JOB MARKET PAPER
Experiences and expectations in asset markets: an experimental study
This paper presents experimental evidence that experienced price patterns in asset
markets have a large impact on expectations and thereby affect the (de)stabilization
of asset prices in the future. In a controlled learning-to-forecast experiment,
subjects first experience a stable or a bubbly asset market before entering into a
same- or mixed-experience market. In markets where all subjects experienced stability,
convergence to the fundamental price is faster. Bubble formation is faster in markets
where all subjects experienced bubbles. In mixed-experience markets, dynamics can go
both ways: prices either stabilize or destabilize. Heterogeneity in expectations is
larger when more subjects have experienced bubbles before.
Managing bubbles in experimental asset markets with monetary policy
We study the effect of a "leaning against the wind" monetary policy on asset price bubbles
in a learning-to-forecast experiment, where prices are driven by the expectations of
participants in the market. We find that a strong interest rate response is successful
in preventing or deflating large price bubbles, while a weak response is not. Giving
information about the interest rate changes and communicating the goal of the policy
increases coordination of expectations and works stabilizing. When the steady state
fundamental price is unknown and the interest rate rule is based on a proxy instead,
the policy is less effective.
Coordination on bubbles in large-group asset pricing experiments
We present a large-group experiment in which participants predict the price of an
asset, whose realization depends on the aggregation of individual forecasts. The
markets consist of 21 to 32 participants, a group size larger than in most experiments.
Multiple large price bubbles occur in six out of seven markets. The bubbles
emerge even faster than in smaller markets. Individual forecast errors do not cancel
out at the aggregate level, but participants coordinate on a trend-following prediction
strategy that gives rise to large bubbles. The observed price patterns can be
captured by a behavioral heuristics switching model with heterogeneous expectations.
Planar learning to forecast market games
The stability of equilibria in the economy depends on the way agents form expectations.
Previous experimental work has found that the sign and strength of feedback from
expectations to realizations is an essential predictor of aggregate market behavior.
In this project we aim to generalize these results by investigating how behavior in a
two dimensional model depends on the eigenvalues of the underlying expectation feedback
system. A motivating example of such a model is the New Keynesian framework. Our findings
suggest that eigenvalues can be used as predictors for stability. In the case of positive
real eigenvalues we observe a change from stable to unstable dynamics inside the unit circle.
We also find that complex eigenvalues of positive real part with a polar angle of π/4 give
for more stable dynamics than their real counterparts with equal absolute value. We find
evidence that participants considered interaction between the two variables in making their
predictions, suggesting the need for some sophistication in generalizing expectation formation
models to higher dimensions.
Please see my CV for more information about my education, research, teaching and work experience.
My academic references are:
Prof. Cars Hommes, University of Amsterdam (email@example.com)
Prof. Joep Sonnemans, University of Amsterdam (firstname.lastname@example.org)
Prof. John Duffy, University of California, Irvine (email@example.com)