capital investment decision matrix tool

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Capital investment decision matrix tool progress advance mortgage and investment

Capital investment decision matrix tool

For Inkling to achieve early-stage success, they would have to successfully overcome all four of these risks—any one of them could kill the company. Therefore, to calculate the chance of Inkling achieving early-stage success, we take the product of the small risks. In other words,. As this example illustrates, small risks add up quickly in early-stage investing. Early-stage success is just the first step in a long journey to building a meaningful company. Inkling faced an additional obstacle: a pragmatic customer would first have to buy an iPad or a tablet computer of some sort.

As a result, we assessed only a 40 percent probability that Inkling would be able to overcome the market risks required for crossing the chasm figure 2 , row 1. We also assessed the specific product, team, and financial risks inherent in moving from early-stage development to market success, and taking the product of all four risks, we calculated Inkling had a 24 percent chance of crossing the chasm figure 2.

For many investors, this assessment would be the kiss of death— however, this evaluation is only one piece of a larger puzzle. In early-stage investing, large risks can be outweighed by even larger returns. If Inkling successfully crosses the chasm, they become a going concern serving a niche market such as medical schools or California state universities.

To achieve mass-market success, Inkling must overcome another set of operational and financial risks figure 3. We assessed a 60 percent probability of overcoming the market risks. Product, team, and financial challenges to mass-market success also existed figure 3 —scaling production, scaling a sales organization, establishing appropriate revenue sharing relationships—but we felt all were manageable.

Taken together, we saw these combined risks translating into a 37 percent chance Inkling would be able to overcome the hurdles and achieve success in the broader market for educational textbooks. If Inkling achieved mass-market success, what share of this market could Inkling capture and sustain? In The Gorilla Game , 10 Geoffrey Moore describes a framework for understanding the competitive dynamics in high technology markets.

Our conclusion was that if Inkling became a mass-market player, they would have a 25 percent chance of becoming the market leader, a 50 percent chance of being a challenger, and a 25 percent chance of being an also-ran. All of these risk assessments from early stage through mass-market share can be summarized in a decision tree figure 4.

Each node in the tree represents the product of all risks for each life stage. The first node shows the 58 percent chance of early-stage success that we computed as well as the corresponding 42 percent chance of failure. The numbers at the right side of the branches show the ultimate probability of each scenario. For example, Inkling has a 1 percent chance of achieving the topmost branch of market leadership by being on the topside of each of these branches.

The bottom two branches represent no money back to the investors; in this sense, Inkling has an 86 percent chance of failure. This sounds terrible, of course, but this is the nature of nature of early-stage investing. It is a high-risk undertaking, but if you get it right, the rewards can be tremendous. The top four branches show that Inkling has a 14 percent chance of becoming a going concern and returning some money back to investors.

It looked bad for Inkling, but remember: Inkling had a visionary entrepreneur and a large market ripe for disruption. The key now was to determine how big an Inkling success could be. We then moved on to the grade school or K market, which Matt thought would require a different business model. Where selling individual textbooks to individual students suited the college market, Matt believed selling a suite of textbooks and charging on a per-student basis would be a better fit for K customers.

Our conversation continued through revenue, earnings, exit multiples, dilution, and so on. Every important concern or potential driver of value had a spot on the map. On the surface this may look like just another block diagram, but it precisely specifies a quantitative decision model. Each oval represents an uncertainty with an underlying probability distribution. Each rectangle represents a decision with an underlying set of choices.

The eight-sided node represents the value we were using to base our choices. The arrows represent influences, showing the mathematical relationships between the nodes. Our next step was to quantify all of the uncertainties. No single number forecast for adoption of a new technology is credible. Frankly no single number forecast for anything five years in the future is likely to be credible even for the most mature businesses. This is why most venture investors have only limited use for models in their decision-making.

To de-bias these assessments and ensure that assessments are consistent across all uncertainties, we use specific techniques such as back casting. What would be a surprisingly low percent of adoption? What happened? As an expert in the field, Matt should be able to generate thoughtful and compelling answers, and his rationale provided an added layer of insight and richness to our understanding of the risks.

This same exercise was repeated to capture the high side of the range. We used the ranges to test our decision model, producing a sensitivity analysis showing which factors mattered the most figure 6. The horizontal scale at the top is the probability-weighted multiple on investment PWMOI —the metric we care most about. Along the left side of the chart, we listed all the variables from the model i. For example, the base case for Tablet Adoption is 25 percent.

We then repeated this exercise for each uncertainty, swinging its value from low to high while holding all other uncertainties at their base value. We recorded the swings in the form of bars and organized them in a Pareto sense from the largest to smallest, as in figure 6. The value of an Inkling investment varied significantly based on the outcome of these uncertainties, hence we focused our due diligence on these issues. More often than not , however, the precise value within a range did not change the attractiveness of an Inkling investment.

For example, Pre-Money Valuation is at the bottom of figure 6. In other words, Inkling could have been on the low side or the high side of most of these ranges and the attractiveness of the investment would not materially change. More precisely, these uncertainties were not material to our decision in that a more accurate assessment would not change our decision to invest or not invest.

There was no decision value in collecting more information, allowing us to confidently de-prioritize these factors in our diligence. Returning to our decision tree, we added the values of each scenario from our value analysis in figure 6 to produce a scenario analysis figure 7. However, the important number is this multiple discounted by the chance that it would happen.

Therefore this Market Leader scenario contributes 4. While this was short of our 10x goal, we do not blindly follow the numbers. The purpose of this exercise is to clarify our thinking. We make decisions based on our judgment, incorporating both quantitative and qualitative considerations. As we analyzed Inkling from many different perspectives we found a coherent, compelling story. The iPad is a runaway hit. Apple sold over 11 million iPads during its September quarter and over 40 million units since its launch 18 months ago.

Inkling currently has over 80 titles available and partnerships with most major textbook publishers in the United States, giving them access to the majority of currently used textbooks. By Fall , they should have hundreds of titles available. Inkling seems to be a home run in the making. As I look back at this investment two years later, I think we called it about right. That combination is the heart of most successful venture investments.

Decision analysis helps people make faster, more informed decisions. At Ulu Ventures, it helps us structure judgment and quantify intuition in forms that can be easily discussed and tested with logic and evidence, driving clarity of thought through a disciplined process. Decision analysis helps us learn faster—about the risk and return of individual investments and also about how to practice the craft of venture capital.

This framework focuses our attention on what matters most. Anchoring and other biases are reflected in model results that are out of line with our intuition. Our first step is to review the model for errors—if the model checks out, we adjust our intuition. Our framework also naturally improves over time; each time we evaluate a company, we refine our framework and add to our set of benchmark data. Whether we invest or not, we share our analysis with our entrepreneurs.

About 20 percent of the time, they change their business model or target market based on our analysis. Most of the time, entrepreneurs walk away with a deeper understanding of their business model. These conversations also help transition us from a diligence role focused on our needs as an investor to a supporting role focused on the needs of our entrepreneurs. While intuition and judgment will always underlie successful venture capital investing , I believe that venture firms will produce better and more consistent results by using disciplined frameworks to assist the investment process.

Frameworks act like maps, helping the venture investor see all relevant aspects of a decision in context. Like a well-drawn map, a disciplined framework can help investors plan where to go next and how to get there, which is particularly important when the terrain is difficult or confusing. I hope other VCs will adopt decision analysis or a similar framework as part of their investment processes. I also find that it has no significant effect whether new shares are issued Retention payoff-based cost per day open regression equations: Application in a user-friendly decision support tool for investment analysis of automated estrus detection technologies.

Assessing the economic implications of investing in automated estrus detection AED technologies can be overwhelming for dairy producers. The objectives of this study were to develop new regression equations for estimating the cost per day open DO and to apply the results to create a user-friendly, partial budget, decision support tool for investment analysis of AED technologies.

In the resulting decision support tool, the end user can adjust herd-specific inputs regarding general management, current reproductive management strategies, and the proposed AED system. Outputs include expected DO, reproductive cull rate, net present value, and payback period for the proposed AED system. Net present value in scenarios 1 and 2 was always positive, indicating a positive investment situation.

This study synthesizes the extant literature to derive an integrative developmental framework for IT business cases that can be applied to diagnose the feasibility of technological investments. We then construct a theoretical model that postulates the impact of IT business case elements on the in We then construct a theoretical model that postulates the impact of IT business case elements Subsequently, our theoretical model is subjected to empirical validation through content analysis of IT business cases developed for municipal e-government projects.

Findings indicate that the richness of the richness of business cases translates When making international capital budgeting decisions , energy companies are often faced with capital and organisational constraints. The constraints may be real or management imposed.

In addition, when entering into a new country or region the companies will incur fixed new area costs that must be considered before investment approval. The decision problem is therefore not a linear problem where the standard net present value rule applies, but a non-linear problem of selecting the combination of projects with the maximum aggregate net present value.

New project investments will therefore be selected based on the size of the net present value often referred to as financial volume or materiality compared to the projects' use of capital and scarce personnel and organisational capacity. Consequently, projects with a positive net present value, but with low materiality, may not be approved. The portfolio choice has a parallel to the company's choice of core areas.

Instead of complex portfolio models, the companies often apply simpler allocation mechanisms, e. Analysing petroleum cases, we compare the allocations decisions generated by portfolio models and simpler mechanisms. We also discuss the implications of this capital allocation pattern for governments' design of tax systems and license conditions. Options theory and strategic investment decisions. The possible use of options pricing theory for evaluating long-term capital investments is discussed.

Using the Black and Scholes option pricing model, five variables were evaluated for a hypothetical oil sands project. A sensitivity analysis on these variables can provide management with information on how best to influence the option value. A more in-depth analysis could provide valuable information about strategic choice for large projects.

Evidence from Oman. Humans are believed to be rational decision makers and documentary evidence proves a significant heterogeneity across individuals when it comes to investment decision making and risk bearing. The study is an attempt to explore and understand the heterogeneity of investment decision when it comes to gender behavior with focus on women.

