A theoretical framework for trading experiments

TL;DR

This paper introduces a theoretical framework to analyze human decision making in trading experiments, distinguishing between fundamental and technical strategies, and predicting outcomes based on various market variables.

Contribution

It provides a novel theoretical model that captures mixed investor behaviors and predicts trading outcomes under different experimental conditions.

Findings

Predicts trading behavior based on a fluctuation ratio.

Accounts for rational expectations and pure speculation scenarios.

Offers qualitative predictions of market dynamics.

Abstract

A general framework is suggested to describe human decision making in a certain class of experiments performed in a trading laboratory. We are in particular interested in discerning between two different moods, or states of the investors, corresponding to investors using fundamental investment strategies, technical analysis investment strategies respectively. Our framework accounts for two opposite situations already encountered in experimental setups: i) the rational expectations case, and ii) the case of pure speculation. We consider new experimental conditions which allow both elements to be present in the decision making process of the traders, thereby creating a dilemma in terms of investment strategy. Our theoretical framework allows us to predict the outcome of this type of trading experiments, depending on such variables as the number of people trading, the liquidity of the market, the amount of information used in technical analysis strategies, as well as the dividends attributed to an asset. We find that it is possible to give a qualitative prediction of trading behavior depending on a ratio that quantifies the fluctuations in the model.