Developing the business valuation technique for Mergers & Acquisitions

2021 ◽  
Vol 14 (3) ◽  
pp. 263-280
Author(s):  
Nikolai S. SEMENOV ◽  
Vitalii V. KLEVTSOV
Keyword(s):  
Synergistic Effect ◽  
Business Strategy ◽  
Prediction Models ◽  
Data Representation ◽  
Business Valuation ◽  
Enterprise Value ◽  
The Monte Carlo Method ◽  
Zero Correlation ◽  
Analysis And Synthesis ◽  
Valuation Technique

Subject. According to empirical data of consulting firms, the synergistic effect does not arise every time, since about 70 percent of M&A deals happen to be unsuccessful, destroying the enterprise value. Objectives. We analyze whether it is possible to make M&A more effective, and develop the business valuation technique for M&A on the basis of the real options method. Methods. The study involves methods of analysis and synthesis, generalization, induction and deduction, methods of systems analysis, statistical methods, chart and graphical techniques for statistical data representation. Results. We analyzed and determined the most applicable method for options premium valuation – the Monte-Carlo method, since it appraises non-listed companies and facilitates computations. As part of equity valuation, we suggest substituting the rating to the assessment of risk components by analyzing corporate performance indicators. Having analyzed potential deals, we proves the zero correlation between the options premium and the maximum premium, thus making a game formula of the synergistic effect. Conclusions and Relevance. The correlation between shareholders’ premium and options premium is identical to the correlation of the maximum premium and options premium. That is, the correlation does not virtually exist. As a result, we made the synergistic effect formula. The conclusions and recommendations herein can be used by business leaders to financially justify non-organic business growth mechanisms, develop the business strategy subsequently. Appraisers may also rely upon the findings to improve the quality of business value prediction models as part of M&A deals.

Chip formation and the interaction of mesoscopic geometric features of cutter

2021 ◽  
pp. 095440542110284
Author(s):  
Xin Tong ◽  
Yanxiang Ren ◽  
Jianing Shen ◽  
Song Yu
Keyword(s):  
Synergistic Effect ◽  
Prediction Models ◽  
Cutting Tools ◽  
Chip Morphology ◽  
Orthogonal Test ◽  
Cutting Performance ◽  
Geometric Features ◽  
High Quality ◽  
Milling Tool ◽  
Interaction Test

Most of the researches on the properties of micro-textured tools are based on an orthogonal test, while the interaction between micro-textured parameters is ignored. Therefore, this thesis is based on an interaction test to study the cutting performance of cutting tools. According to the chip morphology obtained from the interactive test, the micro texture diameter of 60 μm is obtained when the cutting is stable. It was also found that the synergistic effect of multiple mesoscopic geometric features had a significant influence on cutting performance. By analysis, we found the optimized parameters for the milling tool were D = 60 μm, l = 100 μm, l1 = 150 μm, r = 60 μm. Furthermore, prediction models of the cutting performance were established by univariate linear regression and the validity of these models was verified. Thus, this thesis provides a reference for improving the performance of cutting tools and for achieving efficient and high-quality machining of titanium alloys.

scholarly journals MCDM Evaluation of Asset-Based Road Freight Transport Companies Using Key Drivers That Influence the Enterprise Value

2020 ◽  
Vol 12 (18) ◽  
pp. 7259
Author(s):  
Edvardas Liachovičius ◽  
Viktor Skrickij ◽  
Askoldas Podviezko
Keyword(s):  
Multiple Criteria Decision Making ◽  
Freight Transport ◽  
Growth Strategies ◽  
Business Valuation ◽  
Enterprise Value ◽  
Company Value ◽  
Novel Approach ◽  
Road Freight ◽  
Key Drivers

Business owners are trying to enhance company value by developing growth strategies. Besides, they need to know what supports and drives the attractiveness to potential investors. Previously to determine company value, only financial drivers were used. These are essential drivers; however, even they do not reflect the overall situation. This paper proposes a novel approach for the solution of the problem of business valuation by taking into account both financial and non-financial drivers and by using several MCDM (multiple criteria decision making) methods simultaneously both for establishing weights and for the evaluation itself. World-leading road freight transport companies were selected for a case study. MCDM methods were used for determining the weights of the drivers and comparing the listed companies. Key drivers were identified, and the ranking of companies is provided.

scholarly journals Modern Methods of Business Valuation—Case Study and New Concepts