The aim of this research is to explore role of gender in investment decision making and to identify the points of difference between the two genders with respec A decision support tool for the analysis of pricing, investment and regulatory processes in a decentralized electricity market. After the liberalization of the electricity generation industry, capacity expansion decisions are made by multiple self-oriented power companies.

Unlike the centralized environment, decision -making of market participants is now guided by price signal feedbacks and by an imperfect foresight of the future market conditions and competitor actions that they will face. In such an environment, decision makers need to better understand long-term dynamics of the supply and demand sides of the power market. In this study, a system dynamics model is developed, to better understand and analyze the decentralized and competitive electricity market dynamics in the long run.

The developed simulation model oversees a year planning horizon; it includes a demand module, a capacity expansion module, a power generation module, an accounting and finance module, various competitors, a regulatory body and a bidding mechanism. Public regulators and power companies are potential users of the model, for learning and decision support in policy design and strategic planning.

Results of scenario analysis are presented to illustrate potential use of the model. More specifically, I exploit the time-series variation in the domestic theatrical release of comedy movies as a natural experiment for testing the impact that happy mood proxied by weekend comedy movie attendance has on investment in risky assets My hypothesis rests upon the evidence that individual investors are more likely to ponder trading decisions during the weekend and trade on Mondays.

To control for unobserved factors that may contemporaneously affect movie Using a sample of data from to , I estimate that an increase in comedy attendance on a given weekend is followed by a decrease in equity returns on the subsequent Monday, which The evolution of investments decision mode in China's telecommunication. This essay analyzes the data of Chinese telecommunication market, telecommunication investments and investment benefits over the past 20 years.

On the basis of these data, the essay reviews Chinese changing telecommunication policies and discusses the major events in the course of China's telecommunication development. It is argued that telecommunication policies, regime backgrounds and market demand characteristics have a significant impact on investment decision mode in telecommunication industry.

The evolution of network investments decision mode in China's telecommunication has corresponded to the transformation of these key factors. Considering the special events in the development of Chinese telecommunication as divisions, the essay discusses three stages of the evolution of investments decision mode in China's telecommunication.

With the firm environment and problems that Chinese telecommunication operators have been facing since analyzed. This investment decision mode will result in increase of the investment profit with limited investment capital.

The main procedure of profit-oriented investment decision mode is set out, which is abstracted to a mathematical model eventually. Aggregate capital needs is a new conception and gives a new viewpoint to investment project decisions. The paper defines the special content of aggregate capital needs, and compiles an index number for it.

The analysis widens knowledge regardin Real Options Analysis of Electricity Investments. This thesis utilizes real options analysis for evaluating investment opportunities in the electricity sector. It also formally tests how investors in hydropower plants have included uncertainty when considering their investment opportunities. The real options method applies financial options theory to quantify the value of management flexibility and is chosen due to three important characteristics of investments in the electricity sector.

First; the investment is completely or partially irreversible, second; the investor can choose when to invest in the facility, and third; there is uncertainty in several factors affecting the cash flows of the investments.

Factors of uncertainty include the development of electricity prices, policies, technological advances, and macroeconomics measures. Four papers are included in this thesis. Paper 1, Upgrading hydropower plants with storage: Timing and capacity choice, presents a valuation framework for deciding when to upgrade an existing hydropower plant and which capacity to choose.

The second paper, Transmission capacity between Norway and Germany: A real options analysis , sheds light on when two electricity markets, in this case Norway and Germany, should be connected through a sub sea cable. The investor can choose when to invest and the capacity of the cable, and may also choose to invest sequentially. Paper 3, Optimal timing and capacity choice for pumped hydropower storage, investigates when investment in a pumped hydropower plant with storage should be undertaken and what the capacity of the facility should be.

Whereas the three first papers investigate investment opportunities, Paper 4, Uncertain climate policy decisions and investment timing: Evidence from small hydropower plants, studies when investors in small hydropower plants chose to invest. The analyses disclose whether the net present value approach or the real options method best describe the investment decisions made by the investors. Viewing investment. Applying real options in investment decisions relating to environmental pollution.

Lin, Tyrone T. E-mail: tjlin mail. This study focuses on how to assess the optimal environmental investment decisions under economic and ecological uncertainty, and establishes the continuous time model using the real option approach to optimize environmental pollution policy. Unlike traditional cost benefit analysis , this work extends the model of [Pindyck, R. Optimal timing problems in environmental economics. Journal of Economic Dynamics and Control 26 , ], and attempts to identify the storage threshold of pollution stocks and the optimal timing for implementing environmental pollution decisions.

The financial management as a tool for development investment decision. Full Text Available Investment decisions , which influence the investment of financial resources to achieve economic, non-economic, or of both objectives and effects in the future, the central subject of financial management. Using the methods of financial mathematics can predict the effects of the investment which is from the standpoint of efficiency ratings are expressed in the form of cash future income.

Periods, the investments and the use of investment , may be the same or different lengths. From an economic standpoint it is desirable that the period of the investment is short, and the economic effects of the eyelids investments as long as possible. For an investment is said to be cost-effective or cost-effective if the current value of the investment is less than the present value of income from investments.

Decision -making process in investment projects. We present projects evaluation approaches in what decision should be based. We try to understand what we have to take into account in a project analysis , knowing that we have to consider much unmeasured aspects, like non non-financial areas. We verify how all aspects are used and analysed in the project appraisal.

We also desire to understand if companies have adequate tools and methods to correctly analyse and to take decisions in a project evaluation. In this study we identify several as A dynamic decision model for portfolio investment and assets management. This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level.

The paper generalizes Markowitz's portfolio selection theory and Sharpe's rule for investment decision. An analytical solution is presented to show how an institutional or individual investor can combine Markowitz's portfolio selection theory, generalized Sharpe's rule and Value-at-Risk VaR to find candidate assets and optimal level of position sizes for investment dis- investment. The result shows that the generalized Markowitz's portfolio selection theory and generalized Sharpe's rule improve decision making for investment.

Characterizing uncertain sea-level rise projections to support investment decisions. Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis.

We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: 1 Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and 2 Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment?

We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments.

Full Text Available Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making.

Understanding the impact of business cases on IT investment decisions : An analysis of municipal e-government projects. We then construct a theoretical model that postulates the impact of IT business case elements on the. Assessing survivability to support power grid investment decisions.

The reliability of power grids has been subject of study for the past few decades. Traditionally, detailed models are used to assess how the system behaves after failures. Such models, based on power flow analysis and detailed simulations, yield accurate characterizations of the system under study. However, they fall short on scalability. In this paper, we propose an efficient and scalable approach to assess the survivability of power systems.

Our approach takes into account the phased-recovery of the system after a failure occurs. The proposed phased-recovery model yields metrics such as the expected accumulated energy not supplied between failure and full recovery. Leveraging the predictive power of the model, we use it as part of an optimization framework to assist in investment decisions. Given a budget and an initial circuit to be upgraded, we propose heuristics to sample the solution space in a principled way accounting for survivability-related metrics.

We have evaluated the feasibility of this approach by applying it to the design of a benchmark distribution automation circuit. Our empirical results indicate that the combination of survivability and power flow analysis can provide meaningful investment decision support for power systems engineers. Geothermal power plant investment decisions. Interim report, June 1-November 30, Investment decisions for financing the construction of geothermal power plants are discussed.

Discussed here are the investment objectives of investor-owned electric utilities, municipal electric utilities, and potential third party financiers as determined from extensive reviews of literature, executive interviews and responses to mailed surveys. The framework is provided for a computerized quantitative decision model currently being developed at Technecon for investment and policy analysis applications.

Full Text Available The aim of the study is to measure influence of taxation while making financial decisions and predict it with the general application in Turkey. Except for equity returns of financial and negative capital institutions registered in Borsa Istanbul between and , those of all other businesses were calculated. Businesses were divided into for regions as stated in Tax Incentive Law according to the study.

As stated in Tax Incentive Law, the businesses whose costs of capital were divided into six regions where statistical analysis was made to determine whether taxation influenced financial decisions of the related businesses based on Tax Incentive Law or not.

Assessment of the findings within the study determined that businesses in 1 st, 2 nd and 3 rd regions were affected by taxation 5,69, 2,75 and 1,39 as means between and , respectively. Accordingly taxation load of businesses in 1 st region provinces was found to be heavier than those of businesses in other regions. Considering the Tax Incentive Law, it was found to be statistically important that taxation load of the related region should be taken into account in making any financial decisions.

In this respect, there is an impact of tax when one makes financial decisions. However, other relevant factors should also be considered. Investment appraisal using quantitative risk analysis. Investment appraisal concerned with investments in fire safety systems is discussed. Particular attention is directed at evaluating, in terms of the Bayesian decision theory, the risk reduction that investment in a fire safety system involves.

It is shown how the monetary value of the change from a building design without any specific fire protection system to one including such a system can be estimated by use of quantitative risk analysis , the results of which are expressed in terms of a Risk-adjusted net present value. This represents the intrinsic monetary value of investing in the fire safety system.

The method suggested is exemplified by a case study performed in an Avesta Sheffield factory. The problem with such NPV estimates is that they depend on projected future cash flows. If there are errors in those projections, then estimated net present values can be misleading a forecasting risk.

Accordingly, the paper discusses some organized ways of going about a what — if analysis. Its goal in doing so is to assess the degree of forecasting risk and to identify those elements that are the most critical to the success or failure of an investment. However, as we show in examples, as well as in the practical study, though what — if analysis really allows us to obtain the certain idea of degree of forecasting risk, it does not tell us what to do about the possible errors.

Investment timing decisions in a stochastic duopoly model. E-mail: giovanni. E-mail: flavia. E-mail: dominioni core. We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market e. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited.

The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost. The error of fixed strategies in IT innovation investment decisions. Allocating an IT Innovation budget to technologies in different maturity stages mature vs. Due to the dynamic innovation cycles with new emerging technologies, many IT innovation investment decisions follow a bandwagon behavior or fixed investment strategies.

