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Examines the impact of using “unsmoothing” techniques on real estate data to take pension‐plan asset‐allocation decisions. It is generally believed that valuation‐based real estate indices give rise to returns figures which are “smoothed” versions of the underlying transaction prices. Unsmoothing techniques can be used to develop real estate return data series that are believed to be a more accurate representation of underlying transaction prices. If this is done, the resulting data reveal greater volatility of real estate returns. When such data are applied to portfolio selection models, they often reveal a reduced allocation to real estate in efficient portfolios. Looks at the impact of unsmoothing data when taking pension‐plan asset‐allocation decisions. Finds here that the unsmoothed data are more closely correlated with pension plan liabilities. As a result, efficient pension plan portfolios sometimes contain more real estate, rather than less. In general, there is little change in the efficient real estate allocation. These results are very important. They reveal that so‐called “valuation smoothing” may distort property investment decisions less than is commonly thought.

This paper seeks to address the question of consistency, regarding the allocation of real estate in the mixed‐asset portfolio.

To address the question of consistency the allocation of real estate in the mixed‐asset portfolio was calculated over different holding periods varying from five to 25 years. For each portfolio and holding period, the percentage of portfolios with real estate was computed, as was the average real estate allocation in the optimum solution. Then, the risk and return differences between the two efficient frontiers, with and without real estate, were calculated to estimate real estate's marginal impact on portfolio performance.

First, the results suggest strongly that real estate has possessed the attribute of consistency in optimised portfolios. Second, the benefits from including real estate in the mixed‐asset portfolio tend to increase as the investment horizon is extended. Third, the position of real estate changes across the efficient frontier from its return enhancing ability to its risk‐reducing facility. Finally, the results show that the gain in return from adding real estate to the mixed‐asset portfolio is typically less compared with the reduction in portfolio risk.

The results highlight a number of issues in relation to the role of direct real estate within a mixed‐asset framework. In particular, the rationale behind the inclusion of real estate in the mixed‐asset portfolio depends on the length of the holding period of the investor and their position on the efficient frontier.

The study examines the attractiveness of direct real estate in the context of mixed‐asset portfolio.

The purpose of this study is to provide a new way to optimize a portfolio and to show that combining the Hurst exponent and wavelet analysis may help to increase portfolio returns.

The authors use the Hurst exponent and wavelet analysis to study the long-term dependencies between sovereign bonds and sectoral indices of India. The authors further construct and evaluate the performance of three portfolios constructed on the basis of Hurst standard deviation (SD) – global minimum variance (GMV), most diversified portfolio (MDP) and equal risk contribution (ERC).

The authors find that an ERC portfolio generates positive superior return as compared other two. Since our sample includes periods of two crisis – post-2007 financial crisis and the ongoing pandemic, this study reveals that combining government bond with equities and gold provides a higher returns when the portfolios are constructed using the risk exposures of each asset in the overall portfolio risk.

The findings provide guidance to portfolio managers by helping them to select assets using the Hurst approach and wavelet analysis thereby increasing the portfolio returns.

In this study, the authors use a combination of Hurst exponent and wavelet analysis to understand the long-term dependencies among various assets and provide a new methodology to optimize a portfolio. As far as the authors’ knowledge, no study in the past has attempted to provide a joint framework for portfolio optimization and therefore this study is the first to apply this methodology.

Similar to real estate, infrastructure investments are regarded as providing a good inflation hedge and inflation protection. However, the empirical literature on infrastructure and inflation is scarce. Therefore, the purpose of this paper is to investigate the short- and long-term inflation-hedging characteristics, as well as the inflation protection associated with infrastructure and real estate assets.

Based on a unique data set for direct infrastructure performance, a listed infrastructure index, common direct and listed real estate indices, the authors test for short- and long-term inflation-hedging characteristics of these assets in the USA from 1991-2013. The authors employ the traditional Fama and Schwert (1977) framework, as well as Engle and Granger (1987) co-integration tests. Granger causality tests are further conducted, so as to gain insight into the short-run dynamics. Finally, shortfall risk measures are applied to investigate the inflation protection characteristics of the different assets over increasingly long investment horizons.

