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2673Average Edge Across Opposing RegimesA signal earns +6 bps on 70% of days in calm markets and -10 bps on 30% of days in stressed markets. What is its unconditional average daily edge in bps?机器学习中等数值题未尝试面试订阅2674Precision of a Rare Alpha Event DetectorOnly 2% of days contain a true dislocation worth trading. A classifier catches 65% of those days but fires falsely on 4% of normal days. What is the precision of a positive alert?机器学习中等derivation未尝试面试订阅2675Break-Even Hit Rate After Trading CostsA directional model earns +1 unit on a correct trade and -1 unit on an incorrect trade before costs. Each round trip also pays a cost of 0.08 units regardless of outcome. What hit rate p makes expected net PnL zero?机器学习困难derivation未尝试面试订阅2676A Tiny Tail Probability Can Dominate Average PnLA strategy makes +0.04% on 98% of days and loses -2.5% on the remaining 2% of days. What is the unconditional average daily return?机器学习简单数值题未尝试免费2677Half-Life Discounting of Old Regime DataSuppose predictive relevance decays with a half-life of 6 months. Relative to current-regime data, what weight should you attach to observations that are 18 months old under this exponential-decay heuristic?机器学习中等derivation未尝试面试订阅2679Why Hundreds of Stocks Do Not Mean Hundreds of Independent LabelsWhy does a daily cross-sectional equity sample with hundreds of names still provide much less information than its row count suggests?机器学习中等essay未尝试面试订阅2680Why Low R-Squared Can Still Be Valuable Yet Hard to VerifyWhy can a signal with tiny explanatory power still be economically useful, while also being unusually hard to validate convincingly?机器学习困难essay未尝试面试订阅2681Why Live Deployment Changes the Labeling EnvironmentWhy can a model that looked predictive in backtests become less predictive once a desk actually starts trading on it?机器学习简单essay未尝试免费2682Why Crowding Erodes Published Signals FastestWhy do signals that are easiest to explain and copy often decay faster after publication than more fragile niche edges?机器学习简单essay未尝试面试订阅2683Why Long Training Windows Can Learn the Wrong WorldWhy can adding more historical years lower estimation variance and yet make a finance model worse?机器学习中等essay未尝试面试订阅2684Why Short Windows Adapt but Also WhipsawWhy does a short rolling window often react faster to new regimes while simultaneously making parameter estimates much less stable?机器学习困难essay未尝试面试订阅2685Why Crisis Prediction Suffers From Tiny Relevant Sample SizeWhy does a century of daily data still leave very little effective evidence for training a model about true crisis behavior?机器学习困难essay未尝试面试订阅2686Why Correlation Spikes Break Signal Combining RulesWhy can a portfolio of seemingly diversified alpha signals stop diversifying exactly when markets become stressed?机器学习简单essay未尝试免费2687Why Benchmark Stability Does Not Guarantee Label StabilityWhy can a model's benchmark-relative performance appear stable even while the mapping from features to returns is drifting underneath?机器学习中等essay未尝试面试订阅2688Why Transaction Costs Are Model Uncertainty TooWhy is it wrong to treat trading costs as a fixed deduction after the predictive model has already been validated?机器学习中等essay未尝试面试订阅2690Why Fast Strategies Are More Sensitive to Small Modeling ErrorsWhy can a tiny forecast error or latency miss matter much more for a very fast strategy than for a slow rebalancing signal?机器学习困难essay未尝试面试订阅2692Why Negative Skew Strategies Can Look Comfortingly StableWhy can a strategy with severe crash risk still look reassuring in ordinary validation windows?机器学习简单essay未尝试免费2694Why Capacity Scaling Can Erase a Modest EdgeWhy can a signal that is clearly profitable at small size become useless when a larger book tries to deploy it?机器学习中等essay未尝试面试订阅2695Why Two Similar-Looking Features Can Swap Usefulness Across RegimesWhy might one liquidity feature dominate in calm markets while another dominates in stressed markets, even though they looked redundant in a pooled sample?机器学习困难essay未尝试面试订阅2696False Strategy Surviving Two Independent Research GatesA desk tries 80 genuinely null strategy ideas. A strategy is kept only if it passes an in-sample screen at 10% and then a fresh out-of-sample confirmation at 5%, with the two tests treated as independent under the null. What is the probability at least one null idea survives both gates?机器学习简单derivation未尝试面试订阅