Emotional Intelligence and risk taking in investment decision -making. We hypothesized that people with high trait emotional intelligence should be more willing, than people with low trait emotional intelligence, to accept risks when making an investment. Data supported a model in which trait emotional intell Investment decisions in environment of uncertainties integrated to the viability analysis of the distribution and transmission projects; Decisao de investimentos em ambiente de incertezas integrada a analise de viabilidade de projetos de transmissao e distribuicao.

Gazzi, L. In the economic and financial analysis , are considered the needs of the Regulator for the tariff recognition of an investment , using economic engineering techniques to evaluate the feedback of the invested capital but considering an uncertainty environment, where the best decision depends on exogenous variables to the traditional planning process.

In order to make viable the inclusion of the main variables of random behavior that condition the economic and financial performances of the analyzed alternatives for decision making, it was chosen the utilization of the methodology based on 'Real Options', which is an used technique in the financial market for some time.

Outsourcing of investment management is a growing trend among institutional investors. With a broad range of institutions using or exploring the outsourced chief investment officer OCIO model, portfolio size is no longer the determining factor driving the outsourcing decision. For all but the largest institutional investors--those with deep…. The decision making on mutual investment of thai investors The decision making on mutual investment of thai investors.

Journal of Fundamental and Applied Sciences. Journal Home The study was a research survey that used questionnaires to collect data from samples of Thai investors. Investment Decisions with Two-Factor Uncertainty. This paper considers investment problems in real options with non-homogeneous two-factor uncertainty. It shows that, despite claims made in the literature, the method used to derive an analytical solution in one dimensional problems cannot be straightforwardly extended to problems with two.

Full Text Available We propose in this study, to make an analysis of the influence of the investment decision on the return of the company. The goal of our research is the quantification of the influence of investment activity on profitability.

Of course, the realization of such research was possible only after close consideration of the opinions expressed in the relevant literature on this area. Our research aims to be a theoretical-applied one. It is based on comparisons we make between the two criteria for assessing investment projects namely: that of net present value VAN and internal rate of return RIR. By creating a suite of phase calculations, based on information from economic and financial documentation of corporate investments , we separated the influence of the policy investment decisions on profitability.

We are convinced that the most accurate determination of the influence of policy investment decisions on profitability helps the financial management, facilitating the process of adopting the most appropriate policy decisions that ultimately leads to the objectives formulated by the financial policy. The result of our research is the quantification of the influence of investment policy decisions of the firm on profitability.

Full Text Available As the banks have tightened lending requirements, companies look for alternative sources of external funding. One of such is bonds issue. Unfortunately, corporate bonds issue as a source of funding is rare in Lithuania. This occurs because companies face with a lack of information, investors fear to take on credit risk.

Investors, in order to avoid credit risk, have to assess the state of the companies. The goal of the article is to determine the most informative methods of credit risk assessment. The article summarizes corporate lending sources, analyzes corporate default causes and credit risk assessment methods. The study based on the SWOT analysis shows that investors before making an investment decision should evaluate both the business risk,using qualitative method CAMPARI, and the financial risk, using financial ratio analysis.

Modeling strategic investment decisions in spatial markets. Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models.

The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models.

The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly. Energiewirtschaftliches Inst. Peer effects in decision -making: Evidence from corporate investment. Full Text Available We show that peer effects influence corporate investment decisions.

We find that peer effects are more pronounced when firms have information advantages and the information disclosure quality of peer firms is higher, or if they face more fierce competition. When firms are industry followers, are young or have financial constraints, they are highly sensitive to their peers firms.

We also quantify the economic consequences generated by peer effects, which can increase firm performance in future periods. Innovation investment decisions : are post transition economies different from the rest of the EU? Rather, it is worth distinguishing between their decision to increase investment , reduce it, keep their investments at the same level or not invest in innovation activities at all.

To understand these decisions we develop and estimate models for post-transition and developed European countries employing multinomial probit. The analysis relies on responses of firms from 11 post-transition countries and firms from 18 European countries collected by the Flash Eurobarometer - Innobarometer survey. In transition countries, the higher the percent of turnover invested in innovation, the lower the probability of an increase in the future.

In the firms operating in developed economies, lower turnover from new products is related to the decision to decrease innovation investment in the future. Promoting energy efficiency investments with risk management decision tools. This paper reviews current capital budgeting practices and their impact on energy efficiency investments. The prevalent use of short payback 'rule-of-thumb' requirements to screen efficiency projects for risk is shown to bias investment choices towards 'sure bet' investments bypassing many profitable efficiency investment options.

A risk management investment strategy is presented as an alternative to risk avoidance practices applied with payback thresholds. The financial industry risk management tool Value-at-Risk is described and extended to provide an Energy-Budgets-at-Risk or EBaR risk management analysis to convey more accurate energy efficiency investment risk information. The paper concludes with recommendations to expand the use of Value-at-Risk-type energy efficiency analysis.

Decision analysis multicriteria analysis. For the simplest one the engineering judgement is generally enough and the use of a decision aiding technique is therefore not necessary. For some decisions the comparison of the available protection option may be performed from two or a few criteria or attributes protection cost, collective dose, For the more complex decisions , involving numerous criteria or for decisions involving large uncertainties or qualitative judgement the use of these techniques, even the extended cost benefit analysis , is not recommended and appropriate techniques like multi-attribute decision aiding techniques are more relevant.

There is a lot of such particular techniques and it is not possible to present all of them. Therefore only two broad categories of multi-attribute decision aiding techniques will be presented here: decision analysis and the outranking analysis. Full Text Available The investments represent the primary factor in the development strategy of an economic entity. The role of the investments begins with their purpose, meaning that the investments involve the increasing of a stock portfolio.

The research methodology that is approached in this article is based on the analysis of two factors: net present value and internal rate of profitability. Capital budgeting in an investment project that, without a prior analysis of the efficiency of such a decision , can lead to the total or partial loss of the invested capital.

An investment project is efficient if the net present value is positive and has a larger value. An investment project becomes more profitable as the value of the internal rate of profitability gets higher. If the two factors are correctly interpreted they lead to exactly the same conclusions regarding the determination of an investment profitability. We can conclude that the two efficiency factors are complementary, their simultaneous use leading to a better grounding of the investment decision than their separate use.

The effect of environmental information on investment allocation decisions. This paper focuses on the use of environmental information in investment decision making. The research approach employed is based on an experiment where three groups of final year finance students were asked to allocate investment funds between two companies based on financial accounts Hence, this has implications for how the potential value of environmental information is to be assessed.

Finally, experimental studies as a methodology seem to be better suited to indicate actual effects of different types of information on decision making The overall conclusion is that the qualitative environmental information affects short term allocation decisions , hence indicating a risk reduction potential of environmental information comparable Full Text Available The significance of investment is transparent in the world of competitive business.

Traditional costing systems in which their emphasizes are for short term savings rather than long term benefits have shown some lacking in providing accurate and reliable cost data for the investment decisions. Activity-based Costing ABC, which is developed to satisfy some of the weaknesses of the traditional costing systems, can provide valuable insights into the operating processes and come up with more accurate cost data.

In this paper, ABC is used to provide significant information for investment decisions. The adoption of ABC and EVA can represent a considerable change in the managerial thinking and to corporate strategies and business performance. Economic simulation to support investment decisions in pig farming. The study described in this thesis focuses on the development and use of a model that simulates the consequences of long-term investment decisions in pig farming.

The thesis is composed of six parts. Chapter 1 deals with a basic review of the literature on strategic planning under risk and. A multi-objective decision framework for lifecycle investment. In this paper we propose a multi-objective decision framework for lifecycle investment choice. Instead of optimizing individual strategies with respect to a single-valued objective, we suggest evaluation of classes of strategies in terms of the quality of the tradeoffs that they provide.

This "good practice" guide is aimed at anyone in higher education in England who is involved in making decisions on investments. It focuses on the principles to be followed, rather than the techniques of appraisal. The guide outlines the steps for developing an outline business case and then refining it into a full business case for the….

Using a group decision support system to make investment prioritisation decisions. This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system GDSS. While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group.

The paper develops the conceptual framework of decision -making, communication and group support, and de Investment sensitivity and managerial decision making behaviour of Indian firms. Full Text Available Contemporary models of the financial theory support the proposition that the stock prices should be fundamentally a reflection of the discounted value of earnings.

Given the imperfect information structure and market pressures, the Indian firms suffer from mispricing and as such the conventional robust theoretical models of agency conflicts cannot be refuted. This motivates us to examine the interrelation ship between the concerns for valuation and investment sensitivity. We use the earnings response coefficient ERC framework proposed by Ball and Brown for 11 key industries in India.

We find that the surpise in accounting earnings announcements is negatively associated with abnormal stock returns and the investment decisions taken by the firms are negatively sensitive to changes in investment opportunities. Full Text Available There is a worldwide trend towards rapidly growing defined contribution pension funds in terms of assets andmembership, and the choices available to individuals.

This has shifted the decisionmaking responsibility tofund members for managing the investment of their retirement savings. Prior research identifies that deficiencies infinancial literacy is one of the causes of inertia in financial decision -making and findings from internationaland Australian studies show that financial illiteracy is wide-spread. Analysis of stage- investing strategy in equity financing market. Stage- investing strategy is a primary measure to mitigate asymmetric information during equity investment.

This paper attempts to investigate the problem faced by equity investors wishing to make optimal investment decision under stage- investing strategy. A serial investment-decision making model will be designed to help investors to take the best choice. The Department of Energy DOE currently faces a difficult task in the disposition of the numerous excess or to-be excessed facilities owned by the Department. Many of these facilities are in various physical conditions and contain potentially hazardous nuclear, chemical, radiological or industrial materials left behind as a byproduct of nuclear weapons production, nuclear powered naval vessels and commercial nuclear energy production.

During the last period of a facility's life cycle, it is important that surveillance and maintenance S and M be adequate to maintain the facility within an appropriate safety envelope. Inadequate investment in maintenance can cause facilities to deteriorate to the point they are unsafe for human entry. Too often this can mean tremendous increases to cost during deactivation and decommissioning D and D.

