Investor Psychological Bias and Speculation: Asymmetric Impacts of Big Data on Commodity Price

This research attempts to propose a new measure of investor psychological bias with big data crawled from the web. The author constructs the investor bias measure with web search data and investigate the influences of this new measure on crude oil futures prices. Using 225,250 data points from Google, this paper computes the investor bias, and evaluates it with trading volumes. The author establishes a Markov switching model and reveals that the influences of investor bias on crude oil prices are asymmetric in two regimes (rising and decreasing) of crude oil prices. The influence of the new measure on oil prices is negative (positive) in the phases of prices decreasing (rising). This study contributes the new measurement of investor psychological bias leveraging big data crawled from the web to the research community. Big data may become an important source to better understand investors’ trading psychology, and support their decision making.

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