monte carlo simulation excel and model risk

... multiple model outcomes that you can analyze. This is where Monte Carlo simulation comes in handy. WHAT IS MONTE CARLO SIMULATION? What do we mean by " ;simulation? " When we use the word simulation, ... available simulation add-in for Excel is Crystal Ball 2000, which will be used in this example. How did Monte Carlo simulation get its name? Monte Carlo simulation was named for Monte Carlo, Monaco, ... to reproduce. Monte Carlo simulation is a form of simulation that randomly generates values for uncertain variables over and over to simulate a model. Without the aid of simulation, a spreadsheet model...

Ngày tải lên: 08/04/2014, 12:08

... thickness between simulation by MCNP and experimental measurement for thin stainless steel. VNU Journal of Science, Mathematics - Physics 26 (2010) 43-49 43 Monte carlo simulation by ... plastic, aluminum and steel with using the dedicated system of MYO-101, having scintillation detector of YAP(Ce) and gamma-ray of 60 keV of Am-241 source, by Monte- Carlo simulation using the ... the field of application of nuclear technique in industry in Vietnam. Keywords: Monte- Carlo simulation, Monte Carlo N-Particle, Backscattering gamma, Scintillation detector, Nuclear technique....

Ngày tải lên: 22/03/2014, 11:20

... plastic, aluminum and steel with using the dedicated system of MYO-101, having scintillation detector of YAP(Ce) and gamma-ray of 60 keV of Am-241 source, by Monte- Carlo simulation using the ... the field of application of nuclear technique in industry in Vietnam. Keywords: Monte- Carlo simulation, Monte Carlo N-Particle, Backscattering gamma, Scintillation detector, Nuclear technique. ... to support and compare them with experimental results, research method of Monte Carlo simulation by code of MCNP (Monte Carlo N-Particles) for thickness measurement based on the effect of backscattering...

Ngày tải lên: 21/07/2014, 16:21

Ngày tải lên: 14/11/2014, 08:17

... seven substrate concentrations) and its best estimates were further analyzed for better implementation of the experimental error. The application of error models P k i;j in the Monte Carlo simulations has the ... P mean,i,j values and their model standard deviation P M std;j P mean;i ;j ị from the experiment shown in Fig. 2B and the P M i;j values predicted with kinetic parame- ters optimized according to Model I ... stearic acid and oleic acid, representing 22.0, 19.5 and 18.8%, respectively, of the total fatty acid content of platelet phosphoglycerolipids [8]. Keywords arachidonate; Monte Carlo simulation; oleate;...

Ngày tải lên: 18/02/2014, 17:20

... advantage of this simple and useful tool in managing project risks and uncertainties. Overview of Monte Carlo simulation Brief history of Monte Carlo simulation The Monte Carlo simulation encompasses ... the simulation and hands on experience with the Monte Carlo Simulation tech- niques to current and potential project managers are needed to overcome Risk Management Exploring Monte Carlo Simulation ... to respond to risk events. Risk Management Exploring Monte Carlo Simulation Applications 55 project managers ’ reluctance to use Monte Carlo simulation, once the Monte Carlo simulation technique...

Ngày tải lên: 23/03/2014, 04:21

... itself. This applies to all corresponding random variable names in this list. 8 Introduction to simulation and Monte Carlo a fresh worksheet by typing ‘restart’ and also load the statistics package ... Therefore,  I 19 = 1 2 49206 −01 +72928 −01  =08363 (1.7) 6 Introduction to simulation and Monte Carlo Since X n+1 depends on X n and Y n+1 only, and since Y n+1 is independent of X n−1 X n−2 , it follows ... other burgeoning area of simulation, namely Markov chain Monte Carlo and its use in Bayesian statistics. Here, I have been influenced by the works of Robert and Casella (2004) and Gilks et al. (1996)....

Ngày tải lên: 07/03/2014, 15:20

... reduction techniques in Monte Carlo simulation, such as antithetic and common random numbers, control random variables, conditional Monte Carlo, stratified sampling, and importance sampling. ... objective function and some of the constraints are unknown and need to be obtained via simulation. We deal with sensitivity analysis and optimization of both static and dynamic models. We introduce ... undergraduate and graduate students at the Technion and the University of Queensland who helped make this book possible and whose valuable ideas and experi- ments were extremely encouraging and motivating:...

