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This chapter uses stated tourist preferences as a proxy of visitor yield measures, in order to analyse and understand the yield potential of different markets’ preferences. A literature review revealed that there is much progress to be made in terms of discussion, consensus and stability of methodology for the measurement of visitor yield. The aim of the visitor yield analysis, in the current chapter, is also to bring another dimension into yield analysis and discussion, contributing with a new form of measuring yield potential. Since the objective is to identify yield patterns based on tourist preferences over a period of time, dynamics may be captured from the fluctuation patterns, or expressed as volatility of visitor yield and length of stay throughout the years. Destination management organisations and tourist companies may potentially adopt this visitor yield matrix in order to support future strategic decisions.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

In this research, arbitrage opportunity is tested between the yield rates computed by the NSS model, and the computed forward rates between conventional and Islamic finance to see any arbitrage opportunity. The research questions are the conventional and Islamic finance yields at the same level and equal to each other to avoid arbitrage? Whether conventional and Islamic forward rates differ significantly and thus create any arbitrage opportunity. This study aims to find the presence or absence of arbitrage between conventional and Islamic finance yield rates.

The NSS model is the latest model in calculating yield and forward rates. In the method the error level is minimized so expected yield rate and given yield rate both converged (Vahidin and Anastasios, 2020). When they converged it gives the researchers all six months’ yield rates. For the Nelson Siegal method, all the six months’ yield rates are available and these yield rates can be used to compute the forward rates.

The authors concluded there is a significant difference between the conventional yield rate and the Islamic yield rate. It suggests that because there are significant differences, its suggest arbitrage is possible. So anyone interested in making a guaranteed profit. The conventional yield rates are lower; hence, anyone can borrow from the conventional finance system and invest the money in the Islamic financial system because investments are getting higher rates of income in the form of yield rate in Islamic Finance. So, one can make money because of this difference. Statistically, it is possible to make money, but practically, the authors observed the difference, however it is very meager. The arbitrage opportunity between Islamic finance and conventional finance will not affect the economy because the significant difference is too small. The disturbance in the arbitrage opportunity due to the values is very meager and insignificant.

This research does not address the derivative contracts’ role in risk management; future researchers could take up this as another research.

This research will be beneficial for financial institutions, especially institutional investors. Besides, this research will help the regulators and investment bankers in assisting where and future losses especially bond portfolios in conventional finance and Islamic finance. This study will also contribute and help the asset manager of mutual funds in the mutual fund industries.

In effect, this research will strengthen the financial system, capital market and bond market, derivative contracts such as options contracts, futures contracts, swap contracts and forward contracts will use computed forward rates for assessing future losses (value at risk [VaR]) and to hedge them (Balakrishnan, 2020).

As this topic is rarely studied it will increase the literature present in this domain.

The objective of this paper is to examine crop yield predictions and their implications on MPCI in Ghana. Farmers in developing countries struggle with their ability to deal with agricultural risks. Providing aid for farmers and their households remains instrumental in combatting poverty in Africa. Several studies have shown that correctly understanding and implementing risk management strategies will help in the poverty alleviation agenda.

This study examines the importance of crop yield distributions in Ghana and its implication on multiperil crop insurance (MPCI) rating using the Lasso regression model. A Bonferroni test was employed to test the independence of crop yields across the regions while the Kruskal-Wallis H test was conducted to examine statistical differences in mean yields of crops across the ten regions. The Bayesian information criteria and k-fold cross-validation methods are used to select an appropriate Lasso regression model for the prediction of crop yields. The study focuses on the variability of the threshold yields across regions based on the chosen model.

It is revealed that threshold yields differ significantly across the regions in the country. This implies that the payment of claims will not be evenly distributed across the regions, and hence regional disparities need to be considered when pricing MPCI products. In other words, policymakers may choose to assign respective weights across regions based on their threshold yields.

The primary limitation is the unavailability of regional climate data which could have helped in a better explanation of the variation across the regions.

This is the first study to examine the implications of regional crop yield variations on multiperil crop insurance rating in Ghana.

Yield should be equally considered alongside usage rate and monetary value when managing materials. The precise impact that good yield management (or the lack of it) has on a company will vary from business to business depending on the sensitivity to variations in yield achievement. In order to be effectively managed, production yield performance must be planned and controlled, and this can only be achieved if accurate yield information is available to management. Yield performance data should be collected from each and every stage of the manufacturing process for which it is determined to be measurable, then analysed and comparisons made with established yield standards. The information should be presented to management as “exception reports”, thus emphasising priorities.

