Valuation Model Research Articles

매출변동에 따른 이익지속성과 재무지표의 가치관련성

[Purpose]The Ohoson(1995) explains the value relevance between earnings and net assets through earnings persistence. This study investigates whether sales change has a differential impact on earnings persistence and whether this has a differential effect on the value relevance of earnings. [Methodology]By analyzing data from 20,589 firm/years listed on the KOSPI and KOSDAQ, we verify whether differences in earnings persistence when sales increase or decrease and whether there is a difference in the value relevance of accounting earnings when sales increase or decrease. [Findings]First, persistence of net income is lower in times of sales decline than sales increase. Second, the decrease in earnings persistence is more evident in operating income than net income. This result seems to be because net income includes non－recurring items that are highly temporary. Finally, the value relevance of earnings was lower in a period of sales decline than in a period of sales increase. [Implications]We should consider sales change as a critical factor when we estimate earnings persistence, and also should consider the difference of earnings persistence due to sales change when we use Ohlson (1995) type firm valuation model.

Identifying gaps between research results and education

Although research results can enhance the content of education programs at various university levels, many important research results are only partly covered in major university-level textbooks. It is more difficult to transfer contributions from research results to practitioners if the former is not part of regular education programs. Here, we identify areas where researchers and educators can bridge the gap between theory and research results based on empirical studies, allowing findings to be more easily implemented by practitioners in situations that can improve their output. We take the use and accuracy of security and financial statement analysis as our prime target to examine empirical research results. Financial statement analysis and security valuation are two important applications in accounting and finance, and it is possible to measure changes in the models’ parameters and the effect these have on the outcome. We focus on five aspects of security and financial statement analysis: analysts’ use of valuation models, their estimates and accuracy, peer selection using multiples, valuation models target price accuracy, and differences in industry-specific valuation models and valuation factors. We find that most of the important research results are not referenced in major financial accounting textbooks.

A dimension reduction approach for loss valuation in credit risk modeling

This paper addresses the “curse of dimensionality” in the loss valuation of credit risk models. A dimension reduction methodology based on the Bayesian filter and smoother is proposed. This methodology is designed to achieve a fast and accurate loss valuation algorithm in credit risk modeling, but it can also be extended to valuation models of other risk types. The proposed methodology is generic, robust and can easily be implemented. Moreover, the accuracy of the proposed methodology in the estimation of expected loss and value-at-risk (VaR) is illustrated by numerical experiments. The results suggest that, compared to the currently most used Principal Component Analysis (PCA) approach, the proposed methodology provides more accurate estimation of expected loss and VaR of a loss distribution.

Pricing and mispricing of accounting fundamentals: Global evidence

This paper extends the fundamentals-based valuation model in Nichols et al. (2017) to global, developed equity markets. The model is able to explain, on average, 81% of the cross-sectional share price variation among global stocks. To be applicable among international markets, actual cash-flow streams instead of clean surplus accounting figures are used to reflect the different importance of dividends and share repurchases around the world. Firms identified as undervalued outperform overvalued firms by 0.62% p.m. after controlling for size, book-to-market, operating profitability, investment, and momentum. This premium is further not explained by lottery-like stock preferences (MAX, idiosyncratic volatility, skewness), mispricing related variables (FSCORE, ΔXFIN), or stock issuances. In support of a mispricing related explanation, we detect a significant post publication return decline in the easily exploitable long portfolio leg comprising undervalued stocks. Together with our analysis on investor sentiment, portfolio transitions, and arbitrage asymmetry, we provide evidence that deviations of the share price from the model’s estimated value indicate actual mispricing and according returns are unlikely to be a compensation for risk exposure.

