Valuation Model Research Articles

Valuing options to renew at future market value: the case of commercial property leases

In this study, we develop and empirically test a valuation model for a commonly encountered option in office leases: a tenant’s option to renew at future market rent (a fair market value) with lease termination as the maturity date. The model integrates decision analysis with real options analysis and market risk with private risks. “Option value” is defined as the private value of the option to either party pre-contract, while “option price” assumes a fair agreement between transacting parties and can be positive (rental premium paid) or negative (rental discount offered). Without manifest expectations, an analysis of a sample of office leases supports the model’s logic with price estimates in a practical range. The tenants’ option price/value is shown to have a negative relationship with the original/renewal lease term; conversely, the landlords’ option value is positively related to the original/renewal term. Comparative analyses show that transaction costs have a positive effect on tenants’ option value and on prices, while vacancy costs and the vacancy period are both positively related to the landlords’ option value and negatively related to price. Market rent is found to have a negative relationship with option price. Overall, this study provides a theoretical analysis and empirical tests of the value of a real option that allows option holders to renew/extend their contracts at a fair market value.

Inflation-related tax distortions in business valuation models: A clarification

The current corporate income tax (CIT) expense occupies just one line item on the statement of profit or loss and other comprehensive income. However, it is a unique line item following tax rules and not financial reporting rules. The difference between these rules is that it reflects the effective tax rate (ETR), which can differ from the statutory tax rate (STR). With inflation, this ETR-STR difference can be more significant due to the contribution of tax distortions. In this study, we expand on the standard formulas for the ETR by analyzing the effects of inflation-related tax distortions when computed under the following four cases: (i) Historical-cost-based accounting under a nominal tax basis, (ii) Fair-value-based accounting under a nominal tax basis, (iii) Historical-cost-based accounting under a real tax basis, and (iv) Fair-value-based accounting under a real tax basis. Further, we suggest a modified model for business valuation considering these tax distortions and provide a general formula to independently calculate the value of inflation-related tax distortions.

Organization of effective management of the stock market on the basis of researching the processes of formation of the value of shares of the issuer companies

The global economic crisis and the socio-economic consequences of the COVID-19 pandemic have a significant impact on the increase in volatility and risks of manipulation of stock asset quotes. The subject of the study is the organization of management of the investment fund process, taking into account non-market mechanisms for manipulating the value of shares of issuing companies. The purpose of the article is to improve the efficiency of managing the stock process based on the stock market model and procedures for fuzzy valuation of the value of shares of issuing companies within this model. The research methodology is based on the application of methods for analyzing economic phenomena and processes, a systematic approach to studying the development of issuing companies and stock markets. Modeling of fund processes is based on fuzzy logic theory and efficiency theory. The principles of stock market idealization and the principles of stock market management in a manipulated information environment are formulated. A model of the stock market is presented, which includes: an ideal model of the stock market, a model of fundamental disturbing factors and a model of stock market manipulation. Within the framework of the stock market model, an economic and mathematical model for estimating the value of shares of issuing companies has been developed, in which the uncertainty of parameters is described by fuzzy numbers. The novelty of the research lies in the formulated concept of factor psychodynamics (including a list of factors, functions of factors, the strength of factors and inertia of factors), which serves as the basis for the stock market model; as well as in the developed methodology for fuzzy valuation of shares of issuing companies. Participants of the stock market, potential investors, owners and acquirers of companies on the basis of the presented model of the stock market have the opportunity to obtain additional information about ongoing stock processes. Fuzzy procedures for estimating the value of shares of issuer companies make it possible to calculate the value of their shares in accordance with various forecast scenarios for the development of companies.

