DCF Model Research Articles

Deep Collaborative Online Learning Resource Recommendation Based on Attention Mechanism

In view of the lack of hierarchical and systematic resource recommendation caused by rich online learning resources and many learning platforms, an attention-based ADCF online learning resource recommendation model is proposed by introducing the attention mechanism into a deep collaborative DCF model. Experimental results show that the proposed ADCF model enables an accurate recommendation of online learning resources, reaching 0.626 and 0.339 on the HR and NDCG metrics, respectively, compared to the DCF models before improved, up by 1.31% and 1.25%, and the proposed ADCF models by 1.79%, 2.17%, and 2.32%, respectively, compared to the IUNeu and NeuCF models.

Financial Valuation and Investment Analysis of Carrefour

This thesis uses external analysis, internal analysis and DCF model to comprehensively evaluate the endogenous value of Carrefour. Combining the results of the three, this thesis proposes to investors whether to invest in Carrefour in the long-term and short-term and what the specific operation should be. Combining the opinions of market investors and my analysis, this dissertation believes that Carrefour's stock should be bought in the short term and kept on the side-lines in the long term.

A Modified UK Real Value/Short-Cut DCF Model for the Valuation of a Nigerian Sub-Leased Commercial Property

A UK real value/short-cut DCF model that addresses the valuation of geared profit rents generated by sub-let commercial investment properties especially in climes with nationalized land policy has been elusive. This study examines the modification of the extant UK real value/short-cut DCF model for the valuation of head-leased occupancy rights with fixed and non-revisable ground rents pursuant to the provisions of the Nigeria Land Use Act. The model is developed by blending the inputs of the modified rational model with that of the Crosby's real value/short-cut DCF model leading to a valuation model that appears simplified compared to the existing UK contemporary value models. The gearing effect for the hypothetical case of sub-let head-lease occupancy right in Nigeria is manifested as having a diminishing impact of fixed ground rent on profit rent calculation. For the valuation case study involving this hypothetical head-leased occupancy right in Nigeria, it was found that the modified UK real value/short-cut DCF model produced valuation that is identical to those churned out from the full DCF, modified rational, and Crosby's real value/short-cut DCF models. For the same hypothetical case study, less than 1% difference is observed between valuations from the all risks real yield (ARRY) model, which evolved in New Zealand and the valuation produced from the modified UK real value/short-cut DCF model, thereby validating all methods against each other. In consonance with the International Valuation Standards pertaining to income valuation approach, a sustained pedagogy of emerging real value models alongside the extant nominal valuation models is suggested as a way forward. Nevertheless, the modified UK real value/short-cut DCF model is recommended as an alternative to the extant variants of real value and explicit DCF techniques for the valuation of sub-let head-lease occupancy rights with fixed/non-revisable ground rents payable especially in climes with nationalized land policy.

Ensemble Forecasting Methods in DCF Modelling of the Fair Value of Enterprises

The purpose of this study is to improve the methodology for assessing the fair value of enterprises based on the DCF model with the use of ensemble methods for predicting the selling price of their products. The study compares the fair values of three Ukrainian agricultural enterprises. The value of each company was calculated in several ways: using forecast data from statistical agencies, calculated forecast values, and real indicators. The methodology is based on the use of methods and models for forecasting time series. The study uses neural networks, as well as prediction methods such as linear regression, FB Prophet model, Holt-Winters exponential smoothing method, SARIMA, XGBoost, which are combined into a single ensemble with the use of the stacking method. The study employed such general scientific methods as analysis, synthesis, abstraction, and comparison. Also, methods of graphical and tabular presentation of materials were applied. Statistical modelling was used to determine the parameters of the model. The study found that the DCF model can potentially be improved by using ensemble methods when predicting metrics such as inflation, exchange rates, and the selling price of goods and services. These metrics have a significant impact on the final result of the model and therefore the slightest changes in these input data can lead to significant deviations in the result. It was demonstrated that the use of ensemble methods only at the selling price can increase the accuracy of the model by 5-15%. It is advisable to use the results of the study in the investment activities of companies, in mergers and acquisitions of companies, as well as in measuring the fair or investment value of companies.

