Decision tree, Monte Carlo analysis

8 important questions on Decision tree, Monte Carlo analysis

What are to methods to rationalise choice3 in an uncertain world?


  • Decision Trees
  • Monte Carlo simulation
  • Analyze options and consequences

What is taken into account when performing a Monte Carlo simulation?

Includes Uncertainty and variability
Variability at-risk level, uncertainty about claim level  (Min ; ML ; Max)

What are important factors for a Monte Carlo simulation?

  • Input parameters have a range of values often expressed in distributions
  • For each model run, a random value is taken from this range
  • Model outcome calculated for this value
  • Repeated many times ( iterations)
  • The outcome is also a range of values ( distribution)
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How does the distribution look like for an input parameter?

  • Range values: histogram or distribution (fitted)
  • Examples:
    • Normal
    • Lognormal
    • Triangle

What is the influence of risk attitude?

Presenting two decision-makers with the same situation, they maybe making very different decisions, EVEN in the presence of the same risk

What is the risk attitude: Risk neutral?

Individuals who maximize the EMV

What is the risk attitude: Risk Seeker?

Individuals who are not afraid or sensitive to risk, and are eager to enter into a gamble

So what is the function of Decision trees & Monte Carlo simulation?

  • Help to structure the decision problem
  • Advise you of the preferred decision


However:
  • The decision is up to the decision-maker
  • And depending on his/her risk attitude

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