Rational Speculators, Contrarians and Excess Volatility

Abstract

The VAR approach for testing present value models is applied to a nonlinear asset pricing model with three types of agents, using historical US stock prices and dividends. Besides rational long-term investors, that value assets according to expected dividends, the model includes rational and contrarian speculators. Agents choose their regime based on evolutionary considerations. Supplementing the standard present value model with speculative agents dramatically improves the model's ability to replicate the observed market dynamics. In particular the existence of contrarians can explain some of the most volatile episodes including the 1990s bubble, suggesting this was not a rational bubble.JEL Classification: C58, D84, G11

Estimation of financial agent-based models with simulated maximum likelihood

“…Belief coe cients/A-synchronous updating ratio(? )/Intensity of choice Huisman et al (2010) A B S Q M L B e l i e f c o e c i e n t s / I n t e n s i t y o f c h o i c e Kouwenberg and Zwinkels (2014) ABS QML Belief coe cients/Intensity of choice Kouwenberg and Zwinkels (2015) ABS QML Price elasticity/Belief coe cients/Intensity of choice Lof (2012) A B S N L S B e l i e f c o e c i e n t s / I n t e n s i t y o f c h o i c e Lof (2015) ABS Duan and Simonato (1998), GMM for generalized method of moments, and SMD for simulated minimum distance. '?'…”

Comparing Behavioural Heterogeneity Across Asset Classes

“…Various versions of the model, with varying numbers and types of agents, different profit and/or switching functions, and varying results, have been estimated successfully on a large number of asset classes. Especially stock markets (Boswijk et al, 2007;Hommes and in 't Veld, 2017;Chiarella et al, 2014;Lof, 2014) and foreign exchange markets (Frankel and Froot, 1990;De Jong et al, 2010;Spronk et al, 2013) have been extensively analyzed, but the model has also showed itself useful in explaining the price dynamics in, for instance, housing markets (Kouwenberg and Zwinkels, 2014;Bolt et al, 2014), option markets (Frijns et al, 2010), commodity markets (ter Ellen and Zwinkels, 2010;Baur and Glover, 2014;Westerhoff and Reitz, 2005), and credit markets (Chiarella et al, 2015). Even macro-economic variables such as inflation can be described by a heterogeneous agent model, as in Cornea-Madeira et al (2017) 1 .…”

Identifying Booms and Busts in House Prices Under Heterogeneous Expectations

“…Hommes and in't Veld (2014) follow a similar approach, using both the dynamic Gordon present-discounted-value and the Campbell-Cochrane consumption habit fundamental benchmarks, using quarterly S&P500 data 1950-2013 and conclude that the financial crises has been amplified by switching between fundamentalists and trend-following strategies. Lof (2014) estimates a HAM with different VAR-model specifications to the S&P500 index and finds temporary switching between fundamentalists and rational and contrarian speculators. Lux (2009) estimated the parameters of a dynamic opinion formation process with social interactions based on survey data on business expectations (sentiment index data).…”