The formation of share market prices under heterogeneous beliefs and common knowledge

Financial economic models often assume that investors know (or agree on) the fundamental value of the shares of the firm, easing the passage from the individual to the collective dimension of the financial system generated by the Share Exchange over time. Our model relaxes that heroic assumption of one unique "true value" and deals with the formation of share market prices through the dynamic formation of individual and social opinions (or beliefs) based upon a fundamental signal of economic performance and position of the firm, the forecast revision by heterogeneous individual investors, and their social mood or sentiment about the ongoing state of the market pricing process. Market clearing price formation is then featured by individual and group dynamics that make its collective dimension irreducible to its individual level. This dynamic holistic approach can be applied to better understand the market exuberance generated by the Share Exchange over time.Comment: 22 pages, 9 figure

A New Rational Algorithm for View Updating in Relational Databases

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In order to apply the rationality result of belief dynamics theory to various practical problems, it should be generalized in two respects: first it should allow a certain part of belief to be declared as immutable; and second, the belief state need not be deductively closed. Such a generalization of belief dynamics, referred to as base dynamics, is presented in this paper, along with the concept of a generalized revision algorithm for knowledge bases (Horn or Horn logic with stratified negation). We show that knowledge base dynamics has an interesting connection with kernel change via hitting set and abduction. In this paper, we show how techniques from disjunctive logic programming can be used for efficient (deductive) database updates. The key idea is to transform the given database together with the update request into a disjunctive (datalog) logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the original update problem. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of a hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality.Comment: arXiv admin note: substantial text overlap with arXiv:1301.515

How to do things with modals

Mind &Language, Volume 35, Issue 1, Page 115-138, February 2020

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis

Explaining Evidence Denial as Motivated Pragmatically Rational Epistemic Irrationality

This paper introduces a model for evidence denial that explains this behavior as a manifestation of rationality and it is based on the contention that social values (measurable as utilities) often underwrite these sorts of responses. Moreover, it is contended that the value associated with group membership in particular can override epistemic reason when the expected utility of a belief or belief system is great. However, it is also true that it appears to be the case that it is still possible for such unreasonable believers to reverse this sort of dogmatism and to change their beliefs in a way that is epistemically rational. The conjecture made here is that we should expect this to happen only when the expected utility of the beliefs in question dips below a threshold where the utility value of continued dogmatism and the associated group membership is no longer sufficient to motivate defusing the counter-evidence that tells against such epistemically irrational beliefs

Belief merging and revision under social influence: An explanation for the volatility clustering puzzle

A share price in a stock market can be thought of as arising out of an aggregation procedure. The price of a stock aggregates many individual beliefs into a collective one, the collective will of the market, so to speak. How does this aggregation come about? And is this aggregation fair in the sense that it correctly reflects the value? Furthermore,in the context of a stock market, it becomes immediately clear that belief merging cannot be separated from belief revision since investors in the market have a direct stake in what others think and clearly find it optimal to revise their beliefs in the light of the information about what others believe. We show that if investors are revising their beliefs not only after receiving new exogenous information but also after their social interactions with other investors and these revised beliefs are getting merged to generate the stock price under the accepted principles of finance (no arbitrage) then the resulting price dynamics explain a long standing puzzle in finance, the volatility clustering puzzle.Volatility clustering; Social influence; Agent based simulation; Anomaly