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• W4313201250 abstract "In this paper, we used the Baidu feed index to quantify the valuable information from the search engine, and proposed a China's crude oil futures price forecasting model with feed index. The empirical analysis confirms that the feed index, which characterizes the investor attention of participants in China's crude oil futures market, provides valuable information for internet concerns and investor sentiment, and has significant impact on China's crude oil futures price forecasting. We found that the time lag between the search query results and the crude oil futures price changes, which mostly lies within the shorter time range. The forecasting model with the search engine data would produce forecasts with superior performance." @default.
• W4313201250 created "2023-01-06" @default.
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• W4313201250 date "2022-01-01" @default.
• W4313201250 modified "2023-09-26" @default.
• W4313201250 title "China's Crude oil futures forecasting with search engine data" @default.
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• W4313201250 doi "https://doi.org/10.1016/j.procs.2022.11.266" @default.
• W4313201250 hasPublicationYear "2022" @default.
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