The empirical results indicate that in the short run, only direct infrastructure provides a partial hedge against inflation. However, co-integration tests suggest that all series have a long-run co-movement with inflation, implying a long-term hedge. The causality tests reveal reverse unidirectional causality – while real estate asset returns are Granger-caused by inflation, infrastructure asset returns seem to cause inflation. These findings further confirm that both assets represent a distinct asset class. Ultimately, direct infrastructure investments exhibit the most desirable inflation protection characteristics among the set of assets.

This study only presents results based on a composite direct infrastructure index, as no sub-indices for sub-sectors are available yet.

Investors seeking assets that are sensitive to inflation and mitigate inflation risk should consider direct infrastructure investments in their asset allocation strategy.

This is the first study to examine the ability of direct infrastructure to assess inflation risk.

This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the “building block” method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach the ALM goal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Our chapter raises serious questions about the long-term efficiency of stock prices in relation to the realized returns of the underlying corporate real assets. In our large-scale calculations that cover horizons of 10, 20, 30, 40, and 50 years, returns on corporate real assets suffer a long-term decline, and have been below the yields of 10-year Treasury bonds since 1973. Real assets that received more external financing from capital markets and institutions actually report even lower realized long-term returns. The decline in realized returns cannot be attributed to declining risks as the volatilities of realized returns have been increasing over time. These surprising results may stimulate fresh debate on the roles and long-term performance of capital markets and institutions.

This paper aims to determine the specific financial ratio's effects on market value and return of assets for Turkish real estate investment trusts (REITs) traded at Istanbul Stock Exchange (ISE). The paper intends to define liquidity ratios, financial structure ratios, return ratios and stock performance ratios related to market value and return of asset.

The study includes 17 REITs traded in ISE. The period of study is specified as the year from 2009 to 2018. Panel data analysis is applied in this study. Dependent variables are current market value and return of assets, independent variables are 12 financial ratios, which are considered to explain the model significantly. These ratios will be calculated from audited year-end balance sheets for specific periods throughout at least ten years as time series. Two different models and hypotheses have been established to identify the financial ratios that affect the market value and return of assets for REITs.

According to the results, long-term financial loans/total assets, return of equity and working capital ratio are negatively correlated with market value, while market value/book value and total assets are correlated positively. On the other hand, market value/book value ratio, price/earning ratio, long-term financial loans/total assets and earnings per share are correlated with return of assets. REITs have high levels of financial leverage, especially in foreign currency. The striking point is that REITs hardly ever do not use financial derivatives to hedge their position again currency and interest rate risk. This approach makes the financial structures of REITs vulnerable and fragile against market volatility.

In Turkey, as an example of an emerging market, financial borrowing does not increase the return rates and market value for REITs due to market's idiosyncratic properties. This finding provides substantial insight into how the debt and equity allocation of Turkish REITs should be structured. Also, it has been observed that forward-looking expectations are considered more than the current situation in the market.

The capital asset pricing model (CAPM) is the most widely used asset pricing model that measures risk–return relationship. The CAPM is based on Markowitz’s mean variance analysis. The advancement of Islamic finance leads to the question whether or not the practice of modern investment theories and analyses such as the Markowitz’s mean variance analysis and CAPM are in accordance to shariah and could be used in pricing Islamic financial assets. Therefore, this paper aims to present a review of the CAPM and to discourse the set of assumptions underlying the model in terms of shariah compliance.

Although most of the assumptions are not contradictory to shariah principles, there are Islamic variables such as prohibition of short selling, purification and zakat that should be taken into consideration when pricing Islamic financial assets. We then develop a mathematical model which is a modification of the traditional CAPM that incorporates principles of Islamic finance and integrating zakat, purification of return and exclusion of short sales.

As a proof-of-concept, this paper presents the results of an empirical study on the proposed shariah-compliant CAPM in comparison to the traditional CAPM. The results show that the proposed Islamic CAPM is appropriate and applicable in examining the relationship between risk and return in the Islamic stock market.

This study contributes to existing body of knowledge by presenting an algorithm and mathematical derivation of the shariah-compliant CAPM which has been lacking in the literature of Islamic finance. The paper offers a novel approach in pricing Islamic financial assets in accordance to shariah, advocated by modern investment theories of Markowitz’s mean variance analysis and CAPM.