Accurate Valuation Research Articles

The influence of land cover data on farm-scale valuations of natural capital

The valuation of natural capital within individual farms could inform environmentally beneficial land use change and form the basis of agricultural subsidy schemes based on the provision of ecosystem services. Land cover extents can be used in a benefit transfer approach to produce monetary valuations of natural capital rapidly and at low cost. However, the methodology has not before been used within individual farms, and the impact of land cover data characteristics on the accuracy of valuations is uncertain. Here, we apply the approach to five UK farms of contrasting size, configuration and farming style, using three widely available land cover products. Results show that the land cover product used has a substantial impact on valuations, with differences of up to 58%, and the magnitude of this effect varies considerably according to the landscape structure of the farm. At most sites, valuation differences are driven by the extent of woodland recorded in the landscape, with higher resolution land cover products incorporating larger amounts of woodland through inclusion of smaller patches, leading to higher overall valuations. Integrating more accurate land cover data and accounting for the condition, configuration and location of natural capital has potential to improve the accuracy of valuations.

An Insight into The Determinants on the Valuation Accuracy for Bank Stocks in Indian Stock Market- An Empirical Analysis

Investors in stock market using different valuation models to pick the stocks from Indian stock market. Few valuation models are accurate for some stocks due to various reasons. There are different factors determining the accuracy of valuation for bank stocks in Indian Stock Market. This paper studies on the importance of six equity valuation models in terms of valuation accuracy of bank stocks in Indian Stock Market. This paper shows the determinants such as Size, Profitability and Ownership of bank determining the accuracy of valuation models for BSE Bankex stocks in Indian Stock Market. This study selected P/E Model, P/B model, Ohlson Model, CAPM, Dividend Discount Model and Excess return Model for valuation accuracy determinants of Bank Stocks in Indian Stock Market. This study selected a sample of 14 banks which constitute the BSE Bankex. It was found that size, profitability and ownership of bank are the most important determinants determining the valuation accuracy of banks in Indian stock market.

Relative Valuation with Machine Learning

We use a decision-tree-based machine learning approach to perform relative valuation. Stocks are valued using market-to-book, enterprise-value-to-assets and enterprise-value-to-sales multiples. Our machine learning models reduce median absolute valuation errors by between 17% and 50% relative to traditional models. The identified valuation drivers are consistent with theoretical predictions derived from a discounted cash flow approach. Accounting variables related to profitability, growth, efficiency and financial soundness are important valuation drivers. The valuations produced by machine learning models behave like fundamental values. A value-weighted strategy that buys (sells) undervalued (overvalued) stocks generates highly significant abnormal returns. When we use models trained on listed firms to value IPOs, machine learning models outperform traditional models in valuation accuracy and can identify mispriced IPOs.

Quality of Independent Expert Reports Used in Australian Takeovers

In this article, the authors investigate whether there has been an improvement in the quality of independent expert reports following ASIC's revisions to RG111 and RG112. These revisions include additional disclosures on the valuation methodologies used and explanation if the valuation was materially different from the company's recent trading price. It was expected that these revisions have led to an improvement in report quality where quality is determined by the accuracy of the expert's valuation. Results show that after the 2011 revisions, valuations became more accurate based on updated measures of report quality. However, experts with higher fees did not provide higher quality reports on average. The findings indicate that the independence provisions within the new rules were effective. Furthermore, they warn commissioning firms that higher fees are not necessarily indicative of higher quality reports.

American Option Pricing: Optimal Lattice Models and Multidimensional Efficiency Tests

This paper introduces a set of lattice techniques with a view to accelerating computation time and improving the accuracy of American Option valuation. Estimation speed can be enhanced through developing a parsimonious early exercise boundary search routine combined with reliance on dynamic memory and lattice truncation. Furthermore, Black-Scholes and Richardson extrapolation modifications to the lattices can also be applied individually and/or together to improve the accuracy of lattices. In this paper, we investigate the improvement introduced by obtaining the best combination of varying features. By introducing these techniques to the Leisen-Reimer and Tian binomial model, we can achieve a level of accuracy and efficiency combined that surpass analytical analogues prominent in the literature. Significantly, the Leisen-Reimer and Tian structure can accommodate arbitrary improvements in accuracy by simply increasing the density of their own mesh. Analytical methods generally do not afford much scope for optimising speed and efficiency in a granular fashion. We also compare efficient lattice models with analytical formulae for pricing different groups of options according to the deepness of American quality and the moneyness of the options. The appropriate model is recommended for pricing particular types of the options. Lattices importantly afford an explicit trade-off locus between accuracy and speed that can be navigated according to predetermined precision tolerance levels and option types. This should have practical relevance to trading platforms that require real-time estimates of implied volatility.

