Models of Equilibrium Pricing with Internalized Powers of Independent Judgment Based on Autonomy

Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their trading in both markets - the Bombay Stock Exchange (BSE) and the National stock Exchange (NSE). The study contributes to the literature with original findings. It shows that investors in the two Indian stock markets show crowd of positive and negative herding as well significantly and there is huge noise along with information in the markets equilibrium pricing mechanism.

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Equilibrium Pricing in Incomplete Markets

Journal of Financial and Quantitative Analysis ◽

10.1017/s002210900000199x ◽

2005 ◽

Vol 40 (4) ◽

pp. 833-848 ◽

Cited By ~ 9

Author(s):

Abdelhamid Bizid ◽

Elyès Jouini

Keyword(s):

Stochastic Volatility ◽

Incomplete Markets ◽

Stochastic Volatility Model ◽

Time Model ◽

Equilibrium Pricing ◽

Discrete Time Model ◽

Price Process ◽

State Price ◽

Volatility Model ◽

Market Framework

AbstractGiven the exogenous price process of some assets, we constrain the price process of other assets that are characterized by their final payoffs. We deal with an incomplete market framework in a discrete-time model and assume the existence of the equilibrium. In this setup, we derive restrictions on the state-price deflators. These restrictions do not depend on a particular choice of utility function. We investigate numerically a stochastic volatility model as an example. Our approach leads to an interval of admissible prices that is more robust than the arbitrage pricing interval.

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