1. Markovian Nash equilibrium in financial markets with asymmetric information and related forward-backward systems
- Author
-
Albina Danilova and Umut Çetin
- Subjects
Statistics and Probability ,HG Finance ,Markov process ,Bertrand competition ,01 natural sciences ,Markov bridges ,Market maker ,FOS: Economics and business ,010104 statistics & probability ,symbols.namesake ,Stochastic differential equation ,Information asymmetry ,FOS: Mathematics ,forward–backward stochastic and partial differential equations ,QA Mathematics ,0101 mathematics ,Mathematics ,60J60 ,Stylized fact ,Kyle model with risk averse market makers ,Probability (math.PR) ,010102 general mathematics ,Financial market ,91B44 ,Nash equilibrium ,symbols ,Pricing of Securities (q-fin.PR) ,Statistics, Probability and Uncertainty ,60H30 ,Mathematical economics ,Quantitative Finance - Pricing of Securities ,Mathematics - Probability - Abstract
This paper develops a new methodology for studying continuous-time Nash equilibrium in a financial market with asymmetrically informed agents. This approach allows us to lift the restriction of risk neutrality imposed on market makers by the current literature. It turns out that, when the market makers are risk averse, the optimal strategies of the agents are solutions of a forward-backward system of partial and stochastic differential equations. In particular, the price set by the market makers solves a nonstandard "quadratic" backward stochastic differential equation. The main result of the paper is the existence of a Markovian solution to this forward-backward system on an arbitrary time interval, which is obtained via a fixed-point argument on the space of absolutely continuous distribution functions. Moreover, the equilibrium obtained in this paper is able to explain several stylized facts which are not captured by the current asymmetric information models., Published at http://dx.doi.org/10.1214/15-AAP1138 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
- Published
- 2016