标题： 非高斯日内股票收益率模型 显示英文标题

标题： Model for Non-Gaussian Intraday Stock Returns

摘要： 股票价格已知表现出非高斯动力学特性，人们对理解这种行为的起源充满兴趣。 在这里，我们提出了一种模型来解释日内股票价格波动（称为日内收益率）分布的形状和尺度，并使用伦敦证券交易所交易的多只股票的大规模数据库验证了该模型。 我们提供了证据表明这些股票的收益率分布是非高斯的，且形状相似，并且在日内时间尺度上分布似乎保持稳定。 我们通过假设收益率的波动性在日内是恒定的，但在更长的时间段内变化，其倒数平方遵循伽马分布，来解释这些结果。 这使得日内时间尺度上的收益率呈学生分布。 预测结果与我们研究的所有股票的数据以及整个收益率分布的所有区域都显示出极好的一致性。 显示英文摘要

摘要： Stock prices are known to exhibit non-Gaussian dynamics, and there is much interest in understanding the origin of this behavior. Here, we present a model that explains the shape and scaling of the distribution of intraday stock price fluctuations (called intraday returns) and verify the model using a large database for several stocks traded on the London Stock Exchange. We provide evidence that the return distribution for these stocks is non-Gaussian and similar in shape, and that the distribution appears stable over intraday time scales. We explain these results by assuming the volatility of returns is constant intraday, but varies over longer periods such that its inverse square follows a gamma distribution. This produces returns that are Student distributed for intraday time scales. The predicted results show excellent agreement with the data for all stocks in our study and over all regions of the return distribution.