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The question is whether debt market investors see through managers' attempts to hide their pension obligations. The authors establish a robust relation between understated pension liabilities and corporate bond yield spreads after controlling for factors that have been previously identified as having a significant impact on firms' cost of borrowing. The results support the idea that bond market investors are not being misled by the use of high pension liability discount rates by some companies to lower their reported pension obligations. For a small fraction of debt issuers, the reported pension liabilities are larger than the pension liabilities valued at the stipulated interest rate benchmarks. For these issuers with overstated pension liabilities, bond investors adjust their borrowing costs downward.

The authors investigate the relation between corporate bond yield spreads and understated pension liabilities relative to long-term Treasury and high-grade corporate bond yields. They aim to answer two questions. First, what are the sizes of over or understated pension liabilities relative to guideline benchmarks? Second, do debt market investors see through the potential management manipulation of pension discount rates? The authors find that firms with large understated pension liabilities face higher marginal borrowing costs after taking into account issue-specific features, firm characteristics, macroeconomic conditions and other pension information such as funded status and mandatory contributions.

The average understated projected benefit obligations (PBOs) are understated by $394.3 and $335.6, equivalent to 3.5 and 3.0% of the beginning of the fiscal year market value, respectively. The average understated accumulated benefit obligations (ABOs) are understated by $359.3 and $305.3 million, equivalent to 3.1 and 2.6%, of the beginning of the fiscal year market value, respectively. Relative to AA-grade corporate bond yields, the average difference between firm pension discount rates and benchmark yields becomes much smaller; the percentage of firm pension discount rates higher than benchmark yields is also much smaller. As a result, understated pension liabilities become negligible. The authors establish a robust relation between corporate bond yield spreads and measures of understated pension liabilities after controlling for issue-specific features, firm characteristics, other pension information (funded status and mandatory contributions), macroeconomic conditions, calendar effects and industry effects.

S&P Rating Services recognizes the issue that there is considerably more variability in discount rate assumptions among companies than in workforce demographics or the interest rate environment in which firms operate (Standard and Poor's, 2006). S&P also indicates that it would be desirable to normalize different discount rate assumptions but acknowledges that it is difficult to do so. In practice, S&P Rating Services conducts periodic surveys to see whether firms' assumed discount rates conform to the normal standard. The paper makes an initial attempt to quantify the size of understated pension liabilities and their impact on corporate bond yield spreads. This approach can be extended to study firms' costs of equity capital, the pricing of seasoned equity offerings and the pricing of merger and acquisition transaction deals, among other questions.

The purpose of this paper is to establish whether a terminal value is a substantial amount of the final figure in a hotel’s valuation. Malta’s scenario has been delved into. This due to the fact that owing to Malta’s high population density and its restrictive land area, land values attract a high premium as compared with larger developed countries. Other matters such as earnings’ multipliers derived from a cap rate (initial yield), CAPEX has also been delved into.

The methodologies adopted in hotel valuation practice has been delved into. An extensive literature review is undertaken to analyse the earnings multiplier adopted by various authors over the past 30-year period. The hotel cap rate (initial yield) has been compared with similar yields adopted in the institutional and property markets and then compares to market-based data. A discussion is undertaken on the validity of adopting discounted cash flow, as against the short cut market appraisal approach. Capitalization rates, cap rates have also been referred to as obtained from the academic and practitioners field and compared. Depreciation and the anticipated annual accommodation charges have been analysed. A database of hotel rooms value over the past 20-year period has been referred.

A table outlines the earnings’ multipliers in perpetuity or for the limited expected design life for various cap rates. This data will act as a guide in guiding practitioners to establish an earnings’ multiplier to be applied in their valuation methodology. An example in the Appendix clarifies the manner in which this data table is to be utilized. The finding of this example notes that for this hotel in Malta, as constructed on private land, the terminal value for this development hovers around the 30 per cent of the market value.

This analysis is based on five valuations as undertaken on five hotels in Malta with classification grades varying from III to V. This notes that the terminal value varies within a range of 9-45 per cent of the total value. This analysis has to be undertaken for other countries for a global range of land terminal values percentages to be established.

Establishing the terminal value of a hotel business, will offer greater security for secured lending facilities required. It will further act as an important tool to establish the feasibility of a hotel development.

Updated insight is given to existing hotel valuation methodologies by delving into the workings of the earnings’ multiplier and establishes that in today’s market the terminal value of the hotel basis has to be accounted for. The above findings are based on a link between theory and practice.

The purpose of this paper is to analyse the gap between government bonds (index-linked and long-dated) and real estate yields/capitalization rates over time for the UK, Australia and the USA. The global financial crisis was a sharp shock to real estate markets, and while interest rates and government bond yields fell in response around the world, real estate yields (cap rates) have risen.

The absolute yield gap levels and their variation over time in the different countries are compared and linked to the theoretical reasons for the yield gap and, in particular, a changing real estate risk premium. Within this context, it assesses whether there have been structural breaks in long-term relationships during booms and busts based on autoregressive conditionally heteroscedastic (ARCH) models. Finally, the paper provides further insights by constructing statistical models of index-linked and long-dated yield gaps.

