"What are a sensitivity analysis scenario analysis and monte carlo simulation" Essays and Research Papers

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    Application of Monte Carlo Simulation in Capital Budgeting | | |by Prit‚ Aug 2‚ 2008 | |The usefulness of Monte carlo Simulation in Capital Budgeting and the processes involved in Monte Carlo Simulation. It also | |highlights the advantages in some situation compared to other deterministic models where uncertainty is the norm. | |[pic]

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    Sensitivity Analysis

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    Sensitivity analysis is a technique that indicates exactly how much a project’s profitability (NPV or IRR) will change in response to a given change in a single input variable‚ other things held constant. Sensitivity analysis begins with a base case developed using expected values (in the statistical sense) for all uncertain variables. Then‚ each uncertain variable is usually changed by a fixed percentage amount above and below its expected value‚ holding all other variables constant at their expected

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    Sensitivity Analysis

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    Linear Programming Notes VII Sensitivity Analysis 1 Introduction When you use a mathematical model to describe reality you must make approximations. The world is more complicated than the kinds of optimization problems that we are able to solve. Linearity assumptions usually are significant approximations. Another important approximation comes because you cannot be sure of the data that you put into the model. Your knowledge of the relevant technology may be imprecise‚ forcing you to approximate

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    Chapter 9 Monte Carlo methods 183 184 CHAPTER 9. MONTE CARLO METHODS Monte Carlo means using random numbers in scientific computing. More precisely‚ it means using random numbers as a tool to compute something that is not random. For example1 ‚ let X be a random variable and write its expected value as A = E[X]. If we can generate X1 ‚ . . . ‚ Xn ‚ n independent random variables with the same distribution‚ then we can make the approximation A ≈ An = 1 n n Xk . k=1

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    project. PERT became popular around the same time computers were progressing from the mainframe to mini-computers. During the evolution of computer technology‚ advanced programs were developed to provide further probabilistic estimates via simulations (Monte Carlo Analysis). B) PERT assumes the Beta probability distribution to calculate the expected time of an activity within a network. PERT requires that for each activity‚ three duration estimates are needed (optimistic‚ most likely‚ pessimistic).

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    My undergraduate thesis topic was “Analysis the transport properties of graphene using Ensemble Monte Carlo Simulation” in which I studied electrical conductivity‚ effect of temperature on graphene by varying temperature‚ effect of electric field on drift velocity‚ effect of scattering on mobility‚ observed its some mechanical

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    size affect the simulations ability to calculate dose‚ as well as to understand the effects of cutoff energy on the Monte Carlo simulation (MC). Particle interactions are the cause of everything we know to exist‚ such as the bright lights that illuminate the room you are in or the heat you feel when you stay in the sun for too long. To understand how these particle interactions occur we need to be able to simulate how they occur and study their effects with matter. Monte Carlo is a mathematical

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    1 PROBABILISTIC APPROACHES: SCENARIO ANALYSIS‚ DECISION TREES AND SIMULATIONS In the last chapter‚ we examined ways in which we can adjust the value of a risky asset for its risk. Notwithstanding their popularity‚ all of the approaches share a common theme. The riskiness of an asset is encapsulated in one number – a higher discount rate‚ lower cash flows or a discount to the value – and the computation almost always requires us to make assumptions (often unrealistic) about the nature of risk

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    Sensitivity Analysis Source: Introduction to Management Science 10 e‚ Anderson Sweeney Williams Example 1 Max s.t. 5x1 + 7x2 x1 < 6 2x1 + 3x2 < 19 x1 + x2 < 8 x1‚ x2 > 0 x2 8 7 6 5 4 3 2 1 x1 + x2 < 8 Max 5x1 + 7x2 x1 < 6 Optimal: x1 = 5‚ x2 = 3‚ z = 46 2x1 + 3x2 < 19 x1 1 2 3 4 5 6 7 8 9 10 x2 8 7 6 5 4 3 2 1 5 5 Feasible Region 1 1 1 2 3 4 4 4 3 3 2 2 5 6 7 8 9 10 x1 Example 1 • Range of Optimality for c1 The slope of the objective

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    | | | | For my final paper‚ I chose to watch the documentary Ballets Russes. This documentary recalls the history of the legendary dance troupe Ballet Russe de Monte Carlo. The documentary includes in depth interviews with many of the original members of Ballet Russe of Monte Carlo dance troupe. Through analysis of these in depth interviews‚ I was able to observe many aspects of the ballet culture. Such aspects include things such as social roles‚ language‚ authority‚ expressive culture

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