However, experiences often show that once buildings have been declared excess and enter the transition phase as defined in DOE G This is justified by the desire to not spend money 'on a building that is being torn down'. The objective of this study was to provide the U. Department of Energy DOE Environmental Management EM federal project directors and their contractors with a decision support tool to aid in prioritizing S and M investment across a site's excess facilities so that the limited budget available can be used most effectively.

The analytical hierarchy process AHP , a multi-criteria decision making method developed by Dr. Thomas Saaty in the 's, was used to derive the weight of importance of a defined list of risk-based criteria and typical S and M activities. A total of 10 facilities at the Oak Ridge National Laboratory ORNL varying in perceived hazards and conditions were chosen to test the tool by evaluating them with respect to each risk criterion and combining these results with the weight of importance of the S and M.

Method of estimating investment decisions effectiveness in power engineering. A new concept of determining efficient power plants investment decision -making is proposed. The results of research on capital expenditures for building and modernization of power plants are presented. The model introduced is based on the well-known Annual Cost Model which is modified by adding annual risk costs. The risk factor was created on the basis of some elements of the taxonometric method with a high level of estimation probability.

The essential problem is the selection of risk investment variables, most important of which are economic, financial, technical, social, political, legal. These variables create a multidimensional space. A so called 'ideal' model of the power plant is created taking into account capacity, type, fuel used, etc. The values of the multidimensional risk factor e i lie within limit and make it possible to rank the planned plants in series according to the estimated level of risk.

This method can be used not only for risk evaluation in power engineering but also for investment efficiency studies in different industrial branches. We examine the investment decision problem of a group whose members have heterogeneous time preferences. In particular, they have different discount factors for utility, possibly not exponential. We characterize the properties of efficient allocations of resources and of shadow prices that would decentralize such allocations.

We show in particular that the term structure of interest rates is decreasing when all members have DARA preferences. Heterogeneous groups should not use exponential dis Investigating the factors affecting the investment decision in residential development. The purpose of this project is to provide a rare insight into the motivation behind residential property investors when looking to purchase an apartment. The factors driving demand preferences for housing are constantly changing, difficult to measure, and often deemed to be a complex bundle of attributes.

The project attempts to answer the following questions: What are the factors affecting the investment decision in a Residential Development? To identify the significance and weight of su Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce.

This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision -maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints.

The methodology is presented in the context of assessing capability development portfolios for NASA technology programs. The economic rationale for investing decisions innovative projects rationalization of investments for innovative projects.

Full Text Available The article provides a selection of methods for determining the feasibility of an investment -innovative project. Estimated indicators are identified analytically, on their basis a conclusion is made about the economic efficiency and feasibility of the project, which is the basis of its competitiveness.

Such growth analytics is necessary, since the social and economic development of the country and the region largely depends on the investment climate, which is facilitated by the legislation of the Russian Federation the Tax Code of the Russian Federation, the law of the Russian Federation on the regulation of investment activities, etc.. Since competitiveness is also determined by the economic feasibility and financial solvency of innovative projects, modern information and software, as well as the methodology for project appraisal and the corresponding order of their implementation, are needed.

In the Russian Federation, a method is used to assess the efficiency of capital investments in capitalist countries, as well as the methodology of economic competitive analysis of investment -innovative projects. The basis of the method is that reimbursement of investments occurs in two economic forms: net profit and depreciation net income. Of the numerous methods for assessing the feasibility of investment , the most often used along with discount methods taking into account the factor of money changes over time, statistical methods with determining the payback period and the average rate of return on investment.

The methodology specified in the article is useful to the investor in order to rationalize investment flows, helps to achieve the maximum IRR. The implementation of the innovative project serves the competitiveness of the manufacturing enterprise by increasing the technical and technological levels of the products.

Emissions trading and investment decisions in the power sector-a case study in Finland. In this paper, the consequences of the EU ETS on investment decisions are explored in a country-specific setting in Finland. First, we review the general mechanisms through which the EU ETS influences size, timing and cashflows of an investment. Next, we discuss the projected changes in Finnish power producers' investment environment and examine the financial impacts due to the EU ETS on a case investment decision , a hypothetical condensing power plant MW e.

The standard discounted cash flow DCF analysis is extended to take into account the value of two real options: the option to wait and the option to alter operating scale. In a quantitative investment appraisal, the impact of emissions trading not only depends on the expected level of allowance prices, but also on their volatility and correlation with electricity and fuel prices. The case study shows that the uncertainty regarding the allocation of emission allowances is critical in a quantitative investment appraisal of fossil fuel-fired power plants.

Research on the robust optimization of the enterprise's decision on the investment to the collaborative innovation: Under the risk constraints. Abstracts: The robust optimization model is applied to analyze the enterprise's decision of the investment portfolio for the collaborative innovation under the risk constraints. Through the mathematical model deduction and the simulation analysis , the research result shows that the enterprise's investment to the collaborative innovation has relatively obvious robust effect.

As for the collaborative innovation, the return from the investment coexists with the risk of it. Under the risk constraints, the robust optimization method could solve the minimum risk as well as the proportion of each investment scheme in the portfolio on the condition of different target returns from the investment. On the basis of the result, the enterprise could balance between the investment return and risk and make optimal decision on the investment scheme.

Full Text Available Agroforestry System is the ecological and economical interaction of the use of the land, with the combination ofagriculture, livestock and forest production, in temporary sequence and in a simultaneous way. The studies of investments in projectsassume the existence of risks and uncertainties. An alternative to reduce the risk in the forest investment is the association with theagricultural. This work analyzed the situations of risk of a system agroflorestal.

Monte Carlo s method comes from the theory ofsimulations and stands out as a powerful and useful tool to provide a distribution of probabilities for the analysis of decision. The results presented Market research on factors influencing women's preferences in investment decision making. This study aims to gain knowledge on the factors that influence the investment decision making of women in Singapore.

The research explores the fact that investment decision is being affected by the demographic, psychographic factors of the individuals. The individuals may be equal in all aspects but their investment decision varies with their own perception towards various investment plans. The research was conducted among respondents through a survey so as to get an empirical findings o Development of an investment decision tool for aged nuclear power plants under uncertainty.

Under accumulating uncertainties surrounding investment decisions , one of the key questions is how best to manage the existing capacity by choosing a wisest option among dismantling, refurbishment, and replacement. This report attempts to develop a methodology to analyze investment decision on aged nuclear units based on real-option analysis , and then presents illustrative simulation runs to demonstrate functions of the numerical models.

Major findings are summarized as follows: a When compared with the conventional net present value NPV method, the proposed model is capable to deal with uncertainty explicitly by taking volatility in the formula. Also, for the replacement option, one can choose optimal timings of the dismantling the new plant independently.

Additionally, where two of the strategies have similar values, postponement of both decisions can be optimal. Through these exercises, the proposed methodology proved itself capable for raising valuable implications to investment decisions in managing the production fleet. Rejection or selection: influence of framing in investment decisions. According to prospect theory, reflection effects result in preferences for risk-averse choices in gain situations and risk-seeking choices in loss situations.

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In such an environment, decision makers need to better understand long-term dynamics of the supply and demand sides of the power market. In this study, a system dynamics model is developed, to better understand and analyze the decentralized and competitive electricity market dynamics in the long run. The developed simulation model oversees a year planning horizon; it includes a demand module, a capacity expansion module, a power generation module, an accounting and finance module, various competitors, a regulatory body and a bidding mechanism.

Public regulators and power companies are potential users of the model, for learning and decision support in policy design and strategic planning. Results of scenario analysis are presented to illustrate potential use of the model. More specifically, I exploit the time-series variation in the domestic theatrical release of comedy movies as a natural experiment for testing the impact that happy mood proxied by weekend comedy movie attendance has on investment in risky assets My hypothesis rests upon the evidence that individual investors are more likely to ponder trading decisions during the weekend and trade on Mondays.

To control for unobserved factors that may contemporaneously affect movie Using a sample of data from to , I estimate that an increase in comedy attendance on a given weekend is followed by a decrease in equity returns on the subsequent Monday, which The evolution of investments decision mode in China's telecommunication. This essay analyzes the data of Chinese telecommunication market, telecommunication investments and investment benefits over the past 20 years.

On the basis of these data, the essay reviews Chinese changing telecommunication policies and discusses the major events in the course of China's telecommunication development. It is argued that telecommunication policies, regime backgrounds and market demand characteristics have a significant impact on investment decision mode in telecommunication industry.

The evolution of network investments decision mode in China's telecommunication has corresponded to the transformation of these key factors. Considering the special events in the development of Chinese telecommunication as divisions, the essay discusses three stages of the evolution of investments decision mode in China's telecommunication. With the firm environment and problems that Chinese telecommunication operators have been facing since analyzed.

This investment decision mode will result in increase of the investment profit with limited investment capital. The main procedure of profit-oriented investment decision mode is set out, which is abstracted to a mathematical model eventually.

Aggregate capital needs is a new conception and gives a new viewpoint to investment project decisions. The paper defines the special content of aggregate capital needs, and compiles an index number for it. The analysis widens knowledge regardin Real Options Analysis of Electricity Investments. This thesis utilizes real options analysis for evaluating investment opportunities in the electricity sector. It also formally tests how investors in hydropower plants have included uncertainty when considering their investment opportunities.

The real options method applies financial options theory to quantify the value of management flexibility and is chosen due to three important characteristics of investments in the electricity sector. First; the investment is completely or partially irreversible, second; the investor can choose when to invest in the facility, and third; there is uncertainty in several factors affecting the cash flows of the investments.

Factors of uncertainty include the development of electricity prices, policies, technological advances, and macroeconomics measures. Four papers are included in this thesis. Paper 1, Upgrading hydropower plants with storage: Timing and capacity choice, presents a valuation framework for deciding when to upgrade an existing hydropower plant and which capacity to choose. The second paper, Transmission capacity between Norway and Germany: A real options analysis , sheds light on when two electricity markets, in this case Norway and Germany, should be connected through a sub sea cable.

The investor can choose when to invest and the capacity of the cable, and may also choose to invest sequentially. Paper 3, Optimal timing and capacity choice for pumped hydropower storage, investigates when investment in a pumped hydropower plant with storage should be undertaken and what the capacity of the facility should be.

