Cash Flow Simulation Research Articles

Nickel Price Projection Using Multivariate Regression Method and Investment Feasibility Analysis of Nickel Mining in Indonesia with Sensitivity Analysis and Monte Carlo

Nickel is one of the metals commonly used in various industries. Indonesia is one of the countries that has the largest nickel reserves in the world. Nickel prices will be formed through an equilibrium mechanism between production supply and nickel demand. This study will analyse the relationship between nickel price formation, supply, and demand. Nickel prices will also affect the feasibility of nickel mining investment in Indonesia. The data used in this study consists of market data derived from historical reports of the last 5 – 12 years (2010 – 2022) and mining plan assumptions derived from benchmarks with similar industries. The methods used in this analysis are multivariate regression, discounted cash flow, sensitivity analysis, and Monte Carlo simulation. The results of the analysis that have been carried out show the relationship between nickel supply and demand with prices, with estimated nickel price projection ranging from $16,750 / Ton – to $18,927 / Ton. The factors that most influence the feasibility of mining investment are nickel price, sales realization, water content, contractor costs, and fuel costs. The risk of nickel mining investment in Indonesia based on Monte Carlo simulations is estimated at around 11.36%. This shows that nickel mining investment in Indonesia is still very attractive.

APPLICATION OF EXPECTED CREDIT LOSS MODEL AND MARKOV CHAIN TO CALCULATE NET SINGLE PREMIUM OF UNSECURED CREDIT INSURANCE

Transferring credit risk to an insurance company is a way to mitigate risk. Premiums should be calculated accurately to attain economic value for both the lender and the guarantor. The aim of this study was to determine the net single premium (NSP) values for an unsecured credit insurance product using the expected credit loss (ECL) method from IFRS 9. This study used data generated through simulation of insurance policies issued in 2015 or 2016. Their state classifications were monthly observed from 2016 to 2020. The probability of disbursed claim (PDC) parameter replaced the probability of default parameter on the ECL model, whereas the PDC model was constructed based on the components of a state-transition probability matrix, obtained with the Markov chain approach using the cohort method: = 0.999181, = 0.000130, and = 0.000689. The PDC model validation showed relatively decent results, whereas MSE = 2.457% and zs = 0.608 with a = 5%. These results indicated that the PDC model was a good fit to calculate ECL. 5,000 iterations were done as part of the cash flow simulation process, whereas debtors’ loan amounts were randomly generated during each iteration, and the average NPV of these iterations was -Rp564.419.305. Based on model sensitivity analysis, cash flow values were most sensitive to the variable used to construct the PDC model (). Thus, the 5,000-iteration process was repeated with the newly adjusted PDC value, which were = 0.998924 and = 0.000946. The new average NPV of these iterations was Rp409,877,840, indicating that the constructed ECL model was a good fit to calculate NSP values for unsecured credit insurance products.

MoneyWise Cash-Flow Simulation Module: Improving Students’ Grade Through Enhanced Personal Financial Planning System

The development of MoneyWise Personal Cash-Flow Simulation Module in teaching and learning focuses on helping students understand the personal financial management elements. The simulation enables the students to experience the essentials of budgeting, record-keeping, valuable tools, and tips on managing cash flows and other related activities in money management. During the simulation, the students have been able to analyse their financial position in various reports, such as the budget template and cash-flow statement. In the meantime, the module will enhance students’ potentials to obtain excellent grades in the personal financial planning course and elevate their skills and readiness to face real-life situations in the future. The findings have shown that the percentage of student’s scores in Part A has increased from 75.9 per cent in semester 20182 to 84.6 per cent in semester 20184. While 80.6 per cent score in 20192 which is above the targeted average, concludes that the objectives have been achieved. The system not only functions as an e-learning material but is also helpful for individuals to record and manage their daily transactions. MoneyWise is an excellent e-learning innovation and relevant financial tool to elevate financial literacy, aligning with the National Strategy for Financial Literacy 2019-2023.

Pricing climate-related risks of energy investments

This paper presents a framework for pricing the climate resilience of an energy infrastructure project through assessing the value of its required debt and equity investments. Integrating climate scenarios into an asset valuation model provides useful and specific insights for risk management, but there is a lack of academic and market tools that effectively address this need. The critical barrier is that climate-related risks (physical and transition) are typically indirect variables in the cash flow calculation, and they should be computed based on the direct variables such as revenue, capital expenditures, operating expenses, and financing costs. The implementation of this framework shows how to delineate climate-related risks that are asset-specific and transforms them into financial risks. Using cash flow simulation and scenario analysis, it estimates an energy infrastructure asset's probability of default due to climate-related risks and the size and timing of the losses for any given default. To demonstrate the framework's application, we simulate the price climate-related risks of a utility-scale electricity generation facility powered by natural gas.