Modeling the Impact of Accounting Conservatism on Information Behaviour in Equity Valuation Based on PLS-SEM

Based on residual income valuation models, this study used PLS-SEM with a formative approach to investigate the moderating effects of conservative policies on the relation between accounting information of the current and lagged periods with the equity value of companies listed on the Tehran Stock Exchange. The sample consisted of 149 companies from 2012 to 2019. The moderating effect of conditional / unconditional accounting conservatism on the relation between current/lagged accounting information and equity value is insignificant at the 10% level. In contrast, conditional conservatism has a significant relation with current/lagged accounting information, current/lagged market information, and equity values. Unconditional conservatism has significant relation with current/lagged accounting information, lagged market information, and equity values. Unconditional conservatism, however, has no significant relation with the current market information. Referring to Ohlson's vision (1995) on the expected long-term convergence between book value and market equity value, this paper's findings show that the current/lagged book value constitutes the structure of linear dynamics used in the residual income valuation model; therefore, the dynamics in residual income evolve on the dynamics of book value and market equity value.

Intention to enroll and recommend a higher education institution for STEM degrees: a brand valuation approach.

Taking as a framework the brand valuation model proposed by the National Service of Intellectual Rights of Ecuador, the purpose of this study was to evaluate whether the variables that reside in the consumer’s mind, such as brand awareness, associations, and evaluation of choice determinants, are significant in explaining the intention to enroll and recommend a higher education institution. After applying a generalized least squares regression analysis to a sample of 227 potential students of science, technology, engineering, and mathematics (STEM) degrees, it was found that the evaluation of the choice determinants is the only factor that explains the intentions. The high level of consumer involvement with the higher education service could justify this finding.

Comprehensive Review of Socio-Economic Costs and Benefits, Policy Frameworks, Market Dynamics, and Environmental Implications of Microgrid Development in the UAE

This research paper presents a comprehensive review of the literature on microgrid development in the UAE, focusing on the socio-economic costs and benefits, policy frameworks, market dynamics, and environmental implications. The analysis encompasses publications from 2011 to 2021, with a particular emphasis on the United Arab Emirates (UAE) and the Gulf Cooperation Council (GCC) countries. A total of 33 papers were identified and classified, revealing gaps in comprehensive valuation models, consideration of environmental and social governance factors, and research informing policy and investment decisions. The findings highlight the significance of microgrid technology in the UAE, its limited adoption and commercialization, and its predominant usage in remote areas and academic testbeds. The paper underscores the UAE’s vision for net-zero emissions by 2050 and the potential of microgrids in supporting its realization. Recommendations include the development of a comprehensive valuation framework to drive effective investments in microgrid technology, aligning with the UAE’s sustainable energy goals. The study contributes to the understanding of microgrid development in the UAE, offering insights into its socio-economic, policy, market, and environmental dimensions.

Model agnostic interpretable machine learning for residential property valuation

Machine learning algorithms commonly outperform the traditional hedonic models in property valuation; however, it is hard to capture the inner workings of these complex models due to their black-box nature. To address the opaqueness of ML models, this study applies model-agnostic interpretability methods at the both global and local levels for a Random Forest model which provided better prediction accuracy than Support Vector Machines and eXtreme Gradient Boosting algorithms in predicting residential property prices. The results of this study suggest that interpretable ML methods can bring transparency to opaque ML models, and visualize feature effects and interactions in property valuation models.

Artificial Intelligence in Finance: Valuations and Opportunities

This study examines the financial opportunities arising from the new Artificial Intelligence (AI) innovation. Firstly, we present the current and projected AI revenue for the upcoming decade. Secondly, we introduce a valuation model for AI stocks and ETFs, incorporating both AI fundamental and sentiment analyses. We offer two primary models for stock valuation adoption. Our analyses can serve as a benchmark framework for stock valuations and their influence on AI technology. This study holds particular significance as we witness an enthusiastic embrace of AI technology, potentially signaling the financial market's entry into an AI bubble.

Assessing the Explanatory Power of Dwelling Condition in Automated Valuation Models

This study investigates the role of dwelling-condition attributes in automated valuation models (AVMs) by utilizing detailed dwelling-condition assessment reports in Norway. A hedonic linear regression model, a gradient boosted decision tree, and a support vector machine were trained and evaluated to predict the sale price of dwellings in three urban regions. The study aims to evaluate the explanatory power of condition attributes in AVMs through a comparison of predictive performance with and without these attributes. The results indicate that the inclusion of condition attributes significantly improves the accuracy of all models across all regions. Furthermore, the models show consistent results regarding which condition attributes are important and their relationship to the price. The study finds that the condition of the bathroom has a high impact on the price, while the condition of doors, roof, and exterior extensions has a low impact. The study concludes that dwelling condition holds explanatory power in both linear and nonlinear AVMs, which can benefit researchers, practitioners, and homeowners looking to renovate. The findings highlight the importance of including detailed dwelling-condition attributes in AVMs and provide insights into the valuation of different aspects of a dwelling.

