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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. Four sampling distributions


2. R^2






3. Kurtosis






4. SER






5. Beta distribution






6. Mean reversion in variance






7. Consistent






8. Test for statistical independence






9. Deterministic Simulation






10. Marginal unconditional probability function






11. Covariance calculations using weight sums (lambda)






12. BLUE






13. Expected future variance rate (t periods forward)






14. Standard error






15. Law of Large Numbers






16. SER






17. Statistical (or empirical) model






18. Central Limit Theorem(CLT)






19. K - th moment






20. Confidence interval (from t)






21. Difference between population and sample variance






22. Variance of X+b






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


24. Biggest (and only real) drawback of GARCH mode






25. Weibul distribution






26. Logistic distribution






27. Homoskedastic only F - stat






28. Poisson Distribution






29. Square root rule






30. Time series data






31. Variance - covariance approach for VaR of a portfolio






32. Multivariate Density Estimation (MDE)






33. Sample correlation






34. Maximum likelihood method






35. GEV






36. Regime - switching volatility model






37. Two drawbacks of moving average series






38. Sample variance






39. Sample covariance






40. EWMA






41. Tractable






42. Econometrics






43. Poisson distribution equations for mean variance and std deviation






44. Joint probability functions






45. Standard normal distribution






46. Importance sampling technique






47. Extreme Value Theory






48. WLS






49. Adjusted R^2






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