Introducing REITs (Real Estate Investment Trusts) to Enhance the Risk Adjusted Returns of the Risky Direct Real Estate Portfolio

Purpose: The paper has several objectives in mind: to examine whether or not a dynamic, ex ante AHP-SAA model and a dynamic Markowitz QP TAA model that utilizes de-smoothed data, produces an investment strategy, which further optimizes the risk-adjusted return of the pan-Asian real estate portfolio. It examines the required de-smoothing and Modern Portfolio Theory (MPT) for the TAA. Design/Methodology/Approach: This paper reveals that the efficient frontier of risk-adjusted returns for direct real estate portfolio is enhanced by introducing REITS. The portfolio comprises the Pan-Asian office and industrial real estate markets for 13 major Asian cities, to which Asian REITS are added. Direct real estate total return data is in its “smooth” form while the REIT data is “de-smoothed” under the 1st and 4th order autoregressive model. The efficient frontier is constructed under a dynamic Strategic Asset Allocation (SAA) model, incorporating the Analytic Hierarchy Process (AHP) approach. Secondly, the dynamic Markowitz quadratic-programming Tactical Asset Allocation (TAA) model is adopted to obtain a geographically and real estate sector diversified portfolio.Findings: The resulting efficient frontier with the de-smoothed data reveals a higher overall TR for every corresponding standard deviation as compared to the smoothed data. TAA for the de-smoothed returns would lie on the efficient frontier at the maximum Sharpe ratio of 1.44 with a TR on 15.30% and a standard deviation of 7.31%. Conversely, TAA for the smoothed returns would lie on the efficient frontier at the maximum Sharpe ratio of 1.31 with a lower TR of 14.2% and a standard deviation of 7.18%.Practical implications: This paper should serve as a meaningful guide to look at an alternative asset allocation process that can be effectively adopted and refined by practitioners and researchers. It enables asset managers/or investors to deploy expert opinions on an ex ante basis for a longer term dynamic SAA model and a short term dynamic Markowitz QP TAA model. Originality/Value: The paper offers insightful information for in adopting the AHP to develop a dynamic SAA and the dynamic Markowitz QP TAA model in utilizing de-smoothed direct real estate TR data. This paper is specific to a Pan Asian direct real estate portfolio of 13 Asian cities together with the introduction of Asian REITS, to provide greater diversification and risk-return benefits.

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Petroleum Exploration Risk in Prospect Portfolio Selection

Advances in Logistics, Operations, and Management Science - Novel Six Sigma Approaches to Risk Assessment and Management ◽

10.4018/978-1-5225-2703-9.ch003 ◽

2017 ◽

pp. 40-65

Keyword(s):

Standard Deviation ◽

Portfolio Selection ◽

Six Sigma ◽

Efficient Frontier ◽

Sharpe Ratio ◽

Petroleum Exploration ◽

Management Approach ◽

Portfolio Optimisation ◽

Exploration Risk ◽

Return Variance

Presented method is applied to petroleum exploration for prospect portfolio selection to achieve investment objectives controlling risk. DMAIC framework applies stochastic techniques to risk management. Optimisation resolves Efficient Frontier of portfolios for desired range of expected return with initially defined increment. Simulation measures Efficient Frontier portfolios calculating mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target limits. Analysis considers mean return, Six Sigma metrics and Sharpe Ratio and selects the portfolio with maximal Sharpe Ratio as initially the best portfolio. Optimisation resolves Efficient Frontier in a narrow interval with smaller increments. Simulation measures Efficient Frontier performance including mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target. Analysis identifies the maximal Sharpe Ratio portfolio, i.e. the best portfolio for implementation. Selected prospects in the portfolio are individual projects. So, Project Management approach is used for control.

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How do institutional pension managers consider real estate

Journal of Property Investment and Finance ◽

10.1108/jpif-05-2016-0033 ◽

2017 ◽

Vol 35 (1) ◽

pp. 26-43 ◽

Cited By ~ 2

Author(s):

Jon R.G.M. Lekander

Keyword(s):

Real Estate ◽

Asset Allocation ◽

Pension Funds ◽

Real Estate Market ◽

Organizational Capabilities ◽

Future Research ◽

Allocation Decision ◽

Content Type ◽

The Real Estate ◽

Allocation Process

Purpose The asset allocation decision for a pension portfolio needs to consider several, sometimes conflicting, aspects. Most pension managers use models and processes that are developed for the traditional asset classes for analyzing this problem. The purpose of this paper is to investigate how real estate is included in this process, for what purpose and how the real estate portfolio is constructed. Design/methodology/approach Seven individuals responsible for the asset allocation process were interviewed, and their responses were analyzed with regards to organizational options and their real estate strategy. Findings It was found that real estate is held for three different purposes, risk diversification, inflation hedging/liability matching and return enhancement and that the allocation has increased over time. The allocation strategy has evolved at least in part in conjuncture with the organizational structure set in place to overcome real estate market frictions. Research limitations/implications The interviews were geographically limited to pension funds domiciled in Sweden and Finland. Practical implications It is concluded that the organizational capabilities of the pension fund of handling real estate is an important consideration for the ensuing real estate portfolio. Originality/value The originality of this paper lies in that it is based on interviews with individuals who are responsible for the asset allocation decision at large pension funds. The findings of the paper identify areas of interest for future research.

