基于投资者情感倾向的P2P市场成交量预测模型

Prediction Model of P2P Trading Volume Based on Investor Sentiment

当前对Peer-to-Peer市场成交量的研究多种多样,但是常见方法只考虑了将投资者信息和市场信息作为特征,未考虑投资者情感变化与市场的关系。研究显示投资者的情感会对投资者的决策和行为产生深刻的影响。为此,以金融理论为基础,文中提出了基于投资者情感倾向预测P2P市场成交量的方法。首先以网贷之家的文本评论数据为研究对象,利用TextCNN模型对文本进行情感分类,得出情感倾向变化的时间序列,达到度量投资者情感变化趋势的目的;然后,通过格兰杰因果检验和皮尔逊相关系数验证投资者情感时间序列与成交量指数之间的关系;最终使用基于长短期记忆网络的预测模型预测Peer-to-Peer市场的成交量。实验结果表明,将情感特征加入到成交量预测模型能显著提高模型的预测能力。

There are many kinds of studies on the trading volume of Peer-to-Peer market.However,the common methods only take investor and market information as characteristics,and donot consider the relationship between investor sentiment changes and the market.The research shows that investors’sentiments have a profound impact on their investment decisions and behaviors.Therefore,according to the financial theory,this paper proposed a method to predict the trading volume of Peer-to-Peer market based on investor’s sentimental tendency.Firstly,the comments of WangDaiZhiJia is taken as the research object and applied TextCNN model for sentiment classification.The time series of sentiment tendency is obtained,so as to achieve the purpose of measuring the trend of investor sentiment.Secondly,it verifies the relationship between investor’s emotion time series and trading volume index through Granger causality test and Pearson correlation coefficient.Finally,a predictive model based on long short term memory network is employed to predict the trading volume of the Peer-to-Peer market.The experimental results show that by adding sentimental features to the trading volume prediction model,the predictive ability of the model is improved significantly.