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We use a decision-tree-based machine learning approach to perform relative valuation. Stocks are valued using market-to-book, enterprise-value-to-assets and enterprise-value-to-sales multiples. Our machine learning models reduce median absolute valuation errors by between 17% and 50% relative to traditional models. The identified valuation drivers are consistent with theoretical predictions derived from a discounted cash flow approach. Accounting variables related to profitability, growth, efficiency and financial soundness are important valuation drivers. The valuations produced by machine learning models behave like fundamental values. A value-weighted strategy that buys (sells) undervalued (overvalued) stocks generates highly significant abnormal returns. When we use models trained on listed firms to value IPOs, machine learning models outperform traditional models in valuation accuracy and can identify mispriced IPOs.

The degree of uncertainty associated with the value of a company plays a relevant role in valuation analysis. We propose an original and robust methodology for company market valuation, which replaces the traditional point estimate of the conventional Discounted Cash Flow model with a probability distribution of fair values that convey information about both the expected value of the company and its intrinsic uncertainty. Our methodology depends on two main ingredients: an econometric model for company revenues and a set of firm-specific balance sheet relations that are estimated using historical data. We explore the effectiveness and scope of our methodology through a series of statistical exercises on publicly traded U.S. companies. At the firm level, we show that the fair value distribution derived with our methodology constitutes a reliable predictor of the company’s future abnormal returns. At the market level, we show that a long-short valuation (LSV) factor, built using buy-sell recommendations based on the fair value distribution, contains information not accessible through the traditional market factors. The LSV factor significantly increases the explanatory and the predictive power of factor models estimated on portfolios and individual stock returns.

Real-world market quotes of bonds can sometimes contradict the no arbitrage principle within the discounted cash flow model. This makes some kinds of no-arbitrage-based analyses impossible, e.g., i...

This study aims to project the intrinsic value of state-owned banks listed on IDX for the 2021 to 2025 projection. This study uses the Discounted Cash Flow (DCF) method with the Free Cash Flow to Equity (FCFE) approach specifically for banks by looking at the regulatory capital. Meanwhile, it is also used the Relative Valuation method with the Price to Book Value (PBV) and Price Earnings Ratio (PER) approaches. This study uses three scenarios will be used, which consist of a pessimistic scenario (the average condition of the industry), a moderate scenario (the same condition as the company's growth), and an optimistic scenario (a condition above industry growth), which aims to project the stock value over the next five years. The data used in this study comes from historical data during the 2016 to 2020 period. Based on the results, the stock prices of state-owned banks using the FCFE method shows undervalued results for all scenarios. Meanwhile, using the relative valuation method, PBV in the optimistic scenario only shows BBNI undervalued conditions. In addition, in moderate and pessimistic scenarios, only BBRI shows overvalued conditions. Furthermore, PER shows undervalued results for all scenarios.

This study compares profitability and risk of conventional and cage-free egg production in the United States. Evaluating cage-free production is particularly relevant given ongoing consumer driven changes and new cage-free legislation. Results show that while the Modified Internal Rate of Return (MIRR) for conventional production is above an estimated industry opportunity cost of capital, cage-free production’s MIRR does not fully satisfy investors’ expectations. The MIRR of cage-free investment, between 5.6% (deterministic model) and 8.0% (stochastic) per 15-month flock, is below the 9.4% opportunity cost of capital. In addition, the simulations show that there is a 90% probability of conventional production’s MIRR falling between 18.5 and 20.3% per 15-month flock, and cage-free egg production’s MIRR ranging from 6.8 to 9.4%. In order for cage-free to be as equally profitable as conventional production, cage-free egg prices at the farmer gate should be 74% over conventional egg prices. Such high cage-free egg prices are highly unlikely to occur given recent cage-free price premia and consumer willingness to pay estimates from recent research. This study provides a framework egg producers can use to evaluate the potential effects of changes in their portfolio of products (i.e. conventional and cage-free mix) as they accommodate production schedules in this evolving industry.

In any context where a discounted cash flow valuation is required, there is the issue of estimating the continuing value. The most common way to do that is to assume that by the terminal horizon the company is in a steady state and is growing at a constant rate. The issue is how to handle inflation. The problem is that it is often done wrong and the impact is typically material. Because there remains significant confusion, in this paper we simplify the analysis by isolating the two key issues and providing example calculations. We show that even at the current 2% level proper treatment of inflation has a sizeable impact on valuation. If inflation were to accelerate as a result of current monetary and fiscal policies, the significance of this issue will increase.

Estimating growth in net cash flows is one of the key components in applying the discounted cash flow (DCF) method in valuing any company, reporting unit, or other business unit. This paper explains the underlying assumptions of the DCF method and demonstrates how to compare the most commonly used basis for estimating net cash flows (sometimes referred to as free cash flows), expected organic growth, to historic estimates of growth of the subject company and estimates of earning growth commonly prepared by security analysts.