2020 ◽  
Vol 12 (7) ◽  
pp. 2699
Author(s):  
Ireneusz Miciuła ◽  
Marta Kadłubek ◽  
Paweł Stępień
Keyword(s):  
Code Of Conduct ◽  
Fair Value ◽  
Modern World ◽  
Business Valuation ◽  
Enterprise Value ◽  
Critical Elements ◽  
Enterprise Valuation ◽  
New Concepts ◽  
Commercial Transaction ◽  
Modern Business

In the modern world, the terms enterprise value and valuation are of great importance. Knowledge about how much an enterprise is worth is of fundamental importance for both the owner of that company and investors when negotiating the price of an enterprise at the time of conducting a commercial transaction. The article presents the goals of the company’s valuation and characteristic stages of the company’s life at which such valuation is necessary. The article classifies the methods of enterprise valuation used today. On this basis, the valuation methodology is presented according to the MDI-R concept (Assets, Income, Intellectual Capital-Market), which in a broad spectrum measures the effectiveness of the company’s operations and, in accordance with the current features of good valuation, aims to determine the fair value of the company. The purpose of the article is to demonstrate the need to improve the code of conduct and valuation standards. As part of the implementation of the objective, multi-faceted and complex valuation issues are presented, as well as factors that may distort the determination of fair value. The methodology of the study is based on inferences about the methodology of business valuation, and verification is based on practical examples, by which a hypothesis on the existence of critical elements of valuation is verified that allows the use of broad subjectivity in estimating the value of assets. At the same time, the factors that determine the possibility of the existence of too wide a subjectivity in estimating assets, which is in contradiction with the features of good valuation, are presented. The attempt is made to draw attention to the threats arising from modern business valuation methodologies and their challenges in the future. Additionally, this article offers the authors’ proposed hybrid method MDI-R, which draws from existing solutions to improve their functionality and applicability.

scholarly journals Financial Distress and Bankruptcy Prediction in Conditions of Slovak Republic

2021 ◽  
Vol 92 ◽  
pp. 08017
Author(s):  
Filip Rebetak ◽  
Viera Bartosova
Keyword(s):  
Financial Distress ◽  
Prediction Models ◽  
Financial Analysis ◽  
Slovak Republic ◽  
Value Added ◽  
Theoretical Background ◽  
Bankruptcy Prediction ◽  
Important Place ◽  
Non Profit ◽  
Analysis And Synthesis

Research background: Prediction of bankruptcy has an important place in financial analysis of an organization in the globalized economy. Ever since the first publication of a paper on bankruptcy prediction in 1932, the field of bankruptcy prediction was attracting researchers and scholars internationally. Over the years, there have been a great many models conceived in many different countries, such as Altman’s Z score or Ohlson’s model for use for managers and investors to assess the financial position of a company. Globalization in last few decades has made it even more important for all stakeholders involved to know the financial shape of the company and predict the possibility of bankruptcy. Purpose of the article: We aim in this article to examine the financial distress and bankruptcy prediction models used or developed for Slovakia to provide an overview of possibilities adjusted to specific conditions of the Slovak Republic in context of globalization. We will also look at the possibility of use of these prediction models for assessing financial status of non-profit organizations in the Slovak Republic. Methods: We will use analysis and synthesis of current research and theoretical background to compare existing models and their use. Findings & Value added: We hope to contribute with this paper to the theoretical knowledge in this field by summarizing and comparing existing models used.

scholarly journals Quantitative Toxicity Prediction via Ensembling of Heterogeneous Predictors

2019 ◽  
Author(s):  
Abdul Karim ◽  
Vahid Riahi ◽  
Avinash Mishra ◽  
Abdollah Dehzangi ◽  
M. A. Hakim Newton ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Prediction Models ◽  
Individual Performance ◽  
Learning Model ◽  
Data Representation ◽  
Toxicity Prediction ◽  
Machine Learning Model ◽  
Machine Learning Approach ◽  
Benchmark Datasets