THE MODEL OF ASSESSMENT OF GOODS EXPORTS OF UKRAINE TO THE WORLD INTEGRATION ASSOCIATIONS

Foreign trade is an important factor of economic growth and development of open economies. At the same time, the analysis of the state of foreign trade operations is becoming methodologically more complex due to the increase in the number of indicators used and the appearance of new ones. They allow not only to examine the effectiveness of the state trade policy, the set of goods and trade partners, but also to get an idea of the structure of the economy, the level of its development and competitiveness, as well as to assess the quality of the export and import baskets from the point of view of economic growth prospects. Therefore, it is advisable to use models of commodity export valuation, which determines the relevance of the chosen topic. The subject of the study is the methods and models of commodity export evaluation. The purpose of the article is the formation of a model for the evaluation of Ukraine's commodity exports to the integration associations of the world and its approval. Methodology. The theoretical and methodological basis of the conducted research is the dialectical method of cognition, the principles of system analysis and synthesis, statistical processing of information. The methods of structural dynamics were used for the analysis of statistical indicators of commodity exports for 2016-2020; the method of constant market share – for the evaluation of changes in commodity exports of Ukraine for the period under consideration; the method of scientific abstraction is used for the generalization of the obtained results and the formation of conclusions; the graphic method – for the visual presentation of the obtained research results. Results. The article proposes a model for assessing Ukraine's commodity exports to the world integration associations, the main component of which is the constant market share method (CMS analysis). This model is easy to use and allows a qualitative assessment of changes in Ukraine's commodity exports. Approval of the model and assessment of changes in commodity exports of Ukraine was carried out on the international statistical database UNCTADstat for 2016-2020. The data are aggregated into groups according to the Standard International Trade Classification (SITC). The following trading partners have been selected for the CMS analysis: EU-27, ASEAN+3, CIS and REST OF THE WORLD. The obtained results make it possible to assess the state of Ukraine's commodity exports and the level of its competitiveness in foreign markets. Practical implications. The practical implications are related to the possibility of using the proposed model for the evaluation of commodity exports, using various options for the classification of goods and integration associations – partners of the exporting country. Value / originality. The originality lies in the development of a model for the assessment of Ukraine's commodity exports to the world integration associations based on the Constant Market Share (CMS) method, which allows to determine to what extent exports change with the growth of the competitiveness of the goods of the exporting country.

Stock Valuation of Indonesia Property Company using Blended Valuation Method (Case Study of PT. Pakuwon Jati, Tbk)

After Indonesia got hit by a pandemic in 2020, Indonesia’s economy managed to recover in 2021. However, the property industry in Indonesia was experiencing a negative impact due to increasing interest rates. The increasing interest rates means that people will get higher costs if they want to borrow money to buy property. Moreover, people became more hesitant to buy or invest in property because government-borne value added tax incentives (PPN DTP) ended in September 2022. However, PT Pakuwon Jati Tbk. (PWON) seems to be less impacted because PWON have recurring income and non-recurring income as their source of income. Recurring income came from space rental, service apartment, hotel, etc. Non-recurring income came from sale of condominiums and offices and sale of land and buildings. The less restriction on people's mobility to do activities outside their house and the growth of GDP caused by household consumption indicates that PWON’s recurring income will be less impacted negatively by the increasing inflation rate. The possibility of this situation might affect the company’s stock performance since it would result in lower profitability for the company. To help investors to decide in this situation, the intrinsic value of the company stock is required. Therefore, it is important to find the intrinsic value. The intrinsic value of PWON was derived by using a blended valuation method. The author gave weight on the various valuation models that were used. From the method, the intrinsic value of PWON was IDR 440 per share.

Assessment and valuation of technologies, development and application of Valorativo software

