Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/167879 
Year of Publication: 
2016
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 4 [Issue:] 2 [Publisher:] MDPI [Place:] Basel [Year:] 2016 [Pages:] 1-21
Publisher: 
MDPI, Basel
Abstract: 
In this paper, a dynamic inflation-protected investment strategy is presented, which is based on traditional asset classes and Markov-switching models. Different stock market, as well as inflation regimes are identified, and within those regimes, the inflation hedging potential of stocks, bonds, real estate, commodities and gold are investigated. Within each regime, we determine optimal investment portfolios driven by the investment idea of protection from losses due to changing inflation if inflation is rising or high, but decoupling the performance from inflation if inflation is low. The results clearly indicate that these asset classes behave differently in different stock market and inflation regimes. Whereas in the long-run, we agree with the general opinion in the literature that stocks and bonds are a suitable hedge against inflation, we observe for short time horizons that the hedging potential of each asset class, especially of real estate and commodities, depend strongly on the state of the current market environment. Thus, our approach provides a possible explanation for different statements in the literature regarding the inflation hedging properties of these asset classes. A dynamic inflation-protected investment strategy is developed, which combines inflation protection and upside potential. This strategy outperforms standard buy-and-hold strategies, as well as the well-known 1N-portfolio.
Subjects: 
Markov-switching models
inflation
investment strategies
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Appears in Collections:

Files in This Item:
File
Size
976.18 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.