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The purpose of this paper is to present a discrete quantitative trading strategy to directly control a portfolio's maximum percentage of drawdown losses while trying to maximize the portfolio's long‐term growth rate.

The loss control target is defined through a Rolling Economic Drawdown (REDD) with a constant look‐back time window. The authors specify risk aversion in the power‐law portfolio wealth utility function as the complement of maximum percentage loss limit and assume long‐term stable Sharpe ratios for asset class indexes while updating volatility estimation in dynamic asset allocation implementation.

Over a test period of the past 20 years (1992‐2011), a risk‐based out‐of‐sample dynamic asset allocation among three broad based indexes (equity, fixed income and commodities) and a risk free asset, is robust against variations in capital market expectation inputs, and out‐performs the in‐the‐sample calibrated model and traditional asset allocation significantly.

The current proposal can lead to a new mathematical framework for portfolio selection. Besides investors' liquidity and behavioural constraints, macroeconomic and market cycle, and the potential of central bank interventions following a market crash, could be additionally considered for a more rigorous dynamic asset allocation model.

Besides the benefit of a clear mandate to construct suitable client portfolios, the portfolio approach can be applied to design invest‐able securities, such as principal‐guaranteed investment products, target risk asset allocation ETFs, and target‐date mutual funds with a glide path, etc. The formulation can also be implemented as a managed futures hedge fund portfolio.

The paper introduces the Rolling Economic Drawdown (REDD) concept and specifies risk aversion as the floor of maximum percentage loss tolerance. Dynamic asset allocation is implemented through updating estimation of asset class volatilities.

The purpose of this paper is to investigate whether asset allocation across various industries listed on the Ghana Stock Exchange (GSE) varies across different monetary policy states.

This paper adopts the Markov Chain technique to split monetary policy into three different states. The authors further adopt the Markowitz portfolio optimization technique to find the minimum variance and optimum portfolio for the industries listed on the GSE.

The finding reveals a dynamic asset allocation, which varies the industry’s weight mix across the various monetary policy states enhance excess returns compared to the static asset allocation. Specifically, the authors find risk-return trade-off among industries listed on the GSE. Financial and Food and Beverage industries portfolios record high returns relative to the Government of Ghana 91-day Treasury bill. The Food and Beverage portfolio is the only portfolio that records relatively high excess returns across all the monetary policy states. The authors also find that, during expansionary state (high monetary policy rates) of the monetary policy, investors are to allocate about 69 and 30 percent of their investment into food and beverages and financials, respectively. Corner solution is found in the transient state where 100 percent of wealth is allocated to financial to obtain the optimum portfolio. The optimum portfolio in the contraction state assigns 52 percent to financials and 42 percent to manufacturing. In summary, the result supports the dependence of investors’ asset allocation decisions on monetary policy.

Therefore, the authors propose an investment strategy which is dynamic and takes into consideration the monetary policy states rather than static asset allocation which maintains the same industry weight mix over the investment period.

In sum, the authors interpret the result as support for the dependence of investors’ asset allocation decisions on monetary policy. In Ghana, an increase in the monetary policy appears to support industries listed on the equity market. The result also gives knowledge about investors’ asset allocation decisions on the GSE, which is practical balanced source of information for investors’ risk and return choices. For a prudent monetary policy framework, the monetary policy committee should monitor industries listed on the GSE. The result from the analysis has also an implication for investors, portfolio managers and fund managers to consider the state of the monetary policy in Ghana when making investment decisions.

The study differs from earlier research on asset allocation by breaking new grounds on two levels. First of all, based on the notion that different industries have different exposures to monetary policy states, the authors extend the portfolios by grouping the equities listed on the GSE into their industrial sectors. Second, the authors examine how investors’ optimal portfolio allocation may change depending on the state of monetary policy.

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.

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.

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.

The interviews were geographically limited to pension funds domiciled in Sweden and Finland.

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.

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.

This study aims to investigate the association between Muslim individuals’ portfolio allocation choice and Islamic religiosity (levels and dimensions), controlling for risk tolerance and sociodemographic factors.

The study uses primary data collected via survey questionnaires from a sample of 751 Muslim working individuals in Kuala Lumpur, Malaysia. Owing to the ordinal nature of the dependent variable, which reflects the levels of proportions of risky assets in portfolios, the data were analyzed using an ordered probit regression model.

The findings reveal that Islamic religiosity levels in general were insignificantly related to portfolio allocation, but that two dimensions of religiosity (virtue and obligation) significantly impact the allocations of risky assets in the portfolio. The higher the level of virtue, the lower the propensity to allocate risky assets into the portfolio. On the contrary, the higher the level of obligation, the higher the propensity to allocate risky assets in the portfolio. Meanwhile, individuals with higher risk tolerance, income and education levels show greater propensity to allocate risky assets in the portfolio.

The sample is restricted to Muslims in Kuala Lumpur; hence, the findings are not easily generalized to Muslim investors in general. Findings may differ between Muslims across the world, so future research needs to expand from a country specific to an international analysis. In addition, future studies could include other determinants of portfolio allocation, such as financial literacy.

The findings of this study may assist financial planners and policymakers to better understand the drivers of portfolio allocation among their Muslim clients.

While other studies have tended to focus on the impact of religiosity on the holdings of specific financial assets, such as Islamic bank accounts or Takaful, the present study explores the effect of Islamic religiosity dimensions on the allocations of risky assets in the portfolio. The study also develops an ordinal measure of portfolio allocation and makes a methodological contribution by using an ordered probit regression analysis.