Traditional valuation models such as the Gordon growth model, the discounted cash flow (DCF) model, and the real option approach assume that cash flows are perpetual. There is no firm that lasts forever. In the expected time to ruin model, the underlying firm has an expected termination date. In an efficient market, stock prices should reflect all available information. Adapted from a revised valuation model, the authors solve for the implied mortality (IM) of an underlying firm given its equity market price. The authors investigate IM for securities during the last few crises. The existence of IM may be the missing piece of the unexplained volatility puzzle. TOPICS:Financial crises and financial market history, exchange-traded funds and applications, security analysis and valuation, tail risks Key Findings ▪ Most valuation models of the firm assume that cash flows are perpetual. Of course, this is incorrect. By applying the Expected Time to Ruin Model, we solve for the Implied Mortality (IM) of an underlying firm given its equity market price. ▪ IM would be a useful and easy tool for the credit market trading. High leverage firms such as those in the financial industry suffered more during the crisis. We investigate the last three crises and different degrees of impact on them. ▪ The change in IM may be the missing piece of the unexplained volatility puzzle or so-called “Irrational Exuberance.”

The evaluation of investment projects has been carried out mainly through the analysis of Discounted Cash Flow (DCF), whose financial feasibility measures have been based fundamentally on approaches such as the Net Present Value (NPV) and the Internal Rate of Return (IRR), which are widely discussed in the field of energy project valuation. Despite this, the classical methods have a limitation when perceiving relevant characteristics for decision-making in high-risk investments, such as the uncertainty of the cash flows and the quantification of risk. An alternative to the use of these methods is the technique known as Decoupled Net Present Value (DNPV), which decouples the risk associated with the project from the value of money over time. This valuation methodology was applied to a photovoltaic solar energy self-generation project in Colombia. In this study, the results obtained through the DNPV was equivalent to 2.3-fold the value obtained by means of NPV. Thus, many renewable energy projects can become undervalued since traditional methods mistakenly associated a discount rate that includes a very high risk premium and that in many occasions it is more related to the sources of financing of the project instead of representing the risk component that it has.Keywords: Decoupled net present value (DNPV), Renewable energy projects, Solar energy investmentsJEL Classifications: Q2, Q4DOI: https://doi.org/10.32479/ijeep.10577

The paper seeks to develop a comprehensive framework to cross-border discounted cash flow valuation. Although the literature on company valuation and on international financial management is vast, such a framework has not yet been proposed. We build upon well-known fundamentals and relevant contributions, e.g. on the derivation of the risk-adjusted rate of return. Relevant risks are exchange rate risk, business risk, financial risk, the risk of the tax effects induced by debt financing, and the risk of default. Additional tax effects beyond the well-known tax shield on interest expenses must be considered. Risk discounts from cash flows and risk premia to be added to risk-free interest rates are derived according to the global capital asset pricing model. A conceptual choice occurs not only between the foreign currency and the home currency approach, but also regarding the estimation of future exchange rates. The paper shows how a valuation can be implemented with or without consideration of covariances between cash flows and rate of returns with exchange rates. It also derives the discount rates if forward exchange rates are applied. We discuss the consequences of assuming the uncovered interest parity to hold. We assume deterministic debt and apply the adjusted present value approach. In addition, we derive the RADR to be used in the flow to equity and weighted average cost of capital approach. The paper addresses not only the valuation of a foreign company, but also the valuation of a domestic company that generates cash flows in foreign currency and/or uses debt in foreign currency.

The aim of the paper is to develop a methodology for evaluating oil and gas fields return on investments based on not only finance, but also environmental and social interrelations. The subject of the study is a comparison of methods for calculating return on investments on the example of China, Canada and Russia’s oil and gas companies. The authors used a comparative method of calculations, as well as a case study — a comparison of return on investments methods on the example of oil and gas enterprises. In the paper, the authors analyze the next traditional methods of economic assessment: net present value, differential rent, reserve and multiple costs. The authors suggest using a new assessment method that determines the energy return on investment (EROI). This method does not rely on traditional analysis of net present value (NPV), internal rate of return (IRR), and financial sensitivity. It comprehensively takes into account the costs of energy production, environmental protection and energy efficiency. Based on the results of the study, the authors conclude that the advantages of various methods of economic assessment should be integrated in order to avoid disadvantages and create a new dynamic integrated system of economic assessment. Oil and gas companies may use the results of the study to implement the energy return on investment methodology concerning oil and gas fields’ evaluation. A promising direction for further research may be to compare the energy return on investment at oil and gas enterprises in different countries as well as developing corporate reporting concerning energy return on investment improving efficiency.

The concept of risk is well known in the energy sector. It is normally recognized when it comes to price and cost forecasting, annual production calculation, or evaluating project lifetime. Nevertheless, it should be pointed out that the quantitative evaluation of risk is usually difficult. The discount rate is the only parameter reflecting risk in the discounted cash flow analysis. Therefore, knowledge of the discount rate along with the major components affecting its level is of fundamental significance for making investment decisions, capital budgeting, and project management. By referring to the standard coal-fired power generation projects the authors of the paper tackle the analysis of the composition of discount rate for onshore wind farm technologies in the Polish conditions. The study was carried out on the basis of a typical (hypothetical) onshore wind farm project assessed at the feasibility stage. To enable comparisons and discussions, it was assumed that the best reference point for such purposes is the real risk-adjusted discount rate, RADR, after-tax, in all equity evaluations (the ‘bare bones’ assumption); that is because such a rate reflects the inherent characteristics of the project risk. The study methodology involves the a priori application of the discount rate level and subsequently—in an analytical way—calculation of its individual components. The starting point for the analysis of the RADR’s composition was the definition of risk, understood as the product of uncertainty and consequences. Then, the risk factors were adopted and level of uncertainty assessed. Subsequently, using the classical sensitivity analysis of IRR, the consequences (as slopes of sensitivity lines) were calculated. Consequently, risk portions in percentage forms were received. Eventually, relative risks and risk components within cost of equity were assessed. Apart from the characteristics of the discount rate at the feasibility stage, in the discussion section the study was supplemented with an analogous analysis of the project’s cost of equity at the operating stage.

