US Risk Premia under Emerging Markets Constraints

Elias Cavalcante-Filho, Fernando Chague, Rodrigo De Losso, Bruno Giovannetti
Authors registered in the RePEc Author Service: Rodrigo De-Losso, Bruno Cara Giovannetti and Fernando Chague

No 2019_28, Working Papers, Department of Economics from University of São Paulo (FEA-USP)

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 (search for similar items in EconPapers)
JEL-codes: G12 G17 (search for similar items in EconPapers)
Date: 2019-07-30
New Economics Papers: this item is included in nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Journal Article: US risk premia under emerging markets constraints (2022)
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