The relationships between bond and property yields go through a traumatic time around the period of the global financial crisis. These changes are sufficiently strong to be statistically defined as “structural breaks” in the time series. The sudden switch in the yield gaps may have stimulated a greater appreciation of structural change in the property market.

The research focuses on the most transparent real estate markets in the world, but other countries with less developed markets may respond differently.

The practical implications relate to how to value real estate yields relative to interest rates.

This is the first paper that has compared international yield gaps over time and examined the role of the gap between index-linked government bonds and real estate yields.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

This paper aims to describe a robust empirical approach to generating plausible historically based interest rate shocks, which can be applied to any market environment. These interest rate shocks can be readily linked to movements in other key risk factors, and used to measure market risk on institutions with large fixed-income portfolios.

Using yield curve factorization, we parameterize a time series of historical yield curves and measure interest rate shocks as the historical change in each of the model’s factors. We then demonstrate how to add these parameterized shocks to any market environment, while retaining positive rates and plausible credit spreads. Given a set of shocked interest rate curves, joint risk factor movements are calculated based upon historical, reduced form dependencies.

Our approach is based upon yield curve parameterization and requires a parsimonious yet flexible factorization model. In the process of selecting a model, we evaluate three variants of the Nelson–Siegel approach to yield curve approximation and find that, in the current low interest rate environment, a 5-factor parameterization developed by Björk and Christensen (1999) is best suited for accurately translating historical interest rate movements into plausible, current period shocks.

An accurate measure of market risk can help to inform institutions about the amount of capital needed to withstand a series of adverse market events. A plausible set of shocks is required to ensure market value, and cash flow projections are indicative of meaningful market sensitivities.

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.

The purpose of this paper is to investigate the effects of crop insurance premiums being determined by small samples of yields that are spatially correlated. If spatial autocorrelation and small sample size are not properly accounted for in premium ratings, the premium rates may inaccurately reflect the risk of a loss.

The paper first examines the spatial autocorrelation among county-level yields of corn and soybeans in the Corn Belt by calculating Moran's I and the effective spatial degrees of freedom. After establishing the existence of spatial autocorrelation, copula models are used to estimate the joint distribution of corn yields and the joint distribution of soybean yields for a group of nine counties in Illinois. Bootstrap samples of the corn and soybean yields are generated to estimate copula models with the purpose of creating sampling distributions.

The estimated bootstrap confidence intervals demonstrate that the copula parameter estimates and the premium rates derived from the parameter estimates can vary greatly. There is also evidence of bias in the parameter estimates.

Although small samples will always be an issue in crop insurance ratings and assumptions must be made for the federal crop insurance program to operate at its current scale, this analysis sheds light on some of the issues caused by using small samples and will hopefully lead to the mitigation of these small sample issues.

The purpose of this research is to propose a framework for research on Macaulay duration and establish future research directions.

Thematic, bibliometric and content analyses have been used to review 168 research papers published between 1938 and 2019 taken from ISI Web of Science and Scopus contributed by leading authors, journals and regulatory bodies.

Identification and integration of themes of duration theory, duration model development and duration model implementation leading to unattended research gaps, and framework for research on Macaulay duration.

The study is based on an extensive review of the literature to extract important themes, research gaps and frameworks. It does not empirically investigate significance of Macaulay duration and various sectors.

This research has several aspects that are helpful for practitioners. Macaulay duration has been the subject of empirical research only without any guiding framework. This research provides a platform to initiate profound researches in various areas of finance. Various proposed models are required to be tested under holistic approach in conventional and emerging fields, especially in Islamic settings.

This research highlights, research themes leading to framework, research gaps and factors that are crucial in developing, extending and testing duration models leading to enhancement of theoretical base of Macaulay duration.

This article seeks to examine the reference yield calculation method used in crop insurance rating and provides recommendations that could potentially improve actuarial performance of the Federal crop insurance program.

Conceptual, numerical, and statistical analysis is utilized to evaluate the reference yield calculation method used in the US Federal crop insurance program.

The results suggest that reference yields, which at the time of this study are calculated using National Agricultural Statistics Service (NASS) data, do not accurately represent the average actual yields of the insured pool of producers in the Federal crop insurance program. In addition, it is found that not regularly updating these NASS‐based reference yields exacerbates this problem because these reference yields do not appropriately represent the current state of technological progress.

The empirical analysis leads this paper to recommend a reference yield calculation procedure that utilizes county‐average yields from the risk management agency (RMA) participation database and an approach that uses spatially aggregated average yields in cases when data for a particular county are sparse.

No previous study has investigated the reference yield calculation method in the Federal crop insurance program using both RMA and NASS data sets. Moreover, this study contributes to the small literature that examines various aspects of the actual production history (APH) rating platform and suggests refinements to improve actuarial performance.