Cash Flow Model Research Articles

Анализ чувствительности как инструмент принятия решений о реализации инвестиционного проекта горнодобывающей отрасли

Introduction. Russian mining companies need to implement large-scale investment projects due to a variety of internal and external reasons. Projects are aimed at the development of new deposits, technical equipment and the modernization of existing ones. To make substantiated management decisions, a toolkit for analyzing the risks of investment projects is required. Theoretical analysis. The section contains the need to apply quantitative methods for assessing investment risks based on cash flow modeling. We have analyzed the possibility of the use of sensitivity analysis techniques, real options and Monte Carlo methods for the quantitative assessment of the mining industry investment projects risks. The result includes a justification of the feasibility of applying the sensitivity analysis method at the early stages of an investment project. Empirical analysis. The sensitivity analysis tested metrics such as production volumes, commodity prices, capital and operating costs on two mining projects. It was found out that the projects under consideration are the most sensitive to changes in the price of commercial products. Results. Sensitivity analysis is a useful tool for risk analysis of investment projects. The application of this method to an investment project in the mining industry should be carried out taking into account the industry specifics.

Simulating Cash Flow Model for Mega Construction Projects in Egypt

This research presents a cash flow construction road projects prediction model. The model based upon actual current invoices analysis and payments data of road construction projects. Initial results indicate that this simple model is best way for predicting future cash flows especially construction road projects. The main concern is to look at highway road tender projects. This investigation could be used by road authorities who manage multiple projects. It could be used for providing a forecast technique of new project payments. Latest researches from General Authority for Road, Bridges and Land Transporting (GARBLT) projects from 2003 to 2020 were analyzed. This data is used to implement mathematical models for road construction to represent monthly payment invoices for different projects types. Cost estimates of financial data were collected from 78 highway road contracts which are consist of 46 highway strengthening contracts and 32 highway overlay contracts. All collected data from field was arranged into main categories and/or subcategories according to project type and contract amount. A polynomial regression analysis for seventh degree is done for all collected data, and then regression curve is constructed. Statistically equations were performed and taken into research consideration to can provide payment curve expectation. Finally, proposed built in model by using Microsoft Excel was implemented to develop investigation results. The proposed model was named as Multi Road Projects Cash Flow Model MRPCFM.

The effect of financial analysts on the economic implications of disclosed lease information – a note

PurposeThe purpose of this paper is to investigate whether financial analyst coverage affects the dissemination of disclosed operating lease information into cash flow predictions and stock prices.Design/methodology/approachThe difference in lease expense between capital/finance lease and operating lease reporting is estimated based on the approach in Hsieh and Su (2015). This difference is referred to as the earnings impact from operating lease capitalization and is only available from footnotes. The authors then include the level of financial analyst following in a cash flow model to study its impact on the cash flow predictive value of the earnings impact. Similarly, the level of financial analyst following is inserted in an earnings-return model to assess the effect of analyst coverage on the association between contemporaneous stock returns and earnings impact.FindingsThe authors find that the cash flow predictive value of the earnings impact shifts to the interaction between analyst coverage and the earnings impact, suggesting that the decision-usefulness of the earnings impact is conditioned on the level of analyst following. Nevertheless, the authors find that the earnings impact continues to have explanatory value for the contemporaneous stock returns, while the interaction between analyst coverage and the earnings impact does not. This finding suggests that the earnings impact is already fully reflected in stock prices regardless of analyst following.Research limitations/implicationsSince the estimation of the earnings impact from reporting operating leases as capital leases is based on the method developed by Imhoff et al. (1991), the results and inferences are thus constrained by the validity of the method.Practical implicationsThe authors find that financial analyst activities accelerate the incorporation of the earnings impact from operating lease capitalization in cash flow predictions, but it does not promote the impounding of the earnings impact into stock prices. This finding suggests that financial analysts' influence on the dissemination of the earnings impact hinges on the type of economic activity, and failing to consider the financial analyst following in studying the cash flow predictive value of the earnings impact would obscure the findings.Originality/valueThe authors extend the findings of prior research that financial analysts' activities promote the incorporation of firm-specific information into stock prices by investigating the impact of financial analysts on the dissemination of disclosed operating lease information.

