从而使市场不稳定。Ornstein Uhlenbeck (OU)模型已被广泛用于波动性建模,然而,在OU模型中尚未研究投机对波动性的贡献。因此,本研究的重点是通过加入一个时间相关的指数函数来修改OU模型,以满足投机对波动率的贡献。然后研究了改进OU模型的统计特性,并将结果与OU模型的特性进行了比较。NAD/USD汇率数据用于比较和验证改进模型与OU模型。研究发现,OU模型和改进OU模型具有相似的期望价格,而OU模型的价格方差向上稳定至16,改进OU模型的价格方差向下稳定至0.01。改进模型的方差比OU模型的方差小得多。此外,我们发现,对于OU模型,预测价格的分布随不同的提前期而变化,而改进OU模型的预测价格的分布不随不同的提前期而变化。因此,OU模型是特定于时间的模型,而改进的OU模型是不变的时间模型。因此,改进的OU模型被发现比OU模型更有效。
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Modification of the Ornstein Uhlenbeck Process to Incorporate the Influence of Speculation on Volatility in Financial Markets
Corresponding Author: Hendrietha Joan Hendricks Applied Mathematics and Statistics, Namibia University of Science and Technology, Namibia E-mail: theressa.joy.love@gmail.com Abstract: Financial market participants often speculate on how markets would behave in the light of certain information at hand. This speculation contributes to volatility within the financial market and consequently, it makes the market unstable. The Ornstein Uhlenbeck (OU) model has intensively been used in modelling volatility, however, the contribution of speculation on volatility has not been studied in the OU model. Therefore, this study focuses on the modification of the OU model by incorporating a time dependent exponential function that caters for the contribution of speculation on volatility. The statistical properties of the Improved OU model are then studied and the results compared with properties of the OU model. NAD/USD exchange rate data is used to compare and validate the Improved model with the OU model. It was found that both the OU and Improved OU model had a similar expected price, while variance of price for the OU model stabilised upwards up to 16 and variance of price for the Improved OU model stabilised downwards up to 0.01. The variance of the Improved model was found to be much lower than that of the OU model. Additionally, it was found that the distribution of the forecasted price changed with different lead times for the OU model whereas, the distribution of the forecasted price for the Improved OU model did not change with different lead times. Thus, the OU model is a time specific model whereas the Improved OU model is an invariant time model. Consequently, the Improved OU model was found to be more efficient than the OU model.
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