Abstract Representing molecules in the form of only one type of features and using those features to predict their activities is one of the most important approaches for machine-learning-based chemical-activity-prediction. For molecular activities like quantitative toxicity prediction, the performance depends on the type of features extracted and the machine learning approach used. For such cases, using one type of features and machine learning model restricts the prediction performance to specific representation and model used. In this paper, we study quantitative toxicity prediction and propose a machine learning model for the same. Our model uses an ensemble of heterogeneous predictors instead of typically using homogeneous predictors. The predictors that we use vary either on the type of features used or on the deep learning architecture employed. Each of these predictors presumably has its own strengths and weaknesses in terms of toxicity prediction. Our motivation is to make a combined model that utilizes different types of features and architectures to obtain better collective performance that could go beyond the performance of each individual predictor. We use six predictors in our model and test the model on four standard quantitative toxicity benchmark datasets. Experimental results show that our model outperforms the state-of-the-art toxicity prediction models in 8 out of 12 accuracy measures. Our experiments show that ensembling heterogeneous predictor improves the performance over single predictors and homogeneous ensembling of single predictors.The results show that each data representation or deep learning based predictor has its own strengths and weaknesses, thus employing a model ensembling multiple heterogeneous predictors could go beyond individual performance of each data representation or each predictor type.

scholarly journals The Electric Vehicle Time-of-Use Price Optimization Model Considering the Demand Response

2018 ◽  
Vol 160 ◽  
pp. 02009
Author(s):  
Zejing Shi ◽  
Ninghui Zhu ◽  
Jinsong Yu
Keyword(s):  
Electric Vehicles ◽  
Optimization Model ◽  
Prediction Models ◽  
Distribution Grid ◽  
Power Prediction ◽  
Peak Shaving ◽  
Satisfaction Index ◽  
The Monte Carlo Method ◽  
Load Peak ◽  
Coordinated Charging

A large number of electric vehicles connecting to the distribution grids usually introduce significant fluctuations to the grid and the loads. To solve the problem, guiding the users coordinated charging is proposed. Firstly, the uncontrolled charging power prediction models of electric vehicles are established, and the Monte Carlo method is adopted to simulate the power demands of different electric vehicles, and the influences on the load peak-valley ratios and the voltages and losses of the grid are all analyzed. Then the vehicle responses model considering the time-of-use price is analyzed, and the vehicle response ratios are obtained under different time-of-use prices. Finally the multi-objective optimization model is constructed including the minimum peak-valley ratio, maximum consumption satisfaction index and cost satisfaction index. In the procedure, vehicles and the grid are both taken into account. The results indicate the proposed method could guide the users coordinated charging, and the peak shaving and valley filling is also achieved, and the operation of the distribution grid is improved.

scholarly journals Analyzing the Impact of Corporate Governance Factors on Enterprise Value and Capitalization

2021 ◽  
Vol 26 (3) ◽  
pp. 291-309
Author(s):  
Ol'ga D. KOSORUKOVA
Keyword(s):  
Corporate Governance ◽  
Value Management ◽  
Financial Indicators ◽  
Business Valuation ◽  
Enterprise Value ◽  
Value Based Management ◽  
Methods Of Synthesis ◽  
The Impact ◽  
Made In

Subject. The article focuses on business valuation methods and factors with reference to corporate governance principles. Objectives. I analyze how corporate governance factors influence the value and capitalization of public joint-stock companies, and make my suggestions concerning financial and administrative decisions in line with value-based management. Methods. The study is based on methods of synthesis, deduction, induction, statistical analysis, comparison and generalization. Results. Having analyzed the impact of such factors, as revenue, dividends paid, return on sale and equity, for an 11-year life span (2009–2019), on capitalization and value of the population made up of 20 Russian public joint-stock companies from four sectors, as classified by the number of owners and State interest, I figured out that capitalization enterprise value in Russia most of all depend on indicators of companies if it has 11 owners and more (71%), companies without the State interest (67%). As for basic factors, these are revenue and dividend policy that have the strongest effect on enterprise value, while capitalization depends on all the analyzable factors. Conclusions and Relevance. Currently, business valuation and business valuation management are critical for making correct strategic administrative decision. Doing so, the appraiser shall not only measure enterprise value with available financial results, but also consider its various non-financial indicators, which inter alia include corporate governance. Based on corporate governance principles set forth in the Letter of the Bank of Russia, I pointed out that definitely influence the enterprise value. Based on the above analysis, I determined what best results the Russian public joint-stock companies can attain in their corporate governance by sector, the number and quality of owners. Following the findings, I suggest how financial and administrative decisions on enterprise value management should be made, in line with the value-based management principles.