PurposeAlthough Public Research Institutions (PRIs) are large technology producers, they lack automated information tools that follow technical and scientific criteria for assessing and valuing patents. The assessment and valuation processes are stages of technology transfer (TT) that make it possible to obtain productive arrangements and guide the efforts of those involved in the development, maintenance and negotiation. This study aims to analyze the hybrid model of assessment and valuation of technologies by Soares (2018), applying the ‘Valorativo' software. In addition to patent value and indicator scores, the methods allow an understanding of the technology portfolio and its management.Design/methodology/approachThis research is quali-quantitative, following an approach of applied nature and descriptive objectives. The research has bibliographical, documental and case study features based on the software development methodologies described in the study and the theoretical framework.FindingsThe Valorativo software assisted in the analysis of ten patents on PRIs. With the data collection and patent analysis, PAT1 scored highest among engineering patents, PAT3 scored highest among pharmaceutical patents and PAT10 scored highest among biotechnology patents. Five of the assessed patents resulted in a surplus of net present value (NPV), final net present value (NPVF) and royalties; revenue expectations outpaced investments.Practical implicationsThe authors based the developed software on Soares’s (2018) methodology, with additional calculations and graphs. The Web software and the spreadsheet with Visual Basic for Application (VBA) were developed to deal with the patents assessment and valuation, helping in the analysis of their Legal Value, Technological Value and Market Conditions in the assessment process, and the Discounted Cash Flow and NPV in the valuation process.Originality/valueThe software helps with patent analysis and can generate indicators for traders, technology holders and researchers. Thus, it was necessary to understand and develop a theoretical-applied framework to outline and replicate the methodology clearly and easily.

Data Valuation Model for Estimating Collateral Loans in Corporate Financial Transaction

The importance of data assets as intangible corporate assets is being emphasized as more business activities based on digital technology are being carried out. This study proposes the development of a data valuation model that can enable companies to use data assets as collateral for loans in financial transactions. To this end, a model was designed with a focus on the cost approach, which is less likely to involve arbitrariness and error among other valuation model approaches. Furthermore, a model simulation was conducted after securing transaction data of a Korean secondhand marketplace provider. Among the total costs of this marketplace provider, the cost of using data reflecting the ratio of data activities was derived, focusing on financial statements and tangible and intangible assets for the last five years. The data asset acquisition costs were derived, and the data replacement costs were calculated by reflecting the past price and wage growth rates. The results revealed that simulation companies could use a total of KRW 26.8 billion worth of data as collateral for a loan. Accordingly, the data valuation model developed in this study will contribute to reinforcing the value of corporate data assets and proposing a new means of corporate financing.

DESIGNING A TECHNOLOGY VALUATION MODEL IN IRANIAN STARTUPS

Technology valuation is needed by companies in today's knowledge-based economy. The intangible nature of technology, influence of environmental factors and conditions on it, have made calculating its value complicated. At present, a large part of the country's economic activities in the technological ecosystem is carried out by companies and startups, whose growth and development are possible with the influx of capital. Therefore, the aim of the upcoming research was to identify dimensions and explain the technology valuation model in Iranian startups. The approach of the research is qualitative, and in the research process, the Grounded Theory has been used. The 10 participants including active experts, policymakers, consultants, and CEOs in Iran's startup ecosystem, were selected by using the purposeful sampling method and analyzed by using the content analysis method. Participants identified factors such as lack of technology valuation requirements, bubble of startups claiming technology, innovation as causal factors, technology brokers and conflict of interests as interfering factors in the strategies of the desired phenomenon, development and promotion of technology valuation discourse, transformation of existing knowledge in the field of technology to valuable knowledge, leadership and idea management and localization of technology valuation as solution-oriented strategies, benefits of calculating the real value of technology and valuation process itself regardless of the result were expressed as the consequences of expanding the technology valuation model in Iranian startups. In this way, the dimensions of the desired model were extracted and explained.

The Empirical Explanatory Power of CAPM and the Fama and French Three-Five Factor Models in the Moroccan Stock Exchange

This study empirically tests and compares the performances of three famous financial asset valuation models in the Moroccan stock exchange: CAPM, the Fama and French three-factor model, and the Fama and French five-factor model. Our sample considers monthly data covering the sample period of July 2002 to June 2020. The main findings reveal that the GRS test typically rejects each of the examined model. On the basis of our analysis, we find that the value effect is more pronounced than the size effect. However, profitability and investment effects are almost absent. Regarding the factor spanning tests, the results show that the value factor was not redundant. Beyond this, the size and investment factors are the redundant factors. In Morocco, the market factor is the most powerful factor, perhaps assisted by value and profitability factors. Although the CAPM performs poorly in capturing the variation in Moroccan returns, the market factor continues to play an important role, even after adding other factors. Overall, all the tested models were improved slightly, but leave part of the variation in Moroccan stock returns unexplained.

Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles

The median and median target estimates in sign-restricted SVARs are driven by a highly informative prior for the set-identified structural parameters. This paper proposes an approach for point elicitation by minimizing the evidence against the null hypothesis of independence with respect to the orthogonalized residuals implied by the identified set. Finite sample properties of the estimator are studied in a Monte Carlo experiment. As an empirical illustration, we analyze monetary policy effects within the rational bubble model of equity valuation (Galí, 2014). The detected monetary policy shocks lead to distinct response profiles of the fundamental and bubble components of asset prices.

Value Relevance of Environmental Sustainability Information Disclosure

To empirically investigate the value relevance of environmental sustainability information disclosure of listed oil and gas firms in Nigeria, this study made use of Ohlson 1995 Valuation Model and a fifteen (15) year time period beginning from year 2006 to year 2020. Further, the study applied carbon emission information disclosure data as the non-financial information and hypothesized that carbon emission information disclosure is value irrelevant in Nigeria. In this study, ex-post facto and descriptive research design based on a panel data set secondarily sourced from annual financial reports of eight (8) listed oil and gas firms in Nigeria was employed. Robust least square regression analysis technique was employed to test the formulated hypotheses. Results obtained from the descriptive statistics reflects a poor carbon emission reporting situation in Nigeria. The result reveals that on average about 2% of the sampled firms disclosed information relating to carbon emission during the period under study. Specifically, the notion that investors perceive the control of carbon emission as severe cost rather than profit was established. This is due to the outcome from the regression result which suggest that stock market investors reactions towards carbon emission disclosure of oil and gas firms in Nigeria is negative. However, this study recommends that to relieve such negative consequences in the capital market, managers of oil and gas firms in Nigeria must take appropriate action to communicate their commitments and efforts genuinely and adequately around carbon reduction to investors. This study contributes to the growing field of environmental sustainability accounting, particularly from a market that is underdeveloped like Nigeria, by offering empirical evidence relating to the relevant value of carbon emission reporting with practical financial implications that will be most helpful to investors.

Investment in wind-based hydrogen production under economic and physical uncertainties

This paper evaluates the economic viability of a combined wind-based green-hydrogen facility from an investor’s viewpoint. The paper introduces a theoretical model and demonstrates it by example. The valuation model assumes that both the spot price of electricity and wind capacity factor evolve stochastically over time; these state variables can in principle be correlated. Besides, it explicitly considers the possibility to use curtailed wind energy for producing hydrogen. The model derives the investment project’s net present value (NPV) as a function of hydrogen price and conversion capacity. Thus, the NPV is computed for a given price and a range of capacities. The one that leads to the maximum NPV is the ‘optimal’ capacity (for the given price). Next, the authors estimate the parameters underlying the two stochastic processes from Spanish hourly data. These numerical estimates allow simulate hourly paths of both variables over the facility’s expected useful lifetime (30 years). According to the results, green hydrogen production starts becoming economically viable above 3 €/kg. Besides, it takes a hydrogen price of 4.7 €/kg to reach an optimal conversion capacity half the capacity of the wind park. The authors develop sensitivity analyses with respect to wind capacity factor, curtailment rate, and discount rate.

Relevansi Nilai Informasi Akuntansi Di Indonesia Berdasar Simple Accounting-Based Fundamental Analysis

Decreasing the value relevance of accounting information issues cannot be separated from complexity of accounting standards and their implementation. This phenomenon is our motivation to examine whether the valuation model on the prospects of companies that prioritize the parsimony principle by using accounting information also indicates a decrease in the relevance of accounting information in Indonesia. We examined the f-score indicator which is referred to as a simple accounting-based fundamental analysis. This study observed all financial statements of issuers in Indonesia from 2006 to 2019 and their share prices in the secondary market during year t+1.We used multiple regression to estimate the value of r-square in each year of observation. This study could not find any indication of a decrease in the value relevance of accounting information during the observation period based on the r-square which is estimated by the f-score indicator. This finding can be a part of an empirical study that is not only related to value relevance, but also to the topic of accounting information readability.

