A New Predictive Measure Using Agent-Based Behavioral Finance
Authored by Todd Feldman, Shuming Liu
Date Published: 2018
DOI: 10.1007/s10614-017-9652-1
Sponsors:
No sponsors listed
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
We calibrate Friedman and Abraham's (J Econ Dyn Control 33:922-937,
2009) agent-based model using actual financial data in the US stock
market. The evidence shows that the estimated price series from the
model is similar to real S\&P price series and the model does match
return moments at the second and higher order. In addition, we develop a
new measure of investor heterogeneity based on the variability in the
estimated position sizes across all mutual fund managers. Our results
show that the volatility in individual fund manager positions is able to
predict future returns in various time horizons. Moreover, increased
variability in position sizes positively affects the contemporaneous
change in the CBOE Volatility Index and also leads to greater
probability of recession.
Tags
calibration
bubbles
behavioral finance
agent-based finance
Stock returns
Markets
Inflation