### Refine

#### Document Type

#### Keywords

- Capital-Asset-Pricing Modell ; Mehragentensystem ; Volabilität ; Online-Publikation (1)
- Kreditmarkt ; Stochastisches Modell ; Online-Publikation (1)
- Method of simulated moments; moment coverage ratio; herding; discrete choice approach; transition probability approach. (1)
- Structural stochastic volatility; method of simulated moments; autocorrelation pattern; fat tails; bootstrapped p-values (1)
- Wirtschaftspolitik ; Agency-Theorie ; Online-Publikation (1)

The paper proposes an elementary agent-based asset pricing model that, invoking the
two trader types of fundamentalists and chartists, comprises four features: (i) price determination
by excess demand; (ii) a herding mechanism that gives rise to a macroscopic
adjustment equation for the market fractions of the two groups; (iii) a rush towards fundamentalism
when the price misalignment becomes too large; and (iv) a stronger noise
component in the demand per chartist trader than in the demand per fundamentalist
trader, which implies a structural stochastic volatility in the returns. Combining analytical
and numerical methods, the interaction between these elements is studied in the
phase plane of the price and a majority index. In addition, the model is estimated by
the method of simulated moments, where the choice of the moments reflects the basic
stylized facts of the daily returns of a stock market index. A (parametric) bootstrap
procedure serves to set up an econometric test to evaluate the model’s goodness-of-fit,
which proves to be highly satisfactory. The bootstrap also makes sure that the estimated
structural parameters are well identified.

In the framework of small-scale agent-based financial market models, the paper starts
out from the concept of structural stochastic volatility, which derives from different noise
levels in the demand of fundamentalists and chartists and the time-varying market shares
of the two groups. It advances several different specifications of the endogenous switching
between the trading strategies and then estimates these models by the method of simulated
moments (MSM), where the choice of the moments reflects the basic stylized facts
of the daily returns of a stock market index. In addition to the standard version of MSM
with a quadratic loss function, we also take into account how often a great number of
Monte Carlo simulation runs happen to yield moments that are all contained within their
empirical confidence intervals. The model contest along these lines reveals a strong role
for a (tamed) herding component. The quantitative performance of the winner model is
so good that it may provide a standard for future research.