Traditional Valuation Approaches Research Articles

Practice Briefing: The implications of a move towards explicit discounted cash flow (DCF) models for property investment valuations

PurposeThe primary purpose of this Practice Briefing is to examine the implications of the recommendations of the Royal Institution of Chartered Surveyors (RICS) Review of Investment Valuations to shift towards (explicit) discounted cash flow (DCF) valuations on valuers, clients, risk management and market data.Design/methodology/approachThis Practice Briefing will develop a conceptual framework to articulate the impact of the shift towards explicit modelling assumptions in valuations. A comparative analysis is conducted to contrast traditional valuation approaches with an explicit DCF approach.FindingsThe proposed shift to DCF valuations in the real estate industry carries both subtle and profound implications. While on the surface, the move appears to bring minimal change since current valuations are already DCF-based, a deeper exploration reveals a potential transformation to the understanding, analysis and measurement of pricing and risks in commercial real estate.Practical implicationsThe traditional techniques adopted in valuations have become pervasive in the industry, hindering more sophisticated modelling and analysis of individual assets and portfolios. Explicitly modelling assumptions in both the initial years of cash flow and perpetuity calculations would unveil fundamental relationships and rationales that have previously been buried within, and perhaps ignored by, an All Risks Yield (ARY).Originality/valueThis briefing identifies the cause of confusion when interpreting ARY differentials on implied target returns and risk and demonstrates how a change to explicit assumptions, such as growth and letting periods, would enhance transparency, enabling more informed client–valuer discussions, which in-turn will boost confidence in valuation accuracy, lead to more sophisticated asset modelling, market data, forecasting and market analysis.

Non-Fungible Token valuation: State of the art and future insight

Purpose: This paper aims to provide an exploratory analysis of Non-Fungible Tokens (NFTs) valuation. NFTs are a new kind of digital asset born out of the dis-ruptive technologies' introduction (i.e., blockchain). A lot of small and medium en-terprises (SMEs), as innovative start-ups, are involved in this domain. Nowadays, several issues in the evaluation field remain unclear. To fill this gap, this research adopts a holistic approach is crucial to draw a clear picture of the first-time ac-counting treatment of these new digital assets. Design/methodology/approach: Using a structured approach, this research considers some of the state-of-the-art international practices and reviews some major scholars' opinions on the matter. Particularly, the study analyses the main contributions provided by international entities (e.g., European Financial Reporting Advisory Group - EFRAG, Chartered Business Valuators institute - CBV, PriceWa-terhouseCoopers - PWC), digital operators, and academia. Findings: Based on the two main strands defined for the NFT's nature, NFTs valuation issues can be resumed in twofold. The first one that considers NFTs as intangible assets suggests following the traditional valuation approaches (cost, in-come, or market) that is already a part of international accounting standards. The second strand that considers NFTs as financial assets proposes a different valua-tion approach based on quantitative methods coming mainly from finance fun-damentals. Originality/value: The originality of this study includes the different NFT val-uation approaches, which enrich the literature and can help SMEs in managing and accounting for this new kind of digital asset.

Evaluating the efficiency of factors influencing valuation of residential buildings: A priority weight-based model

Valuation of buildings is an utmost complication for different socio-economic stakeholders in the building's buying and selling process. The traditional valuation approaches can vary because it depends on the evaluator's opinions. Also, existing approaches have not considered all the parameters and the interrelation between these parameters for their models. The objective of this study is to develop a priority weights-based rating model for the valuation of existing and new buildings. In this paper, the Fuzzy Analytical Hierarchy Process (FAHP) is used to develop a rating system to use in the valuation process of buildings. The complementary novelty of this paper is the inclusion of the primary principles of engineering, sustainability, and adaptability into the valuation process of a building. Further, the subjectivity of this model is eliminated by using numerical descriptors. The opinions of 100 experts were collected and averaged to develop this model, and the consistency ratio of the experts’ opinions was maintained at less than 10 %. Finally, the valuation of a residential building is performed as a case study to show the numerical possibilities of the proposed model. The proposed model can be used to evaluate existing and new residential buildings in property transactions, insurance purposes, taxation, and making investment decisions.