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Research and Development Risk in Projects Selection

Advances in Logistics, Operations, and Management Science - Novel Six Sigma Approaches to Risk Assessment and Management ◽

10.4018/978-1-5225-2703-9.ch004 ◽

2017 ◽

pp. 66-91

Keyword(s):

Standard Deviation ◽

Six Sigma ◽

Efficient Frontier ◽

Sharpe Ratio ◽

Management Approach ◽

Portfolio Optimisation ◽

Expected Return ◽

Return Variance ◽

Stochastic Techniques ◽

Development Risk

Elaborated method is applied to R&D for project portfolio selection to achieve investment objectives controlling risk. DMAIC framework applies stochastic techniques to risk management. Optimisation resolves Efficient Frontier of portfolios for desired range of expected return with initially defined increment. Simulation measures Efficient Frontier portfolios calculating mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target limits. Analysis considers mean return, Six Sigma metrics and Sharpe Ratio and selects the portfolio with maximal Sharpe Ratio as initially the best portfolio. Optimisation resolves Efficient Frontier in a narrow interval with smaller increments. Simulation measures Efficient Frontier performance including mean return, variance, standard deviation, Sharpe Ratio, and Six Sigma metrics versus pre-specified target. Analysis identifies the maximal Sharpe Ratio portfolio, i.e. the best portfolio for implementation. Selected projects in the portfolio are individual projects. So, Project Management approach is used for control.

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REIT market efficiency through a binomial option pricing tree approach

Journal of Property Investment and Finance ◽

10.1108/jpif-01-2016-0004 ◽

2016 ◽

Vol 34 (5) ◽

pp. 496-520 ◽

Cited By ~ 3

Author(s):

Kim Hin David Ho ◽

Shea Jean Tay

Keyword(s):

At Risk ◽

Standard Deviation ◽

Real Estate ◽

Market Efficiency ◽

Asset Allocation ◽

Real Estate Investment ◽

Tree Model ◽

Content Type ◽

Closing Price ◽

Risk Neutral

Purpose – The purpose of this paper is to examine the risk neutral and non-risk neutral pricing of Singapore Real Estate Investment Trusts (S-REITs) via comparing the average of the individual ratios (of deviation between expected and observed closing price/observed closing price) with the ratio (of standard deviation/mean) for closing prices via the binomial options pricing tree model. Design/methodology/approach – If the ratio (of standard deviation/mean) ratio > the ratio (of deviation between expected and observed closing price/observed closing price), then the deviation of closing prices from the expected risk neutral prices is not significant and that the S-REIT is consistent with risk neutral pricing. If the ratio (of deviation between expected and observed closing price/observed closing price) is greater, then the S-REIT is not consistent with risk neutral pricing. Findings – Capitacommercial Trust (CCT), Capitamall Trust (CMT) and Keppel Real Estate Investment Trust (REIT) have large positive differences between the two ratios (39.86, 30.79 and 18.96 percent, respectively), implying that these S-REITs are not trading at risk neutral pricing. Suntec REIT has a small positive difference of 2.35 percent between both ratios, implying that it is trading at risk neutral pricing. Ascendas REIT has the largest negative difference between the two ratios at −4.24 percent, to be followed by Mapletree Logistics Trust at −0.44 percent. Both S-REITs are trading at risk neutral pricing. The analysis shows that CCT, CMT and Keppel REIT exhibit risk averse pricing. Research limitations/implications – Results are consistent with prudential asset allocation for viable S-REIT portfolio investing but that not all these S-REITs exhibit strong market efficiency in their pricing. Practical implications – Pricing may be risk neutral over a certain period but investor sentiments, fear of risks and speculative activities could affect an S-REIT’s risk neutrality. Social implications – With enhanced risk diversification activities, the S-REITs should attain risk neutral pricing. Originality/value – Virtually no research of this nature has been undertaken for S-REITS.

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Does Value Averaging Strategy Improve Investment Performance? Evidence from the Korean Fund Market

Korean Journal of Financial Studies ◽

10.26845/kjfs.2020.06.49.3.313 ◽

2020 ◽

Vol 49 (3) ◽

pp. 313-340

Author(s):

Hyuk Choe ◽

Ju Il Ban

Keyword(s):

Standard Deviation ◽

Performance Analysis ◽

Asset Allocation ◽

Expected Return ◽

Investment Performance ◽

Average Return ◽

A Value ◽

Ex Ante ◽

Lower Standard ◽

Two Alternatives

This study analyzes whether a value averaging (VA) strategy, which adjusts the amount of investment each period to achieve the target amount of investment in risk assets, as a modified form of a dollar cost averaging (DCA) strategy, improves investment performance. Using 18.5 years of fund market data in Korea from 2001 to June 2019, we compare the investment performance of VA strategy relative to two alternatives: DCA strategy, which invests a certain amount in each period, and Buy-and-Hold (BH) strategy, which refers to half-and-half asset allocation between risky and risk-free assets and has an expected return which is the same as that of DCA in the ex-ante sense. Our historical performance analysis reveals that the VA strategy has lower average return and higher standard deviation compared to the BH strategy and has lower average return and lower standard deviation compared to the DCA strategy. These findings are in stark contrast to the claims made by advocates of VA strategy that the strategy improves investment performance.

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