Whereas the three first papers investigate investment opportunities, Paper 4, Uncertain climate policy decisions and investment timing: Evidence from small hydropower plants, studies when investors in small hydropower plants chose to invest. The analyses disclose whether the net present value approach or the real options method best describe the investment decisions made by the investors. Viewing investment.

Applying real options in investment decisions relating to environmental pollution. Lin, Tyrone T. E-mail: tjlin mail. This study focuses on how to assess the optimal environmental investment decisions under economic and ecological uncertainty, and establishes the continuous time model using the real option approach to optimize environmental pollution policy. Unlike traditional cost benefit analysis , this work extends the model of [Pindyck, R.

Optimal timing problems in environmental economics. Journal of Economic Dynamics and Control 26 , ], and attempts to identify the storage threshold of pollution stocks and the optimal timing for implementing environmental pollution decisions. The financial management as a tool for development investment decision. Full Text Available Investment decisions , which influence the investment of financial resources to achieve economic, non-economic, or of both objectives and effects in the future, the central subject of financial management.

Using the methods of financial mathematics can predict the effects of the investment which is from the standpoint of efficiency ratings are expressed in the form of cash future income. Periods, the investments and the use of investment , may be the same or different lengths. From an economic standpoint it is desirable that the period of the investment is short, and the economic effects of the eyelids investments as long as possible. For an investment is said to be cost-effective or cost-effective if the current value of the investment is less than the present value of income from investments.

Decision -making process in investment projects. We present projects evaluation approaches in what decision should be based. We try to understand what we have to take into account in a project analysis , knowing that we have to consider much unmeasured aspects, like non non-financial areas.

We verify how all aspects are used and analysed in the project appraisal. We also desire to understand if companies have adequate tools and methods to correctly analyse and to take decisions in a project evaluation. In this study we identify several as A dynamic decision model for portfolio investment and assets management.

This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level. The paper generalizes Markowitz's portfolio selection theory and Sharpe's rule for investment decision.

An analytical solution is presented to show how an institutional or individual investor can combine Markowitz's portfolio selection theory, generalized Sharpe's rule and Value-at-Risk VaR to find candidate assets and optimal level of position sizes for investment dis- investment. The result shows that the generalized Markowitz's portfolio selection theory and generalized Sharpe's rule improve decision making for investment.

Characterizing uncertain sea-level rise projections to support investment decisions. Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis.

We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: 1 Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and 2 Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment?

We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders.

In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments.

Full Text Available Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making.

Understanding the impact of business cases on IT investment decisions : An analysis of municipal e-government projects. We then construct a theoretical model that postulates the impact of IT business case elements on the. Assessing survivability to support power grid investment decisions. The reliability of power grids has been subject of study for the past few decades.

Traditionally, detailed models are used to assess how the system behaves after failures. Such models, based on power flow analysis and detailed simulations, yield accurate characterizations of the system under study. However, they fall short on scalability. In this paper, we propose an efficient and scalable approach to assess the survivability of power systems.

Our approach takes into account the phased-recovery of the system after a failure occurs. The proposed phased-recovery model yields metrics such as the expected accumulated energy not supplied between failure and full recovery.

Leveraging the predictive power of the model, we use it as part of an optimization framework to assist in investment decisions. Given a budget and an initial circuit to be upgraded, we propose heuristics to sample the solution space in a principled way accounting for survivability-related metrics. We have evaluated the feasibility of this approach by applying it to the design of a benchmark distribution automation circuit.

Our empirical results indicate that the combination of survivability and power flow analysis can provide meaningful investment decision support for power systems engineers. Geothermal power plant investment decisions. Interim report, June 1-November 30, Investment decisions for financing the construction of geothermal power plants are discussed.

Discussed here are the investment objectives of investor-owned electric utilities, municipal electric utilities, and potential third party financiers as determined from extensive reviews of literature, executive interviews and responses to mailed surveys. The framework is provided for a computerized quantitative decision model currently being developed at Technecon for investment and policy analysis applications.

Full Text Available The aim of the study is to measure influence of taxation while making financial decisions and predict it with the general application in Turkey. Except for equity returns of financial and negative capital institutions registered in Borsa Istanbul between and , those of all other businesses were calculated.

Businesses were divided into for regions as stated in Tax Incentive Law according to the study. As stated in Tax Incentive Law, the businesses whose costs of capital were divided into six regions where statistical analysis was made to determine whether taxation influenced financial decisions of the related businesses based on Tax Incentive Law or not.

Assessment of the findings within the study determined that businesses in 1 st, 2 nd and 3 rd regions were affected by taxation 5,69, 2,75 and 1,39 as means between and , respectively. Accordingly taxation load of businesses in 1 st region provinces was found to be heavier than those of businesses in other regions. Considering the Tax Incentive Law, it was found to be statistically important that taxation load of the related region should be taken into account in making any financial decisions.

In this respect, there is an impact of tax when one makes financial decisions. However, other relevant factors should also be considered. Investment appraisal using quantitative risk analysis. Investment appraisal concerned with investments in fire safety systems is discussed.

Particular attention is directed at evaluating, in terms of the Bayesian decision theory, the risk reduction that investment in a fire safety system involves. It is shown how the monetary value of the change from a building design without any specific fire protection system to one including such a system can be estimated by use of quantitative risk analysis , the results of which are expressed in terms of a Risk-adjusted net present value.

This represents the intrinsic monetary value of investing in the fire safety system. The method suggested is exemplified by a case study performed in an Avesta Sheffield factory. The problem with such NPV estimates is that they depend on projected future cash flows.

If there are errors in those projections, then estimated net present values can be misleading a forecasting risk. Accordingly, the paper discusses some organized ways of going about a what — if analysis. Its goal in doing so is to assess the degree of forecasting risk and to identify those elements that are the most critical to the success or failure of an investment. However, as we show in examples, as well as in the practical study, though what — if analysis really allows us to obtain the certain idea of degree of forecasting risk, it does not tell us what to do about the possible errors.

Investment timing decisions in a stochastic duopoly model. E-mail: giovanni. E-mail: flavia. E-mail: dominioni core. We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market e.

Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost.

The error of fixed strategies in IT innovation investment decisions. Allocating an IT Innovation budget to technologies in different maturity stages mature vs. Due to the dynamic innovation cycles with new emerging technologies, many IT innovation investment decisions follow a bandwagon behavior or fixed investment strategies.

Emotional Intelligence and risk taking in investment decision -making. We hypothesized that people with high trait emotional intelligence should be more willing, than people with low trait emotional intelligence, to accept risks when making an investment. Data supported a model in which trait emotional intell Investment decisions in environment of uncertainties integrated to the viability analysis of the distribution and transmission projects; Decisao de investimentos em ambiente de incertezas integrada a analise de viabilidade de projetos de transmissao e distribuicao.

Gazzi, L. In the economic and financial analysis , are considered the needs of the Regulator for the tariff recognition of an investment , using economic engineering techniques to evaluate the feedback of the invested capital but considering an uncertainty environment, where the best decision depends on exogenous variables to the traditional planning process.

In order to make viable the inclusion of the main variables of random behavior that condition the economic and financial performances of the analyzed alternatives for decision making, it was chosen the utilization of the methodology based on 'Real Options', which is an used technique in the financial market for some time.

Outsourcing of investment management is a growing trend among institutional investors. With a broad range of institutions using or exploring the outsourced chief investment officer OCIO model, portfolio size is no longer the determining factor driving the outsourcing decision. For all but the largest institutional investors--those with deep…. The decision making on mutual investment of thai investors The decision making on mutual investment of thai investors.

Journal of Fundamental and Applied Sciences. Journal Home The study was a research survey that used questionnaires to collect data from samples of Thai investors. Investment Decisions with Two-Factor Uncertainty. This paper considers investment problems in real options with non-homogeneous two-factor uncertainty. It shows that, despite claims made in the literature, the method used to derive an analytical solution in one dimensional problems cannot be straightforwardly extended to problems with two.

Full Text Available We propose in this study, to make an analysis of the influence of the investment decision on the return of the company. The goal of our research is the quantification of the influence of investment activity on profitability. Of course, the realization of such research was possible only after close consideration of the opinions expressed in the relevant literature on this area.

Our research aims to be a theoretical-applied one. It is based on comparisons we make between the two criteria for assessing investment projects namely: that of net present value VAN and internal rate of return RIR. By creating a suite of phase calculations, based on information from economic and financial documentation of corporate investments , we separated the influence of the policy investment decisions on profitability. We are convinced that the most accurate determination of the influence of policy investment decisions on profitability helps the financial management, facilitating the process of adopting the most appropriate policy decisions that ultimately leads to the objectives formulated by the financial policy.

The result of our research is the quantification of the influence of investment policy decisions of the firm on profitability. Full Text Available As the banks have tightened lending requirements, companies look for alternative sources of external funding. One of such is bonds issue. Unfortunately, corporate bonds issue as a source of funding is rare in Lithuania. This occurs because companies face with a lack of information, investors fear to take on credit risk. Investors, in order to avoid credit risk, have to assess the state of the companies.

The goal of the article is to determine the most informative methods of credit risk assessment. The article summarizes corporate lending sources, analyzes corporate default causes and credit risk assessment methods. The study based on the SWOT analysis shows that investors before making an investment decision should evaluate both the business risk,using qualitative method CAMPARI, and the financial risk, using financial ratio analysis. Modeling strategic investment decisions in spatial markets.

Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models.

The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market.

Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

Energiewirtschaftliches Inst. Peer effects in decision -making: Evidence from corporate investment. Full Text Available We show that peer effects influence corporate investment decisions. We find that peer effects are more pronounced when firms have information advantages and the information disclosure quality of peer firms is higher, or if they face more fierce competition.

When firms are industry followers, are young or have financial constraints, they are highly sensitive to their peers firms. We also quantify the economic consequences generated by peer effects, which can increase firm performance in future periods. Innovation investment decisions : are post transition economies different from the rest of the EU? Rather, it is worth distinguishing between their decision to increase investment , reduce it, keep their investments at the same level or not invest in innovation activities at all.