The impact of negative interest rates on the pricing of options written on equity: a technical study for a suitable estimate of early termination

This work aims to investigate the main problems that impact the pricing models and the sensitivity measures of American options written on shares without a pay-out, in the presence of negative interest rates with a specific focus on the Monte Carlo method. The first paragraph carries out a review of the anomalies caused by such an odd condition and focuses thereafter on the core topic of the research by treating a wide range of numerical models suitable for unbiased evaluation of the early exercise, thus expanding the existing literature. The two following paragraphs are dedicated to describing the models used for the correct estimation of fair value: binomial lattice models (Cox-Ross-Rubinstein - CRR Tree, Leisen Reimer - LR Tree, Jarrow-Rudd - JR Tree and Tian Tree), trinomial stochastic trees, Finite Difference Method (FDM) scheme and the Longstaff-Schwartz Monte Carlo. Particular attention is paid to this last approach which allows to combine the flexibility of traditional numerical integration schemes for stochastic processes on equity with the estimation of the convenience of exercising the American option ahead of time. After conducting quantitative tests both on pricing and on the estimation of sensitivity measures, the LR Tree was selected as the most performing deterministic algorithm to be compared with the Monte Carlo stochastic technique. The final part of the work focuses on quantifying the valuation gap introduced by negative interest rates in the valuation of American options written on an unprofitable underlying comparing the traditional valuation approach and the deterministic Leisen Reimer model and the Longstaff-Schwartz stochastic model.

Integrating scientific considerations into R&D project valuation.

Traditional valuation approaches rarely take into account scientific considerations specific to a R&D project. A question-based approach using real options offers a solution.

The Valuation of Patent Real Options – An Analysis Using Patent- and Firm-Level Datasets

The traditional valuation approaches aim to quantify the costs, revenues and market value of the patent assets. More recently, the appraisal of patent real options has been proposed in connection t...

Traditional Approaches for Company Valuation Are Flawed for Valuing In Vivo Gene Therapy Companies.

The era of gene therapy has begun. In recent years, potentially breakthrough datasets and rapidly expanding company pipelines have begun to overshadow the unfulfilled promise characteristic of the gene therapy sector in decades prior. One barometer for progress in the space can be seen in stock markets, where NASDAQ-listed in vivo gene therapy companies we follow have increased from 4 companies with $1.9 billion in market capitalization on January 31, 2014, to 24 companies with $30.5 billion in market capitalization on October 31, 2018. For many in the financial community, a tangible signal for the emergence of the broader gene therapy space is the recent notable mergers and acquisitions activity, a signal that previously heralded the arrival of blockbuster biotechnologies like monoclonal antibodies. Notably, Novartis' $8.7 billion acquisition of in vivo adeno-associated virus 9–based gene therapy player, AveXis, earlier this year has focused many on looking for new investment opportunities in the space, thereby increasing interest in the valuation of gene therapy companies. This perspective discusses the theoretical underpinnings of company valuation and explains why traditional approaches have limitations when valuing in vivo gene therapy companies, which produce single treatments that may achieve durable or curative benefits. We use the AveXis case study to illustrate certain points on the valuation of breakthrough innovation that we think have broader applicability throughout the in vivo gene therapy space. This publication is the first in a three-part series. Future discussions in this series on in vivo gene therapy companies will explore real-world approaches and considerations that have already proven successful in mitigating the limitations of traditional valuation approaches as well as those that may soon emerge.

Sequencing Infrastructure Investments under Deep Uncertainty Using Real Options Analysis

The adaptation tipping point and adaptation pathway approach developed to make decisions under deep uncertainty do not shed light on which among the multiple available pathways should be chosen as the preferred pathway. This creates the need to extend these approaches by means of suitable tools that can help sequence actions and subsequently enable the outlining of relevant policies. This paper presents two sequencing approaches, namely, the “Build to Target” and “Build Up” approach, to aid in sub-selecting a set of preferred pathways. Both approaches differ in the levels of flexibility they offer. They are exemplified by means of two case studies wherein the Net Present Valuation and the Real Options Analysis are employed as selection criterions. The results demonstrate the benefit of these two approaches when used in conjunction with the adaptation pathways and show how the pathways selected by means of a Build to Target approach generally have a value greater than, or at least the same as, the pathways selected by the Build Up approach. Further, this paper also demonstrates the capacity of Real Options to quantify and capture the economic value of flexibility, which cannot be done by traditional valuation approaches such as Net Present Valuation.

