How can stochastic models analyze historical events?

stochastic volatility process (Andersen (1992b)). We now turn to the issue of nonstationarity. So far, we have assumed that volume is stationary. This ignores ... Jun 6, 2018 ... Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While ... Sep 9, 2021 ... In this tutorial we will investigate the stochastic process that is the building block of financial mathematics. ... stochastic process, whether the original process is Markovian or not. ... information sharing called "informational coherence". Informational coherence, in ... ... Random Bridge market information process. This is the first attempt to ... Stochastic Processes and Their Applications, 121, 856-884. https://doi.org ... We studied how this growth process shapes the length distribution of informational polymers. Using stochastic simulations, we find that the process generally ... Applying sequential measurements yields classical stochastic processes whose informational properties are bounded by those of the underlying quantum process. This paper develops a subordinated stochastic process model for asset prices, where the directing process is identified as information. Motivated by recent. In particular, the methods of analyzing the stochastic process of financial ... information, uncertainty, entropy, and ignorance in stochastic processes. Jul 13, 2022 ... This paper proposes a novel model of sequential information design, namely the Markov persuasion processes (MPPs), in which a sender, with informational ...