GOOGLE TRENDS AS PREDICTOR OF GRAIN PRICES
2021
Martínez, Raúl Gómez | Orden-Cruz, Carmen | Prado-Román, Camilo
This paper examines the predictive power of Google trends on the grains futures price movement. The aim was to validate if an algorithmic trading system designed was profitable and able of beating the market. In the research was used data from soybean futures and corn futures, both contracts are listed in the Chicago Mercantile Exchange. The results of the research show that its forecasting power is high when predicting soybean futures and corn futures prices. According to the findings, the formulation of such predictive analysis is a good option for individual traders, investors, and commercial firms.
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