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The question as to whether it is better to diversify a real estate portfolio within a property type across the regions or within a region across the property types is one of continuing interest for academics and practitioners alike. However, this study is somewhat different from the usual sector/regional analysis in that this study is designed to investigate whether a real estate fund manager can obtain a statistically significant improvement in risk/return performance from extending out of a London based portfolio into firstly the rest of the South East of England and then into the remainder of the UK, or whether the manger would be better off staying within London and diversifying across the various property types.

In order to examine these issues we form a number of portfolios that can be directly compared to a number of benchmark portfolios, as well as to each other. Then using the statistical tests developed by Gibbons et al. and Jobson and Korkie, we investigate whether the benefits that accrue from the differing diversification strategies are statistically significant or not.

The results show that staying within only one sector and one region (London) is undesirable in terms of risk and return compared with all three benchmark portfolios considered here. Secondly diversification on a naïve basis, or in an optimal fashion, leads to significant improvements in performance, irrespective of whether it is across different property types within London or within the same sector across the regions. Finally the results indicate that staying within London and diversifying across the various property types may offer performance comparable with regional diversification, although this conclusion largely depends on the time period and the fund manager's ability to diversify efficiently.

The results suggest that diversification almost always offers increased performance. Indeed a little diversification can quickly lead to levels of performance that is superior to number of benchmarks as well as performance insignificantly different from that of the most diversified portfolio that could be constructed! Consequently fund managers should be encouraged to diversify, be it across the regions or across the sectors of the UK.

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.

It is crucial to find a better portfolio optimization strategy, considering the cryptocurrencies' asymmetric volatilities. Hence, this research aimed to present dynamic optimization on minimum variance (MVP), equal risk contribution (ERC) and most diversified portfolio (MDP).

This study applied dynamic covariances from multivariate GARCH(1,1) with Student’s-t-distribution. This research also constructed static optimization from the conventional MVP, ERC and MDP as comparison. Moreover, the optimization involved transaction cost and out-of-sample analysis from the rolling windows method. The sample consisted of ten significant cryptocurrencies.

Dynamic optimization enhanced risk-adjusted return. Moreover, dynamic MDP and ERC could win the naïve strategy (1/N) under various estimation windows, and forecast lengths when the transaction cost ranging from 10 bps to 50 bps. The researcher also used another researcher's sample as a robustness test. Findings showed that dynamic optimization (MDP and ERC) outperformed the benchmark.

Sophisticated investors may use the dynamic ERC and MDP to optimize cryptocurrencies portfolio.

To the best of the author’s knowledge, this is the first paper that studies the dynamic optimization on MVP, ERC and MDP using DCC and ADCC-GARCH with multivariate-t-distribution and rolling windows method.

The paper aims to conduct an empirical study of three models of property derivatives: index-based derivatives, factor hedges, and combinative hedges based on index and factors. The objective is to test whether the latter two models introduced by Lecomte dominate the index-based model used for existing property derivatives such as EUREX futures contracts.

Based on investment property database (IPD) historical database covering 224 individual office properties from 1981 to 2007, the study assesses ex ante hedging effectiveness of the three models. Nine simulations are run under different hypotheses involving individual buildings and portfolios. The 17 factors included in the study cover both macro-factors (e.g. macroeconomic indicators) and micro-factors linked to the properties (e.g. age).

Atomization and periodic rebalancing of property derivatives' underlying make it possible to substantially increase hedging effectiveness for a large majority of buildings in the sample. However, combinative hedges are overall superior to factor hedges owing to the overriding role played by IPD indices in capturing risk.

Due to confidentiality requirements inherent to the use of property level data, the study downplays the role of micro-factors on real estate risk at the property level.

The paper introduces a typology of optimal hedges aimed at individual property owners and portfolio holders in the City office property market.

This is the first time a comprehensive analysis of different models of property derivatives is conducted. The value of the paper stems from the use of property level data.

The investment behaviour of individuals has been a major area of interest for several researchers and policymakers due to its great impact on the economy. This study aimed to assess the investment behaviour of individuals in light of their risk appetite and how financial literacy regulates this relationship.

A self-administered structured questionnaire was used to collect responses from individuals using purposive and convenience sampling techniques. Individuals were presented with 16 investment avenues widely offered by the Indian financial market to choose from to construct a hypothetical portfolio. The association between risk appetite, financial literacy and the composition of the hypothetical portfolio was analysed using a gologit model.

Increased risk appetite increased the probability of respondents creating a portfolio with a greater proportion of risky assets and less diversification. Lower levels of financial literacy pointed towards portfolios with traditional and low-risk avenues. The results also revealed a significant moderating impact of financial literacy on risk appetite and the creation of the type of a hypothetical portfolio.

Even though the intended behaviour is a close estimate of actual behaviour, there is a possibility of deviation that cannot be ignored.

The present study provides insights into how individuals make portfolio choices by incorporating risk appetite and diversification factors whilst making investment decisions, thereby expanding the literature from an emerging economy perspective. The role of financial literacy as a moderator has not been studied in the domain of hypothetical portfolio creation in India, which has been empirically explored in the current study.

