Volatility Depend on Market Trades and Macro Theory

Victor Olkhov
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引用次数: 4

Abstract

This paper presents probability distributions for price and returns random processes for averaging time interval {\Delta}. These probabilities determine properties of price and returns volatility. We define statistical moments for price and returns random processes as functions of the costs and the volumes of market trades aggregated during interval {\Delta}. These sets of statistical moments determine characteristic functionals for price and returns probability distributions. Volatilities are described by first two statistical moments. Second statistical moments are described by functions of second degree of the cost and the volumes of market trades aggregated during interval {\Delta}. We present price and returns volatilities as functions of number of trades and second degree costs and volumes of market trades aggregated during interval {\Delta}. These expressions support numerous results on correlations between returns volatility, number of trades and the volume of market transactions. Forecasting the price and returns volatilities depend on modeling the second degree of the costs and the volumes of market trades aggregated during interval {\Delta}. Second degree market trades impact second degree of macro variables and expectations. Description of the second degree market trades, macro variables and expectations doubles the complexity of the current macroeconomic and financial theory.
波动取决于市场交易和宏观理论
本文给出了价格的概率分布,并返回了平均时间间隔{\Delta}的随机过程。这些概率决定了价格和收益的波动性。我们定义价格的统计时刻,并返回随机过程作为成本和市场交易总量在区间{\Delta}期间的函数。这些统计矩集决定了价格和收益概率分布的特征函数。波动率由前两个统计矩描述。第二统计矩由成本和市场交易量在区间{\Delta}期间聚合的二度函数来描述。在区间{\Delta}期间,我们将价格和收益波动率表示为交易数量和二度成本以及市场交易量的函数。这些表达式支持收益、波动性、交易数量和市场交易量之间相关性的许多结果。预测价格和收益波动取决于对成本和市场交易量在区间{\Delta}期间汇总的第二度建模。二度市场交易影响二度宏观变量和预期。二级市场交易、宏观变量和预期的描述使当前宏观经济和金融理论的复杂性增加了一倍。
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