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.

Pricing Climate-Related Risks of Energy Investments

This paper presents a framework for pricing the climate resilience of an energy infrastructure project through assessing the value of its required debt and equity investments. Integrating climate scenarios into an asset valuation model provides useful and specific insights for risk management, but there is a lack of academic and market tools that effectively address this need. The critical barrier is that climate-related risks (physical and transition) are typically indirect variables in the cash flow calculation, and they should be computed based on the direct variables such as revenue, capital expenditures, operating expenses, and financing costs. The implementation of this framework shows how to delineate climate-related risks that are asset-specific and transforms them into financial risks. Using cash flow simulation and scenario analysis, it estimates an energy infrastructure asset’s probability of default due to climate-related risks and the size and timing of the losses for any given default. To demonstrate the framework's application, we simulate the price climate-related risks of a utility-scale electricity generation facility powered by natural gas.

Default Probability Assessment for Project Finance Bank Loans and Basel Regulations: Searching for a New Paradigm

Syndicated loan data from India suggest that despite the pressure on margins and volumes, available “bankable” deals in infrastructure are still strongly contested by commercial lenders. With the implementation of Ind AS accounting norms (IFRS) for commercial banks, the expected credit loss–based provisions have to be set by the bank based on internally estimated probability of default (PD) for different loan portfolios. This change may lead to heavier risk-weighted capital requirements for banks, thus impacting the project finance business. Basel III norms and subsequent discussion papers propose a revised standardized approach doing away with internal modeling approaches and introduction of standardized output floors for specialized lending, including project finance. In this light, the authors present a cash flow simulation model to address the issue of PD estimation by simulating key risk factors. This method may be useful as each project and each sector is unique and so are the risks associated with it. Thus, the authors argue that the use of a simulation model will result in better assessment and monitoring of credit risk than conventional assessment methods, leading to lower default rates and therefore lower capital charge. The authors then suggest some new rules of engagement for project finance lenders to stay relevant in the changing regulatory scenario. TOPICS:Simulations, project finance, credit risk management Key Findings • Probability of default estimation and subsequent impact on credit risk capital is important for project finance lenders in India especially after emerging Basel III reforms and subsequent discussion papers on credit risk capital. (Informally called as Basel IV) • The authors suggest a cash flow simulation model developed using risk parameters “specific” to each project. The application of the model is shown on a road project and it calculates cumulative default risk probability of the project. • The article argues that this model will result in better assessment and monitoring of credit risk. Authors also suggest new rules for engagement for the project finance lenders in the emerging regulatory scenario.

Impact of pelleting cost on competitiveness of intentionally grown biomass for local space heating: Case example of the Czech Republic

Biomass plays a dominant role in the EU RES portfolio, especially in CE countries. Pellets from locally produced biomass can serve as a substitute of coal still widely used for local heating to date in the Czech Republic and other Central and Eastern European countries. Wood chips from short rotation coppice plantations (SRC) is suitable source of biomass for the production of pellets for local space heating. Cost of pellets production from biomass from SRC plantations is modeled using cash flow simulation related with all parts of pellets production chain. Article presents results of modeling of biomass cost from SRC plantations and its processing into wood pellets in the conditions of the Czech Republic. The cost of pellets, respecting the whole production cycle from biomass cultivation to pelleting, ranges from 7.85–8.55 EUR/GJ for typical yields of SRC plantations 8–10 t(DM)/ha,year. To achieve competitiveness with domestic (Czech) brown coal (6.5–7.3 EUR/GJ) for local space heating, it would be necessary either to increase the ecological tax on coal 10 x (to about 3.3 EUR/GJ) or to subsidize the establishment of the SRC plantation (1300 EUR/ha) or to double the area subsidy per year (to 390 EUR/ha,year).

Valuation of strategic options in public–private partnerships

This paper investigates the feasibility of and develops an economic valuation model for strategic options in Comprehensive Development Agreements (CDAs). A CDA is a form of public–private partnership whereby the right to price and collect revenues from toll roads is leased to a private entity for a long but finite period of time. In exchange, this provides local and state governments with a quick influx of cash and/or additional infrastructure. Uncertainty associated with such long-term leases is of substantial public concern. This paper examines five different strategic options, namely a buyout option, a conditional buyout option, a revenue-sharing option, and two types of minimum revenue guarantee options. The buyout option in particular could give the public sector additional control over the future use of leased facilities and address potential concerns regarding long-run uncertainty and possible unforeseen windfalls for the private sector. The paper’s contributions include the analysis, feasibility assessment and valuation of several strategic options, sensitivity analysis of the solutions, an economic consumer demand-based revenue model for purposes of cash flow simulation, and analysis of option price sensitivity to “moneyness”. The main conclusion is that strategic options can provide useful risk reduction, but generally have significant value relative to the lease itself. By scaling down payoffs, options could be realistically included in CDAs and other PPPs. For some parameter values, option values to the developer and public authority are offsetting, allowing for costless risk reduction.