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.

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.

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.

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.

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.

With enhanced risk diversification activities, the S-REITs should attain risk neutral pricing.

Virtually no research of this nature has been undertaken for S-REITS.

The purpose of this paper is to identify how multicriteria decision aid (MCDA) can assist the investment portfolios formation, increasing the reliability of decision-making.

To develop this paper, a simulation-based approach is used. Information about the assets traded on the spot market of the São Paulo Stock Exchange - BM&FBOVESPA was selected. They had 100 per cent participation in the 246 trading sessions carried out in 2015 and had an average number of business/day greater or equal to 1,000. The stratification resulted in the selection of 111 assets. Aiming assets evaluation, data are collected from 21 financial indicators. Subsequently, the principal component analysis (PCA) is used to reduce the mass of collected data without the loss of essential information. PROMETHEE II method is used for assets ranking; it belongs to the group of methods for MCDA. At the end of these stages, four groups of investment portfolios are created for simulation.

After the construction of portfolios, a simulation was performed with real data of the assets from January 03, 2011 to November 14, 2016. It resulted in a comparison in which it was observed that 100 per cent of portfolios showed positive returns on the investment. The result of portfolios’ group composed of assets based on the 21 financial indicators was higher than the other one formed from PCA criteria. Both of them were higher than Ibovespa result in the same period.

As a contribution to new research, the model presents an opportunity for improvement through linear programming methodologies with the objective of optimizing the results, as the results obtained with the model were not optimized.

This research presents an alternative logic to the traditional one, as it seeks the reduction of investment risk based on the results of the management of the companies, reflected through their indicators. The model implies a change in how companies, financial institutions and small and medium investors choose their assets to form investment portfolios. The authors believe that the model has the potential to attract investors looking for long-term gains, such as public servants, retirees, professionals and others who seek to build heritage to overcome the adversities of the uncertain future. The model offers these investors the opportunity to choose which companies to invest in, based on established indicators in the literature, whose information is available in the market. The model systematizes the information and builds a ranking of the best companies so that the investor can make a conscious decision, thus avoiding what experts call a “herd effect”, which makes the majority of investors decide according to the oscillation of the market, thus ignoring the financial fundamentals of companies.

This study presents a proprietary methodology by merging the PCA tool with MCDA to build efficient investment portfolios.

Managerial finance has become a modern professional discipline with a coherent theory and a growing body of statistical research in support of the theory. Finance faculty in leading business schools around the world are now actively engaged in making the modern theory accessible to executive participants in post‐experience educational programmes. What makes the modern theory of finance exciting is the simplicity and the authority with which issues of concern to management today can be resolved. One of the areas of interest where answers to old questions are being found is in the estimation of discount rates or required rates of return for capital projects.

The paper takes a behavioral approach by making use of the prospect theory to unveil the impact of salience on short-term and long-term investment decisions. This paper aims to investigate the group differences for two types of investors’ groups, i.e. individual investors and professional investors.

The study uses partial least square-based structural equation modeling technique, measurement invariance test and multigroup analysis test on a unique data set of 277 active equity traders which included professional money managers and individual investors.

Results showed that salience has a significant positive impact on both short-term and long-term investment decisions. The impact was almost 1.5 times higher for long-term investment decision as compared to short-term decision. Furthermore, multigroup analysis revealed that the two groups (individual investors and professional investors) were statistically significantly different from each other.

The study has implications for financial regulators, money managers and individual investors as it was found that individual investors suffer more with salience heuristic and may end up with sub-optimal portfolios due to inefficient diversification. Thus, investors should be cautious in fully relying on salience and avoid such bias to improve investment returns.

The study concludes with a discussion of policy and regulatory implications on how to minimize salience bias to achieve optimum and diversified portfolios.

The study has significantly contributed to the growing body of applied behavioral research in the discipline of finance.

The purpose of this study is to evaluate whether a diversification by grape varieties may help wine producers reduce uncertainty in quantity and quality variations due to increasingly erratic climate conditions.

This study hand-collects granular quantity and quality data from wine harvest reports for vintages 2003 to 2017 for the Valais region in Switzerland. The data allows us to obtain detailed data on harvested kilograms/liters and Oechsle/Brix degrees. It is then merged with precise meteorological data over the same sample period. The authors use this data set to capture weather conditions and their impact on harvested quantities and quality. Finally, they build portfolios including different grape varieties to evaluate whether this reduces variations in quality and quantity over vintages.

The findings highlight that the weather varies relatively strongly over the sample period and that climate hazards such as hail, frost or ensuing vine diseases effectively occur. These strongly impact the harvested quantities but less the quality of the wine. The authors further show that planting different grape varieties allows for a significant reduction in the variation of harvested quantities over time and thus acts as a good solution against climate risk.

The effect of climate change on viticulture is becoming increasingly important and felt and bears real economic and social consequences. This study transposes portfolio diversification which is central to reducing risk in the finance industry, into the wine industry and shows that the same principle holds. The authors thus propose a novel idea on how to mitigate climate risk.