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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. Kurtosis






2. Implications of homoscedasticity






3. i.i.d.






4. Deterministic Simulation






5. Cholesky factorization (decomposition)






6. Historical std dev






7. Simulation models






8. Binomial distribution equations for mean variance and std dev






9. Standard variable for non - normal distributions






10. Two ways to calculate historical volatility






11. Two drawbacks of moving average series






12. Inverse transform method






13. Unstable return distribution






14. Continuously compounded return equation






15. Priori (classical) probability






16. Efficiency






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






18. Discrete representation of the GBM






19. Simplified standard (un - weighted) variance






20. Bernouli Distribution






21. Multivariate Density Estimation (MDE)






22. Extreme Value Theory






23. Test for unbiasedness






24. Hazard rate of exponentially distributed random variable






25. Maximum likelihood method






26. Beta distribution






27. Variance of weighted scheme






28. Sample covariance






29. Variance of sample mean






30. GPD






31. Hybrid method for conditional volatility






32. POT






33. Type II Error






34. Sample correlation






35. Sample variance






36. Variance of aX + bY






37. P - value






38. Implied standard deviation for options






39. Two assumptions of square root rule






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


41. Time series data






42. Importance sampling technique






43. Cross - sectional






44. Skewness






45. Logistic distribution






46. Antithetic variable technique






47. Result of combination of two normal with same means






48. BLUE






49. Variance - covariance approach for VaR of a portfolio






50. SER