Penerapan Model Harga Opsi Black Scholes dalam Penentuan Premi Asuransi Jiwa Dwiguna Unit Link

Unit-linked life insurance is one of the most popular insurance products. This product connects the element of protection with investment assets in a product. Regarding option pricing, the Black Scholes model is one method that can be used. The advantage of this model is that it is a call option valuation model and is in great demand among financial associations because the option rate obtained from the calculation of this model is an accurate value. This research aims to determine the premium value of unit-linked endowment life insurance by applying the Black Scholes option pricing model. This research begins by selecting the stocks used and completing the information needed, including the insured's age, gender, insurance period, and life expectancy based on TMI in 2011. The return value and stock volatility can be calculated based on the stock data used. Furthermore, applying the Black Scholes option pricing model on customer data with male gender, age 25 years, a selected interest rate of 5.75%, and an insurance period of 5 years obtained a unit link insurance premium value of Rp123,058,412. The results showed that the Black Scholes option price model is determined by stock prices, interest rates, insurance periods, and volatility. When the longer period of insurance taken causes the premium value to be higher, and for different ages, with increasing age, the value of premiums paid will also increase.

Competitive Analysis of Starbucks

The main purpose of this research report is to conduct a market analysis of Starbucks Corporation. From this analysis, it can be concluded that since 2015, the market value and stock price have risen to a record level. However, due to the financial difficulties faced by the company during the epidemic of COVID-19, it would rebound in 2020. A comparison of Starbucks' market value with its top competitors in the retail coffee and snack industry shows that only McDonald's has a market value of $214.42 billion higher than Starbucks in this industry. In the previous Starbucks stock analysis, the stock price calculated using the absolute valuation model was $94, while the relative valuation model was $89.43, which was lower than the market price of $101.87, indicating that Starbucks' stock was overvalued; Therefore, it is recommended to sell stocks.

An empirical investigation of the relationship between brand value and firm value: Evidence from Turkey

AbstractThis paper aims to investigate the relationship between brand value and firm value by using a two‐step approach. In the first step, we use the financial‐based brand valuation model (FBVEM) to obtain the brand value of firms that operated in the Turkish manufacturing industry during the period between 2014 and 2018. In the second step, we examine the effect of brand value on Tobin's Q. In doing so, we use a novel GMM, with a measurement errors model, which takes into account mismeasurements of the financial variables. We try to get an accurate estimation of the link between brand value and Tobin's Q in our analysis. The obtained findings show that the effect of brand value on firm value is positive in the Turkish manufacturing sector. Our results remain stable after robustness checks. This is the first well‐controlled study that considers the endogeneity problem and consequent measurement errors in the relationship between brand value and firm value.

Revisiting Urban Immovable Property Valuation: An Appraisal of Spatial Heterogeneities in Punjab Using Big Data

