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How does Google search affect trader positions and crude oil prices?

Xin Li; Jian Ma; Shouyang Wang; Xun Zhang
OTHER
香港城市大学深圳研究院
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摘要


Novel data series constructed from Internet-based platforms such as Google have been widely applied to analyze economic and financial indicators and have been demonstrated to be effective in short-term forecasts. However, few studies have demonstrated the role of Google search data in analyzing trader positions and energy price volatility. This paper uses the Google search volume index (GSVI) to measure investor attention, and investigate the relationships among the GSVI, different trader positions, and crude oil prices from January 2004 to June 2014. The empirical results present some new evidences. First, the GSVI measures investor attention from noncommercial and nonreporting traders, rather than commercial traders. Second, the feedback loop between GSVI and crude oil price is verified. Third, the GSVI improves the forecast accuracy of crude oil price in recursive one-week-ahead forecasts. This paper contributes to existing literature by incorporating open source Internet-based data into the analysis and prediction of crude oil prices, as well as other prices in financial markets in the Big Data Era.

关键词

Internet-based dataGoogle search volume indexCrude oil priceGranger causalityTrader positions

出版信息

论文状态
公开发表
期刊名称
Economic Modelling
发表日期
2015-9-1
卷
49
期
-
页码
162-171
DOI
10.1016/j.econmod.2015.04.005

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