Aplikasi Sistem Pendukung Keputusan Untuk Menentukan Harga Layanan Teknologi Informasi

The effects of recency of information technology (IT) will be invested impaired, this makes it difficult to assess the information technology investment. This study intend to calculate the production cost of IT services with the activity based costing system method, to assess IT investments. This study make the position of IT department as an independent business that sells services to other departments within the organization (IT as a service - ITaaS). To assess the IT investment carried out in 3 stages, 1) Do departmentalize overhead, 2) Calculate the production cost of IT services,3) Perform investment analysis using cash flow simulation with the net present value method. The result of this study is decision support system information to assist management in determining the implementation of IT investments, to do their own (in-house) or purchased from an outside party (outsourced). In this way, losses due to errors in executing IT investments can be avoided, because the analysis is done prior IT investments held. Keyword s : IT Investment; Net Present Value (NPV); Activity-Based Costing system (ABC);Value chain; IT as a Service (ITaaS)

Selection of the open pit mining cut-off grade strategy under price uncertainty using a risk based multi-criteria ranking system / Wybór strategii określania warunku opłacalności wydobycia w kopalniach odkrywkowych w warunkach niepewności cen w oparciu o wielokryterialny system rankingowy z uwzględnieniem czynników ryzyka

Abstract Cut-off Grade Strategy (COGS) is a concept that directly influences the financial, technical, economic, environmental, and legal issues in relation to exploitation of a mineral resource. A decision making system is proposed to select the best technically feasible COGS under price uncertainty. In the proposed system both the conventional discounted cash flow and modern simulation based real option valuations are used to evaluate the alternative strategies. Then the conventional expected value criterion and a multiple criteria ranking system were used to rank the strategies based on the two valuation methods. In the multiple criteria ranking system besides the expected value other stochastic orders expressing abilities of strategies in producing extra profits, minimizing losses and achieving the predefined goals of the exploitation strategy are considered. Finally, the best strategy is selected based on the overall average rank of strategies through all ranking systems. The proposed system was examined using the data of Sungun Copper Mine. To assess the merits of the alternatives better, ranking process was done at both high (prevailing economic condition) and low price conditions. Ranking results revealed that at different price conditions and valuation methods, different results would be obtained. It is concluded that these differences are due to the different behavior of the embedded option to close the mine early, which is more likely to be exercised under low price condition rather than high price condition. The proposed system would enhance the quality of decision making process by providing a more informative and certain platform for project evaluation.

Recombining Trinomial Tree for Real Option Valuation with Changing Volatility

This paper presents a recombining trinomial tree for valuing real options with changing volatility. The trinomial tree presented in this paper is constructed by simultaneously choosing such a parameterization that sets a judicious state space while having sensible transition probabilities between the nodes. The volatility changes are modeled with the changing transition probabilities while the state space of the trinomial tree is regular and has a fixed number of time and underlying asset price levels. The presented trinomial lattice can be extended to follow a displaced diffusion process with changing volatility, allowing also taking into account the level of the underlying asset price. The lattice can also be easily parameterized based on a cash flow simulation, using ordinary least squares regression method for volatility estimation. Therefore, the presented recombining trinomial tree with changing volatility is more flexible and robust for practice use than common lattice models while maintaining their intuitive appeal.

Cash Flow Simulation Embedded Real Options

Cash flow simulation embedded option is an option whose value is based on choosing the optimal decision in each time step during a single cash flow calculation simulation run. Cash flow simulation embedded options are mostly operative options with continuous, gradual and nearly immediate exercise with well-known payoff or benefits. Typically these options are difficult to model with other methods than Monte Carlo simulation. However, cash flow simulation embedded options and the common, once exercisable options can be applied simultaneously in an investment valuation by using the simulated cash flow with embedded options as the underlying asset for the lattice, which is then used in valuing other lattice type options and their interactions.

Displaced Diffusion Binomial Tree for Real Option Valuation

This paper describes a real options valuation method for situations where the underlying asset may have negative values and the underlying project present value distribution is something of the shape between normal and lognormal distribution causing skewness to the rate of return distribution. The underlying project value is assumed to follow a displaced diffusion process with a dynamic path having up and down movements with properties of both additive and multiplicative processes. Therefore the approach takes into account the changing volatility according to the level of the underlying asset value. A recombining binomial tree solution for the displaced diffusion is presented with a managerially applicable simulation based parameterization. The results suggest that the assumptions of geometric Brownian motion and a lognormal distribution may not be sufficient for practical cash flow simulation based real option valuation.

