کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
883417 1471643 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Path dependent coordination of expectations in asset pricing experiments: A behavioral explanation
ترجمه فارسی عنوان
هماهنگی وابسته به مسیر انتظارات در آزمایشات قیمت گذاری دارایی: توضیح رفتار
کلمات کلیدی
سیستم‌های چندعامله. مدل قیمت گذاری دارایی؛ اقتصاد تجربی؛ همزیستی جذب؛ بازخورد انتظار
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
چکیده انگلیسی


• A behavioral dynamic asset pricing model with heterogeneous expectations is proposed.
• We explain individual and aggregate behavior in the learning-to-forecast laboratory experiments.
• The outcomes of the experiments are reproduced by our behavioral model.
• The occurrence of a degenerate Neimark-Sacker (Chenciner) bifurcation is analyzed.

In the learning-to-forecast laboratory experiments in Hommes et al. (2005), three different types of aggregate asset price behavior have been observed: monotonic convergence to the stable fundamental steady state, dampened price oscillations and permanent price oscillations. We present a simple behavioral 2-type heuristics switching model explaining individual as well as aggregate behavior in the experiment. Based on relative performance, agents switch between a simple trend following and an anchor and adjustment heuristic that differ in how much weight is given to the long run average price level. The nonlinear switching model exhibits path dependence through co-existence of a locally stable fundamental steady state and a stable (quasi-)periodic orbit, created via a so-called Chenciner bifurcation. Depending on initial states, agents coordinate individual expectations either on a stable fundamental steady state path or on almost self-fulfilling persistent price fluctuations around the fundamental steady state.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Economic Behavior & Organization - Volume 121, January 2016, Pages 15–28
نویسندگان
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