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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.

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.

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.

This study aims to investigate the determinants of credit spreads in hotel loans securitized into commercial mortgage-backed securities (CMBS) between 2010 and 2015.

The sample represents 1,579 US hotel fixed interest rate whole loans with an aggregate mortgage value of $26.6bn at loan origination. The relationship between credit spreads and property, loan and market characteristic is examined via multiple regression analysis. Additionally, the method of 2-stage least squares is used to control for endogeneity bias and identify the effect of the loan-to-value (LTV) ratio on credit spreads.

The multiple regression models explain 80 per cent of the variation in credit spreads and show a significant association of credit spreads with hotel and loan characteristics and market conditions. The findings indicate the debt coverage ratio to be the most important predictor of credit spreads followed by the loan maturity term, implied capitalization rate, LTV and yield curve. The results show the debt yield premium to be a stronger predictor of credit spreads than the debt yield ratio. The spread between the debt yield ratio and mortgage interest rate could be used in future research as an instrumental variable to identify the effect of the LTV on credit spreads.

This study is limited to the CMBS market and the period after the financial crisis. Additional limitations include sample selection bias, exclusion of multi-property loans and variable interest rate loans.

Interest rate increases in an expanding economy would likely increase the cost of borrowing for hotel owners leading to higher debt service payments and lower profitability. If an increase in interest rates is offset by a decline in credit spreads, hotel owners will still benefit from the ensuing stability in borrowing interest rates. The evidence also suggests that CMBS lenders favor select service and extended stay hotels. Owners and operators of these efficient and profitable hotels will likely obtain loans with lower credit spreads given their lower risk of default.

The current study provides evidence on the effects of loan and property characteristics in the pricing of loan risk and serves to inform CMBS market participants about the factors that drive credit spreads in hotel mortgage loans.

The paper is motivated by the paucity of empirical research on the determinants of capitalisation rates/yield in the commercial property market. Compared to property price determinants, the capitalisation rate has received significantly less attention. This is somewhat surprising given that the capitalisation rate is a more insightful indicator for investors on commercial property market performance than merely price changes or trends. The capitalisation rate, measured as the ratio of net operating income to the property’s capital value, captures the asset’s overall ability to generate income which is crucial for investors who typically invest in property for their income-generating capacity. The purpose of this paper is to address these issues.

To evaluate the determinants of capitalisation rates, time series analysis was used. The data capture performance in the Australian commercial property market between 2005 and 2018. All macroeconomic and financial data are freely available from official sources such as the Australian Bureau of Statistics and the nation’s central bank. Methodology wise, given the problematic nature of the data such as a mixed order of integration and the possibility of cointegration amongst some of the I (1) variables, the autoregressive distributed lag model was selected given its flexibility and relative lack of assumptions.

Bond rates, market risk premiums, stock market excess returns and other macroeconomic variables were found to drive capitalisation rates of Australian commercial properties. A 1% increase in the bond rate results in approximately 0.3–2.4% increase in capitalisation rates depending on the sub-market. Further, a 1% increase in excess market returns results in a 0.01–0.02% increase in capitalisation rates. Regarding risk premiums, a 100 basis point increase in the BBB spread results in approximately 0.92–1.27% reduction in cap rates in certain markets.

Asset managers will find these results useful in asset allocation strategies. Commercial properties offer attractive investment qualities such as yield stability in periods of economic uncertainty while allowing for the possibility of capital growth through appreciation of the underlying asset. By understanding the factors that affect the capitalisation rate, practitioners may predict emerging trends and identify threats to portfolio return and stability. This allows better integration of commercial property in the construction of portfolios that remain robust in a variety of market conditions.

The contribution to literature is significant given the lack of similar studies in the Australian market. The performance of real estate assets using cap rates as a comparative measure to equities and bonds influences decisions in asset allocation strategies. It provides crucial information for investors to estimate the performance of commercial property. This research supports the notion that both space and capital market indicators jointly affect capitalisation rates. The findings expand the knowledge base relating to commercial properties and validate the assessments of investors, developers and valuers who utilise yield as a performance benchmark for asset allocation strategies.

This study aims to extend the literature by exploring the degrees of integration of both fixed and adjustable mortgage rates and diverse riskless (Treasury) and risky (corporate) interest rates in the capital markets from January 1, 2010, until November 7, 2018. This period is uniquely characterized by a sharp conversion on January 20, 2017, from enhanced financial regulation during the Obama administration to major deregulatory ambitions during the first 22 months of the Trump administration.

The authors use the augmented Dickey and Fuller and the Phillips and Perron unit root tests to examine time series stationarity and the Johansen cointegration rank and the Stock-Watson common trends tests to inspect various cointegrations and regressions of time series pairs to explore different effects. The authors deploy these techniques over the entire time frame, as well as for distinct sub-periods of similar length.

The authors conclude that a deregulatory setting favors cointegration between mortgage and non-corporate capital markets. However, an enriched regulatory environment supports cointegration between mortgage and corporate capital markets. In addition, the Dodd-Frank Wall Street Reform and Consumer protection Act from July 21, 2010, created a unique though short-term effect on the relationships between Treasury and corporate bonds and fixed-rate mortgages.

The journey contributes to the overall understanding of the interactions among US financial markets. They are considered efficient, competitive and fully developed if their prices quickly adjust to economic changes and regulatory transformations.

The authors study the degrees of integration of various conventional and adjustable mortgage rates and different fixed and floating interest rates in the US capital markets from January 1, 2010, until November 7, 2018. This recent time frame has yet to be examined in the economic literature. This period is also characterized by a sharp transformation on January 20, 2017, from enhanced financial regulation during the Obama administration to major deregulatory drives during the first 22 months of the Trump administration.