How Risky is your Project Really? Corporate Finance Strategies for Assessing Risk

Risk is a vital concept to grasp when investing in a firm or project. It is a key ingredient required to evaluate the cost of capital and perform a valuation. The capital structure used to finance a firm or project and specifically the amount of leverage and debt financing employed must be accounted for to correctly assess a project’s risk and perform an accurate valuation. There are different measures of risk available to us to assess the risk. In this paper we review common risk measures used by practitioners and give an overview of the CAPM beta which measures a firm’s systematic risk and assumes that investors are not rewarded for firm specific risk (Berk and DeMarzo, 2016). We review the CAPM model commonly used in corporate finance and show how to calculate beta. Furthermore we discuss how risk increases with leverage and the level of debt financing used to finance a company or project, which consequently increases expected returns (Brealey et al, 2014). We discuss how CAPM beta can be calculated as the co-movement of returns with the market and/or equivalently as the slope of a regression analysis. For firms and projects that are illiquid and/or have no public data we can imply beta risk from comparable company data, however we are required to unlever and relever beta’s to remove leverage effects from the comparables and introduce the leverage effects of the target to give a reliable indicator of beta risk (Koller et al, 2015). Not only is CAPM beta useful to assess the risk of a firm or project, but it is essential to calculate the weighted average cost of capital (WACC). This is the expected return investors require to invest in a project and incorporate the correct level of risk. Consequently CAPM beta risk is a key ingredient required to value of a firm or project and perform a discounted cash flows (DCF) analysis, see (Burgess 2020a), (Burgess 2020b) and (Burgess 2020c).

A comparison of pricing models for mineral rights: Copper mine in China

Purchasing mineral rights to allow a corporation to extract minerals is a large investment and potentially very profitable. Generally, the assessment and valuation process is conducted by an official organization at the nation's governmental level. From a corporation perspective it is thus crucial to calculate an accurate value of the right to exploit a mineral product or what we call “mineral right”. In this work we compare three valuation methods and we compare their results in case of pricing a copper mine in China. We explain and apply the official valuation method based on a simple Discounted Cash Flow (DCF). We present what we believe is a more accurate valuation based on the term structure of future mineral prices: the so called modified Discounted Cash Flow (mDCF) method. Finally, we contrast with a method based on real options which considers the mineral right as a swaption. We implement two real options models: the classical Black model and a more modern Miltersen and Schwartz model. We highlight and discuss differences and commonalities between the three valuation methods. Finally, we make a recommendation for future financial reporting based what we learn from the three methods.

Efficient valuation of a variable annuity contract with a surrender option

We study the partial differential equation (PDE) approach for efficient and accurate valuation of a variable annuity (VA) contract with a surrender option. Specifically, using the Laplace–Carson Transform (LCT), we derive an analytic pricing formula for a VA contract with a surrender option which is formulated as a PDE with an optimal surrender boundary. To demonstrate the efficiency and accuracy of our approach, we show that our pricing formula efficiently provides the exact value of a VA contract. Moreover, we compare the performance of three numerical methods for Laplace inversion to find the most efficient method. Among these methods, we found that the Gaver–Stehfest method is the most efficient pricing for a VA contract with a surrender option.

The accuracy of self-reported dwelling valuation

Owners’ valuations of dwelling prices are central in the construction of price indices and households’ economic behavior. We analyze the variation of the self-reported valuation bias over the distribution of dwelling sale prices, using a dataset of observations from a Household Expenditure Survey merged with the national sample of housing sale transactions by census tract. We find that self-reported estimates of dwelling values are, on average, 20% higher than the mean market prices of houses in the corresponding census tracts. Estimates reported by people who occupy dwellings in the lowest eight deciles of the price distribution are upward-biased, whereas those who live in the most expensive dwellings more typically understate the value of their homes. The self-reported valuation bias is systematically associated with owner's traits and with dwelling and neighborhood characteristics. Misspecification might be another potential explanation for that bias. The frequency of dwelling sales in the respondent's tract was found to have an effect on the self-reported valuation bias.

