Barone Adesi, Giovanni Mira, Antonietta Pisati, Matteo Maria 2020-06-22 Empirical indicators of sentiment are commonly employed in the economic literature while a precise understanding of what is sentiment is still missing. Exploring the links among the most popular proxies of sentiment, fear and uncertainty this paper aims to fill this gap. We show how fear and sentiment are specular in their predictive power in relation to the aggregate market and to cross-sectional returns. Finally, we document how sentiment and fear time cross-sectional returns: conditionally on a today’s high (low) level of fear we observe a next month high (low) return per unit of risk. The opposite holds for sentiment. After that, we propose a novel framework linking market predictability with pricing through the study of the rationale underpinning predictability. We show how the dynamics of risks and risks pricing are at the base of the predictability of behavioral and fundamental variables. This allows us to explain qualitative and quantitative differences in the dynamics of the predictability detected in bull and bear markets. Finally, we decompose the problem of market predictability into three parts: predictive models, predictors and the functions of the market uncertainty we aim at forecasting. For each of the three parts, we consider potential and challenges posed by these new approaches in the asset pricing field. application/pdf https://susi.usi.ch/global/documents/319228 https://n2t.net/ark:/12658/srd1319228 https://susi.usi.ch/documents/319228/files/2020ECO007.pdf eng info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:rero-006-119823 info:eu-repo/semantics/altIdentifier/ark/12658/srd1319228 info:eu-repo/semantics/openAccess License undefined Behavioral finance Sentiment Fear Machine learning Predictable functions info:eu-repo/classification/udc/33 Essays on financial markets predictability http://purl.org/coar/resource_type/c_db06