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Team study of @risk

Team study of @risk. Team members: Xufeng Huangli Shenglei Zhouhang Yuyueshen Yangyemin. 1. 3. review. Introductions of @risk. Contents. Case study （ how to define input variables & explain ouput results ）. 2. Introductions of @risk. @RISK Shows You Many Possible Outcomes

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Team study of @risk

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  1. Team study of @risk Team members: Xufeng Huangli Shenglei Zhouhang Yuyueshen Yangyemin

  2. 1 3 review Introductions of @risk Contents Case study （how to define input variables & explain ouput results） 2

  3. Introductions of @risk @RISK Shows You Many Possible Outcomes • @RISK uses Monte Carlo simulation to show you many possible outcomes in your Microsoft Excel spreadsheet  – and tells you how likely they are to occur. This means that you finally have, if not perfect information, the most complete picture possible. You can judge which risks to take and which ones to avoid.  @RISK can help you choose the best strategy based on the available information. • The power of Monte Carlo simulation lies in the picture of possible outcomes it creates. Simply by running a simulation, @RISK takes your spreadsheet model from representing just one possible outcome to representing thousands. With @RISK, you can answer questions like, “What is the probability of profit exceeding $10,000,000?” or “What are the chances of losing money on this venture?”

  4. Introductions of @risk • Function Define Uncertainty with EaseReplace uncertain values in your spreadsheet with @RISK probability distribution functions. Furthermore, you can use your own historical data and @RISK’s integrated data fitting tool to select the best function and the right parameters.

  5. Introductions of @risk Present Results with Stunning Graphs @RISK provides a wide range of graphs for interpreting and presenting your results to others. Histograms and cumulative curves show the probability of different outcomes occurring.

  6. Introductions of @risk Identify the Most Important factors @RISK provides you with Sensitivity and Scenario Analyses to determine the critical factors in your models. Use Sensitivity Analysis to rank the distribution functions in your model according to the impact they have on your outputs with Tornado diagram.

  7. Case study

  8. Case study

  9. Use per hippo of our drug Market Size Entrants Inputs and outputs Possible NPV values and possibilities NPV formula simulation

  10. Case study How to run a simulation:

  11. Case study

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  16. review Determine the variables/input values Step 1 Determine output cell’s Calculating formula Step 2 Set simulation and Run simulation Step 3 Get results and analyze Step 4

  17. Thank You !

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