'Cheat Sheet MDM Risk analysis\r'

'Decisions found on them argon heartbreaking! A single point only of only meter tells us what the average of twain cases is, never what happens amid the two cases! Poor realiseing of downside jeopardize pitiable understanding of upside opportunity 2) Scenario summary: desexualize your scenarios; trounce-worst-base There argon a ope vagabond of results! hamper if essay makes a difference 3) do distributions for the uncertainties to come across key peril drivers Choose distribution ground on historical entropy or dexterous opinion Distribution is authoritative for the guise; based on the spendn distribution, the simulator ill be to a greater extent/ slight likely to pick numbers in specific cultivates Uniform: same prospect of all numbers in a given range Triangle: point within the range is frequently more likely than the other points Normal: you cut the middle point but it could be finish off by X in either commissioning 4) Run (at)Risk (Monte-Carlo manne quin) Define distributions (step 3) Define outturn carrell fir which to simulate results Things to look out for pixilated of objective versatile (usually NAP) Compare results with scenario results (atrias will give offend indication of the range than the scenarios! ascertain at full range of outcomes Look at well-worn deviation and at confidence range Look at downside risk and upside potential. What is % of being to a higher(prenominal) place/below specific number? What is breakable chance? What is the distribution like? Perform Monte-Carlo simulation to pass judgment several(predicate) possible outcomes Determine expected result, range of results, chance of results (e. G. Probability of break-even), downside risk, etc.. Advantages: avoid the Flaw of Averages, understand the risk, test your experience 5) Sensitivity analysis remember Examine sensitivity of results when model parameters are alter Observe channelise in results due to change in as warmheartednessptions Identify main unbelief drivers / key risk drivers Methodology What-if analysis (simple changing of numbers to influence what happens) One-way & two-way sensitivity analysis scissure diagrams One-way & two-way sensitivity analysis pulmonary tuberculosis one-way sensitivity analysis (data evade) to check how changes to a variable effect the output variable. aim finis Seek to find breakable point of that variable. Use two-way sensitivity analysis (data table) to check for changes in two antithetical variables at the same time Tornado diagram Check for impact of for individually one variable / parameter, sorted in order of order of magnitude Shows you on which variables you should focus close, where the most important risks remain! Some Excel info points: Simulation settings: illustration QUESTIONS ON RISK ANALYSIS 1 .In what subject of decision context could risk analysis be useful and why may it be sober to rely on single point forecasts? What techniques nomi nate you use to overcome the problems of such forecasts? How do you take root what technique is most appropriate to use? any telephone circuit decision entails risk dangerous! A single point only ever tells us what the average Of two cases is, never what happens between the two cases! pillowcase answer for this part: These numbers are based on the average scenario which is not inevitably representative of the true value (argue why could over- or underestimate). Furthermore, they do not tell us anything roughly the risk.Technique: scenario analysis or simulation 2. Explain in your own words how Monte Carlo Simulation could be useful to a decision master assess different possible outcomes Averages, understand the risk, test your intuition 3. Explain how the simulation process works to aver results that are useful to a decision maker eccentric answer: This is different from the E,250 that Carolinas predecessor estimated because the current estimate was made using only sing le-value estimates for from each one of the variables.However, by using a Monte Carlo simulation that allows for a range of possible value (with a triangular distribution to account for the higher likeliness of the values Of 5% and 20% for saving and business, respectively). This intend that, based on 1 ,OHO iterations of possible combinations for each of the variables as per the arranging definition of the potential values for each variable under each iteration, the ungenerous of the court is E 10,277. 4. A friend of yours has still learned more or less simulation methods and has asked you to conduct a complicated risk analysis to help her fashioning a choice. She said she would be happy to let you solve the problem and then recommend what process she should take. Explain why she needs to be mixed in the analysis and modeling process and what pattern of cultivation you need from her.Risk analysis requires information about the characteristics of a particular uncertaint y (e. G. Shape of probability striation function, range of likely values etc) 5. A simulation model has produced the following three risk profiles displayed below. What advice would you give to the decision maker on the basis of this output? Choice depends on risk attitude, personalised wealth, importance of project success and cost of enthronement alternative. Alternative C has the highest associated payoff. However, range of possible payoffs is kind of large. The steeper the shape of the probability distribution function, the littler the range of possible expected payoffs (look at measurement deviation of outcomes).Consider 5% confidence breakup of most likely payoffs. Alternative A has quite a big confidence interval with relatively directly slope at the edges. Look at crossover of B and C and argue which one is less risky. 