Cross-national Market Valuations of Patent Strategies

The traditional valuation approaches rely on the quantification of costs, revenues or market value of the patent assets. The market value model relying on the Tobin's q equation has seen several ap...

Decision-making in incomplete markets with ambiguity—a case study of a gas field acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian Motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore, we use Gaussian generalized autoregressive score (GAS) and GARCH models, extending them to Student’s t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. As a result, markets are incomplete which makes preference free pricing impossible and thus standard option pricing methodology inapplicable. Therefore, we parametrize the investor’s risk preference and use utility indifference pricing techniques. We use Least Squares Monte Carlo simulations as a dimension reduction technique in solving the resulting stochastic dynamic programming problems. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time-dependent stochastic structures.

Decision Making in Incomplete Markets with Ambiguity -- A Case Study of a Gas Field Acquisition

We apply utility indifference pricing to solve a contingent claim problem, valuing a connected pair of gas fields where the underlying process is not standard Geometric Brownian motion and the assumption of complete markets is not fulfilled. First, empirical data are often characterized by time-varying volatility and fat tails; therefore we use Gaussian GAS (Generalized AutoRegressive Score) and GARCH models, extending them to Student's t-GARCH and t-GAS. Second, an important risk (reservoir size) is not hedgeable. Thus markets are incomplete which also makes preference free pricing impossible and thus standard option pricing inapplicable. Therefore we parametrize the investor's risk preference and use utility indifference pricing techniques. We use Lease Square Monte Carlo simulations as a dimension reduction technique. Moreover, an investor often only has an approximate idea of the true probabilistic model underlying variables, making model ambiguity a relevant problem. We show empirically how model ambiguity affects project values, and importantly, how option values change as model ambiguity gets resolved in later phases of the projects considered. We show that traditional valuation approaches will consistently underestimate the value of project flexibility and in general lead to overly conservative investment decisions in the presence of time dependent stochastic structures.

Valuers’ receptiveness to the application of artificial intelligence in property valuation

Studies have shown that the level of valuation inaccuracy in Nigeria is higher than the acceptable international standard. This may be linked to the preference for traditional valuation approaches. This study investigates the readiness of Nigerian valuers to adopt the artificial intelligence (AI) property valuation techniques that have proven to be reliable and accurate in property valuation. A cross-sectional study was conducted via a web-based questionnaire survey to registered estate surveyors and valuers practicing in Nigeria. The collected data were analyzed and presented with descriptive statistics in percentiles and mean score, in addition to the chi-square analysis. The results show that more than half of the respondents are aware of the AI valuation techniques. However, the techniques are not used in practice. The low adoption of the AI techniques is attributed to professional bodies responsible for regulation of real estate practice and tertiary educational institutions in Nigeria, who were not proactive enough to promote their know-how and application. It was found that active collaboration between local professional bodies and similar international organizations on member training and development may improve the usage of the AI techniques. The study highlights the need for a paradigm shift in the Nigerian property valuation practice.

Integrating ESG into valuation models and investment decisions: the value-driver adjustment approach

ABSTRACTTrue Environmental, Social and Governance issues (ESG) integration means ESG factors are systematically fed into the valuation models and investment decisions of analysts and portfolio managers (PMs). However, most ESG approaches fail to do this. As a result, sustainable investing is much less an application success than a marketing success. Our Value-Driver Adjustment approach is different: it ties into traditional valuation approaches by linking ESG issues to value drivers via their impact on business models and competitive positions. For equities, the initial results find that the average target price impact of ESG factors is 5% overall, and 10% conditional on non-zero adjustments; dispersion is wide as target price changes ranged from −23% to +71%. The investment team has experienced a pay-off in terms of more in-depth analysis of companies, a clearer view on risk and better informed decisions.

Integrating ESG into Valuation Models and Investment Decisions: The Value Driver Adjustment Approach

True ESG integration means ESG factors are systematically fed into the valuation models and investment decisions of analysts and PMs. However, most ESG approaches fail to do this. As a result, sustainable investing is much less an application success than a marketing success. Our Value Driver Adjustment (VDA) approach is different: it ties into traditional valuation approaches by linking ESG issues to value drivers via their impact on business models and competitive positions. For equities, the initial results find that the average target price impact of ESG factors is 5% overall, and 10% conditional on non-zero adjustments; dispersion is wide as target price changes ranged from -23% to 71%. The investment team has experienced a pay-off in terms of more in-depth analysis of companies, a clearer view on risk and better informed decisions.

