Performance Analysis for Portfolio Construction and Stock Price Prediction of Social Media Platforms

Xintong Lin; Xuepu Tan; Xuening Yang

doi:10.54691/bcpbm.v26i.2067

Authors

Xintong Lin
Xuepu Tan
Xuening Yang

DOI:

https://doi.org/10.54691/bcpbm.v26i.2067

Keywords:

component; Portfolio Construction; Stock Price Prediction; Social Media Platforms; ARIMA Model

Abstract

The stock price prediction and portfolio construction are very important in the application of quantified investments. Risk control and stock price prediction are two challenge problems that we want to solve. In this paper, two main steps are processed to quantify the risk and predict the stock price. Especially, the first step is portfolio optimization, which is based on the Mean-Variance method. The second step is the stock price prediction, which is designed based on the Arima-based method. The results show that the stock “TWTR” and the stock “WB” have the above 90% ratio of the stock combination, which shows that the “Twitter” and “Weibo” social media corporations have a higher expected return with a lower risk. In addition, the best ARIMA model used to fit our data will be the one with parameters p=4, d=0, q=3. Our research has great significance in the application of quantified investments.

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