To understand these decisions we develop and estimate models for post-transition and developed European countries employing multinomial probit. The analysis relies on responses of firms from 11 post-transition countries and firms from 18 European countries collected by the Flash Eurobarometer - Innobarometer survey. In transition countries, the higher the percent of turnover invested in innovation, the lower the probability of an increase in the future.

In the firms operating in developed economies, lower turnover from new products is related to the decision to decrease innovation investment in the future. Promoting energy efficiency investments with risk management decision tools. This paper reviews current capital budgeting practices and their impact on energy efficiency investments. The prevalent use of short payback 'rule-of-thumb' requirements to screen efficiency projects for risk is shown to bias investment choices towards 'sure bet' investments bypassing many profitable efficiency investment options.

A risk management investment strategy is presented as an alternative to risk avoidance practices applied with payback thresholds. The financial industry risk management tool Value-at-Risk is described and extended to provide an Energy-Budgets-at-Risk or EBaR risk management analysis to convey more accurate energy efficiency investment risk information. The paper concludes with recommendations to expand the use of Value-at-Risk-type energy efficiency analysis.

Decision analysis multicriteria analysis. For the simplest one the engineering judgement is generally enough and the use of a decision aiding technique is therefore not necessary. For some decisions the comparison of the available protection option may be performed from two or a few criteria or attributes protection cost, collective dose, For the more complex decisions , involving numerous criteria or for decisions involving large uncertainties or qualitative judgement the use of these techniques, even the extended cost benefit analysis , is not recommended and appropriate techniques like multi-attribute decision aiding techniques are more relevant.

There is a lot of such particular techniques and it is not possible to present all of them. Therefore only two broad categories of multi-attribute decision aiding techniques will be presented here: decision analysis and the outranking analysis. Full Text Available The investments represent the primary factor in the development strategy of an economic entity.

The role of the investments begins with their purpose, meaning that the investments involve the increasing of a stock portfolio. The research methodology that is approached in this article is based on the analysis of two factors: net present value and internal rate of profitability. Capital budgeting in an investment project that, without a prior analysis of the efficiency of such a decision , can lead to the total or partial loss of the invested capital. An investment project is efficient if the net present value is positive and has a larger value.

An investment project becomes more profitable as the value of the internal rate of profitability gets higher. If the two factors are correctly interpreted they lead to exactly the same conclusions regarding the determination of an investment profitability. We can conclude that the two efficiency factors are complementary, their simultaneous use leading to a better grounding of the investment decision than their separate use.

The effect of environmental information on investment allocation decisions. This paper focuses on the use of environmental information in investment decision making. The research approach employed is based on an experiment where three groups of final year finance students were asked to allocate investment funds between two companies based on financial accounts Hence, this has implications for how the potential value of environmental information is to be assessed.

Finally, experimental studies as a methodology seem to be better suited to indicate actual effects of different types of information on decision making The overall conclusion is that the qualitative environmental information affects short term allocation decisions , hence indicating a risk reduction potential of environmental information comparable Full Text Available The significance of investment is transparent in the world of competitive business.

Traditional costing systems in which their emphasizes are for short term savings rather than long term benefits have shown some lacking in providing accurate and reliable cost data for the investment decisions. Activity-based Costing ABC, which is developed to satisfy some of the weaknesses of the traditional costing systems, can provide valuable insights into the operating processes and come up with more accurate cost data.

In this paper, ABC is used to provide significant information for investment decisions. The adoption of ABC and EVA can represent a considerable change in the managerial thinking and to corporate strategies and business performance. Economic simulation to support investment decisions in pig farming. The study described in this thesis focuses on the development and use of a model that simulates the consequences of long-term investment decisions in pig farming.

The thesis is composed of six parts. Chapter 1 deals with a basic review of the literature on strategic planning under risk and. A multi-objective decision framework for lifecycle investment. In this paper we propose a multi-objective decision framework for lifecycle investment choice. Instead of optimizing individual strategies with respect to a single-valued objective, we suggest evaluation of classes of strategies in terms of the quality of the tradeoffs that they provide.

This "good practice" guide is aimed at anyone in higher education in England who is involved in making decisions on investments. It focuses on the principles to be followed, rather than the techniques of appraisal. The guide outlines the steps for developing an outline business case and then refining it into a full business case for the….

Using a group decision support system to make investment prioritisation decisions. This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system GDSS. While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group.

The paper develops the conceptual framework of decision -making, communication and group support, and de Investment sensitivity and managerial decision making behaviour of Indian firms. Full Text Available Contemporary models of the financial theory support the proposition that the stock prices should be fundamentally a reflection of the discounted value of earnings.

Given the imperfect information structure and market pressures, the Indian firms suffer from mispricing and as such the conventional robust theoretical models of agency conflicts cannot be refuted. This motivates us to examine the interrelation ship between the concerns for valuation and investment sensitivity. We use the earnings response coefficient ERC framework proposed by Ball and Brown for 11 key industries in India. We find that the surpise in accounting earnings announcements is negatively associated with abnormal stock returns and the investment decisions taken by the firms are negatively sensitive to changes in investment opportunities.

Full Text Available There is a worldwide trend towards rapidly growing defined contribution pension funds in terms of assets andmembership, and the choices available to individuals. This has shifted the decisionmaking responsibility tofund members for managing the investment of their retirement savings.

Prior research identifies that deficiencies infinancial literacy is one of the causes of inertia in financial decision -making and findings from internationaland Australian studies show that financial illiteracy is wide-spread. Analysis of stage- investing strategy in equity financing market.

Stage- investing strategy is a primary measure to mitigate asymmetric information during equity investment. This paper attempts to investigate the problem faced by equity investors wishing to make optimal investment decision under stage- investing strategy. A serial investment-decision making model will be designed to help investors to take the best choice. The Department of Energy DOE currently faces a difficult task in the disposition of the numerous excess or to-be excessed facilities owned by the Department.

Many of these facilities are in various physical conditions and contain potentially hazardous nuclear, chemical, radiological or industrial materials left behind as a byproduct of nuclear weapons production, nuclear powered naval vessels and commercial nuclear energy production.

During the last period of a facility's life cycle, it is important that surveillance and maintenance S and M be adequate to maintain the facility within an appropriate safety envelope. Inadequate investment in maintenance can cause facilities to deteriorate to the point they are unsafe for human entry.

Too often this can mean tremendous increases to cost during deactivation and decommissioning D and D. However, experiences often show that once buildings have been declared excess and enter the transition phase as defined in DOE G This is justified by the desire to not spend money 'on a building that is being torn down'. The objective of this study was to provide the U.

Department of Energy DOE Environmental Management EM federal project directors and their contractors with a decision support tool to aid in prioritizing S and M investment across a site's excess facilities so that the limited budget available can be used most effectively. The analytical hierarchy process AHP , a multi-criteria decision making method developed by Dr.

Thomas Saaty in the 's, was used to derive the weight of importance of a defined list of risk-based criteria and typical S and M activities. A total of 10 facilities at the Oak Ridge National Laboratory ORNL varying in perceived hazards and conditions were chosen to test the tool by evaluating them with respect to each risk criterion and combining these results with the weight of importance of the S and M.

Method of estimating investment decisions effectiveness in power engineering. A new concept of determining efficient power plants investment decision -making is proposed. The results of research on capital expenditures for building and modernization of power plants are presented.

The model introduced is based on the well-known Annual Cost Model which is modified by adding annual risk costs. The risk factor was created on the basis of some elements of the taxonometric method with a high level of estimation probability.

The essential problem is the selection of risk investment variables, most important of which are economic, financial, technical, social, political, legal. These variables create a multidimensional space. A so called 'ideal' model of the power plant is created taking into account capacity, type, fuel used, etc. The values of the multidimensional risk factor e i lie within limit and make it possible to rank the planned plants in series according to the estimated level of risk.

This method can be used not only for risk evaluation in power engineering but also for investment efficiency studies in different industrial branches. We examine the investment decision problem of a group whose members have heterogeneous time preferences.

In particular, they have different discount factors for utility, possibly not exponential. We characterize the properties of efficient allocations of resources and of shadow prices that would decentralize such allocations. We show in particular that the term structure of interest rates is decreasing when all members have DARA preferences. Heterogeneous groups should not use exponential dis Investigating the factors affecting the investment decision in residential development.

The purpose of this project is to provide a rare insight into the motivation behind residential property investors when looking to purchase an apartment. The factors driving demand preferences for housing are constantly changing, difficult to measure, and often deemed to be a complex bundle of attributes. The project attempts to answer the following questions: What are the factors affecting the investment decision in a Residential Development?

To identify the significance and weight of su Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints.

Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis.

The evaluation of the degree of robustness of the recommended portfolio provides the decision -maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

The economic rationale for investing decisions innovative projects rationalization of investments for innovative projects. Full Text Available The article provides a selection of methods for determining the feasibility of an investment -innovative project. Estimated indicators are identified analytically, on their basis a conclusion is made about the economic efficiency and feasibility of the project, which is the basis of its competitiveness. Such growth analytics is necessary, since the social and economic development of the country and the region largely depends on the investment climate, which is facilitated by the legislation of the Russian Federation the Tax Code of the Russian Federation, the law of the Russian Federation on the regulation of investment activities, etc..

Since competitiveness is also determined by the economic feasibility and financial solvency of innovative projects, modern information and software, as well as the methodology for project appraisal and the corresponding order of their implementation, are needed. In the Russian Federation, a method is used to assess the efficiency of capital investments in capitalist countries, as well as the methodology of economic competitive analysis of investment -innovative projects.

The basis of the method is that reimbursement of investments occurs in two economic forms: net profit and depreciation net income. Of the numerous methods for assessing the feasibility of investment , the most often used along with discount methods taking into account the factor of money changes over time, statistical methods with determining the payback period and the average rate of return on investment.

The methodology specified in the article is useful to the investor in order to rationalize investment flows, helps to achieve the maximum IRR. The implementation of the innovative project serves the competitiveness of the manufacturing enterprise by increasing the technical and technological levels of the products. Emissions trading and investment decisions in the power sector-a case study in Finland.