This study employed big data and spatial analysis to assess property values in two cities, Lahore and Faisalabad. Traditional housing price models overlook spatial nuances, focusing solely on structural attributes. To address this, we constructed valuation models using ordinary least square regression and Fast Geographic Weighted Regression (FastGWR), implemented through Python and MPI, based on spatial variables. The models explained up to 75 percent of variance in Faisalabad and around 85 percent in Lahore. Factors like floor area, proximity of health facilities, recreational sites, and marketplaces add a premium to prices, while the nearness of educational institutions, worship places, and solid waste transfer stations or dumping sites lessen the property values in both cities. However, the proximity of industrial units and graveyards affects property values negatively in Lahore but positively in Faisalabad. This study highlights the critical significance of spatial factors in urban immovable property appraisal. As a result, it is recommended to integrate these factors into the process of policy formulation and urban planning.
 1. INTRODUCTION
 Pakistan’s real estate market emerges as a potential economic powerhouse, with a substantial portion of the nation’s wealth concentrated within its real estate assets, estimated at 60-70 percent. While the sector contributes around 2 percent to the GDP, the combined impact of housing and construction reaches nearly 9 percent. The value of Pakistan’s real estate sector, evaluated at approximately $700 billion by the Federal Board of Revenue, signifies its economic significance. Impressively, returns on investment can soar beyond 100 percent (Ouattara et al., 2018). However, this promising market is juxtaposed against a backdrop of challenges and disparities. Pakistan’s population, surpassing 225 million, expands annually at a 2.4 percent rate, characterised by an average household size of 6.5 (Pakistan Bureau of Statistics, 2019). With a yearly housing requirement of 700,000 units, merely half of this demand is met, leading to an alarming gap of roughly 10 million units (Rizvi, 2018). This housing shortage necessitates innovative strategies, particularly in the realm of low-cost housing schemes. The intricacies of property valuation further complicate the real estate landscape. Government land acquisitions relying on DC valuation tables often incite public protests due to perceived undervaluation (Sabir et al., 2017). The importance of precise valuation for equitable compensation is underscored by research (Malaitham et al., 2020). Notably, property valuation is not just pivotal for buyers and sellers; it resonates with stakeholders such as investors, banks, agents, and insurers. The geographical location holds substantial influence over a property’s price, further emphasising the necessity for accurate valuation (Mankad, 2021).
 In dynamically growing cities, the accurate prediction of urban land use evolution plays a pivotal role in fostering sustainable urban planning (Liang et al., 2018) such as Lahore and Faisalabad in Pakistan. Notably, vast untapped potential resides within public properties, including Government Officers Residences (GORs) and railway lands, representing latent avenues for wealth creation. Leveraging these assets effectively can substantially contribute to economic prosperity. The implications of this study extend to policymakers, offering insights to navigate the intricate domains of housing and urban development. A robust housing market stands as a linchpin of a resilient economy; however, Pakistan’s housing sector faces an intricate array of challenges. Urbanisation and migration galvanise demand within urban centers, an issue compounded by insufficient supply catalysed by diverse factors. Shortcomings in land usage, planning, and property rights impede progress, while inadequate revenue collection from property taxes curtails infrastructure financing. The labyrinthine regulations further stall land development, exacerbating housing availability discrepancies, particularly pronounced in megacities like Karachi and Lahore. Notably, housing construction trails behind the meteoric pace of population expansion. Skyrocketing market conditions render housing unattainable for many, channeling them towards informal settlements (Dowall & Ellis, 2009; Haque, 2015; Wani et al., 2020; Yuen & Choi, 2012). The challenges are particularly pronounced within Punjab’s housing markets, accentuated in cities like Lahore and Faisalabad, grappling with deficits in affordable housing (Malik et al., 2020; Wajahat, 2012). A glaring obstacle lies in the hands of speculative investors who control 75 percent of residential plots, perpetuating this complex issue (Zaman & Baloch, 2011). This practice thrives on secure real estate investments and tax loopholes, compounding the predicament. Although plot prices surge significantly (Gul et al., 2018), official valuations lag behind, generating volatility in Pakistan’s property prices. The repercussions of such fluctuations extend to the public, shouldering the burden of investor gains. Despite intermittent housing policies, the issue remains inadequately addressed, emphasising the urgency of public sector interventions to stabilise spiraling prices (Ahmed et al., 2021).

Revisiting Urban Immovable Property Valuation: An Appraisal of Spatial Heterogeneities in Punjab Using Big Data

