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4425Monthly Refit Count With Quarterly Test Blocks 10A walk-forward process uses 24 months of initial training and then evaluates 3-month test blocks, advancing the whole scheme by 1 month each time through a total history of 39 months. How many model refits are performed?机器学习中等数值题未尝试面试订阅4426Rolling Versus ExpandingA market regime has shifted several times in the last three years. Why can a rolling walk-forward window be more informative than a purely expanding window?机器学习中等essay未尝试面试订阅4427Refit CadenceWhy can refitting every single day be worse than refitting monthly, even when more frequent updating sounds adaptive?机器学习中等essay未尝试面试订阅4428Embargo IntuitionWhy is a time embargo helpful when labels depend on future returns that overlap across neighboring samples?机器学习中等essay未尝试面试订阅4429Walk-Forward Is Not MagicWhy does a clean walk-forward protocol still not guarantee that a strategy will survive live trading?机器学习中等essay未尝试面试订阅4430Comparing Window SchemesTwo walk-forward schemes give different validation results. What is the first structural question you should ask before deciding one is 'better'?机器学习中等essay未尝试面试订阅4431Longer Train WindowIf you lengthen the training window in walk-forward validation, what tradeoff usually changes?机器学习中等essay未尝试面试订阅4432Longer Test WindowIf you lengthen the test block while holding the train block fixed, what usually happens to score variance and regime purity?机器学习中等essay未尝试面试订阅4433Faster Step SizeIf you move the walk-forward step from monthly to daily while keeping long horizons, what often happens to dependence between adjacent folds?机器学习中等essay未尝试面试订阅4434Embargo Too ShortWhat is the most likely consequence of using an embargo shorter than the label horizon?机器学习中等essay未尝试面试订阅4435Refitting Less OftenIf you refit less often in a stable regime, what usually happens to turnover of the model parameters?机器学习中等essay未尝试面试订阅4436Before Designing WindowsWhat is the first thing you should map before choosing train, test, and embargo lengths in financial walk-forward validation?机器学习中等essay未尝试面试订阅4437Before Claiming RobustnessWhat should you inspect first before saying a walk-forward result is robust?机器学习中等essay未尝试面试订阅4438Before Shortening WindowsBefore shrinking both train and test windows to 'adapt faster,' what should you quantify first?机器学习中等essay未尝试面试订阅4439Before Comparing ModelsTwo models were validated under different walk-forward schemes. What is the first reason not to compare their average scores naively?机器学习中等essay未尝试面试订阅4440Before Refitting More OftenWhat should you check first before increasing refit frequency because recent performance dipped?机器学习中等essay未尝试面试订阅4441Fee-Adjusted Composite Alpha 1A desk forms a composite alpha A = 0.6 A fast + 0.4 A slow. The expected gross daily alpha of A fast is 8 bps and of A slow is 5 bps. Their daily turnover is 90% and 20%, and every 1% of turnover costs 0.02 bps. What is the composite's expected net daily alpha?机器学习中等数值题未尝试面试订阅4442Implied Correlation From Composite Vol 2Two standardized signals are combined as C = 0.5 S1 + 0.5 S2. Their standard deviations are 1.2 and 0.8, and the composite standard deviation is observed to be 0.9. What correlation between S1 and S2 is implied?机器学习中等数值题未尝试面试订阅4443Orthogonalized Fast Signal Coefficient 3A fast signal F has standard deviation 1.5 and a slow signal S has standard deviation 1.0. Their correlation is 0.4. If you orthogonalize the fast signal as F res = F - beta*S so that F res is uncorrelated with S, what beta should you use?机器学习中等数值题未尝试面试订阅4444Beta-Neutral Blend Weight 4A fast signal book has market beta 0.8 and a slow signal book has market beta -0.4. You form C = w*fast + (1-w)*slow and want the composite beta to be 0. What weight w on the fast book achieves that?机器学习中等数值题未尝试面试订阅