Eficiência de mercado: evidências a partir do Google Trends e algoritmos de trading

Abstract

Information is one of the most studied topics in the economy and finance, therefore, this work analysis the relationship between Ibovespa, amount traded and a proxy about investor attention in the period between 2016 and 2020. The present work innovates when using a new methodology to elaborate the proxy demand for information or investor attention by using Principal Component Analysis (ACP) in several tickers researched in Google Trends. From that, this work analyzes the relationship of this proxy and the value of the Ibovespa and the amount traded of Ibovespa by an VEC-VAR methodology and the elaboration of an trading strategy. Still, the market shows an efficient behavior in most of the analyzed period, so the trading algorithm has a lower performance than the market return in that period, however for the period that refers to the pandemic, the behavior shows a different behavior from what is characterized efficient, in this period the algorithm surpassed the return to the market, indicating that strategies developed from quantitative methods are indicated in periods of uncertainty and panic.