This study employed big data and spatial analysis to assess property values in two cities, Lahore and Faisalabad. Traditional housing price models overlook spatial nuances, focusing solely on structural attributes. To address this, we constructed valuation models using ordinary least square regression and Fast Geographic Weighted Regression (FastGWR), implemented through Python and MPI, based on spatial variables. The models explained up to 75 percent of variance in Faisalabad and around 85 percent in Lahore. Factors like floor area, proximity of health facilities, recreational sites, and marketplaces add a premium to prices, while the nearness of educational institutions, worship places, and solid waste transfer stations or dumping sites lessen the property values in both cities. However, the proximity of industrial units and graveyards affects property values negatively in Lahore but positively in Faisalabad. This study highlights the critical significance of spatial factors in urban immovable property appraisal. As a result, it is recommended to integrate these factors into the process of policy formulation and urban planning.
 1. INTRODUCTION
 Pakistan’s real estate market emerges as a potential economic powerhouse, with a substantial portion of the nation’s wealth concentrated within its real estate assets, estimated at 60-70 percent. While the sector contributes around 2 percent to the GDP, the combined impact of housing and construction reaches nearly 9 percent. The value of Pakistan’s real estate sector, evaluated at approximately $700 billion by the Federal Board of Revenue, signifies its economic significance. Impressively, returns on investment can soar beyond 100 percent (Ouattara et al., 2018). However, this promising market is juxtaposed against a backdrop of challenges and disparities. Pakistan’s population, surpassing 225 million, expands annually at a 2.4 percent rate, characterised by an average household size of 6.5 (Pakistan Bureau of Statistics, 2019). With a yearly housing requirement of 700,000 units, merely half of this demand is met, leading to an alarming gap of roughly 10 million units (Rizvi, 2018). This housing shortage necessitates innovative strategies, particularly in the realm of low-cost housing schemes. The intricacies of property valuation further complicate the real estate landscape. Government land acquisitions relying on DC valuation tables often incite public protests due to perceived undervaluation (Sabir et al., 2017). The importance of precise valuation for equitable compensation is underscored by research (Malaitham et al., 2020). Notably, property valuation is not just pivotal for buyers and sellers; it resonates with stakeholders such as investors, banks, agents, and insurers. The geographical location holds substantial influence over a property’s price, further emphasising the necessity for accurate valuation (Mankad, 2021).
 In dynamically growing cities, the accurate prediction of urban land use evolution plays a pivotal role in fostering sustainable urban planning (Liang et al., 2018) such as Lahore and Faisalabad in Pakistan. Notably, vast untapped potential resides within public properties, including Government Officers Residences (GORs) and railway lands, representing latent avenues for wealth creation. Leveraging these assets effectively can substantially contribute to economic prosperity. The implications of this study extend to policymakers, offering insights to navigate the intricate domains of housing and urban development. A robust housing market stands as a linchpin of a resilient economy; however, Pakistan’s housing sector faces an intricate array of challenges. Urbanisation and migration galvanise demand within urban centers, an issue compounded by insufficient supply catalysed by diverse factors. Shortcomings in land usage, planning, and property rights impede progress, while inadequate revenue collection from property taxes curtails infrastructure financing. The labyrinthine regulations further stall land development, exacerbating housing availability discrepancies, particularly pronounced in megacities like Karachi and Lahore. Notably, housing construction trails behind the meteoric pace of population expansion. Skyrocketing market conditions render housing unattainable for many, channeling them towards informal settlements (Dowall & Ellis, 2009; Haque, 2015; Wani et al., 2020; Yuen & Choi, 2012). The challenges are particularly pronounced within Punjab’s housing markets, accentuated in cities like Lahore and Faisalabad, grappling with deficits in affordable housing (Malik et al., 2020; Wajahat, 2012). A glaring obstacle lies in the hands of speculative investors who control 75 percent of residential plots, perpetuating this complex issue (Zaman & Baloch, 2011). This practice thrives on secure real estate investments and tax loopholes, compounding the predicament. Although plot prices surge significantly (Gul et al., 2018), official valuations lag behind, generating volatility in Pakistan’s property prices. The repercussions of such fluctuations extend to the public, shouldering the burden of investor gains. Despite intermittent housing policies, the issue remains inadequately addressed, emphasising the urgency of public sector interventions to stabilise spiraling prices (Ahmed et al., 2021).