Machine learning approach to residential valuation: a convolutional neural network model for geographic variation

Geographic location and neighbourhood attributes are major contributors to residential property values. Automated valuation models (AVM) often use hedonic pricing with location and neighbourhood attributes in the form of numeric and categorical variables. This paper proposed a novel approach to automated property valuation using a machine learning model with a convolutional neural network (CNN), fully connected neural network layers with numeric and categorical variables. In this study we compare the results of a fused model, which treat geographical data as an input with the performance of the baseline neural network model with only numerically or categorically represented data. Furthermore, the residential valuation by the proposed fused model was tested with actual sold price data in Greater Sydney, Australia. The study found that the fused model produced valuations with a significantly lower mean absolute percentage error (MAPE) (8.71%) than the MAPE of the baseline model (11.59%). The results show that the fused model with CNN significantly improves the accuracy for residential valuation, reducing spatial information loss by data manipulation and distance calibration.

Valuation of Compensation for Land Use Restriction

The Spatial Planning Act of Taiwan was implemented on May 1, 2016. To protect the legal rights of landholders, the Ministry of the Interior stipulated Measures for Compensating Loss Incurred during The Implementation of Spatial Planning in accordance with Article 32, Paragraph 3 of the Spatial Planning Act. Compensation is available for relocation or for alteration, where alteration refers to compensation for losses incurred when constructible land is made non-constructible by a special municipality or county (city) and the land cannot be built on. It therefore includes compensation for the value of the right to develop the land.
 Real estate is immobile and inflexible, which reduces uncertainty in its use. Studies have generally used net present value to analyze investment in and development of land. The conventional passive net present value method is employed to appraise land value, usually assuming that the investment plan must be developed immediately and is reversible. This is contrary to the characteristics of real estate investment and development, where ignoring the opportunities and flexibility generated by asset value uncertainty can readily lead to misappraisal of the value of an investment plan. The inclusion of future uncertainty in the valuation is the main difference between the option valuation model and the conventional valuation model.
 Because correctly calculating the compensation for alteration is crucial to whether landowners successfully obtain appropriate compensation when applying for compensation, this study proposed a real option valuation model to appraise compensation for the alteration of privately-owned constructible land. In the model, landowners possessed complete ownership of and decision-making power regarding the land before compensation. Subsequently, the study adopted real options theories to assist private landowners in determining real options at the decision-making stage. The study also took the case of constructible land in Taichung City that was made non-constructible in accordance with the spatial planning of Taichung City as an example to apply the model.

Do sustainability disclosure mechanisms reduce market myopia? Evidence from European sustainability companies

Market myopia is a behavioural bias that causes investors to overvalue short-term earnings and undervalue long-term profits. This anomaly should not be compatible with sustainability disclosure mechanisms, the set of tools which firms use for reporting on their sustainable practices, and which contribute towards long-term performance improvements. Our aim is to study whether market myopia, as a symptom of market inefficiency, decreases with the implementation of sustainability disclosure mechanisms. We test for the presence of market myopia in a sample of firms listed on the S&P Europe 350 Index. For this purpose, we propose to use an adaptation of the valuation model for residual income under linear information dynamics developed by Felthan and Ohlson. Using the rating provided by RobecoSAM Sustainability Yearbook, we find market myopia to be less prevalent in companies classified as high sustainability reporters. An association is also found between persistent enforcement of sustainability disclosure mechanisms and a reduction of the market myopia effect.

