US Risk Premia under Emerging Markets Constraints

Abstract

USA market is the benchmark for empirical finance and considered the closest example of how an efficient market should behave. On the other hand, divergent results from the observed in the USA are often associated with unreliable and due deviations from efficient hypothesis. However, how would the US market results behave had the data the same constraints as an emerging market economy? To answer that question we analyze the risk premia market estimation under the typical constraints from emerging equity markets: the small number of assets and the short time-series sample available for estimation. We use parameters of time-series length, number of assets and accounting variables distribution from the Brazilian equity market. Surprisingly, we conclude that the US market risk premia convey the same data features as the Brazilian risk premia if under the same time constraints. Then, we evaluate two potential causes of problems in risk premia estimations with small T: i) small sample bias on betas, and ii) divergence between ex-post and ex-ante risk premia. Through Monte Carlo simulations, we conclude that for the T around 5 years the beta estimates are no longer a problem. However, it is necessary to analyze a time-series sample exceeding 40 years to obtain robust ex-ante risk premia.

Keywords: Equity Risk premia, Asset pricing, Multi-factor model

JEL Classification: G12, G17