1. |
- Hardardottir, Hjördis, et al.
(author)
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Risk aversion, noise, and optimal investments
- 2017
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In: Journal of Portfolio Management. - : Pageant Media US. - 0095-4918 .- 2168-8656. ; 43:3, s. 51-59
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Journal article (peer-reviewed)abstract
- In contrast to the efficient market hypothesis (EMH), the noisy market hypothesis (NMH) asserts that prices are but noisy indications of fundamental values. The authors study losses in certainty equivalents of investing according to one hypothesis (NMH or EMH) when the other is true. Their findings suggest that, for reasonable parameter values, investing according to the EMH when the NMH is true yields lower losses than investing according to the NMH when the EMH is true. Further, investing according to the right hypothesis is much more important for risk-tolerant investors than for risk-averse investors.
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2. |
- Nystrup, Peter, et al.
(author)
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Dynamic Allocation or Diversification : A Regime-Based Approach to Multiple Assets
- 2017
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In: Journal of Portfolio Management. - : Pageant Media US. - 0095-4918 .- 2168-8656. ; 44:2, s. 62-73
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Journal article (peer-reviewed)abstract
- This article investigates whether regime-based asset allocation can effectively respond to changes in financial regimes at the portfolio level in an effort to provide better long-term results when compared to a static 60/40 benchmark. The potential benefit from taking large positions in a few assets at a time comes at the cost of reduced diversification. The authors analyze this trade-off in a multi-asset universe with great potential for static diversification. The regime-based approach is centered around a regime-switching model with time-varying parameters that can match financial markets’ behavior and a new, more intuitive way of inferring the hidden market regimes. The empirical results show that regime-based asset allocation is profitable, even when compared to a diversified benchmark portfolio. The results are robust because they are based on available market data with no assumptions about forecasting skills.
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3. |
- Peter, Nystrup, et al.
(author)
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Regime-Based Versus Static Asset Allocation: Letting the Data Speak
- 2015
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In: Journal of Portfolio Management. - : Pageant Media US. - 0095-4918 .- 2168-8656. ; 42:1, s. 103-109
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Journal article (peer-reviewed)abstract
- Regime shifts present a big challenge to traditional strategic asset allocation. This article investigates whether regimebased asset allocation can effectively respond to changes in financial regimes at the portfolio level, in an effort to provide better long-term results than more static approaches can offer. The authors center their regime-based approach around a regime-switching model with time-varying parameters that can match financial markets’ tendency to change behavior abruptly and the fact that the new behavior often persists for several periods after a change. In an asset universe consisting of a global stock index and a global government bond index, they show that, even without any level of forecasting skill, holding a static portfolio may not be optimal.
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4. |
- Rehring, Christian, et al.
(author)
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An Empirical Evaluation of Normative Commercial Real Estate Swap Pricing
- 2011
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In: The Journal of Portfolio Management. - : With Intelligence LLC. - 0095-4918 .- 2168-8656. ; 37:5, s. 154-169
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Journal article (peer-reviewed)abstract
- Despite the fact that commercial real estate is composed of a large proportion of investable assets, a functioning derivatives market for private real estate has only existed since early 2005 when swap contracts began to be traded in the U.K. in significant amounts. Among other concerns about commercial real estate derivatives, the pricing issue is a major obstacle for the development of the market due to the specific characteristics of appraisal-based indices used as the underlying of these derivatives. In this article, Rehring and Steininger empirically evaluate a model of normative commercial real estate swap pricing, based on private real estate market indices, by estimating future appraisal-based index returns and accounting for time-varying equilibrium risk premia. The authors analyze the differences between the U.S. and the U.K. They interpret the development of actual commercial real estate swap prices in recent years in light of calculated “fair” swap prices. Qualitatively, the estimated swap prices track actual market developments quite well, indicating that the modeled swap prices enhance our understanding of the pricing of commercial real estate swaps.
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5. |
- Peter, Nystrup, et al.
(author)
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Practical Applications Summary: Regime-Based versus Static Asset Allocation: Letting the Data Speak
- 2016
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In: Journal of Portfolio Management. - : Pageant Media US. - 0095-4918. ; 42:1, s. 103-109
-
Journal article (peer-reviewed)abstract
- Regime shifts present a big challenge to traditional strategic asset allocation. This article investigates whether regimebased asset allocation can effectively respond to changes in financial regimes at the portfolio level, in an effort to provide better long-term results than more static approaches can offer. The authors center their regime-based approach around a regime-switching model with time-varying parameters that can match financial markets’ tendency to change behavior abruptly and the fact that the new behavior often persists for several periods after a change. In an asset universe consisting of a global stock index and a global government bond index, they show that, even without any level of forecasting skill, holding a static portfolio may not be optimal.
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6. |
- Steininger, Bertram I.
(author)
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Return-Risk Analysis of Real Estate Tokens : An Asset Class of Its Own
- 2023
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In: Journal of Portfolio Management. - : PAGEANT MEDIA LTD. - 0095-4918. ; 49:10, s. 83-102
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Journal article (peer-reviewed)abstract
- This study analyzes the return-risk metrics of real estate security tokens as digital representatives of fractional ownership in physical properties. The author uses approximately 40,000 pricing data points for 180 tokenized properties in the United States between 2019 and 2022 to construct a monthly index. This index is used in various analyses to see whether the tokens ' returns follow the performance of the underlying markets for housing, securitized real estate, stock, and cryptocurrency. The token index shows no clear pattern of similarity to other asset classes and has its own return-risk pattern. The principal component analysis shows that debt and macroeconomic factors are the major drivers and that the crypto market and housing market are of minor importance in explaining variation in returns. This absence of a clear linear relationship with other assets makes real estate tokens attractive as diversifiers in a multiasset portfolio. However, investors looking for an alternative investment vehicle for the real estate asset class cannot rely on tokenized real estate.
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