基于市场的价格自相关
Market-Based Price Autocorrelation
AI总结：
本文通过假设市场交易额与交易量的随机性决定价格特性，推导出价格统计矩、波动率及自相关对交易统计特性的依赖关系，并指出预测价格自相关需先预测交易额与交易量的统计矩和相关性。
摘要：
本文假设市场交易额与交易量的随机性决定了随机市场价格的特性。我们推导出价格的前两个统计矩和价格波动率对市场交易额与交易量的统计矩、波动率及相关性的直接依赖关系。这有助于描述基于市场的价格在时间 t 与 t-τ 之间的自相关对交易额与交易量之间统计矩和相关性的依赖。这突显了市场交易规模随机性对价格统计矩和自相关的影响。市场交易额与交易量的统计矩和相关性通过传统的基于频率的概率进行评估。基于市场的价格自相关与通过价格时间序列的基于频率的概率分析所评估的自相关之间的区别，揭示了对价格概率定义的不同方法。为了预测基于市场的价格自相关，应当预测交易额与交易量的统计矩和相关性。
英文摘要：
This paper assumes that the randomness of market trade values and volumes determines the properties of stochastic market prices. We derive the direct dependence of the first two price statistical moments and price volatility on statistical moments, volatilities, and correlations of market trade values and volumes. That helps describe the dependence of market-based price autocorrelation between times t and t-τ on statistical moments and correlations between trade values and volumes. That highlights the impact of the randomness of the size of market deals on price statistical moments and autocorrelation. Statistical moments and correlations of market trade values and volumes are assessed by conventional frequency-based probabilities. The distinctions between market-based price autocorrelation and autocorrelation that are assessed by the frequency-based probability analysis of price time series reveal the different approaches to the definitions of price probabilities. To forecast market-based price autocorrelation, one should predict the statistical moments and correlations of trade values and volumes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