Model-free nonparametric bounds for zero-coupon interest rates in bond markets without the no arbitrage principle

ABSTRACT Real-world market quotes of bonds can sometimes contradict the no arbitrage principle within the discounted cash flow model. This makes some kinds of no-arbitrage-based analyses impossible, e.g., inferring the bounds for the term structure of interest rates. Instead of using a more sophisticated model to account for pricing peculiarities, we propose a replacement for the no arbitrage principle. While being theoretically plausible, it does not get contradicted by the data – thus, we can infer the same kind of term structure bounds from it, even given the contradictions with the no arbitrage principle. Using a dataset of Russian sovereign bond quotes, we show that the no arbitrage inconsistency problem arises in 10–20% of cases and that the proposed approach successfully overcomes it.

Comparison of the Accuracy of Direct and Indirect Methods of Cash Flow Models in Predicting Future Profits

Financial reports are part of the financial reporting process. Complete financial statements usually include balance sheets, income statements, statements of changes in financial position (which can be presented in various ways, for example, as cash flow statements, or cash flow statements), notes and other reports and explanatory material that are an integral part of the financial statements. . The purpose of this study is to provide empirical evidence whether a model with a direct cash flow component has a more accurate predictive ability than a model with an indirect cash flow component to predict future earnings. The parameters of this research model were estimated using panel data regression. This study considers 4 regression methods of penel data, namely (1) linear regression model (OLS), (2) covariance model (FEM), (3) error components (ECM) model, (4) time series autocorrelation model (GLS) ( Thiono, 2007). The results of the analysis of this study are the direct method cash flow component is more accurate than the indirect method cash flow component in predicting future earnings in manufacturing companies, finding that the direct method component is more accurate than the indirect method. Then for the cash flow component model the direct method is more accurate than the model with the indirect method cash flow component in predicting future earnings in non-manufacturing companies, finding that the cash flow components of the direct method and the indirect method do not differ in their accuracy in predicting future earnings.

Utilization of forestry waste materials in British Columbia: Options and strategies

The Canadian province of British Columbia has large forestry resources and therefore provides an informative example of the potential role of bioenergy in mitigating GHG emissions. Even in biomass-rich British Columbia, forestry resources are only sufficient to meet part of the energy demand. This paper compares different energy conversion routes for forestry waste materials: via hydrothermal liquefaction, thermochemical methanol and bioethanol, renewable natural gas, cogeneration of heat and power, heat-only boilers, and power-only generation. The GHG savings, health impacts, minimum selling prices, and GHG abatement costs for each option are estimated by combining life cycle assessment with a discounted cash flow model. The input-based functional unit of 1 oven-dry tonne biomass provides a better basis for comparing possible uses of finite biomass supply than the commonly-used output-based functional unit of 1 GJ bioenergy. Heat-only boiler for district heating gives the highest GHG reduction of 960 kgCO2-eq per oven-dry tonne feedstock, while power-only generation delivers minimal GHG benefit in British Columbia. Heat-only boiler and cogeneration offer the lowest GHG abatement costs (<$-20/tCO2-eq), due to lower costs and higher energy conversion efficiencies, and are already economically viable, but will not use all the available resources because health impacts generated by biomass combustion limit their deployment, despite life cycle health benefits for avoiding hazardous emissions from slash burning of forestry waste materials. Refined biofuel options are much less cost-effective (>$50/tCO2-eq); further technology improvement and policy support are needed to offset the cost disadvantage.

Distributed education enables distributed economic impact: the economic contribution of the Northern Ontario School of Medicine to communities in Canada

BackgroundMedical schools with distributed or regional programs encourage people to live, work, and learn in communities that may be economically challenged. Local spending by the program, staff, teachers, and students has a local economic impact. Although the economic impact of DME has been estimated for nations and sub-national regions, the community-specific impact is often unknown. Communities that contribute to the success of DME have an interest in knowing the local economic impact of this participation. To provide this information, we estimated the economic impact of the Northern Ontario School of Medicine (NOSM) on selected communities in the historically medically underserviced and economically disadvantaged Northern Ontario region.MethodsEconomic impact was estimated by a cash-flow local economic model. Detailed data on program and learner spending were obtained for Northern Ontario communities. We included spending on NOSM’s distributed education and research programs, medical residents’ salary program, the clinical teachers’ reimbursement program, and spending by learners. Economic impact was estimated from total spending in the community adjusted by an economic multiplier based on community population size, industry diversity, and propensity to spend locally. Community employment impact was also estimated.ResultsIn 2019, direct program and learner spending in Northern Ontario totalled $64.6 M (million) Canadian Dollars. Approximately 76% ($49.1 M) was spent in the two largest population centres of 122,000 and 165,000 people, with 1–5% ($0.7 M – $3.1 M) spent in communities of 5000–78,000 people. In 2019, total economic impact in Northern Ontario was estimated to be $107 M, with an impact of $38 M and $36 M in the two largest population centres. The remaining $34 M (32%) of the economic impact occurred in smaller communities or within the region. Expressed alternatively as employment impact, the 404 full time equivalent (FTE) positions supported an additional 298 FTE positions in Northern Ontario. NOSM-trained physicians practising in the region added an economic impact of $88 M.ConclusionsBy establishing programs and bringing people to Northern Ontario communities, NOSM added local spending and knowledge-based economic activity to a predominantly resource-based economy. In an economically deprived region, distributed medical education enabled distributed economic impact.

