基于一种炒股行为生成的随机变量与分布估计

A random variable generated based on a behavior of investing in stocks and its estimation of distribution

从大数据、机器学习和行为金融学的角度出发,通过设计一个算法定义了一个表现按照某种初级炒股行为买卖一支股票的收益状况的随机变量R,并进行有关研究。基于这支股票的一定的折现历史数据运用所设计的算法求出R的一个样本;根据该样本做出R的一个经验分布;再根据该经验分布建立关于R的近似解析分布的一个序,并进而给出一种求优化近似解析分布的方法。基于R的生成方式及相关探讨展示它的意义,并揭示出一些值得进一步研究的问题。所做工作可为炒股提供一定的启示,可为从大数据、机器学习和行为金融学的角度出发进一步研究股市提供一定的启示。

From the perspective of big data,machine learning and behavioral finance,by designing an algorithm,which models the process that a person buys and sells a stock in a primary trading behavior,define a random variable R that represents the result of the process and make some related discussions.A sample of Ris made out with the designed algorithm basing on some discounted history data of the stock and further a empirical distribution of Ris made according to the sample.An order relation of the approximate analytical distribution of Ris defined according to the empirical distribution and further approach to obtain the approximate analytical distribution of optimization is proposed.Finally the significance of the defined random variable is demonstrated and some problems deserved to further research are revealed basing on the way by which we define the random variable Rand the related discussions.What we done can provide some enlightenments for investing in stocks,and can also provide some ideas for scholars to study market of stocks from the perspective of big data,machine learning and behavioral finance.