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This study analyzes the variability of rates of return for 11,772 U.S. commercial banks from 1979 through 1985. The objective is to determine whether variability that is not explained by exogenous variables can be explained by prospect theory. Below target, strong correlations are shown, consistent with prospect theory. When regression analysis is applied, the results are confirmed.

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.

This article is based on responses to the 1982 general invitation from the Review Board for Government Contracts. The authors' main contention is that the pricing of government contracts has hitherto been deficient in at least two fundamental respects — the use of the historic cost accounting model as a computational framework for the costing and pricing of non‐competitive Government contracts and the use of ex post accounting rates of return for estimating target rates of return.

The purpose of this paper is to find applicable Islamic pricing benchmarks (IPBs) instead of the market interest rates which are currently used in Islamic finance as benchmark.

The suggested model (Islamic pricing benchmark model (IPBM)) obviously reveals the feasibility and practical effectiveness of a substitute to London Interbank Offered Rate (LIBOR) and as an evaluator tool to suggested investment projects. The model is a suggested mechanism which could be used as an alternative choice to the conventional borrowing based on the forbidden Riba or on interest. The suggested IPBM depends on estimating the rate of return for any project on consideration of the cash flows in future which is expected to be relative to the invested capital.

The IPBM approach might be applied to financial tools, where the fund owner bears the loss since it is not because of negligence. An instrument to help identify the investment for target rates of return (as an alternative choice to LIBOR) to identify a breakeven point based on expected cash flows for the project to be financed instead of based on seeking the indicators of interest or Riba (as LIBOR). This feature of the IPBM model as an Islamic benchmark renders it as a Shariah pricing mechanism for the Islamic financial products.

The IPBM could be used as a financial instrument to assist in identifying the investment for the target return rates to determine a breakeven point based on expected cash flows for the project to be funded instead of being based on seeking the interest indicators or Riba (as LIBOR). This feature as an Islamic benchmark is considered as a Shariah pricing mechanism for the Islamic financial products. In particular, the proposed model incorporates the Shariah parameters. In that, it is hoped that the Islamic financial instruments will be more comprehensive in their Shariah compliance and thereby may bring more credibility to the Islamic financial system in general.

This paper highlights several important issues related to the IPBMs in Islamic financial institutions which are not widely discussed among researchers. This study contributes to finding an alternative IPB for the Islamic financial products which is currently using the conventional interest rate (LIBOR) as its benchmark. The current study provides empirical evidence for the possibility of relying on the IPBM as an Islamic benchmark to price Islamic financial transactions.

The present paper aims to introduce a new methodology taking risk behavior of decision maker into account to fine‐tune the value of a risky public‐private‐partnership (PPP) project and the corresponding cost of capital based on the target rate of return set by the project sponsor and the degree of project risks.

The proposed methodology combines the cumulative prospect theory (CPT) to characterize the risk preference of the project sponsor and the Monte Carlo simulation to assess the project riskiness. The methodology requires a pre‐set target rate of return that will define the relative gains and losses for a prospect theory project sponsor. The application was illustrated using a build/operate/transfer toll road project as a case study.

As the project sponsor sets a greater target return, the probability of the project not meeting the target is accordingly greater. Given that losses have greater impact than gains on the decision, other things being equal, a higher target return leads to a higher value correction. It has also been demonstrated that the corresponding project's cost of capital can be up‐ or downadjusted depending on the project's riskiness which may result in a reverse preference to favor a higher risk scenario.

The methodology uses the CPT parameters that need to be further confirmed and validated if applied to value large risky projects like PPP investments.

The proposed methodology offers a different approach to correctly value a risky PPP project by extending the application of the cumulative prospect theory that well explains the irrationality of human decision behavior under risk into a financial decision‐making process. It takes the full benefit of simulation to understand project risks and also assists financial decision‐making.

The purpose of this paper is to discuss the principal measures of performance used in property and other investment types. In particular, the briefing will explore the relationship of the expected IRR with the initial return, highlighting the role of growth in the investment dynamic.

This education briefing is an overview of investment growth models with worked examples.

The analysis of property growth models is akin to the Fisher and Gordon growth models used in other finance markets.

This comparison of the models can work for all forms of investment. Similarly, instead of looking at the overall return as the measure of comparison (expected vs required), it is possible to work backwards and deduce market expectations and compare these with the investors view on those variables.

This is a review of existing models.