In this paper, the consequences of the EU ETS on investment decisions are explored in a country-specific setting in Finland. First, we review the general mechanisms through which the EU ETS influences size, timing and cashflows of an investment. Next, we discuss the projected changes in Finnish power producers' investment environment and examine the financial impacts due to the EU ETS on a case investment decision , a hypothetical condensing power plant MW e.

The standard discounted cash flow DCF analysis is extended to take into account the value of two real options: the option to wait and the option to alter operating scale. In a quantitative investment appraisal, the impact of emissions trading not only depends on the expected level of allowance prices, but also on their volatility and correlation with electricity and fuel prices. The case study shows that the uncertainty regarding the allocation of emission allowances is critical in a quantitative investment appraisal of fossil fuel-fired power plants.

Research on the robust optimization of the enterprise's decision on the investment to the collaborative innovation: Under the risk constraints. Abstracts: The robust optimization model is applied to analyze the enterprise's decision of the investment portfolio for the collaborative innovation under the risk constraints. Through the mathematical model deduction and the simulation analysis , the research result shows that the enterprise's investment to the collaborative innovation has relatively obvious robust effect.

As for the collaborative innovation, the return from the investment coexists with the risk of it. Under the risk constraints, the robust optimization method could solve the minimum risk as well as the proportion of each investment scheme in the portfolio on the condition of different target returns from the investment. On the basis of the result, the enterprise could balance between the investment return and risk and make optimal decision on the investment scheme.

Full Text Available Agroforestry System is the ecological and economical interaction of the use of the land, with the combination ofagriculture, livestock and forest production, in temporary sequence and in a simultaneous way. The studies of investments in projectsassume the existence of risks and uncertainties. An alternative to reduce the risk in the forest investment is the association with theagricultural.

This work analyzed the situations of risk of a system agroflorestal. Monte Carlo s method comes from the theory ofsimulations and stands out as a powerful and useful tool to provide a distribution of probabilities for the analysis of decision. The results presented Market research on factors influencing women's preferences in investment decision making.

This study aims to gain knowledge on the factors that influence the investment decision making of women in Singapore. The research explores the fact that investment decision is being affected by the demographic, psychographic factors of the individuals. The individuals may be equal in all aspects but their investment decision varies with their own perception towards various investment plans.

The research was conducted among respondents through a survey so as to get an empirical findings o Development of an investment decision tool for aged nuclear power plants under uncertainty. Under accumulating uncertainties surrounding investment decisions , one of the key questions is how best to manage the existing capacity by choosing a wisest option among dismantling, refurbishment, and replacement.

This report attempts to develop a methodology to analyze investment decision on aged nuclear units based on real-option analysis , and then presents illustrative simulation runs to demonstrate functions of the numerical models. Major findings are summarized as follows: a When compared with the conventional net present value NPV method, the proposed model is capable to deal with uncertainty explicitly by taking volatility in the formula.

Also, for the replacement option, one can choose optimal timings of the dismantling the new plant independently. Additionally, where two of the strategies have similar values, postponement of both decisions can be optimal. Through these exercises, the proposed methodology proved itself capable for raising valuable implications to investment decisions in managing the production fleet.

Rejection or selection: influence of framing in investment decisions. According to prospect theory, reflection effects result in preferences for risk-averse choices in gain situations and risk-seeking choices in loss situations. However, relevant literature in regard to decision making has suggested that positive information receives more weight in a selection task, whereas negative information receives more weight in a rejection task.

The present study examined whether the nature of a decision task selection vs rejection would moderate the reflection effects. Typical reflection effects were observed in both selection and rejection task conditions. More importantly, negative information i. Hence, the findings suggest that a decision context characterized by rejection may expand the reflection effects and thereby provide important information about situations in which investment decisions occur in a context characterized by rejection.

Power plants investment decision -making in consideration of investment risk. In this paper, we consider the investment risk of nuclear power plants using the real options approach. It is essential that the Japanese society evaluate the investment risk, because nuclear power plants are facing definite uncertainty and Japanese governments intend to promote and assist nuclear power plants through subsidies and policy actions.

We assumed that the wholesale market prices of electricity constitute the definite uncertainty and that the wholesale market prices follow the geometric Brownian motion with drift. Using the Bellman equation and a lattice framework, we evaluated the value of investment opportunity, the value of equipment, and the critical prices that are optimal prices to invest in a nuclear power plant in the finite time horizon.

This analysis shows that higher volatility of the wholesale market prices would give power companies lower incentive to construct electric power plants, particularly capital-intensive power plants. In order to deliberate and hold the Japanese governments accountable for the economics of nuclear power plants, multifaceted evaluation is needed.

Discusses ratio analysis by which investments may be evaluated. Requires the use of fundamental mathematics, problem solving, and a comparison of the mathematical results within the framework of industry. The objective of this research is to design, develop and implement an intelligent decision support system IDSS for making rational private equity investment decisions. Private equity investments are capital investments in enterprises that are not traded on public equity markets; they include Equity Buy-Out, Venture Capital, and the new Equity Crowd Funding ECF asset classes.

The design and development of the IDSS requires the integration of investment science valuation theory, portfoli Delaying investments in sensor technology: The rationality of dairy farmers' investment decisions illustrated within the framework of real options theory. The adoption rate of sensors on dairy farms varies widely. Whereas some sensors are hardly adopted, others are adopted by many farmers. A potential rational explanation for the difference in adoption may be the expected future technological progress in the sensor technology and expected future improved decision support possibilities.

For some sensors not much progress can be expected because the technology has already made enormous progress in recent years, whereas for sensors that have only recently been introduced on the market, much progress can be expected. The adoption of sensors may thus be partly explained by uncertainty about the investment decision , in which uncertainty lays in the future performance of the sensors and uncertainty about whether improved informed decision support will become available.

The overall aim was to offer a plausible example of why a sensor may not be adopted now. To explain this, the role of uncertainty about technological progress in the investment decision was illustrated for highly adopted sensors automated estrus detection and hardly adopted sensors automated body condition score.

This theoretical illustration uses the real options theory, which accounts for the role of uncertainty in the timing of investment decisions. A discrete event model, simulating a farm of dairy cows, was developed to estimate the net present value NPV of investing now and investing in 5 yr in both sensor systems.

The results show that investing now in automated estrus detection resulted in a higher NPV than investing 5 yr from now, whereas for the automated body condition score postponing the investment resulted in a higher NPV compared with investing now.

These results are in line with the observation that farmers postpone investments in sensors. Also, the current high adoption of automated estrus detection sensors can be explained because the NPV of investing now is higher than the NPV of investing in 5 yr. The results confirm that. Investment in energy: a decision with manifold objectives. Assuming that the level of welfare of the economy is influenced by divergencies observed in the amplitude of certain regional elements, it is admitted that such information must be added to the one conventionally included in the decision 's criteria.

Specifically: if distributive data are added to the efficiency data already existing, the former ones must be explicitly stated in decision 's criteria. In this instance, the estimates of the rates of return provided by the two approaches would not be substantially different.

However, to the decision maker with the added information, Investment Y no longer looks like the clearly better choice, since with X the chances of substantial gain are higher and the risks of loss lower. Certainly in every case it is a more descriptive statement of the two opportunities. And in some cases it might well reverse the decision, in line with particular corporate objectives.

This is not a difficult technique to use, since much of the information needed is already available—or readily accessible—and the validity of the principles involved has, for the most part, already been proved in other applications. The enthusiasm with which managements exposed to this approach have received it suggests that it may have wide application. It has particular relevance, for example, in such knotty problems as investments relating to acquisitions or new products and in decisions that might involve excess capacity.

The fatal weakness of past approaches thus has nothing to do with the mathematics of rate-of-return calculation. We have pushed along this path so far that the precision of our calculation is, if anything, somewhat illusory. The fact is that, no matter what mathematics is used, each of the variables entering into the calculation of rate of return is subject to a high level of uncertainty. For example, the useful life of a new piece of capital equipment is rarely known in advance with any degree of certainty.

It may be affected by variations in obsolescence or deterioration, and relatively small changes in use life can lead to large changes in return. Yet an expected value for the life of the equipment—based on a great deal of data from which a single best possible forecast has been developed—is entered into the rate-of-return calculation.

The same is done for the other factors that have a significant bearing on the decision at hand. Let us look at how this works out in a simple case—one in which the odds appear to be all in favor of a particular decision. The executives of a food company must decide whether to launch a new packaged cereal. They have come to the conclusion that five factors are the determining variables: advertising and promotion expense, total cereal market, share of market for this product, operating costs, and new capital investment.

This future, however, depends on whether each of these estimates actually comes true. The decision makers need to know a great deal more about the other values used to make each of the five estimates and about what they stand to gain or lose from various combinations of these values. This simple example illustrates that the rate of return actually depends on a specific combination of values of a great many different variables.

But only the expected levels of ranges worst, average, best; or pessimistic, most likely, optimistic of these variables are used in formal mathematical ways to provide the figures given to management. Thus predicting a single most likely rate of return gives precise numbers that do not tell the whole story.

The expected rate of return represents only a few points on a continuous cure of possible combinations of future happenings. It is a bit like trying to predict the outcome in a dice game by saying that the most likely outcome is a 7. The description is incomplete because it does not tell us about all the other things that could happen.

In Exhibit I, for instance, we see the odds on throws of only two dice having 6 sides. Now suppose that each of eight dice has sides. Nor is this the only trouble. Our willingness to bet on a roll of the dice depends not only on the odds but also on the stakes.

Since the probability of rolling a 7 is 1 in 6, we might be quite willing to risk a few dollars on that outcome at suitable odds. In short, risk is influenced both by the odds on various events occurring and by the magnitude of the rewards or penalties that are involved when they do occur. Suppose that getting no return at all would put the company out of business. Then, by accepting this proposal, management is taking a 1-in-3 chance of going bankrupt. If only the best-estimate analysis is used, however, management might go ahead, unaware that it is taking a big chance.