The methodology to assess the impact of corporate governance on the enterprise value

2021 ◽  
Vol 27 (9) ◽  
pp. 2008-2032
Author(s):  
Ol'ga D. KOSORUKOVA
Keyword(s):  
Corporate Governance ◽  
Business Value ◽  
Public Companies ◽  
Business Valuation ◽  
Corporate Managers ◽  
Enterprise Value ◽  
Corporate Governance Code ◽  
Pricing Factors ◽  
Legal Forms ◽  
The Impact

Subject. The article investigates pricing factors that determine the enterprise value with respect to the effect of corporate governance factors. Objectives. I analyze the impact of corporate governance factors on the enterprise value and build a technique for assessing the effect of corporate governance on the business valuation of the Russian public companies. Methods. The study relies upon the synthesis, deduction, induction, methods of statistical analysis, comparison and generalization. Results. I devised the method, which comprises five steps considering the effect of corporate governance factors on the enterprise value. Following the steps of the method, the specifics of the valuation subject is analyzed in terms of business and legal forms, the use of modern Russian corporate governance principles, the composition and the number of shareholders, industry the entity operates in, and fundamental metrics of the enterprise value. Conclusions and Relevance. Currently, there is few information in the literature about the impact of corporate governance principles set forth in the 2014 Corporate Governance Code, on business value. The article presents the method for assessing the impact of corporate governance on the business valuation, which accounts for the specifics of business and legal forms in terms of corporate governance principles, capital structure, the number of shareholders, the State’s involvement, industry, and fundamental metrics of business valuation. The proposed method can be used by financial analysts, appraisers, corporate managers so as to build and manage the enterprise value.

scholarly journals A Comparison on Leading Methodologies for Bankruptcy Prediction: The Case of the Construction Sector in Lithuania

Economies ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 82
Author(s):  
Gintare Giriūniene ◽  
Lukas Giriūnas ◽  
Mangirdas Morkunas ◽  
Laura Brucaite
Keyword(s):  
Statistical Data ◽  
Prediction Models ◽  
Scientific Literature ◽  
Data Representation ◽  
Bankruptcy Prediction ◽  
Construction Sector ◽  
Macroeconomic Variables ◽  
Graphic Data ◽  
Macroeconomic Indicators ◽  
Business Conditions

Different economic environments differ in their characteristics; this prevents the usage of the same bankruptcy prediction models under different conditions. Objectively, the abundance of bankruptcy prediction models gives rise to the idea that these models are not in compliance with the changing business conditions in the market and do not meet the increasing complexity of business tasks. The purpose of this study is to assess the suitability of existing bankruptcy prediction models and the possibilities to increase the effectiveness of their application. In order to analyze theoretical aspects of the application of bankruptcy forecasting models and frame the research methodology, a systemic comparative and logical analysis of the scientific literature and statistical data, graphic data representation, induction, deduction and abstraction are employed. Results of the analysis confirm research hypotheses that bankruptcy prediction models based on macroeconomic variables are effective in identifying the number of corporate bankruptcies in a country and that the application of the model created on the grounds of macroeconomic indicators together with the traditional bankruptcy prediction model can improve the reliability of bankruptcy prediction. However, it was identified that models which are not specially adapted to companies in the construction sector are also suitable for forecasting their bankruptcies.

scholarly journals Optimized data representation and convolutional neural network model for predicting tumor purity

2019 ◽  
Author(s):  
Gerald J. Sun ◽  
David F. Jenkins ◽  
Pablo E. Cingolani ◽  
Jonathan R. Dry ◽  
Zhongwu Lai
Keyword(s):  
Copy Number ◽  
Prediction Models ◽  
Cancer Genomics ◽  
Bioinformatic Analysis ◽  
Data Representation ◽  
Next Generation Sequencing Data ◽  
Clinical Samples ◽  
Sequencing Data ◽  
Tumor Purity ◽  
Machine Learning Model

AbstractHere we present a machine learning model, Deep Purity (DePuty) that leverages convolutional neural networks to accurately predict tumor purity from next-generation sequencing data from clinical samples without matched normals. As input, our model utilizes SNP-based copy number and minor allele frequency data formulated as a scatterplot image. With a representation matching that used by expert human annotators, we best an existing algorithm using only ~100 manually curated samples. Our simple, data-efficient approach can serve as a straightforward alternative to traditional, more complex statistical methods, for building performant purity prediction models that enable downstream bioinformatic analysis of tumor variants and absolute copy number alterations relevant to cancer genomics.

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