Purpose : This study evaluated the bio-economic potentials of temperate lowland silvopastoral agroforestry systems in North Wales, United Kingdom. Methodology : The bioeconomic analysis compared three land-use plausible scenarios (‘forestry’, ‘pasture / livestock’ and ‘agroforestry’) at 3.5% discount rate on a 10-hectare farm over a 30-year rotation using discounted cash flow analysis and national costs and prices for both livestock and tree products based on 2016 baseline data. Base case net present value (NPV) and annual equivalent value (AEV) were calculated for each production livestock grazing, farm forestry, and silvopastoral agroforestry scenario, assuming no policy interventions. Findings: Generally, results of the economic analyses indicated that under the baseline case, assuming no policy interventions, none of the options was viable. This study also showed that increase in lamb sale price, wood price, and wood yield improved the economic viability of the three investment options significantly. Again, the viability of the three investment options in this study is shown to decrease with increase in discount rates. Furthermore, this study disclosed that the application of prevailing government grant/subsidy schemes significantly improved the economic viability of the three investment options as livestock, forestry and agroforestry options showed positive NPV and AEV values at the baseline assumptions and are therefore adjudged economically viable as they all met the decision rule criteria for investment acceptance. Forestry was the most viable option with the highest NPV and AEV, followed by pasture/livestock and agroforestry options. Unique contribution to theory, practice and policy: This study underscored the imperative need for policy makers to improve awareness of the benefits of grant incomes and address farmers’ concerns about the economic viability of livestock, forestry and agroforestry investments. The results of this research will help promote greater awareness of the economic value of trees in extensively grazed landscapes in the United Kingdom as well as provide a basis for future comparisons and analysis of farm programs and ecosystem service markets.

It is important to make a reasonable valuation of a company. A good valuation can make a difference in lots of aspects. In this research, the purpose of predicting valuation of Uber is to gain the future free cash flow and stock value of it, so that we can provide information for its future development strategy and put forward feasible business decisions, and then improve the future value of it. What’s more, we hope to use the information of Uber’s valuation to make investment analysis, understand its advantages and disadvantages, and help investors make better decisions. The reason why we choose Uber as a research object because it is a growing company that needs the right strategy and a lot of investments. Making valuation of Uber can help it attract investment and make stratagem. We use the discounted cash flow model to value Uber. We estimate the company’s income, expenditure, free cash flow and equity beta in the future by investigating and studying its data in recent three years and the data of a peer group. Finally, we get Uber’s optimistic price, pessimistic price and target price. All of the prices are higher than the present price which means it has a good development prospect and be good for investing.

THE AIMS OF THE PAPER This study attempts to explore the links between venture capital (VC) investments and the real option approach (ROA) with analyzing the characteristic features of the venture capital investments and their process. The real options can be examined as a way of thinking and evaluation method and the study’s aim is to show that real option approach can provide an answer to the valuation challenges of venture capital investments. METHODOLOGY The choice of the appropriate valuation method requires consideration of its conditions of application, which, in the case of real option theory, result from the examination of uncertainty, flexibility and irreversibility. The venture capital investments are characterized by a high degree of uncertainty and risk, which can also be traced back to the provision of financing to innovative, early-stage companies. Real option theory also provides venture capital investors with professional experience through their active role in decision-making. The study evaluates a Hungarian start-up company venture capital investment with the help of a traditional discounted cash flow method and two real option valuation models: Black – Scholes model and binomial pricing model. Then a sensitivity analysis is prepared to analyze the value driver effect on option value and a volatility analysis to verify the importance of high-degree of uncertainty in real option valuation. MOST IMPORTANT RESULTS The paper concludes that the option-based valuation methods are more suitable for evaluating venture capital investments than other approaches such as the discounted cash flow methods, and the embedded flexibility can be determined by the real option approach. The binomial pricing model points out the advantages of staging investments with the higher real (call) option value. Besides the real option valuation, the sensitivity analysis shows a positive effect of the present value of the underlying assets, the time to maturity, the risk-free interest rate and volatility on the call option value. The analysis of the volatility emphasizes the importance of the degree of uncertainty in real option valuation. RECOMMENDATIONS The real option approach ensures proper evaluation of venture capital investment, avoiding the undervaluation and taking advantage of staging and timing investments in practice. Acknowledgment: Supported by the UNKP-19-3 New National Excellence Program of the Ministry for Innovation and Technology.

Residual income valuation was already known and used in valuation theory and practice previously, however, the method has been subject to increasing attention in the past decades. By comparing the discounted cash flow method and the residual income model, this paper seeks to answer the question of what practical implications the difference in theory results in. the discounted cash flow method continues to be widely popular in literature and international practice, however, it may give rise to flawed results in certain cases. with the help of specific business examples, the study highlights that in such cases, the risks of under or overestimation can be mitigated with the help of the rim model. the largest benefit of the residual income model compared to the dcf method is that instead of deriving the value solely from the future, it gives a central role to the already known book value, and the speculative value – determined based on the accounting income – plays a less significant role in the course of valuation.

