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FRM Foundations Of Risk Management Quantitative Methods

Instructions:
  • Answer 50 questions in 15 minutes.
  • If you are not ready to take this test, you can study here.
  • Match each statement with the correct term.
  • Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Adjusted R^2






2. Maximum likelihood method






3. Limitations of R^2 (what an increase doesn't necessarily imply)

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4. Standard variable for non - normal distributions






5. Pooled data






6. Chi - squared distribution






7. Variance of sample mean






8. Mean reversion






9. Variance(discrete)






10. Discrete random variable






11. Heteroskedastic






12. GARCH






13. Variance of X - Y assuming dependence






14. Econometrics






15. Cholesky factorization (decomposition)






16. Shortcomings of implied volatility






17. Covariance






18. Sample mean






19. Key properties of linear regression






20. Importance sampling technique






21. Least squares estimator(m)






22. Conditional probability functions






23. Tractable






24. Stochastic error term






25. Simulating for VaR






26. Historical std dev






27. Unbiased






28. Marginal unconditional probability function






29. Covariance calculations using weight sums (lambda)






30. Implied standard deviation for options






31. Extreme Value Theory






32. Non - parametric vs parametric calculation of VaR






33. Implications of homoscedasticity






34. Central Limit Theorem






35. GPD






36. Variance of X+Y






37. Sample covariance






38. Discrete representation of the GBM






39. Mean(expected value)






40. Two assumptions of square root rule






41. Standard normal distribution






42. GEV






43. Binomial distribution equations for mean variance and std dev






44. Potential reasons for fat tails in return distributions






45. Exact significance level






46. Expected future variance rate (t periods forward)






47. Variance of aX






48. Normal distribution






49. R^2






50. EWMA