Experimental finance

The goals of experimental finance are to understand human and market behavior in settings relevant to finance. Experiments are synthetic economic environments created by researchers specifically to answer research questions. This might involve, for example, establishing different market settings and environments to observe experimentally and analyze agents' behavior and the resulting characteristics of trading flows, information diffusion and aggregation, price setting mechanism and returns processes. The goals of experimental finance are to understand human and market behavior in settings relevant to finance. Experiments are synthetic economic environments created by researchers specifically to answer research questions. This might involve, for example, establishing different market settings and environments to observe experimentally and analyze agents' behavior and the resulting characteristics of trading flows, information diffusion and aggregation, price setting mechanism and returns processes. Fields to which experimental methods have been applied include corporate finance, asset pricing, financial econometrics, international finance, personal financial decision-making, macro-finance, banking and financial intermediation, capital markets, risk management and insurance, derivatives, quantitative finance, corporate governance and compensation, investments, market mechanisms, SME and microfinance and entrepreneurial finance. Researchers in experimental finance can study to what extent existing financial economics theory makes valid predictions and attempt to discover new principles on which theory can be extended. Experimental finance is a branch of experimental economics and its most common use lies in the field of behavioral finance. In 1948, Chamberlin reported results of the first market experiment. Since then the acceptability, recognition, role, and methods of experimental economics have evolved. From the early 1980s on a similar pattern emerged in experimental finance.The foundational work in experimental finance was the work of Forsythe, Palfrey and Plott (1980), Plott and Sunder (1982), and Smith, Suchanek and Williams (1988). Financial economics has one of the most detailed and updated observational data available of all branches of economics. Consequently, finance is characterized by strong empirical traditions. Lots of analysis is done on data from stock exchanges including bids, asks, transaction prices, volume, etc. There is also data available from information services on actions and events that may influence markets. Data from these sources is not able to report on expectations, on which theory of financial markets is built. In experimental markets the researcher is able to know expectations, and control fundamental values, trading institutions, and market parameters such as available liquidity and the total stock of the asset. This gives the researcher the ability to know the price and other predictions of alternative theories. This creates the opportunity to do powerful tests on the robustness of theories which were not possible from field data, since there is little knowledge on the parameters and expectations from field data. Financial data analysis is based on data drawn from settings created for a purpose other than answering a specific research question. This results in the situation where any interpretation of the results may be challenged since it ignores other variables that have changed. Traditional data analysis issues include omitted-variables biases, self-selection biases, unobservable independent variables, and unobservable dependent variables. Properly designed experiments are able to avoid several problems: