Lifu Jin | Searcharxiv

arXiv2026

Effects of analyst sentiment on volatility dynamics in financial market

Text emotions are extracted using natural language processing technique on a substantial corpus of analyst reports on the Chinese stock market. Subsequently, the text-based analyst sentiment indices are constructed. It is observed that both optimistic and pessimistic sentiments represent short-range memory. Optimistic and pessimistic sentiments are correlated with volatility positively and negatively, respectively. The analysis of transfer entropy reveals that past pessimistic sentiment affects future volatility. Further, we model the driving effect of analyst sentiment on volatility using a GARCH model. The results show that pessimistic sentiment is an explanatory factor for volatility, while optimistic sentiment is not.

physics.soc-ph↗

arXiv2024

Properties of the Strong Data Processing Constant for Rényi Divergence

Strong data processing inequalities (SDPI) are an important object of study in Information Theory and have been well studied for $f$-divergences. Universal upper and lower bounds have been provided along with several applications, connecting them to impossibility (converse) results, concentration of measure, hypercontractivity, and so on. In this paper, we study Rényi divergence and the corresponding SDPI constant whose behavior seems to deviate from that of ordinary $Φ$-divergences. In particular, one can find examples showing that the universal upper bound relating its SDPI constant to the one of Total Variation does not hold in general. In this work, we prove, however, that the universal lower bound involving the SDPI constant of the Chi-square divergence does indeed hold. Furthermore, we also provide a characterization of the distribution that achieves the supremum when $α$ is equal to $2$ and consequently compute the SDPI constant for Rényi divergence of the general binary channel.

cs.IT↗