Trimming the Retail: The investment outlook for CVS’s growth strategy

CVS Health Corporation owns the retail pharmacy chain and also owns CVS Caremark, the pharmacy benefits manager, and the Aetna health insurance provider (Kolakowski, 2023). Recent acquisitions in 2022 and 2023 include Oak Street Health, Inc., and Signify Health. CVS’s proactive growth strategy aims to acquire health care firms across various sectors of health care, yet the management is not averse to divesting the firm of less profitable subsidiaries. In November 2021 the firm announced the closing of 300 stores per year through 2024. A decline in stock price of CVS would suggest analyzing whether the company is still a good long-term investment. A deeper study may be warranted, but seven methods should suffice to either reject CVS immediately or accept CVS for further consideration. The analysis includes the following: The price-to-earnings ratio or P/E multiple approach for validating stock price. Evaluating expected return of the stock with the capital asset pricing model (CAPM). The corporate valuation model using free cash flows for stock-price valuation. A review of the company’s dividend history. Comparison of the company’s capital structure with its peers. Evaluating the company’s historical stock prices. Review of the recent financial statements and the five categories of financial ratios to determine the overall health of the firm. As a company with a large retail business unit, CVS stock would be considered a moderately conservative investment. A decision on long-term investing in CVS stock would consider the risk and potential returns. Subject to further scrutiny, this study accepts CVS as a potential investment choice. Although the acceptance is based on analysis, the author makes no guarantee of future results. This paper is the original work of the author and is not previously published.

Application of DCF Model in Enterprise Valuation

The home appliances industry is an important manufacturing industry that reflects the consumption level of Chinese residents. Midea Group is the leading enterprise in the household appliances industry and one of the enterprises with high brand value in China. For Midea Group in the home appliance industry, this paper will apply the DCF model for enterprise valuation. This paper mainly uses the financial information of Midea Group and the discounted cash flow model for enterprise valuation. Then, the advantages and disadvantages of the DCF valuation model are analyzed through practical cases, and the overall valuation process is summarized. The company value of Media that valued by the DCF model is 384,922.89 million RMB. The analysis results show that the DCF model can better reflect the status quo of enterprise value, but in the process of DCF valuation model, it is not easy to predict the accurate amount of future cash flow. It also has limitations in industry and product selection, and its estimation of the risk rate is not accurate enough.

Analysis of Huaxing Yuanchuang M&A Based on PEG and EVA Valuation Model

In the process of expanding operations, enterprises often encounter bottlenecks in terms of capital, technology, management, and other aspects. In order to tackle these problems, enterprises often choose to issue bonds, go public, mergers and acquisitions, etc. to expand their production and business scope, update management models, and improve their competitiveness. Due to the short introduction of the merger and acquisition mechanism, the analysis and research of mergers and acquisitions by various enterprises are relatively shallow, and the success rate of mergers and acquisitions by Chinese enterprises is low. This study conducts a research and analysis on the first merger and acquisition case on the Science and Technology Innovation Board, i.e., the case of Huaxing Yuanchuang's acquisition of Olyto. Based on PEG and EVA valuation models, it analyzes the motivation and results of Huaxing Yuanchuang's acquisition of Olyto's business behavior. By valuing and comparing the stock price of Huaxing Yuanchuang before and after the merger and acquisition behavior, the conclusion that the merger and acquisition behavior is not successful is drawn. Research has found that under the PEG valuation model, the stock price of Huaxingyuan Chuang after the merger is slightly overvalued, while under the EVA valuation model, the stock price is greatly underestimated.

Research on Theory and Methods of Corporate Valuation

Corporate evaluation has been a long-history research field, mostly in finance. There are traditional methods such as DCF, CAPM and APT, which were the most popular valuation method being used in 20th century. Nevertheless, more neoclassical theories have been brought up recently, from the perspectives of investment, pricing or other qualitative areas. Besides, the specific times in post-pandemic environment provide valuable research samples of how company keep survived during the period of declination in economic. Based on the previous traditional research as well as neoclassical and recent studies on business new valuation model, this article gives a more comprehensive overview and appraisal about corporate valuation theories, ranging from absolute to relative valuation models, and finally to recent neoclassical models such as EVA valuation, along with other elements that need to concern when processing corporate valuation, which might contribute to the practical use of corporation acquisition and other investors decisions in both capital and money market.

A reduced-form model for lease contract valuation with embedded options

A reduced-form model for lease contract valuation with embedded options