Property is a key investment asset class that offers considerable benefits in a mixed-asset portfolio. Previous studies have concluded that property allocation should be within the 10-30 per cent range. However, there seems to be wide variation in theory and practice. Historical Australian superannuation data shows that the level of allocation to property asset class in institutional portfolios has remained constant in recent decades, restricted at 10 per cent or lower. This is seen by many in the property profession as a subjective measure and needs further investigation. The purpose of this paper is to compare the performance of the AU$431 billion industry superannuation funds’ strategic balanced portfolio against ten different passive and active investment strategies.

The analysis used 20 years (1995-2015) of quarterly data covering seven benchmark asset classes, namely: Australian equities, international equities, Australian fixed income, international fixed income, property, cash and alternatives. The 11 different asset allocation models are constructed within the modern portfolio theory framework utilising Australian ten-year bonds as the risk free rate. The Sharpe ratio is used as the key risk-adjusted return performance measure.

The ten different asset allocation models perform as well as the industry fund strategic approach. The empirical results show that there is scope to increase the property allocation level from its current 10-23 per cent. Upon excluding unconstrained strategies, the recommended allocation to property for industry funds is 19 per cent (12 per cent direct and 7 per cent listed). This high allocation is backed by improved risk-adjusted return performance.

The constrained optimal, tactical and dynamic models are limited to asset weight, no short selling and turnover parameters. Other institutional constraints that can be added to the portfolio optimisation problem include transaction costs, taxation, liquidity and tracking error constraints.

The 11 different asset allocation models developed to evaluate the property allocation component in industry superannuation funds portfolio will attract fund managers to explore alternative strategies (passive and active) where risk-adjusted returns can be improved, compared to the common strategic approach with increased allocation to property assets.

The research presents a unique perspective of investigating the optimal allocation to property assets within the context of active investment strategies, such as tactical and dynamic models, whereas previous studies have focused mainly on passive investment strategies. The investigation of these models effectively contributes to the transfer of broader finance and investment market theories and practice to the property discipline.

The purpose of this paper is to conduct a controlled experiment to examine the effect of goal setting and affect framed feedback on repeated asset allocation investment decisions.

The design of the experiment is a 2×2 between subject design. Subjects allocated monies among four investments for 20 periods. One manipulation varied whether subjects received performance feedback in the form of a happy or sad face, while another manipulation varied whether subjects set a financial goal for themselves and received goal attainment performance feedback.

The main findings include: subjects initially allocate assets in a manner roughly consistent with their stated preference for risk; prior year asset performance leads subjects to make significant changes in portfolio asset allocation in a manner consistent with beliefs of positive autocorrelation in asset returns; and the addition of happy or sad faces to performance feedback information leads to even greater changes in asset allocation.

Using ideas from the theory on the self‐regulation of behavior and the role of affect in decision making, the authors develop an original framework to account for the results.

This paper re‐examines the role of real estate within mixed asset portfolios from the perspective of an Irish portfolio manager. The nature of the investment market in the Republic of Ireland leads to the study extending the existing literature by expanding the universe of assets beyond a solely domestic setting and by imposing constraints on the optimal portfolios. Irish funds generally hold proportionately more in international equities than in the domestic market due to the small and illiquid nature of the Irish market; therefore, unconstrained tests do not adequately model the behaviour of Irish portfolio managers. The study finds that while real estate plays an important role in both the domestic and international unconstrained portfolios, it exits the optimal portfolios at relatively low return levels. Additionally, the real estate series adjusted for smoothing fails to enter any of the optimal portfolios. However, the use of 20 per cent band constraints leads to an increase in the diversification role real estate can play in a mixed asset portfolio, with the asset maintaining a presence up to more acceptable return levels.

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 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 purpose of this paper is to establish an optimum mix of liquid, publicly traded assets that may be added to a real estate portfolio, such as those held by open-ended funds, to provide the liquidity required by institutional investors, such as UK defined contribution pension funds. This is with the objective of securing liquidity while not unduly compromising the risk-return characteristics of the underlying asset class. This paper considers the best mix of liquid assets at different thresholds for a liquid asset allocation, with the performance then evaluated against that of a direct real estate benchmark index.

The authors employ a mean-tracking error optimisation approach in determining the optimal combination of liquid assets that can be added to a real estate fund portfolio. The returns of the optimised portfolios are compared to the returns for portfolios that employ the use of either cash or listed real estate alone as a liquidity buffer. Multivariate generalised autoregressive models are used along with rolling correlations and tracking errors to gauge the effectiveness of the various portfolios in tracking the performance of the benchmark index.

The results indicate that applying formal optimisation techniques leads to a considerable improvement in the ability of the returns from blended real estate portfolios to track the underlying real estate market. This is the case at a number of different thresholds for the liquid asset allocation and in cases where a minimum return requirement is imposed.

The results suggest that real estate fund managers can realise the liquidity benefits of incorporating publicly traded assets into their portfolios without sacrificing the ability to deliver real estate-like returns. However, in order to do so, a wider range of liquid assets must be considered, not just cash.

Despite their importance in the real estate investment industry, comparatively few studies have examined the structure and operation of open-ended real estate funds. To the authors’ knowledge, this is the first study to analyse the optimal composition of liquid assets within blended or hybrid real estate portfolios.