This study seeks to examine the effectiveness of controlling the currency risk for international diversified mixed‐asset portfolios via two different hedge instruments, currency forwards and currency options. So far, currency forward has been the most common hedge tool, which will be compared here with currency options to control the foreign currency exposure risk. In this regard, several hedging strategies are evaluated and compared with one another.

Owing to the highly skewed return distributions of options, the application of the traditional mean‐variance framework for portfolio optimization is doubtful. To account for this problem, a mean lower partial moment model is employed. An in‐the‐sample as well as an out‐of‐the sample context is used. With in‐sample analyses, a block bootstrap test has been used to statistically test the existence of any significant performance improvement. Following that, to investigate the consistency of the results, the out‐of‐sample evaluation has been checked. In addition, currency trends are also taken into account to test the time‐trend dependence of currency movements and, therefore, the relative potential gains of risk‐controlling strategies.

Results show that European put‐in‐the‐money options have the potential to substitute the optimally forward‐hedged portfolios. Considering the composition of the portfolio in using in‐the‐money options and forwards shows that using any of these hedge tools brings a much more diversified selection of stock and bond markets than no hedging strategy. The optimal option weights imply that a put‐in‐the‐money option strategy is more active than at‐the‐money or out‐of‐the‐money put options, which implies the dependency of put strategies on the level of strike price. A very interesting point is that, just by dedicating a very small part of the investment in options, the same amount of currency risk exposure can be hedged as when one uses the optimal forward hedging. In the out‐of‐sample study, the optimally forward‐hedged strategy generally presents a much better performance than any types of put policies.

The research shows the risk and return implications of different currency hedging strategies. The finding could be of interest for asset managers of internationally diversified portfolios.

Considering the findings in the out‐of‐sample perspective, the optimally forward‐hedged minimum risk portfolio dominates all other strategies, while, in the depreciation of the local currency, this, together with the forward‐hedged tangency portfolio selection, would characterize the dominant portfolio strategies.

Risk capital is an important input for management functions. Capital structure decisions, capital budgeting, and ex post performance measurement require different measures of risk capital. While it has become common to estimate risk capital using VaR models, it is not clear that VaR‐based capital estimates are optimal for applications to management functions (e.g. risk management, capital budgeting, performance measurement, or regulation). This article considers three typical problems that require an estimate of credit risk capital: an optimal equity capital allocation; an optimal capital allocation for capital budgeting decisions; and an optimal capital allocation to remove moral hazard incentives from a compensation contract based on ex post performance. The optimal credit risk capital allocation is different for each problem and is never consistent with a credit VaR estimate of unexpected loss. The results demonstrate that the optimal risk capital allocation depends on the objective.

The purpose of this paper is to discuss the use of the internal rate of return (IRR) as a principal measure of performance of investments and to highlight some of the weaknesses of the IRR in evaluating investments in this way.

This Education Briefing is an overview of the limitations of the IRR in making capital budgeting decisions. It is illustrated with a number of counter-intuitive examples.

The advantage of the IRR is that it is, on the surface, a wonderfully simple benchmark. One figure that tells a story. But, the disadvantage is that if used in isolation the IRR can give misleading results when used to assess investment proposals.

The IRR should be used in conjunction with other analyses to appraise projects, so that the user can determine its veracity in the context of other benchmarks. This context is particularly important when assessing investments with unusual cash flows.

This is a review of existing models.

The purpose of this paper is to provide conclusive evidence that infrastructure constitutes a separate asset class and cannot be classified as real estate from an investment point‐of‐view. Furthermore, optimal allocations are determined for direct and indirect infrastructure within a multi‐asset portfolio.

Portfolio allocations are optimized by using an algorithm, which accounts for downside risk, rather than variance. This approach is more in accordance with the actual investor behaviour and might meet their investment objectives more effectively. An Australian dataset comprising stocks, bonds, direct real estate, direct infrastructure and indirect infrastructure is applied for portfolio construction.

Although infrastructure and real estate have common characteristics, the conclusion is that that they constitute two different asset classes. Furthermore, the diversification benefits of direct and indirect infrastructure within multi‐asset portfolios are highlighted and determine efficient allocations up to 78 percent for target rates of 0.0 percent, 1.5 percent and 3.0 percent quarterly.

The results will help investors and portfolio managers to efficiently allocate funds to various asset classes. Most institutional investors are not familiar with investments in infrastructure. The study facilitates a better understanding of the asset class infrastructure and yields some important implications for the optimal allocation of infrastructure within institutional investment portfolios.

This is the first study to examine the role of direct and indirect infrastructure within a multi‐asset portfolio by applying a downside‐risk approach.