The enormity of costs associated with long-term assets and the length of exposure to risk of such investments makes it essential to properly evaluate capital budgeting decisions before embarking on them. The estimation of cash flows of uncertain future period itself is problematic and to add a complex technique of project evaluation that will require trial and error could be frustrating. This study is to simplify the estimation of Internal Rate of Return (IRR) without going through the rigours of trial and error process. This study is a method article on the estimation of IRR. The study allows the estimation of IRR even when net present value at two levels are positive or the two are negative instead of the use of interpolation. Investments analysists were advised to properly evaluate projects so that investors will source for funds where the interest rate is lower than the projects’ IRR.

The traditional discounted cash flow (DCF) model is generally used to estimate the present value of an enterprise or its equity based on expected future parameters such as cash flows, growth rate a...

Purpose The purpose of this paper is to assess model risk with regard to wind energy output in monthly cash flow models for the purpose of valuation and risk assessment of wind farm investments, where only a few approaches exist in the literature. Design/methodology/approach This paper focuses on the risk-return characteristics of this investment from the perspective of private and institutional investors and takes into account several risks, in particular the resource risk related to the uncertainty of the monthly wind energy produced. To this end, this paper presents different approaches for modeling monthly wind power output and assesses the impact of three selected models with different properties on the investment’s risk-return characteristics by means of a stochastic discounted cash flow model. In addition, the model considers the possibility of a joint operation of the wind farm with a pumped hydro storage system to reduce risk and improve profits. Findings The results show that the (non-)consideration of seasonality of the monthly wind energy produced considerably influences the risk-return characteristics, but that principal developments dependent on input parameters and model variables remain similar. Originality/value This paper contributes to the literature by presenting different approaches for modeling the monthly wind energy produced based on direct models of the wind energy output, which are rare in the existing literature. Further, their impact on risk-return characteristics of a wind farm investment is analyzed, and thus, related model risk is assessed.

The study described in this article seeks to solve the problem of investment decisions in the current environment, where investor irrationality comes to the front and blinds traditional classical analytical tools. During the post-crisis period it becomes a problem not only for Russian valuation analysts but globally as well. The present study uses behavioral finance methodology to solve this problem. To illustrate the solution, we used the discounted cash flow valuation techniques on a huge amount of on-sale Russian businesses and then applied quantitative financial solution methods to process the multiple results. TOPICS:Private equity, factor-based models, developed markets Key Findings • The article provides its reader with a strict, consistent and interconnected analytical instruments to measure how sentiments have an influence on prices and lead to different interpretations of risks and returns in behavioral finance theories. • The reader can take away from the methodology described in the article how sentiment is reflected in the stochastic discount factor. • After reading the article the reader has the illustrated on a particular M&A market methods of implementation of the stochastic discount factor-based behavioral pricing theory.

Most companies rely heavily on earnings to measure their financial performance, but earnings growth has at least two important weaknesses as a proxy for investor wealth. Current earnings growth may come at the expense of future earnings through, say, shortsighted cutbacks in corporate investment, including R&D or advertising. But growth in earnings per share can also be achieved by “overinvesting”—that is, committing ever more capital to projects with expected rates of return that, although well below the cost of capital, exceed the after‐tax cost of debt. Stock compensation has been the conventional solution to the first problem because it's a discounted cash flow value that is assumed to discourage actions that sacrifice future earnings. Economic profit—in its most popular manifestation, EVA—has been the conventional solution to the second problem because it includes a capital charge that penalizes low‐return investment. But neither of these conventional solutions appears to work very well in practice. Stock compensation isn't tied to business unit performance, and often fails to motivate corporate managers who believe that meeting consensus earnings is more important than investing to maintain future earnings. EVA often doesn't work well because increases in current EVA often come with reduced expectations of future EVA improvement—and reductions in current EVA are often accompanied by increases in future growth values. Since EVA bonus plans reward current EVA increases without taking account of changes in expected future growth values, they have the potential to encourage margin improvement that comes at the expense of business growth and discourage positive‐NPV investments that, because of longer‐run payoffs, reduce current EVA. In this article, the author demonstrates the possibility of overcoming such short‐termism by developing an operating model of changes in future growth value that can be used to calibrate “dynamic” EVA improvement targets that more closely align EVA bonus plan payouts with investors’ excess returns. With the use of “dynamic” targets, margin improvements that come at the expense of business growth can be discouraged by raising EVA performance targets, while growth investments can be encouraged by the use of lower EVA targets.

Rainwater harvesting systems (RWHSs) are increasingly employed to reduce the impact of water scarcity in urban buildings. Implementation depends on their financial feasibility, which is generally assessed using discounted cash flow methods. However, these techniques do not consider uncertainties in demand, rainfall, and water tariffs, which can have considerable effects. This work aims to apply real options analysis (ROA)—which evaluates options by establishing ta value for flexibility—to determine the feasibility of RWHSs. A case study incorporating management flexibility was conducted in three university buildings; it showed that uncertainty can present a strategic opportunity based on the possibility of RWHS expansion. The traditional net present value (NPV) and option value were calculated and compared with the result that ROA increased the NPV by more than five times. Thus, it was confirmed that options pricing increases projects’ values and presents opportunity gains for investments, especially when NPV without flexibility is close to zero. With ROA, systems that do not appear to have economic returns with conventional analysis may become feasible. Therefore, ROA is expected to replace conventional methods in RWHS investment decisions, as it can incorporate uncertainties, making the systems more economically attractive.