Alpha enhancement in global equity markets with ESG overlay on factor-based investment strategies

Studies show that companies with a strong Environment, Social and Governance (ESG) profile are more competitive than their peers, as they use resources, human capital and innovation more efficiently. High ESG-rated companies have lower exposure to systematic risk factors and low expected cost of capital, leading to higher valuations in a DCF model framework. They are typically more transparent, particularly with respect to their risk exposures, risk management and governance standards and have better long-term vision. The paper finds that higher Alpha can be harvested by restricting investment exposure to the ESG theme combined with various style characteristics, as they display low systematic and idiosyncratic tail risks. It shows that an ESG overlay on such factor-based strategies, particularly on ‘multi-factor’, ‘value’ and ‘low volatility’ in that order, reduces both systematic and idiosyncratic risks further. ESG overlay on ‘quality’ factor provides the highest return among ESG target indices, however, the underlying ‘quality’ factor provides even higher excess return. These findings can provide some insight on return enhancement to investors investing in the global equity markets.

Revisiting discounted cash flows model as a capital budgeting decision tool

Purpose- In this study, the classical discounted cash flows (DCDF) model is revisited and the input factors of the model are analysed in details. Methodology- A model analysis approach is used in this research. The fundamental assumptions and the input factors (cash flows, time period, risk, discount rate, etc.) of DCF model are questioned. Findings- NPV and IRR are two methods using discounted cash flows and oftenly applied for capital budgeting decisions. The assumptions used in the DCF analysis are very strong and not fitting well in the reality of practical life. Economic life of the project may be much longer or shorter than projected in the analysis. The computation of discount rate bases on subjective interpretations (weights of capital components, cost of debt, opportunity cost of equity). Estimation of cash flows is the most critical input of the analysis but generally the least weighted factor (CF or FCF, inclusion of only relevant cash flows, depreciation and interest expenses, installments, credit sales and purchases, etc.). Risk adjustment can be made either on the discount rate or expected cash flows. Moreover, the analysis of international capital investments makes the issue more complicated. Also, the inclusion of real options adds an economic value to the analysis. Conclusion- DCF is not straight forward a capital budgeting model anyone can easily use. The application of DCF requires expertise and a picky view on details. Nevertheless, the acceptance of capital investments utilizing DCF method can not be independent of overall company strategic goals.

Alternative Real Value Hybrid Model for the Valuation of Reversionary Leasehold Investment Properties

Abstract This study is a design of an alternative real value hybrid model for the valuation of reversionary leasehold investment properties characterized by divergence in the revision period of sub-rent and head rent respectively. The development of this model commenced with a synthesis of inputs for the modified rational- and real value hybrid models, and the derivation of an equivalent cash flow multiplier for terminal investments. With exception of the generic real value model, term incomes across all other contemporary models including the alternative real value hybrid model were discounted using the equated yield. The discounted reversionary cash flows in the valuation template associated with the alternative real value hybrid model appears identical to that in the generic real value model, while exhibiting itself as a surrogate reversionary income multiplier for the modified rational, and the real value/short-cut DCF models respectively. The alternative real value hybrid model was validated as capable of producing valuations that are identical to those churned out from all the existing contemporary models for the valuation of this category of reversionary leasehold investment property. The study is a novel attempt towards redesigning the modified rational model of leasehold investment property valuation and according it a real value perspective.

OPTIONS METHOD FOR OIL EXPLOITATION INVESTMENT PROJECT EFFICIENCY EVALUATION UNDER RISK CONDITIONS

In this work modern methods of investment project efficiency evaluation were studied, advantages and disadvantages of using the real option model were shown in comparison with the DCF model. It is proved that a rainbow option is an effective valuation tool in conditions of high oil prices volatility and low study of reserves and resource. Two stages may be identified: mineral exploration and maintenance work. Black-Scholes model was used for option pricing.

