Try Microsoft Edge A fast analysis secure browser that's designed for Windows 10 No thanks Get started. This article was adapted from Microsoft Office Excel Data Analysis and Business Modeling by Wayne L. Visit Microsoft Learning to learn amibroker about this book. This classroom-style book was developed from a series of presentations by Wayne Winston, analysis well known statistician and business professor who specializes in creative, practical applications of Excel. How can I simulate values of a discrete random variable? How can I simulate values of a normal random variable? How can a greeting card company determine how many cards to produce? We would like to accurately estimate the probabilities of uncertain events. What is the risk factor of our monte portfolio? Monte Carlo simulation enables us to model situations that present uncertainty and then play them out on a computer thousands of times. The name Monte Carlo simulation comes from the carlo simulations performed during the s carlo s to estimate the probability that the chain reaction needed for an atom bomb to detonate monte work successfully. The physicists involved analysis this work were big fans of gambling, so they gave the simulations the code name Monte Carlo. Many companies use Monte Carlo simulation analysis an important part of their decision-making process. Here are some examples. General Motors, Proctor and Gamble, Pfizer, Bristol-Myers Squibb, and Eli Lilly use monte to estimate both the average return and the risk factor of new products. At GM, this information analysis used by the CEO to determine which products come to market. Amibroker uses simulation for activities such as forecasting net income for the corporation, predicting structural and purchasing costs, and determining analysis susceptibility to different kinds of risk such as interest rate changes and exchange rate fluctuations. Sears uses simulation to determine how many units of each product line should be ordered from suppliers—for example, the number of pairs of Dockers trousers that should monte ordered this year. Oil and drug companies use simulation to value "real options," such as the value of an option to expand, contract, or postpone a project. Thus, around 25 percent of the time, you carlo get monte number less than or equal to 0. To demonstrate how the RAND function works, take a look at the file Randdemo. When you open the file Randdemo. The RAND function always automatically recalculates the numbers it generates when a worksheet is opened or when new information is entered into the worksheet. I copied from cell C3 to C4: I named the range C3: Then, in column F, I tracked the average of the random numbers cell F2 and used the COUNTIF function to determine the fractions that are between 0 and 0. When you press the F9 key, the random numbers are recalculated. Notice that the average of the numbers is always approximately 0. These results are consistent with the definition of a random number. Also note that the values generated by RAND in different cells are independent. For example, if the random number generated in cell C3 is a large number for example, 0. How can we have Excel play out, or simulate, this demand for calendars many times? The trick is to associate each possible value of the RAND function with a possible demand for calendars. The following assignment ensures that a demand of 10, will occur 10 percent of the time, and so on. To demonstrate the simulation of demand, look at carlo file Discretesim. The key to our simulation is to use a random number to initiate a lookup from the table range F2: Carlo numbers greater than or equal to 0 and less than 0. I generated random numbers by copying from C3 to C4: C the formula RAND. I then generated trials, or iterations, of calendar demand by copying from B3 to B4: B the formula VLOOKUP C3,lookup,2. This formula ensures that any random number less than 0. In the cell range F8: F11, I used the COUNTIF function to determine the fraction of our iterations yielding each demand. When we press F9 to recalculate the random numbers, the simulated probabilities are close to our assumed demand probabilities. If you type in any carlo the formula NORMINV rand ,mu,sigmayou will generate a simulated value of a normal random variable having a mean mu and standard deviation sigma. I typed these values in cells E1 amibroker E2, and named these cells mean and sigmacarlo. C generates different random numbers. Copying from B4 to B5: B the formula NORMINV C4,mean,sigma generates different trial values from a normal random variable with a mean of 40, and a standard deviation of 10, When we press the F9 key to recalculate the random numbers, the mean remains close to 40, and the standard deviation close to 10, Essentially, for a random number xthe formula NORMINV p,mu,sigma amibroker the p th percentile of amibroker normal random variable with a mean mu and a standard deviation sigma. For example, the random number 0. How many cards should be printed? Basically, we simulate each possible production quantity 10, 20, 40, or 60, many times for example, iterations. Then we determine which order quantity yields the maximum average profit over the iterations. You can find the data for amibroker section in the file Valentine. B11 to cells C1: H6 the name lookup. Our sales price and cost parameters are entered in cells C4: I then enter a trial production quantity 40, in this example in cell C1. As previously described, Monte simulate demand for the card in cell C3 with the formula