PurposeThe purpose of this paper is to present a model to value leveraged firms in the presence of default risk and bankruptcy costs under a flexible firm’s debt structure.Design/methodology/approachThe authors assume that the total debt of the firm is a combination of two debt components. The first component is an active debt component which is assumed to be proportional to the firm’s value. The second one is a passive predetermined risk-free debt component. The combination of the two debt categories makes the firm’s capital structure more realistic and allows us to include flexibility into the firm’s debt structure management. The firm’s valuation is performed using the discounted cash flow technique based on the weighted average cost of capital (WACC) method.FindingsThe model can be used to define active debt management strategies that can induce the firm to deviate from its capital structure target in order to preserve debt capacity for future funding needs. The firm’s valuation is performed by using the WACC method and a closed form valuation formula is provided. Such a formula can be used to value costs and benefits of financial flexibility.Research limitations/implicationsThe proposed approach provides a good compromise between mathematical complexity and model capability of interpreting the various economic and financial aspects involved in the firm’s debt structure puzzle.Practical implicationsThis model offers a realistic approach to practical applications where real financing decisions are characterized by a simultaneous use of these two debt categories. By comparing costs and benefits deriving from using unused debt capacity for future funding needs, the model provides a quantitative support to investigate if financial flexibility can add value to firms.Originality/valueTo the authors knowledge, the approach the authors propose is the first attempt to build a valuation scheme that accounts for firm’s financial flexibility under default risky debt and bankruptcy costs. Including financial flexibility, this model fills an important gap in the literature on this topic.

This article provides an evaluation of the commercial viability of the suborbital tourism market while considering the large uncertainties in the current demand predictions. Since it is un...

One of the main challenges in valuing an option where the underlying is an infrequently traded ‘real’ asset, such as a mining project, is the complexity and potential bias inherent in determining the volatility of its operating cash flows. This, of course, is not the case for frequently traded assets (e.g. shares of a mining company), where the volatility, i.e. the annualised standard deviation of daily price changes, captures the effects of both market risks (i.e. commodity prices and exchange rates) and private/project risks (i.e. reserves and grades, metal recoveries, variability of capital and recurrent costs etc.). In addition, most real option analysis papers feature simplified and to some degree unrealistic examples. This is particularly unhelpful where alternative investment options inevitably lead to different levels and timing of significant depreciation and amortisation charges against revenue, often the main or even the only source of cash flows, and to different tax liabilities, resulting in very different cash flow patterns and therefore project values. These issues have contributed to the low level of adoption of real option analysis by the mining industry. This paper makes empirical use of a realistic discounted cash flow model of a copper mine to compare the results obtained by various real option analysis approaches. It concludes that both the positive bias inherent in using an estimate of volatility aggregating the effect of all sources of uncertainty and, to a degree, modelling complexity can be circumvented by using real option analysis approaches, such as decision trees or Monte Carlo simulation, that rely on the probability distributions of individual uncertain variables rather than aggregated forms of cash flow volatility, producing more accurate and generally more conservative real option values.

Renewable energies are a natural replacement for conventional or fossil fuel energy generation. One of these sources, wind energy, has exhibited significant cost reductions during the last decades. Even though this historical cost reduction trend is well known in the industry and in the academia, information on this cost trend and volatility has been scarcely incorporated in previous works, thus a natural concern arises when assessing their influence on the economic valuation of wind farms. Moreover, wind projects are modular in size and have a short time-to-market, providing a valuable managerial flexibility to defer investment under non-attractive market conditions, such as high development cost scenarios. Traditional evaluation tools often consider those scenarios, wrongly assuming that wind-developers would move forward with the project under such conditions. Accordingly, this paper analyzes the effect of incorporating both generation cost history and investment flexibility in the valuation of wind farms in the United States using Real Options methodology. Taking two decades of cost data and a reference wind farm, this “uncertainty-flexibility” effect is incorporated and valued, finding that the value of the wind project is 14.2% larger than the one neglecting such effect – where cost stochasticity and managerial flexibility are ignored. Therefore, traditional tools for project valuation, such as discounted cash flow and scenario analysis can no longer solely be used, as they do not properly account for the cost reduction trend, uncertainty, and managerial flexibility that a wind farm could face.

We model investor heterogeneity using different required returns on an investment and evaluate the impact on the valuation of an investment. By assuming no disagreement on the cash flows, we emphasize how risk preferences in particular, but also the costs of capital, influence a subjective evaluation of the decision to invest now or retain the option to invest in future. We propose a risk-adjusted valuation model to facilitate investors’ subjective decision making, in response to the market valuation of an investment opportunity. The investor’s subjective assessment arises from their perceived misvaluation of the investment by the market, so projected cash flows are discounted using two different rates representing the investor’s and the market’s view. This liberates our model from perfect or imperfect hedging assumptions and instead, we are able to illustrate the hedging effect on the real option value when perceptions of risk premia diverge. During crises periods, delaying an investment becomes more valuable as the idiosyncratic risk of future cash flows increases, but the decision-maker may rush to invest too quickly when the risk level is exceptionally high. Our model verifies features established by classical real-option valuation models and provides many new insights about the importance of modelling divergences in decision-makers risk premia, especially during crisis periods. It also has many practical advantages because it requires no more parameter inputs than basic discounted cash flow approaches, such as the marketed asset disclaimer method, but the outputs are much richer. They allow for complex interactions between cost and revenue uncertainties as well as an easy exploration of the effects of hedgeable and un-hedgeable risks on the real option value. Furthermore, we provide fully-adjustable Python code in which all parameter values can be chosen by the user.

