Expectations and bubbles in asset pricing experiments

Abstract

We present results on expectation formation in a controlled experimental environment. In each period subjects are asked to predict the next price of a risky asset. The realized market price is derived from an unknown market equilibrium equation with feedback from individual forecasts. In most experiments prices deviate from the benchmark fundamental and bubbles emerge endogenously. These bubbles are inconsistent with rational expectations and seem to be driven by trend chasing behavior or "positive feedback expectations" of the participants. We also analyze individual predictions of participants and find that participants within a group tend to coordinate on a common prediction strategy.

Monetary Policy Under Behavioral Expectations: Theory and Experiment

“…These heuristics were obtained and estimated as descriptions of typical individual forecasting behavior observed in Hommes et al (2005b), Hommes et al (2008), andAssenza et al (2014b) building upon a rich literature on expectation formation (see Hommes, 2011, for a recent survey). 5 Based upon the calibration in these papers, we use the WTR weak trend-following rule x e 2,t+1 = x t−1 + 0.4(x t−1 − x t−2 ) STR strong trend-following rule x e 3,t+1 = x t−1 + 1.3(x t−1 − x t−2 ) LAA anchoring and adjustment rule x e 4,t+1 = 0.5(x av t−1 + x t−1 ) + (x t−1 − x t−2 )…”

Complex Evolutionary Systems in Behavioral Finance

“…The difference between these last two groups lies in the upper bound for price predictions, set to 100 (as in the case with robot traders) and 1000 respectively. Hommes et al (2008) ran experiments without robot traders and a high upper bound of 1000 (maintaining the same fundamental price p f = 60) and in 6 out of their 7 markets long lasting price bubbles (almost) reaching the upper bound were observed, with price levels up to 15 times the fundamental value.…”

Individual expectations, limited rationality and aggregate outcomes

“…Our work is also related to the LtFEs with expectations feedbacks between individual forecasts and aggregate market prices in macroeconomic models, see e.g. Sunder (1993, 1994), , Adam (2007) and Pfajfar and Zakelj (2009), and in asset pricing models, Hommes et al (2005Hommes et al ( , 2008 and Sonnemans and Tuinstra (2008). Hommes (2010) gives a survey of learning to forecast experiments in macroeconomics and finance.…”