Efficient Market Hypothesis in Brazilian and American Markets: A Study Using Time Windows

Resumo

Financial markets play a fundamental role in contemporary societies, directly influencing social well-being. Traditionally, economists have sought to understand the underlying processes driving the dynamics of these markets. However, in recent decades, there has been a significant increase in the contribution of researchers from various disciplines, including physics, mathematics, and computer science. In this context, econophysics has emerged, employing typical physics methods to study systems commonly investigated in economics and finance.
Financial markets are recognized as complex systems, whose behavior can be observed through indicators such as prices and trading volumes. However, the statistical characterization of these time series remains an ongoing challenge, as does understanding their emergence from microeconomic relationships.
The Efficient Market Hypothesis (EMH) suggests that future price time series in financial markets contain little useful information for prediction, making it extremely difficult. In this study, we conduct analyses of financial time series to investigate this expectation. We use a return trend prediction model based on differential equations with a focus on time segmenting. The accuracy of this model can provide insights into the presence of the information suggested by the EMH in financial time series.