Sensitivity Analysis for Cash Flow Simulation Based Real Option Valuation

Sensitivity analysis identifies the critical aspects of the investment model that affect model output uncertainty. Common sensitivity analysis on options considers how the solution changes as a result of change in one of the key parameters (underlying asset value, volatility, exercise price, interest rate, time to maturity, dividends). In case of cash flow simulation based real options, these are mostly indirect variables that are computed based on the primary input variables – demand, unit selling price, and unit costs – in the cash flow calculation. The method presented in this paper combines the uncertainties in the underlying asset together by simulation, and then uses regression analysis approach for estimating how a change in a primary variable or variables affects simultaneously the stochastic process parameters of expected value and volatility during different time periods. As a result, the presented method shows how a change in a primary variable affects project value with real options. This information is also essential as it shows decision makers which uncertainties to follow, and thus this mitigates the common black box syndrome of consolidated cash flow simulation based methods.

Estimating Changing Volatility in Cash Flow Simulation Based Real Option Valuation with Regression Sum of Squares Error Method

This paper presents a practical volatility estimation method for cash flow simulation based real option valuation with changing volatility. During cash flow simulation, present value of the future cash flows and their corresponding cash flow state variable values are recorded for all time periods. Then, for each time period, regression analysis is used for relating the present value to the cash flow state variables of the same time period. Each regression equation provides an estimate of the expected present value as a function conditioned on the resolution of all uncertainties up to that time. Then, basic regression statistics of Pearson’s correlation R2 and sum of squares error (or standard error) for each equation provide all the information required for estimating how the standard deviation and volatility of the stochastic process change over time. The method is computationally efficient because it requires only one pass of simulation runs regardless of the number of time periods. It can also handle negative underlying asset values. Straightforward calculation of required regression statistics and their availability in any statistical software and even in spreadsheet programs make this approach very easy to apply for a practitioner.

Regression sensitivity analysis for cash flow simulation based real option valuation

Sensitivity analysis on financial options considers how the solution changes because of a change in one of the key parameters (underlying asset value, volatility, exercise price, interest rate, time to maturity, dividends). In case of real option valuation with cash flow simulation, however, these are mostly indirect variables which are computed based on the uncertain direct variables – e.g. demand, unit selling price, and unit costs - in the cash flow calculation. The method presented detects the most significant primary variables, and based on this analysis, shows how changes in the direct uncertainties can be used to estimate with the response surface method the simultaneous changes in the indirect parameters defining the underlying asset process and thus the real option value.

Separating Ambiguity and Volatility in Cash Flow Simulation Based Volatility Estimation

Volatility is a significant parameter both in financial and real options valuation. However, in the case of several real option projects there is no historical data available. In such cases, one alternative is to use Monte Carlo simulation on projects' cash flows for estimating volatility. An important issue that has not been taken into account with most of these volatility simulation procedures is that not only the volatility but also the value of the underlying asset is often uncertain in the beginning. Because most of the existing methods do not take this into account, they overestimate the actual volatility of the project. This paper presents a procedure that separates the underlying asset uncertainty in the beginning from the volatility and hence improves the volatility estimation.

Liquidity, solvency and cash flow simulation models in non‐life insurance companies: the Italian experience

This paper discusses dynamic financial approaches to solvency analysis in non‐life insurance companies by explaining cash flow simulation models which are based on the planning of their typical cash inflows and outflows. Posits that these models take into account patterns of loss reserve run‐offs and asset cash flows by implementing several hypotheses that also include expectations about external economic conditions such as inflation rates and interest rates. Acknowledges the cash inflows and outflows have been planned over a period of time to evaluate how positive net cash flow (liquidity) leads to the increase in assets over liabilities (solvency).

Insolvency Risk in the Italian Non-life Insurance Companies. An Empirical Analysis Based on a Cash Flow Simulation Model

Policyholders do not accurately know the financial condition of insurers because of asymmetric information that makes prices unable in discriminating risk behaviour of insurance companies and provides rationale for prudential regulation. Regulators often imposed capital requirements to ensure solvency having some drawbacks in preventing the assumption of excessive risks. Hence, other methods should be taken into account in order to estimate their ability in identifying troubled insurers. This study analyses insolvency risk in the Italian non-life insurance market by adopting a deterministic cash flow simulation model in order to predict insolvencies over the period from 1990 through 1994. The model is based on future projections of principal cash inflows and outflows of insurance companies. Several hypotheses about the evolution both of insurance and economic variables such as premiums, losses for claims, stock prices, interest rates and inflation rates are implemented in the model. The results show a strong ability of the model in identifying insolvent insurers during the period examined here and suggest that cash flow simulation models may provide regulators and managers with useful information on insurance solvency.