6. Your boss has asked you to work up a simulation model to examine the uncertainty regarding the success or failure of five different investment proj ects. He provides probabilities for the success of each project individually (numbers given). Because the projects are run by people in different segments of their investment market, you both agree that it would be reasonable to believe that, given these probabilities, he outcomes of the projects are independent.He points out, however, that he really is not fully confident in these probabilities and that they could be off by as a great deal as 0. 05 in either direction on any given probability. (a) How can you incorporate this uncertainty about the probabilities in the simulation model? Use convening distributions for each project with Sd= 0. 05 (b) Now regard he changes probability to include ranges. How can you modify your simulation model to take this additional information into account? Update probability distributions †triangle, discrete, uniform, normal pillowcase answer: He should use historical data and his expert judgment to estimate the distribution of inputs. H e should reach a normal distribution if the different values are independent of each other.Example for normal distribution argument: However, since the number of high smell applications is the sum of the individual decisions â€Å"whether or not to apply/ of a substantial amount of high aegir young professionals, and since this decision is taken by each potential applicant to a large hide independently of each other, the normal distribution with bastardly 630 seems reasonable. Moreover, given the potential range of high gauge applications is between 51 0 and 750, a mensuration deviation of 60 seems reasonable; that is, the range of 240 students corresponds to 4 standard deviations. Since the proportion of offers accepted is again the sum of many individual decisions, the normal distribution with mean 58% and standard deviation of 2% dexterityiness be reasonable. 7. Interpret the following risk analysis result tables ask at: Minimum, expected, maximum, P(loss) = x % (downsi de risk), P(> X) = Y% (upside potential) 8. Interpret sensitivity analysis Describe how output variable is sensitive to given assumptions/parameters.Describe how output variable minimizes and maximizes with the different scenarios; what is the upside potential and downside risk Example answer: The essence cost decreases by El ,800 for each 5% increase in the business class no-show rate from 15% to 20% (at which point it is minimized), but then increases by E,700 per circumstances point increase from 20% to 30%. The rate Of increase is consistent regardless of the rate of economy no-show. (could include more insights!!! ) The two-way sensitivity table and the accompanying chart show us that in the lower ranges of the possible no-show rates, the total cost is sensitive to both variables in fairly comparable proportion, until the optimum combination (I. E. The minimized cost) is reached at 5% economy and 20% business. After this inflection point, the total cost becomes much more sen sitive to changes in the business class no-show rate. 9.Describe, compare and pardon the shape of a distribution. Risk profile: probability of making a loss vs. a expediency Minimum versus maximum Variance Size of 90% confidence interval around the mean evaluate return mean average) take arguments why distributions might differ with different scenarios 1 0) Make testimonial based on the results. Will usually be trade-off between high risk for higher return on average and lower risk for lower return on average Include risk profiles, probabilities, maximum and minimum numbers… Example answer: The policy that we have recommended is better than the others, because it has the terminal average total cost.Furthermore, the 95% confidence interval has the narrowest range of possible values, as well as the lowest probability that costs will perish El 7,000. However, even though our recommended policy is better overall, it is not necessarily going to be the best on each individual flight. However, this doses t point since the average cost is the single most important criterion when choosing a policy because you have 365 * 4 flights per year. One additional insight you could generate is the simulate cost difference between the current and suggested policies. The naked as a jaybird policy is worse than the original policy 6% of the times. 1 1) What can be further through to improve profitability and manage the risks involved?\r\n'