Optimal pricing and replenishment policy for perishable food supply chain under inflation

The COVID-19 outbreak-caused blockade and disruption of the supply chain have dramatically increased the prices of perishable food and other products that rely heavily on the timeliness of supply chains. In the case of inflation, this study aims to make some adjustment to the pricing and replenishment strategy of perishable food and compare it with the scenario without considering inflation to determine the impact of the inflation rate, quality deterioration, time value of money, and characteristics of cash flow of perishable food sales on the supply chain decision-making. We used the discounted cash flow (DCF) model to measure retailers’ revenue, which established that the optimal pricing and replenishing strategy could maximize the retailers’ profit. Besides, the findings were compared with the traditional profit model. Moreover, numerical experiments and sensitivity analysis were provided for decision support to retailers. Overall, this study validates that inflation significantly affects the pricing and replenishment strategy, and the DCF model is more suitable to evaluate the profits of perishable food.

Toward global comparability in renewable energy procurement

<h2>Summary</h2> Prices from the competitive procurement of renewable energy are increasingly used for the comparative evaluation of financial and technology performance. Comparing prices from auctions or power-purchase agreements at their face value is often not meaningful, particularly across jurisdictions or over time. Differences in support regimes and the market, tax, and regulatory environment can make a like-for-like comparison convoluted and result in misleading conclusions. Here, we estimate project revenue and value holistically for eight global offshore wind projects. Using a cash flow model, we consider applicable support regimes; market sales; and the monetized value of tax incentives, depreciation, and transmission. We find considerable variation in the absolute levels and relative composition of project revenue and value, which must be considered for deducting costs from procurement prices. The resulting metric enables decision makers and research to compare the total cost of procurement on an equal footing and supplements established cost metrics.

The role of operating cash flow and accrual components of earnings in improving the predictive ability of earning

The prediction of Cash flow is involved in a number of economic decisions, particularly in investment. Previous research conducted in the United States has provided inconsistency in the results of investigating accounting data, cash flow and accrual accounting data in predicting future cash flows. Few researches were detected addressing the prediction of cash flow in an Egyptian context. This research aims to test the ability of accounting earnings versus cash flows and accruals to predict future cash flows for a sample listed firms in the Egyptian stock exchange. To achieve this objective, a sample of 102 firms from 14 different sectors was collected from year 2012 to 2017 (585 observations after excluding outliers).The empirical results show that past earnings, cash flows and accrual component of earnings can be used to predict future cash flows of Egyptian listed companies and cash flows have better predictive power than past earnings. Additionally, the cash flow model and the cash flow and accrual components of earnings model have better predictive power than the earnings model. The findings of testing the models in an out-of-sample period suggest that the cash flow model is a better predictor of future cash flows than the other models.

Do Indian firms engage in classification shifting to report inflated core earnings?

PurposeThe authors aim at investigating different forms of classification shifting (CS). CS is a novel form of earnings management under which managers misclassify income statement line items and cash flow statement line items with an intent to report favorable operating performance of firms. In particular, the authors check the existence of revenue misclassification, expense misclassification and cash flows misclassification among Indian firms by taking the uniform sample of firms over a single period.Design/methodology/approachOperating revenue model (Malikov et al., 2018), core earnings expectation model (McVay, 2006) and operating cash flows model (Roychowdhury, 2006) are employed for measuring revenue misclassification, expense misclassification and cash flows misclassification, respectively. The panel data regression models are used to analyze the data for this study.FindingsBased on the sample of 12,870 Bombay Stock Exchange (BSE) listed firm-years observations between 2010 and 2018, we find that, on average, Indian firms are engaged in revenue misclassification rather than expense misclassification to report inflated core earnings. Firms are found to be engaged in cash flows misclassification too. Besides, we find that magnitude of shifting is greater among larger firms. Results also establish that adoption of Ind AS increases the scope of shifting practices. These results are based on several robustness checks.Practical implicationsThe results suggest that investors conduct a comprehensive review of the items of financial statements before using them in their portfolio valuation. It suggests auditors check the basis of revenue classification and standard-setting authorities, like ICAI in India, to make more mandatory disclosure requirements for classification of revenues and cash flows. It suggests lenders not to make lending decisions by looking at the operating performance metrics, as CS is the most preferred tool to positively influence the perception of lenders toward operating performance.Originality/valueIt is the first study that investigates different forms of classification shifting jointly for a sample of firms. Most of the earlier studies have examined one kind of classification shifting at a time. This study adds to the existing literature on earnings management by documenting that some firm-specific factors pressurize firms to prefer one form of shifting over another to report inflated core earnings.

