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monte-carlo

  1. Nicole Seaman

    P1.T2.21.6 Bootstrapping and antithetic/control variates

    Learning objectives: Explain the use of antithetic and control variates in reducing Monte Carlo sampling error. Describe the bootstrapping method and its advantage over Monte Carlo simulation. Describe pseudo-random number generation. Describe situations where the bootstrapping method is...
  2. Nicole Seaman

    P1.T4.806. Putting value at risk (VaR) to work (Allen Ch.3)

    Learning objectives: Describe the limitations of the delta-normal method. Explain the full revaluation method for computing VaR. Compare delta-normal and full revaluation approaches for computing VaR. Explain structured Monte Carlo, stress testing, and scenario analysis methods for computing...
  3. jairamjana

    Carter Dyson Roulette Algorithm

    Before I explain, Just want to make it clear that I do not promote betting nor involve myself in it.. I see it as an exercise in understanding probability. And yes, this is not related to FRM.. But I found this of real interest. He explains a method where we can always profit from playing...
  4. Nicole Seaman

    P1.T2.601. Variance reduction techniques (Brooks)

    Learning objectives: Explain how to use antithetic variate technique to reduce Monte Carlo sampling error. Explain how to use control variates to reduce Monte Carlo sampling error and when it is effective. Describe the benefits of reusing sets of random number draws across Monte Carlo...
  5. H

    Stress Test Covariance and Correlation Matrix

    Hello David, I've seen the terms "covariance matrix" and "correlation matrix" a couple of times now, and I think I roughly know what they are and how they work, but I'm not sure as to how they apply and are being used in scenario analysis (stress testing). Also I am getting a bit overwhelmed by...
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