Asset pricing models in emerging markets: Factorial approaches vs. information stochastic discount factor

The factorial asset pricing models generally performs poorly in emerging markets. This prediction bias implies anomalies. This study analyzes whether it is consequence of ignoring other source of risk. We apply a non-parametric approach (stochastic discount factor) to improve the forecasts of the usual factorial models. For a sample of 26 emerging equity markets, we find that the information portfolio built from the stochastic discount factor shows better goodness of fit of emerging market and, only the factor that accounts value stocks versus growth stocks is relevant to emerging equity markets, specifically, it is a sensitivity measure at risk. •First application of non-parametric stochastic discount factor (SDF) for emerging equity markets.•Information SDF portfolio shows a goodness of fit higher than factor models.•SDF methodology uses new sources of information to reduce anomalies in asset pricing.•Only HML provides relevant information, but as a measure of sensitivity at risk.