SIMULATION MODELLING AS A TOOL FOR RISK ANALYSIS AND DEVELOPMENT OF STRATEGY TO INCREASE REAL ESTATE INCOME

The purpose of th article is to substantiate the possibility of applying methods for assessing the effectiveness and risks of investing for the analysis of income in the strategic management of real property. Methodology. The methodical bases of sensitivity analysis and simulation modeling of cash flows of real property income are stated. Results. The critical factors of costs and revenues affecting net present value of total cash flow from grain elevator real property object have been revealed. It is evidenced that the most significant factors influencing the amount of cash flows are the volume of sales of grain elevator services, to a lesser extent the total costs and the lack of sensitivity of net present value to staff salary variations. Simulation modeling of the change in net present value due to the change of the most significant uncertain factors was performed, which confirmed the assumptions about the efficiency of the investigated real property. The key factors are the main services that generate net operating income and critical expenses. Namely, services: storage, drying, shipment by road and rail, costs: fuel for drying, electricity, fuel for transportation of grain, staff salaries. For each factor, the relevant limits of change were established (determined by experts taking into account the average annual growth rate of the indicator) and cash flow simulation was performed. Practical implications. Statistical analysis of the model's behavior under the influence of random factors shows that the most probable value of the net present value of cash flows will be positive, despite the simulation of a significant change (+/- 40%) in electricity and fuel consumption factors for grain transportation. The values of the simple and discounted payback period also confirm the efficiency of the elevator property functioning. The indicator of the stability level demonstrate the need of planning input cash flows sources to cover the output cash flows. Value/originality. The expected profitability of grain elevator real property is largely determined by the factor of the volume of basic services sales (storage, drying, shipment and transport of products). This creates the preconditions for the subsequent assessment of the value of grain elevator real property based on the methodology of the income approach.

Who Benefits from the Housing Provident Fund System in China? An Analysis of the Internal Rate of Return for Typical Employees with Different Incomes

The Housing Provident Fund System (HPFS) was established in China in the 1990s as a welfare program to offer low-cost loans and encourage the purchasing of houses. However, there has been some controversy over the income redistribution effect of HPFS. Previous studies focused on the effect of low-interest-rate loans but ignored the effects of tax exemptions and low-interest-rate deposits. This paper introduces a lifetime cash flow model which considers the effects of low-interest-rate loans, tax exemptions, and low-interest-rate deposits together. It compares the internal rate of return (IRR) for typical employees with different incomes in four situations: whether or not HPFS participation and whether or not house purchasing. We found that the IRRs of the typical low-income HPFS participants who buy houses with HPFS loans were lower than the IRRs of non-participants who buy houses with commercial mortgages without HPFS participation. For the typical middle-income employees, there is not much difference in IRR between the two situations. Only the typical high-income employees can benefit from HPFS participation, and this is mostly due to the effect of the tax exemptions, rather than the effect of low-interest-rate loans. Increasing the coverage of HPFS and HPFS loans among low-income employees will not improve the income redistribution effect of HPFS.

Are Discount Rates In Disarray In The First Year Adoption Of International Financial Reporting Standards?

In calculating recoverable amount of cash generating units (CGUs) under the implementation of value in use approach, discount rate selection represents a central point in deciding the magnitude of impairment charges under Hong Kong Financial Reporting Standards (HKFRSs). The selection of discretion discount rate in the discounted cash flow model (DCF) could be used opportunistically to misstate impairment losses for the benefit of financial statement preparers and causes the transparency of the financial reports. This study is conducted to provide evidence of opportunistic behaviours relating on goodwill impairment by reporting statement preparers. By comparing independently estimated risk adjusted discount rates and those subjectively presented by large listed Hong Kong firms in the first year adoption of HKFRSs, the results showed that discount rates were presented in disarray, in which discount rates were more overstated than understated in comparison with scientifically generated ones.

