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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. Chi - squared distribution






2. Unstable return distribution






3. Test for statistical independence






4. Sample correlation






5. SER






6. Discrete representation of the GBM






7. Empirical frequency






8. ESS






9. GPD






10. Discrete random variable






11. Variance of X+Y assuming dependence






12. Priori (classical) probability






13. Weibul distribution






14. Monte Carlo Simulations






15. Logistic distribution






16. Covariance calculations using weight sums (lambda)






17. Test for unbiasedness






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


19. Variance of X - Y assuming dependence






20. R^2






21. Kurtosis






22. Binomial distribution equations for mean variance and std dev






23. i.i.d.






24. Antithetic variable technique






25. Confidence interval (from t)






26. Regime - switching volatility model






27. Cholesky factorization (decomposition)






28. Perfect multicollinearity






29. Normal distribution






30. Cross - sectional






31. GEV






32. Joint probability functions






33. Confidence interval for sample mean






34. Econometrics






35. Gamma distribution






36. EWMA






37. Binomial distribution






38. Bootstrap method






39. Four sampling distributions


40. Covariance






41. Two assumptions of square root rule






42. K - th moment






43. Tractable






44. Efficiency






45. Lognormal






46. Variance - covariance approach for VaR of a portfolio






47. Two drawbacks of moving average series






48. Multivariate probability






49. Sample covariance






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