Abstract
I investigate a relation between the conditional mean and variance of the aggregate stock return using a model that allows the relevance of the risk-return trade-off and autocorrelation to change over time. The model detects a positive risk-return relation, but the importance of the risk-return relation fluctuates with the level of information flow, measured by volatility. During low-volatility periods, market-wide persistence in returns increases, leading to a failure of the pure risk-return explanation for expected returns. This offers an explanation as to why detection of a positive risk-return trade-off has been challenging, while autocorrelation has been a robust finding.
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