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This study examined the dynamic role of the Japanese property sector, particularly the real estate investment trusts (REITs), in mixed-asset portfolios of stocks and bonds, as well as office, retail, hotel and residential REITs.

Daily data were retrieved from 01 January 2008 to 31 December 2019. The sample time frame consisted of in-sample and out-of-sample periods. The dynamic conditional correlation-generalised autoregressive conditional heteroskedastic (DCC-GJRGARCH) model was deployed to obtain the forecast estimates of time-varying volatility of REITs and correlations with other assets. The estimates were employed to construct out-of-sample portfolios based on the three assets for daily investment. The five sets of portfolios with each individual property sector REITs, as well as a portfolio of stocks and bonds that served as a benchmark, were produced. The average utility for each set of portfolios was estimated and compared with the average utility of the benchmark portfolio. The average transaction cost (TC) for portfolio rebalancing was calculated as well.

The forecast of volatility estimates for each property sector revealed that each asset displayed a similar pattern with the differences in the volatility magnitude. Notably, hotel and retail REITs were more volatile than other property sector REITs. The property sector REITs exhibited a positive correlation with stocks but negatively linked with bonds. The results unveiled the diversification benefits of incorporating property sector REITs. The portfolio with property sector REITs had higher risk-adjusted returns and utility, compared to portfolio consisting of stocks and bonds. The benefits outweighed the TC for portfolio rebalancing.

This study highlights the importance of quantifying the conditional time-varying volatility and correlations of the property sector REITs with other asset returns, especially for investment decision, to select and include property sector REITs in mixed-asset portfolios. For fund managers seeking liquid assets in daily investment, this analysis suggests the inclusion of hotel and retail REITs to enhance REITs' portfolio performance.

This study is the first to investigate the dynamic characteristics of the volatility and correlation of each property sector REITs with other financial assets by employing the conditional framework that accounted for short- and long-run persistency in economic shocks. The reported outcomes shed light on the differences in the underlying properties that contribute to the variances in dynamic volatility of each sector REITs, as well as REITs' correlations with stocks and bonds. This application enables the authors to transmit the dynamics of variance-covariance matrix amongst each property sector REITs, stocks and bonds into asset allocation problem on a daily basis.

The purpose of this paper is to study the scope for country diversification in international portfolios of mutual funds for the “core” EMU countries. The author uses a sample of daily returns for country indices of French, German and Italian funds to investigate the quest for international diversification. The author focuses on fixed-income mutual funds during the period of the financial market turmoil since 2007.

The author compute optimal portfolio allocations from both unconstrained and constrained mean-variance frameworks that take as input the out-of-sample forecasts for the conditional mean, volatility and correlation of country-level indices for funds returns. The author also applies a portfolio allocation model based on utility maximization with learning about the time-varying conditional moments. The author compares the out-of-sample forecasting performance of 12 multivariate volatility models.

The author finds that there is a “core” EMU country also for the mutual fund industry: optimal portfolios allocate the largest portfolio weight to German funds, with Italian funds assigned a lower weight in comparison to French funds. This result is remarkably robust across competing forecasting models and optimal allocation strategies. It is also consistent with the findings from a utility-maximization model that incorporates learning about time-varying conditional moments.

This is the first study on optimal country-level diversification for a mutual fund investor focused on European countries in the fixed-income space for the turmoil period. The author uses a large array of econometric models that captures the salient features of a period characterized by large changes in volatility and correlation, and compare the performance of different optimal asset allocation models.

The study aims to consolidate knowledge, explore current dynamics, understand knowledge progression, identify primary research streams, present content analysis and provide future research directions for green bonds research.

The authors reviewed 150 high-quality Scopus-indexed articles on green bonds in two stages. First, they use bibliometric analysis to understand the field's most relevant articles, authors, institutions and journals. Second, they analysed 49 curated articles to identify and analyse primary research streams and offer research directions.

The authors report the most influential articles, authors, journals and clusters based on article co-citation networks. They identify five green bond research streams: issuance, greenium and its drivers, connectedness, drivers and barriers, and sustainable development.

Using different databases, tools, sample periods or article screening criteria may yield different results. The study's findings are robust to document selection or analytical tools.

The study helps researchers, practitioners, regulators, policymakers, issuers and investors understand green bond issuance, pricing and connectedness research.

This unique study sheds light on publication trends, the most influential articles, authors, journals and the conceptual and intellectual structure of the field. It identifies and elaborates primary research streams, succinctly summarizes the most influential articles and offers future research directions.