Comprehensive flood economic losses: review of the potential damage and implementation of an agricultural impact model

With an annual loss averaging 580 M€ between 1990 and 2014, floods are the main natural catastrophe (Nat Cat) risk for the French Nat Cat compensation scheme. As part of its role in this scheme, the Caisse Centrale de Reassurance (CCR) offers state guaranteed reinsurance programs and has been modelling the risk of flooding since 2003. This model is based on the traditional valuation approach of direct tangible costs which pairs a physical model with exposure through damage curves. CCR wishes now to widen the studied damage scope to insured and noninsured economic costs and has been collaborating with the SAF research laboratory from the Institute of Financial and Insurance Sciences (ISFA) since 2014. CCR’s model has been used to estimate the insured direct damage to residential and non-residential properties and it is now being developed to include damage to vehicles, agriculture and network infrastructures. Research is also being carried out to take into account business interruptions and indirect losses using an Input-Output model. This article describes the undergoing work on model development to estimate the damage to agriculture.

Valuation: From the Discounted Cash Flows (DCF) Approach to the Real Options Approach (ROA)

There exists an abysm between market prices and traditional valuation approaches such as Discounted Cash Flows (DCF), a fact that neither academics nor practitioners could continue ignoring. Recently, a complementary approach has taken a foothold into the valuation world. Building on the DCF approach yet going further in the sense of incorporating flexibility in management investment decisions, and taking advantage of the advances in option pricing theory, the real options approach (ROA) has become the alternative to capital budgeting and, lately, to corporate valuation. Empirical evidence shows that ROA explains actual prices better than DCF approaches and nowadays there is no question that from a theoretical point of view, ROA is a much more appealing concept than passive NPV. However, its acceptance by practitioners has been very slow due to the complexity of real options pricing.

VALUING THE “GREEN” AMENITIES IN A SPATIAL CONTEXT

ABSTRACTDespite extensive public infrastructure spending, little is known about the benefits of access to “green amenities” like parks within cities. This paper uses spatial econometric methods to estimate the value of proximity to parks using land markets in a Chinese megacity. Our research design captures mechanisms of spatial interaction effects and highlights the importance of avoiding the biases inherent in the traditional valuation approach. Our results suggest that land adjacent to parks is significantly valued by land developers and that these valuations are not distributed evenly over space. Our evidence provides support for considering locations in explaining the amenity value differentials that are grounded in the social, economic, and local contextual forces at stake.

Computer Assisted Mass Appraisal of Second-Hand Houses in China Based on Hedonic Price Model and Trading Cases

Computer Assisted Mass Appraisal (CAMA) is one of the technical foundations to the imposition of property tax at the moment in China. This paper first gives a comparative summary of traditional valuation approaches, which are the sales comparison approach, the income approach, and the cost approach. According to the characteristic of real estate in domestic and the availability of relevant basic data, it then presents an improved sales comparison approach, which combines hedonic price model with trading cases. The new approach is empirically tested by selecting second-hand house trading cases in City of Dongguan in China, and currently implemented in taxation bureaus in 11 provinces in China. The result shows that the proposed approach improves the accuracy of mass appraisal significantly compared with traditional sales comparison approach in China.

Interest Tax Shields: A Barrier Options Approach

There is a link between barrier options and tax shields of interest expense. We combine this link with a traditional valuation approach, to present practical valuation formulas for interest tax shields in three debt scenarios with risk of default: (1) constant debt, (2) delayed debt, and (3) debt refinancing. In all cases, default and refinancing are contingent on the random evolution of the income of the firm. For each scenario, we work out sensitivity analysis of the value of tax shields with respect to income, growth, systematic and business risk, risk-free interest rate, interest coverage ratio covenant, and the firm’s refinancing strategy.

Using Real Property Option Valuation Methods When Market Data is not Available

Titman (1985) famously applied optionality to derive the value of a vacant block of land then used as a car park at UCLA for which, in common with traditional property valuation approaches, a willing but not anxious buyer was assumed. However, what might the value of such a vacant block of land be in a property market downturn when willing but not anxious buyers are hesitant and there is an absence of comparable sales for reference? This paper applies concepts of optionality and indifference pricing to explore how such a vacant block of land might be considered relative to other, non-property asset classes to derive an assessment of value in the absence of an active property market.