FORECASTING OF THE STOCK RATE OF LEADING WORLD COMPANIES USING ECONOMETRIC METHODS AND DCF ANALYSIS

In this article, we will cover various models for forecasting the stock price of global companies, namely the DCF model, with well-reasoned financial analysis and the ARIMA model, an integrated model of autoregression − moving average, as an econometric mechanism for point and interval forecasting. The main goal is to compare the obtained forecasting results and evaluate their real accuracy. The article is based on forecasting stock prices of two companies: Coca-Cola HBC AG (CCHGY) and Nestle S.A. (NSRGF). At the moment, it is not determined which approach is better for predicting the stock price − the analysis of financial indicators or the use of econometric data analysis methods.

Accuracy of the German income approach in comparison to German DCF valuations

ABSTRACT The traditional German Income Approach (GIA) is often criticised for resulting in smooth and stable estimations of value that do not adequately represent market movements. So far, empirical evidence has been scarce. The first part of the analysis consisted of a direct comparison of actual valuations and sale prices according to GIA and DCF models in Germany. The second part of the analysis used hedonic regressions to derive fitted sale prices that could be compared to valuations of held properties in order to assess valuation accuracy on a larger and more homogenous dataset. The Heckman Correction was used to reduce the impact of sample selection bias. The research hypothesis, that GIA valuations and DCF valuations result in equally accurate proxies for market prices, could not be rejected. Both techniques produced on average a comparable amount of valuations within the selected threshold of 15%. This finding suggests that the underlying valuation technique, at least with respect to DCF and GIA, is not able to explain the observed smoothness of German valuation-based indices. Future research should focus on a country comparison of valuation accuracy in order to put the results of this study into perspective.

Valuation Techniques and the Economics of Software as a Service

A significant amount of literature favors the notion that a real-options approach to capital budgeting is superior to the conventional discounted cash flow technique when uncertainty is present in the investment opportunity. Unlike traditional licensed-based software, SaaS1 inherently provides the buyer with the flexibility to change the course of the investment as uncertainty related to the product or service is resolved. In this respect, SaaS changes the game with regard to the economic benefits provided by the product or service. The SaaS model builds management flexibility into the investment decision and that same flexibility may be valuable when uncertainty is present. With that said, the question at hand is whether or not conventional valuation techniques such as DCF2 can be counted on to make accurate SaaS capital budgeting decisions. And if such methods cannot be counted on, do OPM3 techniques such as binomial lattices or modified Black Scholes models provide a more accurate picture of their value? The final and perhaps more important question seeks to understand which of the two methods is most likely to be used by finance professionals when making SaaS capital budgeting decisions. This paper will show that a considerable gap exists between those that intend to use conventional DCF models versus more sophisticated OPM techniques when making capital investment decisions that involve SaaS. This gap should be a concern for those that buy or sell products and services delivered via SaaS for the value of flexibility may go unrecognized.

The financial returns from buying versus renting

PurposeThe UK experienced a substantial rise in owner occupation over the twentieth century, and many tenants still aspire to homeownership. These strong aspirations to own are attributed to a set of financial and non-financial benefits. This paper aims to calculate, for the first time, the financial returns from buying versus renting in Britain for first-time buyers in 11 regions.Design/methodology/approachIt applies a DCF approach based on historical housing and mortgage market data from 1975 to 2012.FindingsThe paper finds strong evidence that, in purely financial terms, buying has been always superior to renting in all regions of the UK over the period.Practical implicationsIt gives a clear message of the financial benefits of homeownership over renting in Britain, even over very short time periods.Originality/valueThe paper is the first to apply a comprehensive DCF model to the choice between renting and owning.

DCF Please! Evidence from a Textual Analysis of Analyst Reports

Using textual analysis for a large sample of analyst reports, we find that analysts are more likely to use a DCF model and to discuss more cash flow and discount rate information for firms with more uncertainty, especially under heightened aggregate economic uncertainty and bearish market sentiment. The market reactions to target price changes based on a DCF model are stronger, particularly when the analysts present more cash flow and discount rate discussions. These results indicate that analyst valuation process reflects investors’ information demand under uncertainty, and has a bearing on the informativeness of analyst research.