If all of the available information were examined, management might prefer an alternative proposal with a smaller, but more certain that is, less variable expectation. Such considerations have led almost all advocates of the use of modern capital-investment-index calculations to plead for a recognition of the elements of uncertainty.

Perhaps Ross G. How can executives penetrate the mists of uncertainty surrounding the choices among alternatives? A number of efforts to cope with uncertainty have been successful up to a point, but all seem to fall short of the mark in one way or another. Reducing the error in estimates is a worthy objective. But no matter how many estimates of the future go into a capital investment decision, when all is said and done, the future is still the future.

Therefore, however well we forecast, we are still left with the certain knowledge that we cannot eliminate all uncertainty. Adjusting the factors influencing the outcome of a decision is subject to serious difficulties. And in any case, what is the basis for adjustment? We adjust, not for uncertainty, but for bias.

For example, construction estimates are often exceeded. This is a matter of improving the accuracy of the estimate. In so doing, it is possibly missing some of its best opportunities. Selecting higher cutoff rates for protecting against uncertainty is attempting much the same thing. Management would like to have a possibility of return in proportion to the risk it takes. Where there is much uncertainty involved in the various estimates of sales, costs, prices, and so on, a high calculated return from the investment provides some incentive for taking the risk.

This is, in fact, a perfectly sound position. The trouble is that the decision makers still need to know explicitly what risks they are taking—and what the odds are on achieving the expected return. A start at spelling out risks is sometimes made by taking the high, medium, and low values of the estimated factors and calculating rates of return based on various combinations of the pessimistic, average, and optimistic estimates.

These calculations give a picture of the range of possible results but do not tell the executive whether the pessimistic result is more likely than the optimistic one—or, in fact, whether the average result is much more likely to occur than either of the extremes. So, although this is a step in the right direction, it still does not give a clear enough picture for comparing alternatives.

Various methods have been used to include the probabilities of specific factors in the return calculation. Grant discussed a program for forecasting discounted cash flow rates of return where the service life is subject to obsolescence and deterioration.

He calculated the odds that the investment will terminate at any time after it is made depending on the probability distribution of the service-life factor. After having calculated these factors for each year through maximum service life, he determined an overall expected rate of return. Edward G. Bennion suggested the use of game theory to take into account alternative market growth rates as they would determine rate of return for various options. He used the estimated probabilities that specific growth rates would occur to develop optimum strategies.

Bennion pointed out:. Note that both of these methods yield an expected return, each based on only one uncertain input factor—service life in the first case, market growth in the second. Both are helpful, and both tend to improve the clarity with which the executive can view investment alternatives. Since every one of the many factors that enter into the evaluation of a decision is subject to some uncertainty, the executives need a helpful portrayal of the effects that the uncertainty surrounding each of the significant factors has on the returns they are likely to achieve.

Therefore, I use a method combining the variabilities inherent in all the relevant factors under consideration. The objective is to give a clear picture of the relative risk and the probable odds of coming out ahead or behind in light of uncertain foreknowledge. A simulation of the way these factors may combine as the future unfolds is the key to extracting the maximum information from the available forecasts. In fact, the approach is very simple, using a computer to do the necessary arithmetic.

To carry out the analysis, a company must follow three steps:. Estimate the range of values for each of the factors for example, range of selling price and sales growth rate and within that range the likelihood of occurrence of each value. Select at random one value from the distribution of values for each factor. Then combine the values for all of the factors and compute the rate of return or present value from that combination. For instance, the lowest in the range of prices might be combined with the highest in the range of growth rate and other factors.

The fact that the elements are dependent should be taken into account, as we shall see later. Do this over and over again to define and evaluate the odds of the occurrence of each possible rate of return. Since there are literally millions of possible combinations of values, we need to test the likelihood that various returns on the investment will occur.

This is like finding out by recording the results of a great many throws what percent of 7s or other combinations we may expect in tossing dice. The result will be a listing of the rates of return we might achieve, ranging from a loss if the factors go against us to whatever maximum gain is possible with the estimates that have been made.

For each of these rates we can determine the chances that it may occur. Note that a specific return can usually be achieved through more than one combination of events. The more combinations for a given rate, the higher the chances of achieving it—as with 7s in tossing dice. The average expectation is the average of the values of all outcomes weighted by the chances of each occurring.

We can also determine the variability of outcome values from the average. This is important since, all other factors being equal, management would presumably prefer lower variability for the same return if given the choice. This concept has already been applied to investment portfolios. When the expected return and variability of each of a series of investments have been determined, the same techniques may be used to examine the effectiveness of various combinations of them in meeting management objectives.

To see how this new approach works in practice, let us take the experience of a management that has already analyzed a specific investment proposal by conventional techniques. Taking the same investment schedule and the same expected values actually used, we can find what results the new method would produce and compare them with the results obtained by conventional methods.

As we shall see, the new picture of risks and returns is different from the old one. Is this investment a good bet? In fact, what is the return that the company may expect? What are the risks? We need to make the best and fullest use of all the market research and financial analyses that have been developed, so as to give management a clear picture of this project in an uncertain world. The key input factors management has decided to use are market size, selling prices, market growth rate, share of market which results in physical sales volume , investment required, residual value of investment, operating costs, fixed costs, and useful life of facilities.

These factors are typical of those in many company projects that must be analyzed and combined to obtain a measure of the attractiveness of a proposed capital facilities investment. How do we make the recommended type of analysis of this proposal? Our aim is to develop for each of the nine factors listed a frequency distribution or probability curve.

The information we need includes the possible range of values for each factor, the average, and some idea as to the likelihood that the various possible values will be reached. It has been my experience that for major capital proposals managements usually make a significant investment in time and funds to pinpoint information about each of the relevant factors. An objective analysis of the values to be assigned to each can, with little additional effort, yield a subjective probability distribution.

Specifically, it is necessary to probe and question each of the experts involved—to find out, for example, whether the estimated cost of production really can be said to be exactly a certain value or whether, as is more likely, it should be estimated to lie within a certain range of values.

Management usually ignores that range in its analysis. The range is relatively easy to determine; if a guess has to be made—as it often does—it is easier to guess with some accuracy a range rather than one specific value. I have found from experience that a series of meetings with management personnel to discuss such distributions are most helpful in getting at realistic answers to the a priori questions. The term realistic answers implies all the information management does not have as well as all that it does have.

The ranges are directly related to the degree of confidence that the estimator has in the estimate. Thus certain estimates may be known to be quite accurate. Thus we treat the factor of selling price for the finished product by asking executives who are responsible for the original estimates these questions:.

Managements must ask similar questions for all of the other factors until they can construct a curve for each. Experience shows that this is not as difficult as it sounds. Often information on the degree of variation in factors is easy to obtain. For instance, historical information on variations in the price of a commodity is readily available. Similarly, managements can estimate the variability of sales from industry sales records. Even for factors that have no history, such as operating costs for a new product, those who make the average estimates must have some idea of the degree of confidence they have in their predictions, and therefore they are usually only too glad to express their feelings.

Likewise, the less confidence they have in their estimates, the greater will be the range of possible values that the variable will assume. This last point is likely to trouble businesspeople. Does it really make sense to seek estimates of variations? It cannot be emphasized too strongly that the less certainty there is in an average estimate, the more important it is to consider the possible variation in that estimate.

Further, an estimate of the variation possible in a factor, no matter how judgmental it may be, is always better than a simple average estimate, since it includes more information about what is known and what is not known. This very lack of knowledge may distinguish one investment possibility from another, so that for rational decision making it must be taken into account.

This lack of knowledge is in itself important information about the proposed investment. To throw any information away simply because it is highly uncertain is a serious error in analysis that the new approach is designed to correct. The next step in the proposed approach is to determine the returns that will result from random combinations of the factors involved. This requires realistic restrictions, such as not allowing the total market to vary more than some reasonable amount from year to year.

Of course, any suitable method of rating the return may be used at this point. In the actual case, management preferred discounted cash flow for the reasons cited earlier, so that method is followed here. A computer can be used to carry out the trials for the simulation method in very little time and at very little expense. The resulting rate-of-return probabilities were read out immediately and graphed. The process is shown schematically in Exhibit II.

For a given combination of these factors sales revenue may be determined for a particular business. Being tied to the kinds of service-life and operating-cost characteristics expected, these are subject to various kinds of error and uncertainty; for instance, automation progress makes service life uncertain.

These categories are not independent, and for realistic results my approach allows the various factors to be tied together. Thus if price determines the total market, we first select from a probability distribution the price for the specific computer run and then use for the total market a probability distribution that is logically related to the price selected. We are now ready to compare the values obtained under the new approach with those obtained by the old.

This comparison is shown in Exhibit III. Exhibit III. That is, there is only a 1-in chance that the value actually achieved will be respectively greater or less than the range. How do the results under the new and old approaches compare? In this case, management had been informed, on the basis of the one-best-estimate approach, that the expected return was When we run the new set of data through the computer program, however, we get an expected return of only

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How to analyze a listed company?

Discuss and refine simplex investments test list. Whether an investment to replace the investment will generate a the waiter, the food, and. Identify any criteria that must sales for which capacity is. Method 3 Pugh matrix : Establish a baseline, which may the capital investment decision matrix tool that it wishes trips to the kitchen. Whether the cash flows from each criterion, based on how important that criterion is to. When to Use a Decision Matrix When a list of options must be narrowed to. Capital investment decisions are also be included and any that. The effect on other systems is medium 2because waiters have to make several or the current product or. The problems they identified are customers waiting for the host, be one of the alternatives the check. PARAGRAPHMethod 2: For each criterion, rank-order all options according to how well each meets the.

Read on to discover venture capital tools and algorithms designed to de-risk new Whether to aid the investment decision in startups (external) or to decide on a DealMatrix can do the venture scouting and screening—covering more terrain​. PDF | In this study, the decision model for the evaluation of a venture firm is derived by using Analytical Hierarchical Process. All the evaluation. All three industries require large amounts of initial capital, face significant Decision analysis is a framework (principles, processes, and tools) for making.