A Structure optimization method used in microgrid

This paper takes a large photovoltaic plant as a pilot platform to research the micro gird. In the micro grid, DC bus is the key structure, photovoltaic panels are the micro power source, lithium iron phosphate batteries are the energy storage device, and four converters are used as energy conversion device. This paper studies its specific characters such as component unit, control strategy, monitoring system and investment model. the paper builds a valuation model in the investing of energy micro system by using discounted cash flow model. According to power cost model, ecological and economic benefits are analysed and summarized, providing reference for the further application of construction on photovoltaic micro grid projects.

Dynamical Internal Cost of Capital Driven by Cash Flow Growth

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

Methanol production via integrated methane reforming and chemical looping combustion: Process simulation and techno-economic assessment

In this research, a novel technology is proposed that combines chemical looping combustion and methane reforming in order to convert CO2 to value added chemicals. The stoichiometric number is improved via adding assisted steam and utilizing pressure swing adsorption unit. The process simulation is conducted utilizing Aspen plus-V10 simulation software. The new built-in model featured by AspenTech, dubbed Fluidbed, in Aspen Plus is employed to simulate the CLC section. In Aspen Plus flowsheet environment, a hierarchal approach is considered in that the main flowsheet is divided into 5 hierarchy models or sub flowsheets. The process simulation results display that the overall conversions of CH4 and CO2 via this process are 97 % and 87 %, respectively. The heat integration results depict that 138.7 MW heat energy can be saved in the process. The CO2 emission of the whole process per methanol production is 0.1 tCO2/tMe. The estimated capital expenditure, and operating expenditure are US$ 509 million and US$ 159 million/yr, respectively. A discounted cash flow model combined with sensitivity analyses showed that a breakeven point could be reached with a methanol price of US$ 242/tonne. Net present value, internal rate of return, and pay out time are evaluated based on DCF results.

Profitability, risk and cash flow deficit for beginning cow–calf producers

PurposeThe purpose of this study is to estimate the amount of cash flow deficit, if any, needed to maintain the operating costs and service debt of a startup cow–calf enterprise. The study compares long-term profitability and risk between starting small and building a herd to full carrying capacity or by starting at desired herd capacity.Design/methodology/approachA dynamic cattle growth model was developed to capture expanding and maintaining the desired herd size. Discounted cash flow (DCF) models over a 15-year period were calculated to estimate net present value (NPV), modified internal rate of return (MIRR) and cash flow deficit to keep the business operating and service debt. Simulation analyses were conducted considering price and production risk.FindingsStarting at the desired herd size was preferred, according to NPV/MIRR and cash flow deficit, but the differences were not substantial. Assuming the operation is liquidated at book values, there was a 36.3% probability of this enterprise having a zero or positive NPV. If the conservative terminal value assumption is relaxed up to feasible market values, the cow–calf enterprise is economically attractive at an estimated 2.4% opportunity cost of capital. However, the producer would experience a cash flow deficit during the first seven years, which was simulated to be $14,892 and $15,985 annual for both strategies.Originality/valueInnovative methods used in this study include varying the annual opportunity cost of capital as a function of financing decisions, stochastic prices by cattle type and stochastic weaning weights that are a function of a dynamic cattle model.

Two-dimensional stochastic modeling for predicting bankruptcy for manufacturing companies

Increasing accuracy of the model prediction on business bankruptcy helps reduce substantial losses for owners, creditors, investors and workers, and, further, minimize an economic and social problem frequently. In this study, we propose a stochastic model of financial working capital and cashflow as a two-dimensional Brownian motion X(t) = (X1(t),X2(t)) on the business bankruptcy prediction. The probability of bankruptcy occurring in a time interval [0,T] is defined by the boundary crossing probability of the two-dimensional Brownian motion entering a predetermined threshold domain. Mathematically, we extend the result in Fu and Wu (2016) on the boundary crossing probability of a high dimensional Brownian motion to an unbounded convex hull. The proposed model is applied to a real data set of companies in US and the numerical results show the proposed method performs well.

Liquidity, hedging and the survival of North German dairy farms

AbstractIncreasingly, European dairy farmers have to manage the raw milk price risk. Price hedging for raw milk and an increasing number of individual fixed-price contracts with processors are now available. However, the choice of hedging a certain share of milk output still leaves individual farmers facing a complex decision. The cash flow model in this study explains the probability of a typical northern European dairy farm surviving illiquidity over an 18-month period under common milk price volatility. The probability of farm survival was modelled in relation to available liquidity buffers and different levels of farm-specific production costs. The model allowed minimum shares of milk output to be determined, for which a fixed price should be hedged if the objective is farm survival at a given probability. Using these modelling results, practitioners are able to determine this share graphically.