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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. Confidence ellipse






2. Regime - switching volatility model






3. Implied standard deviation for options






4. Importance sampling technique






5. Variance - covariance approach for VaR of a portfolio






6. Persistence






7. GPD






8. Adjusted R^2






9. Variance of X+Y assuming dependence






10. Variance of aX + bY






11. Bernouli Distribution






12. Reliability






13. Type II Error






14. Logistic distribution






15. ESS






16. Marginal unconditional probability function






17. F distribution






18. T distribution






19. Block maxima






20. Covariance calculations using weight sums (lambda)






21. Continuous representation of the GBM






22. Deterministic Simulation






23. Extreme Value Theory






24. Hazard rate of exponentially distributed random variable






25. GEV






26. Time series data






27. Two requirements of OVB






28. Cholesky factorization (decomposition)






29. Mean reversion in variance






30. Homoskedastic






31. Mean reversion in asset dynamics






32. Two assumptions of square root rule






33. Simplified standard (un - weighted) variance






34. Standard variable for non - normal distributions






35. Tractable






36. Four sampling distributions






37. Standard error






38. SER






39. Significance =1






40. Antithetic variable technique






41. Extending the HS approach for computing value of a portfolio






42. Potential reasons for fat tails in return distributions






43. BLUE






44. Monte Carlo Simulations






45. P - value






46. Multivariate Density Estimation (MDE)






47. K - th moment






48. Difference between population and sample variance






49. Implications of homoscedasticity






50. Control variates technique