An Empirical Study on the Evaluation of Technology Asset: For Non-listed SMEs

본 연구는 미래성장성이 높은 비상장 기술혁신형 중소기업이 보유한 기술자산의 경제적 가치를 비용자본화 모형을 통하여 실증적으로 추정한다. 기술자산의 가치를 고려하지 않은 기업가치 산정은 그만큼 기업의 미래성장성을 과소평가하게 되어 투자 및 대출 등의 자금공급과 M&A에서 상대적으로 불이익을 받을 수밖에 없다. 기술자산추정을 위한 분석방법론으로는 비용자본화 모형, 초과이익확장모형, 내재가치모형 중 비상장중소기업에 상대적으로 제한이 적은 비용자본화 모형을 선택하였다. 2009년∼2013년 사이의 중소기업진흥공단이 보유하고 있는 13,250개의 비상장 중소기업을 대상으로 추정한 기술자산의 가치는 외감기업의 경우 평균 18.83억 원이며, 비외감 기업의 경우 5.78억 원으로 각각 나타났으며, 총자산대비 기술자산가치의 비율은 각각 13.64%(외감)와 15.86%(비외감)으로 추정되어 기술자산의 경제적 가치는 결코 작지 않은 것으로 분석되었다. 기술자산가치를 반영한 최종기업가치는 DCF 모형을 이용한 경우 27.9억 원(중위수), EVA 모형을 이용한 경우 28억 원(중위수)로 거의 비슷한 것으로 나타났다. 다만 다소 보수적으로 기업가치를 산출한 DCF의 모형에 비해, EVA의 평균이 84억 원으로 DCF의 평균 47억 원보다 상당히 높은 값을 보인다.This study empirically estimates the economic value of technology assets of technology - innovative SMEs. It is important to incorporate technology asset value into the firm valuation in order to avoid underestimation of the future growth potential for the technology-innovative SMEs. As an analytical methodology for estimating technology assets, we select the cost capitalization model, which is relatively less limited to apply for unlisted SMEs. Using the sample of 13,250 private SMEs offered by the SME promotion corporation for the period of 2009-2013, we estimate the value of technology assets and the ratio of technology assets to total assets at 18.83 billion won and 13.64% for external audit companies and 578 million won and 15.86% for non-external audit companies. This result suggests that the economic value of technology assets takes a significant portion of the company value. The final SME median value incorporating the technology asset value is almost equivalently estimated at 27.9 billion won using DCF model and 28 billion won using EVA model. However, the average EVA value is estimated at 8.4 billion won, which is considerably higher than the conservatively estimated DCF average of 4.7 billion won.

Does Enterprise Value Really Depend on WACC and Free Cash Flow? The Evidence of Irrationality from the Oil and Gas Sector

The main objective is to check whether traditional DCF model, based on stable rational expectations for cash flows and discount rates really works in an intermediate term-from a quarter to three years. The sample was formed from six major companies of oil and gas sector. The main conclusions are-changes of enterprise value are independent of the changes WACC, free cash flow, and operating cash flows. This may be explained by the impossibility to make durable assessment neither for expected cash flow nor for the discount rate, which in fact means failure of strongly rational models like CAPM or MM. To handle out this implied irrationality the new model proposed, based on the stochastic cost of capital, which follows the model of generalized method of moments by J. Cochrane.

Tiffany's Financial Modeling and Valuation Analysis

As the impact of the financial crisis subsided and the global economic recovery, the global financial markets gradually recovered. This article selects Tiffany Company as the research object. Through the financial data published in recent years, using FCFF and DCF model for modeling analysis and forecasting, it is found that the expected stock price at the time of research is far higher than the real-time stock price at that time and the expected stock price Evaluate the model with the stock price now and give investors advice.