It is well recognised that the UK commercial property market has traditionally used nominal market benchmarks such as the all‐risk yield based on the assumption that rents are received annually in arrears. Obviously, the reality of the market is that rents are invariably received quarterly in advance and it has been suggested that valuers should move towards valuation techniques that reflect the actual timing of the cash flow. The Investment Property Forum issued a paper in September 1999 promulgating the use of quarterly in advance valuations. Parry’s Tables provides quarterly in advance formulae that reflect the reality of rental income and indicates that an annual effective yield should be used instead of a nominal yield to compensate for the subsequent compounding resulting from an income received quarterly. However, as will be shown, the effective yield formula provided by Parry’s does not reflect quarterly payments that are received in advance so compromising the accurate transition from annually in arrears to quarterly in advance formulae based valuations. Tables produced by the IPF have rectified this problem in part as they correctly work on the premise that capital values will not change as the profession changes to a quarterly approach. It is the yield which will be expressed differently. The use of an all risk yield technique for valuation is actually a comparative method. The way in which the yield is expressed is not the critical issue, it is the multiplier against the rent which will determine value. This paper provides the formula required to accurately transfer annually in arrears data into quarterly in advance data together with the formulae required for contemporary growth explicit discounted cash flows (DCF).

In this paper, quasi‐Tresca yield surfaces are reviewed. In order to do elasto‐plastic analysis, a new yield criterion is presented. The proposed yield surface can be used in nonlinear three‐dimensional analysis of structures. Function of the yield surface is presented in principal stress space and also Cartesian one. A computer program has been developed for nonlinear analysis in C++. Numerical examples have been solved by the proposed yield surface and good results have been obtained.

A method is presented by which elastoplastic constitutive relations for the solid material equivalent to a perforated plate can be obtained, by performing numerical experiments employing the finite element method. The method is applied to a plate of elastic‐perfectly plastic material, perforated in an equilateral triangular penetration pattern of circular holes. The following situations are considered: plane stress, as existing in thin plates under in‐plane loading, generalized plane strain, which approximates the behaviour of thick plates subjected to in‐plane loading and the plate bending condition. First results have been obtained for the plane stress situation. These results show that, for the case of monotonic loading, the elastoplastic behaviour is nearly isotropic in the plane of the plate, whereas under cyclic loading below the limit load, the equivalent solid material exhibits distortional hardening.

The purpose of this paper is to assess the production risk for winter wheat producers in Beijing, China, particularly in its 13 districts.

A parametric approach is used to model wheat‐yield distribution for samples and the Kolmogorov‐Smirnov test is used to choose the most appropriate yield distribution. Parameters of the special yield distribution are estimated through the maximum likelihood estimation approach.

The Burr distribution is found to be the most appropriate parametric distribution to model winter wheat‐production risks for the districts of Beijing, except in the districts of Fengtai and Shunyi. Findings also show that the Johnson family distribution is the most appropriate model for these two districts (SB for the Fengtai District and SU for the Shunyi District). The wheat‐production loss ratios of the Beijing districts are between 6 and 15 percent, which is considered medium range in most regions. The highest production risks are located in the Western regions of Beijing (Mentougou and Fengtai) while the lowest production risk is located in the Southeastern region of Beijing (Daxing District).

To generate an objective yield trend and an accurate production risk assessment, linear moving average, instead of linear (or quadratic) regression, is used in this paper.

In Part One of this paper, the logical basis of the conventional approach was examined and found to be wanting. The contemporary approaches have a more logical basis but the application of technique has a serious flaw in the analysis stage. While the conventional techniques require no subjectivity at the analysis stage of the valuation process, the contemporary models require a subjective choice of an equated yield, prior to calculation of implied growth rate and capitalisation rate. This choice of equated yield must be made regardless of whether the comparable is rack rented or reversionary. In the use of comparables, both conventional and contemporary techniques do not have any serious flaws when the comparison is perfect. To be perfect the comparison must not only be similar in locational and physical characteristics, but it must also be identical in lease structure, that is to say it must have the same unexpired term and rent received to CRV ratio. Where the perfect comparison exists, investment valuation techniques are irrelevant: direct capital comparison can take over. The debate regarding the use of techniques for market valuation must therefore revolve around the use and manipulation of non perfect comparables and the second part of this paper investigates the objectivity and logic of the application of technique to the valuation of reversionary freehold investments.