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Detecting change points in VIX and S&P 500: A new approach to dynamic asset allocation
Author(s) -
Peter Nystrup,
Bo William Hansen,
Henrik Madsen,
Erik Lindström
Publication year - 2016
Publication title -
journal of asset management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.362
H-Index - 16
eISSN - 1479-179X
pISSN - 1470-8272
DOI - 10.1057/jam.2016.12
Subject(s) - asset allocation , sharpe ratio , econometrics , volatility (finance) , index (typography) , portfolio , economics , basis risk , asset (computer security) , investment strategy , computer science , financial economics , market liquidity , finance , capital asset pricing model , computer security , world wide web
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

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