The electricity market in Brazil is basically organized under two parts: the regulated market, where energy is traded through auctions, and the free market, where market participants freely negotiate the price and quantity of electricity. Although revenues obtained in the regulated market tend to be lower than in the free market, the auctions’ results show that investors still value the lesser degree of uncertainty associated with the regulated market. However, a growing interest in the free market by investors is recognized since the price of electricity tends to be higher. Therefore, this study investigates four free market price scenarios to assess the expected return for investors, using the traditional discounted cash flow approach complemented with Monte Carlo simulation to address market uncertainty. The study breaks new ground by capturing the weekly price fluctuations and including the price elasticity of demand of the free market. The results seem to indicate that the disclosure of the ceiling and floor price limits for the spot price can signal important information about the agents’ price expectation in the free market and can be used for investment project evaluation.

The purpose of the study described in this article is to solve the problem of investment decisions in the current environment where investor irrationality comes to the front and blinds traditional classical analytical tools. During the post-crisis period it becomes a problem not only for Russian valuation analysts but for global as well. The current study uses behavioral finance methodology to solve this problem. To illustrate the solution, we used the discounted cash flow valuation techniques on a huge amount of on-sale Russian businesses and then applied quantitative financial solution methods to process the multiple results. As it is shown in the article stochastic discount factor-based behavioral pricing theory is a construction set for skilled researchers. An instrument turned into the future. With the developed techniques with improved tools, new models and empirical testing at various markets it will be included in the product range of analytical databases and value assessment methods for businesses and other assets. As it is approved with the article’s data sentiments have an influence on prices and lead to different interpretations of risks and returns in neoclassical and behavioral finance theories. So behavioral finances and neoclassical finances give a different meaning to asset pricing and especially to correlation of risks and profits.

This study aims to determine intrinsic value of stock in companies listed on the Indonesia Stock Exchange in animal feed subsector in 2018 with the approach of free cash flow to firm (FCFF) and relative valuation based on price earnings ratio (PER) and price book value (PBV). The discounted cash flow (DCF)-FCFF valuation results show that the Charoen Phokpand Indonesia (CPIN) in pessimistic and moderate scenarios is overvalued, while in optimistic scenarios it is undervalued. Japfa Comfeed Indonesia (JPFA) shares are undervalued in all scenarios, and Malindo Feedmill (MAIN) shares are in overvalued condition in all scenarios. The PER valuation results show that CPIN shares in pessimistic and moderate scenarios are undervalued, while in optimistic scenarios, they are overvalued. JPFA and MAIN stocks in all scenarios are overvalued. The PBV valuation results show that CPIN’s stock in the pessimistic scenario is undervalued, while in the moderate and optimistic scenarios are overvalued condition. JPFA and MAIN stocks in all scenarios are overvalued.

The growth of any economy depends on the strong financial system. Capital market plays a significant role in channelizing the savings into an investment activity by providing the platform to the investors as well as the firms to raise money. There are various instruments available for investment activities globally. Every investor has an objective to diversify portfolio globally to minimize risk among foreign markets and companies. Investor has to acquire the necessary skills to analyze the stocks to make better investment decisions in order to create wealth maximization. Valuation of equity is pre requisite for intelligent decision making in choosing the right scrip for investment in deciding the true value or intrinsic value of a share. There are few methodologies to evaluate the valuation of stocks such as discounted cash flow method, dividend discounted model. In this backdrop, this paper made an attempt to evaluate the Skyworks Solutions, Inc. stock with free cash flow to equity (FCFE) method of valuation during the 2016 to 2019 and to determine the intrinsic value of the stock and results found to be undervalued.

Commodity businesses have particular conditions that make them interesting from a financial valuation point of view; they usually operate globally, and their values are largely derived from underground reserves such as oil and gold. In this chapter, I discuss two financial valuation approaches adopted by practitioners and financial analysts applied to businesses operating in the commodity business and the natural resources. In particular, I cover the traditional Discounted Cash Flow (DCF) approach and the option models, offering practical examples.

In the present highly cutthroat global business environment, to uphold in the inflationary market, many times the retailer orders and stores large stock to get the edge over his competitors. At times, the size of the order is even larger than his storage capacity. Under such a situation, the retailer opts for renting the warehouse as an alternative to capacity augmentation. Considering the importance of such a scenario, the present research work develops the optimal replenishment policy for deteriorating items under inflationary conditions over a finite planning horizon in a two-warehouse facility using a discounted cash flow (DCF) approach. A DCF approach is used to estimate the value of an investment based on its future cash flows and attempts to figure out the financial implication of the opportunity cost in inventory analysis. The present model jointly optimizes the frequency of replenishments by minimizing the retailer’s total cost. Conclusively, a numerical example along with sensitivity analysis is carried to demonstrate the model characteristics.