Population density and the accuracy of the land valuations in the 1798 federal direct tax

The peculiar operation of the 1798 federal direct tax has led scholars to question whether tax officials reported the land valuations from their districts faithfully. Peter Lindert and Jeffrey Williamson argue that southern tax assessors systemically under reported the value of southern real estate, and they adjust their income estimates to account for the likelihood of corruption. This paper affirms the reliability of the tax returns by demonstrating that population density, rather than corruption or lax enforcement, can explain nearly all of the variation between the assessment districts. Accepting the tax valuations as accurate would lower Lindert and Williamson’s income estimates, imply slower growth rate between 1774 and 1800, and suggest a higher growth rate between 1800 and 1850.

Re: Accuracy of Valuations of Surgical Procedures in the Medicare Fee Schedule.

Re: Accuracy of Valuations of Surgical Procedures in the Medicare Fee Schedule.

Farmers' Heterogeneous Willingness to Pay for Farmland Non-Market Goods and Services on the Basis of a Mixed Logit Model-A Case Study of Wuhan, China.

The exploration of different stakeholders’ heterogeneous willingness to pay for farmland ecological value is a fundamental part of understanding the total value of farmland protection and designing a scientific farmland protection policy. Unlike the homogenous assumption used in the previous studies, the mixed logit model of choice experiment method was applied to estimate respondents’ heterogeneous willingness to pay for farmland non-market value (represented by farmland area, farmland fertility, water quality, air quality, species richness, and recreational value) in this study. Data came from a sample of 289 farmers in Wuhan, China who were face-to-face interviewed. Results showed that: (1) Farmers were unsatisfied with the status quo of the present farmland ecological environment and were willing to pay to preserve all the attributes of farmland non-market value. (2) Farmers had a heterogeneous preference for the status quo and recreational value—the error variances of these two attributes were both significant at the 1% level, and their willingness to pay for the farmland non-market value in Wuhan was 1141.88 Yuan/hm2. (3) Farmers’ cognition degree of farmland importance and whether respondents bought medical insurance or not had significant impacts on their willingness to pay. The results can provide the basic foundation for accurate valuation of farmland non-market services, help farmland regulators make the right farmland conversion decisions, and improve the resource allocation efficiency of local financial expenditure during farmland protection in Wuhan.

Simulative Verification of the Possibility of using Multiple Regression Models for Real Estate Appraisal

Abstract The possibility of using multiple regression models in real estate valuation is the subject of disputes, both in theory and in practice. Econometric modelling is a difficult process, since a number of issues of substantive and numerical nature occur during that process. Modern technologies enable quick and easy model estimation with the use of virtually any quality of data. Naturally, it provokes property appraisers to use such models in the practice of real property valuation, particularly in mass appraisal, frequently without taking those issues into account. Consequently, the models obtained and applied in practice turn out to be of poor quality and, objectively speaking, should not serve as the basis for determining real estate value. The specificity of the real estate market and of the real properties themselves as objects traded in that market additionally exert a negative impact on the quality of the obtained models. In this article, the authors present the results of research which involved a simulation of various types of disturbances of a model artificially developed database of real estate prices and attributes as well as their impact on the quality of estimated models. The research will make it possible to answer the question of the degree and type of disturbances that are permissible in the functioning of a real estate market if the estimated models are to still satisfy the qualitative requirements defined for them, and thereby produce accurate valuation results. A model database will be disturbed by the deviation of prices from model prices and by reducing its size. Radom generators were used to obtain database disturbances.

