Test your basic knowledge |

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. Law of Large Numbers






2. Mean reversion






3. Normal distribution






4. Covariance calculations using weight sums (lambda)






5. SER






6. LAD






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


8. GPD






9. Sample covariance






10. Regime - switching volatility model






11. Binomial distribution equations for mean variance and std dev






12. Homoskedastic only F - stat






13. Cholesky factorization (decomposition)






14. GARCH






15. Marginal unconditional probability function






16. Two assumptions of square root rule






17. Binomial distribution






18. LFHS






19. Standard error for Monte Carlo replications






20. Perfect multicollinearity






21. SER






22. Weibul distribution






23. Continuous representation of the GBM






24. Test for unbiasedness






25. Implications of homoscedasticity






26. Variance of X+b






27. Stochastic error term






28. Standard normal distribution






29. Importance sampling technique






30. Bootstrap method






31. Shortcomings of implied volatility






32. Priori (classical) probability






33. Hazard rate of exponentially distributed random variable






34. Tractable






35. K - th moment






36. Pooled data






37. Confidence ellipse






38. Two ways to calculate historical volatility






39. Key properties of linear regression






40. Poisson Distribution






41. Simulation models






42. Exact significance level






43. Standard variable for non - normal distributions






44. Antithetic variable technique






45. Potential reasons for fat tails in return distributions






46. Joint probability functions






47. Efficiency






48. Kurtosis






49. Variance of aX






50. Extreme Value Theory