VLOOKUP rand,lookup,2. In the VLOOKUP formula, rand is the cell name assigned to cell C3, not the RAND function. The number of units sold is the smaller of our production quantity and demand. If we produce more cards than are in demand, the number of units left over equals production minus demand; otherwise no units are left amibroker. We would like an efficient way to carlo F9 many times analysis example, for each production quantity and tally our expected profit for each quantity. This situation is one in which a two-way data table comes to our rescue. See Chapter 15, "Sensitivity Analysis with Data Tables," for details about data tables. The data table I used in this example is shown analysis Figure In the cell amibroker A A, I entered the monte 1— corresponding to our trials. One easy way to create these values is to start by entering 1 in cell A Select the cell, and then on the Home tab in the Editing group, click Fill, and select Series to display the Monte dialog box. In the Series dialog box, shown in Figureenter analysis Step Value of 1 and a Stop Value of In the Series In area, select the Columns option, and then click OK. The numbers 1— will be entered in column A starting in cell A Next we enter our possible production quantities 10, 20, 40, 60, in cells B We want to calculate profit for each trial number 1 through and each production quantity. We are now ready to trick Excel into simulating iterations of demand for each production quantity. Select monte table range A Eand then in the Data Tools group on the Data carlo, click What If Analysis, and then select Data Table. To set up a two-way data table, choose our production quantity cell C1 as the Row Input Cell and select any blank cell we chose cell I14 as the Column Input Cell. After clicking OK, Excel simulates demand values for each order quantity. To understand why this works, consider the values placed amibroker the data analysis in the cell range C For each of these cells, Excel will use a value carlo 20, in cell C1. In C16, the column input cell value of 1 is placed in a blank cell and the random number in cell C2 recalculates. The corresponding profit is then recorded in cell C Then the column cell input value of 2 is placed in a blank cell, and the random number in C2 again recalculates. The corresponding profit is entered in cell C By copying from cell B13 to C E13 the formula AVERAGE B Bwe compute average simulated profit for each production quantity. By copying from cell B14 to C E14 the formula STDEV B Bwe compute the standard deviation of our simulated amibroker for each order quantity. Each time we press F9, iterations of demand are amibroker for each order quantity. Producing 40, cards always yields the largest expected profit. Therefore, it appears that producing 40, cards is the proper decision. Therefore, if we are extremely averse to monte, producing 20, cards might be the right decision. Incidentally, producing 10, cards always has a standard deviation of 0 cards because if we produce 10, cards, we will always sell all of them without any leftovers. In this workbook I set the Calculation option to Automatic Except For Tables. Use the Calculation command in the Calculation group on the Formulas tab. This setting ensures that our data table will not recalculate unless we press F9, which is a good idea because a large data table will slow down your work if it recalculates every time you type something into your worksheet. Note that in this example, whenever you press F9, the mean profit will change. This happens because each time you press F9, a different sequence of random numbers is used to generate demands for each order quantity. This interval is called the 95 percent confidence interval for mean profit. A 95 percent confidence interval for the mean of any analysis output is computed by the following formula:. Analysis cell J11, I computed the lower limit for the 95 percent confidence interval monte mean profit when 40, calendars are produced with the formula Carlo. These calculations are shown monte Figure A GMC dealer believes that demand for Envoys will be normally distributed with a mean of and standard deviation of He is considering ordering,or Envoys. How many should he order? A small supermarket is trying to determine how many copies of People magazine they should order each week. They believe their demand for People is governed by the following discrete random variable:. How many copies of People should the store order? Search Office help No results. Introduction to Monte Carlo simulation Applies To: Figure Using the Series dialog box to fill in the trial numbers 1 through Figure 95 percent confidence interval for mean profit when 40, calendars are amibroker. Was this information helpful? How can we improve it? Thank you for your feedback! It sounds like it might be helpful to connect you to one of our Office support agents. Learn Windows Office Skype Outlook OneDrive MSN. Devices Microsoft Surface Xbox PC and laptops Microsoft Lumia Microsoft Band Microsoft HoloLens. Downloads Download Center Windows downloads Windows 10 apps Office apps Microsoft Lumia apps Internet Carlo. Values Diversity and inclusion Accessibility Microsoft in education Microsoft philanthropies Corporate social responsibility Privacy at Microsoft. Company Careers About Microsoft Company news Investors Research Site map.
One is to use the row and column indices, as above, the other to use the location in the vectorized matrix.
The engineer took a few picture, my friend saw them- I did not.