Ngày tải lên: 27/06/2014, 08:20

... sequence appear random. Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 John Wiley & Sons, Ltd 6 Introduction to simulation and Monte Carlo Since X n+1 depends ... 21 2006 il /S i ffi Simulation and Monte Carlo 2 Uniform random numbers All simulations work on a ‘raw material’ of random numbers. A sequence R 1 R 2  is said to be a random number sequence ... Introduction to simulation and Monte Carlo 1 1.1 Evaluating a definite integral 2 1.2 Monte Carlo is integral estimation 4 1.3 An example 5 1.4 A simulation using Maple 7 1.5 Problems 13 2 Uniform random...

Ngày tải lên: 09/08/2014, 16:21

... support  0   . Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 John Wiley & Sons, Ltd Envelope rejection 43 Now −ln  R 2  and y are independent ... ‘SUPER-DUPER’ random number suite (Marsaglia, 1972; Marsaglia et al., 1972). Its statistical properties are quite good and have been investigated by Anderson (1990) and Marsaglia and Zaman (1993). > ... methods and tests and is located at http://random.mat.sbg.ac.at/. 2.5 Combinations of generators By combining the output from several independent generators it is hoped to (a) increase the period and...

Ngày tải lên: 09/08/2014, 16:21

... n, and a, a simulation sampled   j j = 15000  . Table 5.1 shows the resulting   and e.s.e.     . The standard error for a naive Monte Carlo simulation is    1 −  /5000 and ... standard normal random variables, X 1 and X 2 . The joint density is f X 1 X 2  x 1 x 2  = 1 2 e −  x 2 1 +x 2 2  /2 Simulation and Monte Carlo: With applications in finance and MCMC J. S. ... variates from standard distributions 4.1 Standard normal distribution The standard normal distribution is so frequently used that it has its own notation. A random variable Z follows the standard normal...

Ngày tải lên: 09/08/2014, 16:21

... Wiener process, will be described. Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 John Wiley & Sons, Ltd 112 Simulation and finance Let VX  t  t be ... queue simulation in Problem 1. Write a Maple program and investigate the variance reduction achieved for different parameter values. 8. Write procedures for naive and conditional Monte Carlo simulations ... O  h 2  = O  1/m 2/d  . However, using Monte Carlo, the error is still O  1/ √ m  . Therefore, for d>4 and for sufficiently large m, Monte Carlo will be better than the trapezium rule....

Ngày tải lên: 09/08/2014, 16:21

... (1978), Law and Kelton (2000), and Pidd (1998). Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 John Wiley & Sons, Ltd 154 Discrete event simulation (b) ... probabilities  i / i + i  and  i / i + i  respectively. 8 Markov chain Monte Carlo Markov chain Monte Carlo (MCMC) refers to a class of methods for sampling random vectors X  0  X  1  (generally, ... is P  D  = P  D  P    P  D   (8.1) Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 John Wiley & Sons, Ltd Problems 151 allowed  = 0 then this model reduces to an...

Ngày tải lên: 09/08/2014, 16:21

... original study by Gaver and O’Muircheartaigh (1987) and also in several follow- up analyses of this data set, including those by Robert and Casella (2004, pp. 385–7) and Gelfand and Smith (1990), an ... output of every X n . To obtain a random number in [0,1) insert R= x/61. Answers: (a)  = 60, (b)  = 30. Simulation and Monte Carlo: With applications in finance and MCMC J. S. Dagpunar â 2007 ... densities lambda[9] prior and posterior densities lambda[8] prior and posterior densities lambda[7] prior and posterior densities lambda[6] prior and posterior densities lambda[5] prior and posterior densities lambda[4] prior...

Ngày tải lên: 09/08/2014, 16:21

... the random number generator schrage. The final execution group sets an (initial) seed and calls ‘expon’ three times. 2 6 6 6 6 6 6 6 4 Simulation and Monte Carlo: With applications in finance and ... independent times between starting at the point x 0 ;y 0 ị and landing in the treacle. The function stats [ random,norma ld ] (1) creates a random standard normal deviate. 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 Appendices ... restart; h > randomize(462695):#specify a seed h > distance:=proc(n) local j,x1,x2,y1,y2,d; for j from 1 to n do; x1:= rand()/10^12; y1:=rand()/10^12; x2:=rand()/10^12; y2:=rand()/10^12; d [ j ] :=sqrt((x1-x2)^2+(y1-y2)^2); end...

Ngày tải lên: 09/08/2014, 16:21

Ngày tải lên: 09/08/2014, 16:21

Ngày tải lên: 09/08/2014, 16:21

Ngày tải lên: 09/08/2014, 16:21

Ngày tải lên: 12/08/2014, 07:22