Terminal Value Calculation in DCF Valuation Models: An Empirical Verification

Abstract The paper presents an empirical verification of the main assumptions underlying the calculation of terminal value in DCF valuation models. The test results suggest that the volatility of free cash flows and the dynamism of the operating environment do not allow us to make a reliable long-term forecast of value creation potential of the public companies in Poland. Regardless of their organic growth phase, the overwhelming majority of the sampled firms are evidenced to exhibit extreme year-on-year fluctuations of sales, investments and cash flows over the short- and medium-term observation windows. The variability of operating results and the probabilistic nature of company-level fundamentals may preclude the possibility of constructing a reliable cash flow forecast for the purposes of a DCF valuation. This methodological issue appears to pose a particular challenge during the calculation of terminal value, which is heavily dependent on highly subjective and uncertain steady-state fundamentals. Therefore, the predictive power of the deterministic DCF models may be reduced to a snapshot of the current market sentiment regarding a particular stock. The paper postulates that a further discussion on the tenets of terminal value calculation may be necessary in order to overcome the existing flaws and increase the accuracy of valuation models. We contribute to this discussion by outlining the principal methodological and theoretical issues which challenge the practicing valuators at the stage of terminal value calculation. Our conclusions may help to shed light on the problems of market short-termism, and high inconstancy of investment recommendations.

TOO BIG TO IGNORE � HOW TO DEFINE THE ENTERPRISE VALUE OF AI AND BIG DATA FIRMS

ABSTRACT Artificial Intelligence and Big Data companies (AI&BD) are already now key drivers for disruption in many industries and will change the way business works from its core. These companies possess very different financial metrics due to a high amount of intangible assets in form of data and algorithms and exponential economic growth potential. A conceptual enterprise valuation methodology for these firms is thus introduced based on three major adjustments for a modified DCF model: First, the growth phases are estimated as typical for young growth and data driven companies. Second, expenses for software R&D are treated as CapEx instead of OpEx to account for software/IP as intangible assets. Third, a base multiple derived from comparable peer firm transactions is modified with regard to the firm's specific AI&BD-specific value drivers. Specifically Data, Algorithm and Team as the major value drivers for AI&BD firms are considered. These adjustments result in changes in the enterprise value and are targeting an objective valuation result for AI&BD firms and shall thus provide a concept for more adequate valuations in the steadily growing AI&BD sector. Keywords Artificial Intelligence, Enterprise Valuation, Discounted Cash Flow, Intangible Assets, M&A

Application of Discounted Cash Flow Model Valuation Wal-Mart

The objective of this research paper is to examine if DCF models offer reliable and accurate valuations of Wal-Mart. With the purpose of achieving most accurate results, an efficient combination between theory and practice was implemented throughout the valuation. The DCF valuation of free cash flow to equity holders was performed and the stock price of Wal-Mart was suggested it to be $81.63. Afterwards, we tracked the six-month stock price movement of Wal-Mart, (from 2016 Jan to 2017 Jun) and surprisingly found that the price had climbed from $69.24 to $80.47.

The accuracy of alternative stock valuation methods – the case of the Warsaw Stock Exchange

The main aim of this article is to examine the accuracy of different methods of share valuation used by Polish analysts in reports prepared in order to issue recommendations for companies listed on the Warsaw Stock Exchange. In the literature on the subject, the view which prevails is that the more sophisticated methods, i.e. those taking into account the discounting process, are characterised by higher valuation accuracy. However, the results of the present analysis show that Polish analysts achieve more accurate valuations using the market approach than the DCF model. Nevertheless, the highest level of accuracy is achieved by the target price, which in most cases is the value of the weighted average of valuations obtained via a market valuation and discounting methods. In terms of the multiples which are taken into account in this research, the highest accuracy is achieved with the use of EV/EBIT, although there are no statistically significant differences between the valuations calculated using this multiple and the results obtained with the P/E and EV/EBITDA multiples. Valuations prepared with the use of individual multiples usually generate greater errors compared to the DCF model and the market approach, which uses the weighted average of the valuations achieved with individual multiples.