Sunday, 28 January 2018

Experimental Finance: Why ‘Experiments’ in Finance?

Finance is a branch where we have the most up-to-minute data from stock exchanges and the field is characterized by strong empirical traditions. Still we conduct experiments in finance and try to gather even more data, is it needed? In the words of Editor, Econometrica, “Finance is in no need of experiments. We have lots of data.”. Also, the real world markets are bigger and complex as compared to the laboratory so can an experimentally proved model fit the real world market.


Experiments prove their relevance as they facilitate the researchers in isolating and manipulating a single variable at a time, thus, the causal effects are illustrated better by filtering the effects of different variables associated with the model. Another aspect of experiments is that it allows to observe the otherwise unobservable, dependent and independent variables due to the laboratory settings and eliminates the complications of self-selection by assigning subjects randomly to the different treatments. 

However, a key challenge is to construct an experiment that is purely based on the assumptions of the model and in which the alternative hypotheses are plausible such that the results of the experiment do not rely completely on the forgone conclusions. It can be done by examining the settings which are too complex to be definitively modeled or by relaxing the different assumptions underlying the the model, namely, behavioral, structural and equilibrium assumptions.

Archival data analysis faces major challenge in interpreting the results as data that are considered for analysis are not meant for answering the research questions. This may lead to problems such as omitted variables biases, self-selection biases, unobservable independent variables, and unobservable dependent variables.