It is the process of establishing a variety of market conditions to test the investing habits of traders in each circumstance. In terms of using experimental finance in a stock market setting, this may be done by setting up trading simulations and applying various theories to see how each trader reacts. This data may then be used to predict how stocks will move in the future if these circumstances become a reality.
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 micro finance 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 methods in finance offer complementary methodologies that have allowed for the observation and manipulation of underlying determinants of prices, such as fundamental values or insider information. Experimental studies complement empirical work, particularly in the area of theory testing and development. Exploiting this experimental methodology has revealed some important findings over the past years. These findings could not have been reached by traditional field data analysis alone and are therefore experimental finance’s main contributions to the field of finance:
– Security markets can aggregate and disseminate information (there are efficient markets), but this process is less effective as the information becomes less widely held and the number of information components that must be aggregated increases.
– But this is not always the case (some of them are inefficient).
– When information dissemination occurs, it is rarely perfect or instantaneous. Learning takes time.
– More information is not always better from the point of view of the individual trader. Only those insiders who are much better informed than others can outperform other traders.
– Markets for longer-lived assets have a strong tendency to generate price bubbles and crashes, prolonged deviations from fundamental values.
– Emotions of traders play a role in generating bubbles in experimental asset markets.
– Asset mispricing has been largely associated with trader overconfidence.
– Prices as well as bids, offers, timing, etc., convey information. There are many channels for information flow.
– Well-functioning derivative markets can help to improve primary markets’ efficiency.
– Statistical efficiency or inability to make money using past data does not mean informational efficiency. Not being able to earn abnormal returns from the market does not mean that the price is right.
Experiments are an underused method in finance and have natural advantages for behavioral finance. Experiments can provide a useful means to circumvent several common econometric issues such as omitted variables, unobserved variables, and self-selection. Experiments can extend the theoretical models they test by relaxing various assumptions or examining settings that are too complex to be addressed analytically. Whether or not theoretical predictions are clearly known in advance, experiments are most informative when they rely on controlled manipulation, which is the source of their inferential power.
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