Dynamic Interactions, Information Transmission, and Asset Prices: Experiments

Traditional models in finance assume that investors learn only through trading orders and transaction prices. However, with the availability of several channels of communication among investors, it is natural to surmise that traders also leam via these non-market interpersonal meetings. This type of interpersonal exchange allows investors to spread infonnation to one another directly, and appears often in informal accounts of stock market behavior. The emerging field of social economics and finance recognizes that people observe and talk to each other.

Several recent empirical studies have documented strong positive correlations in trading decisions among investors that are more likely to be in direct contact with one another. However, systematic studies of how this important channel of non-market interaction affects price flow dynamics in the context of asset markets are still limited. A key challenge in establishing a causal relation between such interpersonal communication and asset price is that the information exchange process among investors isn’t always observable. We propose the use of laboratory experiments to study the relationship between dynamic interactions, information percolation and asset price fluctuations, abstracting away from all other factors.

The principal goal of the proposed research is to explore the interplay between, on the one hand, the impersonal public channel of learning through trading orders and observation of market price in a centralized marketplace, and on the other hand, a private channel of leaming through personal dynamic interactions among investors. At a more fundamental level, we intend to integrate the element of dynamic social interaction among investors through bilateral random meetings into the experimental asset markets. Such integration represents a novel element of the experimental asset markets which, to the best of our knowledge, has not yet been studied.

We believe that our proposed research will contribute to a broader research agenda that aims to understand the impact of different types of social communication on asset market outcomes. These types include static information exchange, social trading including the knowledge of peers’ past performance, copy trading and delegation of wealth to top perfonning traders, and the proposed dynamic social interactions and information percolation. In today’s world, which is becoming more interconnected than before, it is important to understand the relationship between different types of social communication and human behavior in financial decision making. Our results will have implications for policy-making that aims to regulate mechanisms that influence the intensity of social communication among investors.