Detecting change points in VIX and S&P 500: A new approach to dynamic asset allocation

Peter Nystrup (), Bo William Hansen, Henrik Madsen and Erik Lindström
Additional contact information
Peter Nystrup: DTU Compute, Asmussens Allé
Bo William Hansen: DTU Compute, Asmussens Allé
Henrik Madsen: DTU Compute, Asmussens Allé
Erik Lindström: DTU Compute, Asmussens Allé

Journal of Asset Management, 2016, vol. 17, issue 5, No 5, 374 pages

Abstract: Abstract The purpose of dynamic asset allocation (DAA) is to overcome the challenge that changing market conditions present to traditional strategic asset allocation by adjusting portfolio weights to take advantage of favorable conditions and reduce potential drawdowns. This article proposes a new approach to DAA that is based on detection of change points without fitting a model with a fixed number of regimes to the data, without estimating any parameters and without assuming a specific distribution of the data. It is examined whether DAA is most profitable when based on changes in the Chicago Board Options Exchange Volatility Index or change points detected in daily returns of the S&P 500 index. In an asset universe consisting of the S&P 500 index and cash, it is shown that a dynamic strategy based on detected change points significantly improves the Sharpe ratio and reduces the drawdown risk when compared with a static, fixed-weight benchmark.

Keywords: regime changes; change point detection; dynamic asset allocation; volatility regimes; daily returns; non-parametric statistics (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1057/jam.2016.12 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
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:pal:assmgt:v:17:y:2016:i:5:d:10.1057_jam.2016.12

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/41260

DOI: 10.1057/jam.2016.12

Access Statistics for this article

Journal of Asset Management is currently edited by Marielle de Jong and Dan diBartolomeo

More articles in Journal of Asset Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().