Property valuation methods in practice: evidence from Australia

PurposeImproving valuation accuracy, especially for sale and acquisition purposes, remains one of the key targets of the global real estate research agenda. Among other recommendations, it has been argued that the use of technology-based advanced valuation methods can help to narrow the gap between asset valuations and actual sale prices. The purpose of this paper is to investigate the property valuation methods being adopted by Australian valuers and the factors influencing their level of awareness and adoption of the methods.Design/methodology/approachAn online questionnaire survey was conducted to elicit information from valuers practising in Australia. They were asked to indicate their level of awareness and adoption of the different property valuation methods. Their response was analysed using frequency distribution, χ2 test and mean score ranking.FindingsThe results show that the traditional methods of valuation, namely, comparative, investment and residual, are the most adopted methods by the Australian valuers, while advanced valuation methods are seldom applied in practice. The results confirm that professional bodies, sector of practice and educational institutions are the three most important drivers of awareness and adoption of the advanced valuation methods.Practical implicationsThere is a need for all the property valuation stakeholders to synergise and transform the property valuation practice in a bid to promote the awareness and adoption of advanced valuation methods, (e.g. hedonic pricing model, artificial neural network, expert system, fuzzy logic system, etc.) among valuers. These are all technology-based methods to improve the efficiency in the prediction process, and the valuer still needs to input reliable transaction data into the systems.Originality/valueThis study provides a fresh and most recent insight into the current property valuation methods adopted in practice by valuers practising in Australia. It identifies that the advanced valuation methods could supplement the traditional valuation methods to achieve good practice standard for improving the professional valuation practice in Australia so that the valuation profession can meet the industry’s expectations.

Reducing the property appraisal bias with decision support systems: An experimental investigation in the South African property market

Background – Researchers have observed that valuation accuracy and valuation variation are caused by human adaptive approaches called cognitive shortcuts. Of particular interest for valuation tasks is the susceptibility of decision-makers to the anchoring and adjustment heuristic, a mental shortcut which involves deliberate and conscious adjustment of values. Various studies have shown that valuers are prone to anchoring to asking price, previous estimates, and other reference points. Aim – The research aim is to determine the efficacy of a decision-support tool in reducing property appraisal bias. Setting and Methods – A controlled experimental study design was used. The design in which test persons had to appraise a fictitious property is based on a German study that uses a self-written valuation software, adapted to South African conditions. The software comprises two versions, a standard software and a decision-support software. Descriptive statistics and non-parametric testing were used to interpret the results. Findings – Despite the results not being as robust as expected, the study revealed that test subjects were susceptible to the anchoring bias and that using a decision-support tool can help reduce this and so decrease the valuation variations. Practical implications – This study heightened the need to counter the effect of bias in valuation. Few studies have delved into debiasing methods and even fewer have used technical tools for this task. Other forms of cognitive shortcuts used by valuers should be incorporated into the decision-support tool, and a similar test run for different valuation settings.

Approaching rainfall-based weather derivatives pricing and operational challenges

This article approaches some of the current rainfall derivatives pricing and operational challenges through an empirical application to Comunidad Valenciana, Spain. Regarding the former, two different issues are addressed. First, we examine the rightness of suggesting the Gamma distribution to price rainfall contracts, which is the alternative chosen by previous authors applying the Index Value Simulation technique. This is done for the purpose of determining whether the consideration and comparison of other alternatives may lead to more accurate valuation results. Concretely, two different distributions, in addition to the Gamma, are proposed: the exponential and the mixed exponential, whose fits are assessed through the Kolmogorov–Smirnov/Lilliefors test and graphical analyses. The outcomes attained indicate that this selection process leads indeed to a precise generation of the rainfall index’s moments. Next, we examine the viability of using a unique distribution to model the rainfall risk of regions located nearby, since this would considerably decrease valuation complexity. Our analysis shows that the most convenient choice depends on the period and location considered, although the mixed exponential appears as a reasonable option in most cases. Finally, a relevant operational challenge related to geographical basis risk is approached. Concretely, an evaluation of this type of risk among the locations studied is conducted. The results attained indicate that, given the insufficient degree of correlation between nearby locations, rainfall risk hedging measures may rely on compound derivatives referred to several neighbor stations.

Full‐fledged SABR Through Markov Chains

We present a general purpose technique for the efficient and accurate valuation of options in the shifted stochastic alpha, beta, rho (shifted-SABR) model which includes SABR as a special case. The method is based on a novel double-layer continuous-time Markov chain from which closed form matrix expressions for European options are derived. We also propose a recursive risk-neutral valuation technique for pricing discretely monitored path-dependent options, and use it to price Bermudian and barrier options. In addition, we provide single Laplace transform formulae for discretely monitored arithmetic Asian options. Numerical experiments confirm the accuracy and efficiency of the proposed method, which is suitable for practical use.