Stock price valuation analysis of the digital technology industry based on the HP-ARIMA method - with 18 listed companies of different volume sizes in its 3 segments as an example

The world securities market has formed a more complete system since its origin in the 17th century, with a considerable number of small and medium-sized investors and institutional investors, and proposing innovative new methods for securities valuation models can assist investors in making more accurate investment decisions. This paper proposes for the first time to use an interdisciplinary analysis method, ARIMA + HP filter analysis, to analyze the valuation of the securities market, by taking the opening prices of individual stocks in digital technology industry segments: blockchain, artificial intelligence, and Beidou navigation as examples for valuation analysis, firstly, the initial data of the opening prices of individual stocks from 2019-2021 are analyzed by HP filter analysis, and secondly, the data are analyzed while doing Tobit model test. By analyzing the long-term trend of the digital technology industry after noise reduction, its corresponding valuation forecast and value judgment results show that the head effect of the digital technology industry is more significant, and the opening price volatility shows a U-shaped relationship with company size and profitability, and the opening price volatility of individual stocks is less, while the shorter the company's establishment time, the greater the stock price volatility. While the past literature focused on the traditional valuation of financial conditions and historical data analysis of a single variable, this paper analyzes the data of individual stocks in the digital technology industry through an interdisciplinary analysis method, which allows for a more comprehensive use of historical data and prediction of possible stochastic fluctuations, providing a more reliable valuation method for securities investors and opening up new ideas for research related to the field of valuation analysis.

Project Financial Analysis Within a Firm

The implementation of capital project approval techniques within a firm requires a disciplined approach with uniform and comprehensive evaluation standards. In addition, organizational guidelines need to ensure timely consolidation across projects within each business unit and corporate level for submission and approval. In this article, we provide insights into implementation issues in capital project evaluations within a firm. We discuss project evaluation and authorization guidelines, and economic and financial valuation models that include the financial benefits from the merits of the project, incremental cash flow analysis, and types of project evaluations. Next, we discuss the data requirements and collection process within a firm and the standardized documentation for submission to obtain corporate approval. We illustrate our approach with a detailed numerical example. This approach simplifies the evaluation process and facilitates sensitivity analyses, which enables the consolidation of projects both at the business unit and corporate levels. We hope that future research in financial analysis will further enhance this capital budgeting evaluation process and thereby guide both students and practitioners to better understand and appreciate the evaluation process.

Determining the optimal land valuation model: A case study of Hanoi, Vietnam

In Vietnam, the central Government issues land price brackets, and people's committees promulgate land price tables for five years. The published land prices are always lower than transaction prices in the market, resulting in many problems such as loss of state budget, inequality in charge of compensation, and land clearance for citizens. The study aims to uncover factors that influence land prices to build optimal land valuation models for land valuation. Using the Bayesian Model Average, the findings show that several factors strongly influence urban residential land prices in Hanoi's outskirts (Quoc Oai district), such as road type, hospitals, and industrial areas. Other factors as green space and schools, are insignificant in land purchases. The finding also indicated that the optimal model in this study showed a slight difference in valuation prices from the actual market prices. The study also determined that the mass land valuation model would be promising in Vietnam and dual-price countries.

Valuation of Coca-Cola's share price at the end of 2021 based on the SWOT analysis method of analyzing multiples valuation model

Appraising the enterprise value of a company in the soft drinks industry in terms of its earnings, fixed assets, intangible assets, goodwill, human resources, etc. has always been a complex issue. Given the convenience of the valuation method, analysts often choose to avoid complex valuation models by opting for multiple valuation models. When using the multiple valuation method, it becomes a question of how to use the correct multipliers and how to target the analysis to the soft drinks industry. In this article, PepsiCo, Monster Beverage Corp, and Nestlé SA were chosen as comparable companies and a multiple valuation model was used to derive three different Coca-Cola share prices at that time based on financial data at the end of 2021 using P/E, EV/EBITDA, and EV/Sales as multipliers respectively. It was found that the median could not be used as a multiplier for calculation purposes and that EV/Sales performed much worse than the other two multiples. In response to these two findings, the article makes several recommendations for valuation practices in the soft drinks industry and for the operations of soft drinks companies.