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4865Infer Fine Estimate From Richardson Output 20A second-order finite-difference scheme uses Richardson extrapolation E R = (4E fine - E coarse)/3. If E R=2.8 and E coarse=2.4, what fine-grid estimate E fine is implied?数理金融困难数值题未尝试面试订阅4886Infer Second-Stratum Volatility From Target Neyman Share 21Two strata have population weights N1=0.6 and N2=0.4. Their standard deviations are sigma1=2 and sigma2=unknown. Under equal-cost Neyman allocation, the desk wants stratum 2 to receive 50% of the samples. What sigma2 is implied?数理金融中等数值题未尝试面试订阅4887Updated Neyman Share After a Volatility Change 22Two equal-size strata each have population weight 0.5. After a shock, sigma1 rises to 2 while sigma2 stays at 1.5. Under equal-cost Neyman allocation, what sample share should stratum 1 now receive?数理金融中等数值题未尝试面试订阅4888Infer Variance Ratio From Equal Neyman Shares 23Two strata have population weights N1=0.7 and N2=0.3. Under equal-cost Neyman allocation they end up with equal sample shares. What ratio sigma2/sigma1 is implied?数理金融中等数值题未尝试面试订阅4889Three-Stratum Neyman Share 24Three strata have population weights 0.5, 0.3, and 0.2, with standard deviations 1, 2, and 3. Under equal-cost Neyman allocation, what sample share should the third stratum receive?数理金融中等数值题未尝试面试订阅4890Updated Small-Stratum Share After Tail Risk Doubles 25Two strata have population weights 0.8 and 0.2. The first stratum has sigma1=1. The second stratum's standard deviation jumps from 4 to 8. Under equal-cost Neyman allocation, what sample share should the second stratum now receive?数理金融中等数值题未尝试面试订阅4926Infer One-Day VaR From Multi-Day Scaling 11Under square-root-of-time Gaussian scaling, a 10-day VaR is 7.589466. What 1-day VaR does that imply?数理金融中等数值题未尝试面试订阅4928Infer Pareto Tail Index From ES To VaR Ratio 13For a Pareto tail, suppose ES/VaR = alpha/(alpha-1). If VaR is 8 and ES is 12, what tail index alpha is implied?数理金融中等数值题未尝试面试订阅4929Infer Pareto Tail Index From ES To VaR Ratio 14For a Pareto tail with ES/VaR = alpha/(alpha-1), if VaR is 5.5 and ES is 9.166667, what alpha is implied?数理金融中等数值题未尝试面试订阅4931Infer Portfolio Covariance Loading From Component VaR 16For a linear Gaussian portfolio, component VaR satisfies component i = w i * z alpha * (Sigma w) i / sigma p. If z alpha=1.645, sigma p=0.2, w i=0.6, and the reported component VaR is 0.11844, what covariance loading (Sigma w) i is implied?数理金融困难数值题未尝试面试订阅4932Infer Portfolio Covariance Loading From Component VaR 17For a linear Gaussian portfolio, z alpha=2.326, sigma p=0.3, w i=0.35, and the reported component VaR is 0.111260333. What covariance loading (Sigma w) i is implied?数理金融困难数值题未尝试面试订阅4933Infer Portfolio Covariance Loading From Component VaR 18For a linear Gaussian portfolio, z alpha=1.96, sigma p=0.25, w i=0.5, and the component VaR is 0.1176. What covariance loading (Sigma w) i is implied?数理金融困难数值题未尝试面试订阅4936Tail Severity Interpretation 21Two desks report the same 97.5% VaR, but one desk has a much larger 97.5% ES. What does that tell you about the shape of its tail losses beyond the VaR cutoff?数理金融困难essay未尝试面试订阅4937Backtesting Intuition 22Why is ES harder to backtest directly than VaR in day-to-day risk control?数理金融困难essay未尝试面试订阅4938Scaling Failure Intuition 23Why can square-root-of-time VaR scaling fail badly during volatility clustering?数理金融困难essay未尝试面试订阅4939Tail Preference Intuition 24Why is ES typically preferred to VaR when the main concern is tail severity rather than breach frequency?数理金融困难essay未尝试面试订阅4940Allocation Intuition 25Why is a single firm-wide VaR or ES number not enough for desk incentives unless it is broken into component contributions?数理金融困难essay未尝试面试订阅4971Expected Time to Absorption With One Reset LinkA CTMC has states 0, 1, 2 with state 2 absorbing. From 0 it jumps to 1 at rate a=1, and from 1 it jumps to 2 at rate b=2 or back to 0 at rate c=1. What is the expected time to hit state 2 starting from 0?随机过程中等数值题未尝试面试订阅4972Reset Rate Implied by a Target Expected Hitting TimeA CTMC has states 0,1,2 with state 2 absorbing. From 0 it jumps to 1 at rate a=1, and from 1 it jumps to 2 at rate b=1.5 or back to 0 at rate c. If the expected time to hit state 2 from state 0 is 3, what is c?随机过程中等数值题未尝试面试订阅4973Forward Rate Implied by a Target Expected Hitting TimeA CTMC has states 0,1,2 with state 2 absorbing. The rates are a=2 from 0 to 1 and c=1 from 1 back to 0, while the rate from 1 to 2 is b. If the expected time to hit state 2 from state 0 is 1.5, what is b?随机过程中等数值题未尝试面试订阅