Dynamic Pricing Theory Research Articles

Reconciling Behavioral Finance and Rational Finance

In this paper, we explain main concepts of Prospect Theory and Cumulative Prospect Theory within the rational dynamic asset pricing framework. We derive option pricing formulas when asset returns are altered by a generalized Prospect Theory value function or a modified Prelec’s weighting probability function. We introduce new parametric classes for Prospect Theory value functions and probability weighting functions consistent with rational dynamic pricing theory. After the behavioral finance notion of “greed and fear” is studied from the perspective of rational dynamic asset pricing theory, we derive the corresponding option pricing formulas when asset returns follow continuous diffusions or discrete binomial trees. We define mixed subordinated variance gamma process to model asset return and derive the corresponding option pricing formula. Finally, we apply the proposed probability weighting functions to study the greedy or fearful disposition of option traders when asset returns follow a mixed subordinated variance gamma process. The results indicate availability bias and diminishing sensitivity of option traders.

Price Dispersion in Dynamic Equilibrium

In product markets, there exists substantial dispersion in prices for transactions of physically identical goods, and incumbent sellers sell at higher prices than entrants. This study develops a theory of dynamic pricing that explains these facts as results from the same fundamental friction: Buyers are imperfectly aware of which sellers are operating, and the degree of awareness about a seller is endogenous. The equilibrium is unique and efficient, and features randomized pricing strategies where incumbents post higher prices than entrants. If buyers' memory depreciation is low, then the equilibrium of the industry tends to approximate perfectly competitive conditions over time.