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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. GARCH






2. i.i.d.






3. Deterministic Simulation






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


5. Variance - covariance approach for VaR of a portfolio






6. Sample covariance






7. Economical(elegant)






8. Confidence interval (from t)






9. Sample variance






10. Homoskedastic only F - stat






11. Stochastic error term






12. Inverse transform method






13. EWMA






14. Variance of X+Y assuming dependence






15. Statistical (or empirical) model






16. Control variates technique






17. Two requirements of OVB






18. Standard error






19. Joint probability functions






20. Exact significance level






21. Regime - switching volatility model






22. Hybrid method for conditional volatility






23. SER






24. Unstable return distribution






25. Reliability






26. Standard error for Monte Carlo replications






27. Logistic distribution






28. Normal distribution






29. Variance of aX + bY






30. Simulating for VaR






31. Weibul distribution






32. Difference between population and sample variance






33. Block maxima






34. SER






35. Pooled data






36. Consistent






37. Implied standard deviation for options






38. Unconditional vs conditional distributions






39. Confidence ellipse






40. GPD






41. Variance of X+b






42. Least squares estimator(m)






43. Central Limit Theorem






44. Shortcomings of implied volatility






45. Type II Error






46. Heteroskedastic






47. Two assumptions of square root rule






48. Key properties of linear regression






49. Poisson Distribution






50. T distribution