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I develop an adaptive learning model where periods of stability lead
to periods of instability, similar to Minsky’s financial instability
hypothesis. In tranquil times, investors increase their subjective
risk-return assessments. They buy more stocks, driving up prices,
and reinforcing the change in beliefs. Crashes arise endogenously
as rapid booms increase perceptions of risk as well as returns. The
model can help explain observed asset pricing phenomena. I also
establish new results on instability and cycles in adaptive learning
models. As long as agents put sufficient weight on new information,
learning from asset returns leads to instability that drives
endogenous booms and busts.
