On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations

Noemi Schmitt and Frank Westerhoff

No 119, BERG Working Paper Series from Bamberg University, Bamberg Economic Research Group

Abstract: After showing that the distribution of the S&P 500's distortion, i.e. the log difference between its real stock market index and its real fundamental value, is bimodal, we demonstrate that agentbased financial market models may explain this puzzling observation. Within these models, speculators apply technical and fundamental analysis to predict asset prices. Since destabilizing technical trading dominates the market near the fundamental value, asset prices tend to be either overvalued or undervalued. Interestingly, the bimodality of the distribution of the S&P 500's distortion confirms an implicit prediction of a number of seminal agent-based financial market models.

Keywords: stock market dynamics; bubbles and crashes; chartists and fundamentalists; nonlinear dynamics; bimodality tests; time series analysis (search for similar items in EconPapers)
JEL-codes: G12 G14 G17 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/152260/1/879416602.pdf (application/pdf)

Related works:
Journal Article: On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:bamber:119

Access Statistics for this paper

More papers in BERG Working Paper Series from Bamberg University, Bamberg Economic Research Group Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().