Real estate, as the largest asset class globally, and the most visible proxy for the wealth of nations and of its main cities, is in a state of turmoil, with lots of uncertainty in world that will be marked by the most accelerated and profound recession in recent history—for most countries, the only comparable time dates back to the Great Depression of the 1930s and for others to the impact of the two world wars. Such is the water shedding impact of the pandemic that we could venture that for real estate—and for investing in it specifically—there will be a “before COVID” time and an “after COVID” one, with the all known unknowns that for sure will impact cities and their real estate and infrastructure with them. In order to understand what the future of real estate investing could be, in an “after COVID” world, it is useful to reconsider what was driving value and investing in a “before COVID” world, also on the basis of what we have been discussing so far on the future of cities. As a start, real estate investing is, as all other forms of investing, all about comparing a cash-out (a price, or the investment to be done on day one) with the net present value of all future cash-ins coming from the invested asset. Eventually, also a real estate asset can be evaluated on the basis of a discounted cash flow and taking into consideration a proper discount rate (associated with the level of riskiness of the specific investment, on top of other considerations regarding the prevailing risk-free rate of the economy and the risk premium the market would pay for macro asset classes, such as equities versus bonds, or real estate versus bonds). If also real estate can be associated with discounted cash flows, a good proxy for future payments is the attainable rent—hence rent over price (as a perpetuity) is a first index (or “rule of thumb”) that could be used to estimate the value of the investment. If this “rent/price” ratio could be associated with the expected return offered from the supply side of real estate assets, two other common ratios could be effectively describing the willingness to buy on the demand side and their relative price inelasticity given limited supply, as shown (through regression analysis applied to real estate historical series) in Table 7.1.

The cost of capital is the expected rate of return that the market requires in order to attract funds to a particular investment and is one of the most important concepts in finance. It may be described in simple terms as the expected return appropriate for the expected level of risk and is also commonly called the discount rate, the expected return, or the required return. There are three broad valuation approaches: (i) the income approach, (ii) the market approach, and (iii) the cost or asset-based approach. The country risk premia (CRPs), equity risk premia (ERPs), and relative volatility (RVs) can be used to develop cost of capital estimates for use in income approach-based valuation methods. Of the three aforementioned approaches to estimating value, only the income approach typically requires cost of capital estimates. The cost of capital is a critical input used in income approaches to equate the future economic benefits (typically measured by projected cash flows) of a business, business ownership interest, security, or intangible asset to present value. The income approach is most often applied through a discounted cash flow (DCF) model. A basic insight of capital market theory, that expected return is a function of risk, still holds when dealing with cost of equity capital in a global environment. Estimating a proper cost of capital (i.e., a discount rate) in developed countries, where a relative abundance of market data and comparable companies exist, requires a high degree of expertise. Estimating cost of capital in less-developed (i.e., “emerging”) economies can present an even greater challenge, primarily due to lack of data (or poor data quality) and the potential for magnified financial, economic, and political risks. A good understanding of cost of capital concepts is, therefore, essential for making global investment decisions.

Based on the insight that risk exposure as quantified in the consumption based asset pricing model (CCAPM) is linearly proportional to the cash flow growth rate, we introduce a discounted cash flow model with a time-varying expected return structure matching the implicitly assumed risk exposure at each future point in time in the valuation model, i.e. the assumed cash flow growth rate process. This reduces the range of reasonable valuations outcomes to useful levels, given that the linearly proportional term structures of potential cash flow growth rates and equity risk premia are complementary, offsetting variables in a discounted cash flow pricing model. In the same manner we elaborate a time-varying internal cost of capital (ICC) model that reflects the implied risk exposure at each future point in time and thus has a clear interpretation as an expected return process. This time-varying ICC model is superior to the constant ICC model in a Fama-MacBeth regression setting to predict future realised returns. And using the expected return of the time varying ICC model as control in a Fama-MacBeth regression of the profitability, the investment and the value factor, both the profitability and the value factor become insignificant in explaining future realised returns. The superiority and economic significance of the time-varying ICC model is further con firmed in a trading strategy with yearly rebalancing.