Why is biodiversity data-deficiency an ongoing conservation dilemma in Africa?

Recent reports illustrate deficiencies in knowledge about current conditions and long-term trends in population sizes of hundreds of African plants and animals’ species. In this commentary, I discuss the lack of standardized data for assessing and monitoring biodiversity in Africa. I present my own views on the causes for these knowledge and data gaps, their consequences for conservation, and future directions that could improve the current situation.There are many reasons for lack of standardized data including; ongoing conflicts and political instability in many biodiversity-rich countries; absence of regular and policy-driven monitoring programs; weak facilities; and irregular or insufficient funding. Existing biodiversity monitoring initiatives are often short-term, poorly-designed surveys, largely dependent on volunteer researchers or international partners, biased towards large “charismatic” animal species, and published in difficult-to-access outlets. Consequently, up-to-date and rigorous reports about conditions and trends of African biodiversity are limited, and conservation planning, comparative studies and accurate valuation of ecosystem services continue to be difficult.Urgent actions include: 1) commitments and support of local governments to implement effective conservation monitoring programs; 2) establishment of a network of carefully designed long-term and continent-wide monitoring initiatives for endangered species and biodiversity; and 3) involvement of universities, research centers, Non-Governmental Organizations (NGOs) and local communities in such monitoring efforts. Such actions could stimulate further in-depth studies and systematic analysis of the root causes and solutions for the decades-long African biodiversity knowledge gap. Examples of highly needed systematic analysis and documentation in the coming efforts towards filling up the biodiversity data gap in Africa should clearly define biodiversity data-deficiency by taxonomic groups and by countries.

The pricing accuracy of alternative equity valuation models: Scandinavian evidence

AbstractIn many decision contexts, there is a need for benchmark equity valuations, based on simplified modeling and publicly available information. Prior research on U.S. data however shows that the accuracy of such valuation models can be low and sensitive to the choice of model specifications and value driver predictions. In this paper, we test the applicability and pricing accuracy of three fundamental valuation (dividend discount, residual income, and abnormal earnings growth) models, all based on forecasts of company dividends, earnings, and/or equity book values. Extending prior research, we apply these models to Scandinavian firms with accounting data from the period 2005–2014, explicitly testing two approaches for the prediction of the value drivers—exogenously forecasted numbers versus projected historical numbers. Given access to the forecasted value drivers, the dividend discount model comes out as the most accurate valuation model. In particular, this holds in a comparison between the most parsimonious model specifications. The residual income valuation model generates the best pricing accuracy given the prediction of value drivers based on historical financial numbers. Notably, we observe pricing errors that in general are lower than what has been reported in prior U.S.‐based research for the dividend discount and the residual income valuation models. The pricing accuracy of the abnormal earnings growth models is surprisingly weak in the Scandinavian setting. However, these models improve somewhat after a couple of complexity adjustments, in particular with value driver predictions based on the projected history setting.

Undervaluation in probate inventories probate inventory values and auction protocol market prices in eighteenth and nineteenth century Sweden

ABSTRACTIn this article we examine the accuracy of valuations of movable property for a sample of 22 probate inventories from Swedish. The sample comprises a total of 785 probated items which we have been able to match with contemporary auction protocols, giving us an official sales price for each item. This enables us to determine the consistency between the appraisal values in the probates and prevailing market prices, despite the fact that the probated items were invariably second-hand and of uncertain quality, as the comparison can be made for one and the same items. Our results show that probate appraisal values were marked underestimates of contemporary market prices, but also, that they lacked internal consistency. We find a mean undervaluation for probated items of −36 ± 3 percent, but the degree of undervaluation varied both depending on (i) the category of item, (ii) the year of the probate, as well as depending on (iii) the social class of the deceased. Our results apply, first and foremost, for the Swedish counties of Uppland and Södermanland, but as there is no reason to assume that Swedish probate proceedings exhibited significant regional variation, our results are most likely valid for the whole country.