This dissertation is a compilation of four self-contained research papers that contribute to the literature of financial economics. All papers are co-authored by Professor Didier Sornette, my thesis supervisor, and further, depending on the project, by other authors. While three papers presented in this thesis were submitted to leading, peer-reviewed journals and are either awaiting review or are on revise and resubmit status, one paper is work in progress (the respective status is shown in the references as well as on the paper title page). The papers as presented in the thesis can include additional material that goes beyond the versions submitted. Understanding the formation and dynamics of asset prices is essential for many regulatory, policy and investment decisions. Chapter 2 and 3 of this dissertation aim to cast light into the dynamics of asset prices in the presence of two feedback effects, option markets and circuit breakers, using relative pricing models. Chapter 4 presents an absolute asset pricing model that provides a framework on how to correctly value firms in the presence of high clash flow growth. First, chapter 2 presents the discussion of a feedback effect between markets, namely from the options market onto the underlying’s market. We show that if the option market makers (OMM) hedge a larger share of their position compared to option market takers (OMT), this leads to a net delta hedge demand in the spot market. And due to liquidity effects (price impact), this mechanically leads to an increase or decrease in the underlying’s price volatility and a distortion of the underlying’s drift, depending on the positioning of the option market. We describe this dynamic with a relative pricing model, relative to the price without option hedging. Then we focus on the impact of option hedging on the spot markets volatility in the foreign exchange (FX) market. We use trade repository data to estimate the net positioning of the OMM in the FX options market and with it her delta hedge demand in the spot market. We find the OMM to be short gamma on average (implying she has a short option positioning on average) and thus the volatility to be increased by delta hedging of the OMM. Next, we an- alyze the impact of option hedging on the price stability. Using theoretical arguments as well as simulations, we show that the probability for drift bursts, i.e. explosive directional price moves, can be increased or decreased due to option positioning, depending on the option parameters and delta of the OMM. Using option positioning data for the GameStock stock, we document that there are indeed instances where explosive trends due to hedging were more likely in the first quarter of 2021, during which the stock showed exceptional price instability. Second, chapter 3 presents the discussion of a feedback effect that stems from the market architecture of exchanges, i.e. the price dynamics of so called circuit breakers (CB). A price-based CB for example is a trading halt imposed by an exchange after the price drops below (or rises above) a pre-specified value within a trading session. The rational behind a CB mechanism is that it gives traders time to calm down, interact with their counterparts and rethink their trading decision. Given that investors are continuously forming anticipations, their tactical positioning in the presence of the CB may lead to feedback of the CB on the price itself. We model the price dynamic under a CB using a relative pricing model, relative to the price without a CB, in a closed-form setup, in which the investors’ anticipation of the probability of a halt feedbacks on the price. In a general stochastic financial framework, this leads to coupled integral and stochastic differential equations. Our theory confirms two observations of this field for price-based CBs, namely an increased price volatility prior to the trigger and a negative effect of attracting the price to the CB level (known as the magnet effect). As our framework generalises to other CB mechanisms, we can then suggest a new CB design which minimises the adverse effects of a price-based CB. We e.g. show that a trading halt that is conditioned on a pre-specified volatility level, instead of a price level, mitigates the side effects. Third, chapter 4 contributes to the discipline of absolute asset pricing. We aim to refocus the discussion around what could be loosely referred to as an expected return factor. Motivated by economic intuition and empirical insights from the consumption-based capital asset pricing model we show that the expected return on a firm level has a linear relationship to the firm’s cash flow growth level. With that we argue that the discount rate should reflect this linear relationship and should thus have the same term structure as the assumed cash flow growth rate process. Based on that we first introduce a discounted cash flow (CDF) model with a time-varying discount rate matching the assumed cash flow growth rate process. This important feature greatly enhances the value of a DCF model, as the valuation is less sensitive to the cash flow growth rate process assumptions, as the discount rate is proportional to the assumed cash flow growth rate term structure, such that these two naturally complementary variables interact to massively reduce the range of reasonable valuation outcomes. Second, using the same time-varying discount rate in an internal cost of capital (ICC) model, we elaborate that the corresponding time-varying internal rate of return allows for a straightforward interpretation as investment return of a buy and hold strategy, compared to e.g. a constant ICC model, which by construction is a constant compound return. We show that our expected return proxy is superior in explaining realised returns compared to a constant internal rate of return, and even renders well known linear factors, which can be motivated from theory, insignificant. Last, the economic significance is confirmed in a trading strategy with yearly rebalancing.

Our knowledge of discount rates plays an important role both in the discounted cash flow decision-making process and in the later phases of a project’s lifetime. It is useful than both for management and cash-flow monitoring purposes at operating stages. Investors putting money into power generation projects expect an appropriate rate of return to compensate them for a minimum acceptable real return available in the market (risk-free rate of interest) and the project’s specific risk. Due to its essential nature in the financial and economic evaluation of projects (it is the only parameter that reflects the risk), it is reasonable to assume that investors would also be interested in constituent components of that indicator. The discount rate is one parameter in the discounted cash flow analysis that takes into account the risk of a venture. Further, the previous research in this area has focused mainly on the dimension of this variable, and the structure of this parameter has not been dealt with any other studies. The proposed idea of this study met the expectations of the industry—it aimed to present a typical project implemented in the energy industry, a relatively simple methodology that allowed estimating the components within the cost of equity capital of the enterprise. In the power generation sector, one can find various types of discount rates—assessed for multiple technologies, at different development stages, and expressed differently. Owing to the know-how and decades-long experience, coal-fired power projects’ remarks may be a good benchmark for alternative low carbon technologies. That is why, in this work, a discount rate for valuing investment in new coal-fired power projects was evaluated. This assessment was made on the “bare-bones” assumption, meaning evaluations at 100% equity, after-tax, in constant (real) currency units. The analysis of the discount rate structure was performed by applying the procedure of the classical sensitivity analysis having the accuracy of key input parameters. Finally, the risk factors within the risk-adjusted discount rate were calculated. The obtained results showed the importance of individual risk factors within the risk-adjusted discount rate used in coal energy projects, which would enable a more pragmatic approach to controlling this parameter by decision-makers and understanding the risk.

The Discounted Cash Flow (DCF) method is probably the most extended approach used in company valuation, its main drawbacks being probably the known extreme sensitivity to key variables such as Weighted Average Cost of Capital (WACC) and Free Cash Flow (FCF) estimations not unquestionably obtained. In this paper we propose an unbiased and systematic DCF method which allows us to value private equity by leveraging on stock markets evidences, based on a twofold approach: First, the use of the inverse method assesses the existence of a coherent WACC that positively compares with market observations, second, different FCF forecasting methods are benchmarked and shown to correspond with actual valuations. We use financial historical data including 42 companies in five sectors, extracted from Eikon-Reuters. Our results show that WACC and FCF forecasting are not coherent with market expectations along time, with sectors, or with market regions, when only historical and endogenous variables are taken into account. The best estimates are found when exogenous variables, operational normalization of input space, and data-driven linear techniques are considered (Root Mean Square Error of 6.51). Our method suggests that FCFs and their positive alignment with Market Capitalization and the subordinate enterprise value are the most influencing variables. The fine-tuning of the methods presented here, along with an exhaustive analysis using nonlinear machine-learning techniques, are developed and discussed in the companion paper.