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中文题目A PM is backtesting a signal-driven strategy and also wants to value a stop-loss overlay that behaves like an option. Which measure should dominate each part of the workflow?
打开 →Why is ES harder to backtest directly than VaR in day-to-day risk control?
打开 →A PM deck says: ‘The event-study p-value is 0.03, so there is a 97% probability the signal is real.’ What is the statistical mistake?
打开 →Why can a period of forward paper trading add more evidence than squeezing one more clever slice out of the historical sample?
打开 →Why would it be a category error to judge a forecasting model's backtest solely against risk-neutral densities implied by option prices?
打开 →A daily factor is z-scored using the full-sample mean and standard deviation before the backtest is run. What is the main problem?
打开 →A backtest ranks stocks each month using the latest fully restated accounting data available today, even for years long ago. What is wrong with that setup?
打开 →For a monthly equity backtest, which universe construction is least survivorship-biased? A. Use today’s index constituents for the entire historical sample. B. Use monthly historical constituents and keep delisted names in the panel until their actual exit dates. C. Keep only st
打开 →Why does changing slippage curves, fee schedules, or borrow assumptions after seeing backtest performance count as extra model search?
打开 →Why does backtest overfit become especially dangerous for very high-turnover strategies?
打开 →Why should a PM expect live performance to come in below the very best backtest rather than treat any shortfall as an implementation surprise?
打开 →Why is a broad plateau of good parameter values often more convincing than one spectacularly sharp optimum in a backtest heatmap?
打开 →Why is it dangerous to retire a strategy after disappointment and later relaunch a close cousin because a refreshed backtest looks strong again on overlapping history?
打开 →Why does picking a stop-loss threshold after looking at the full historical equity curve count as backtest search rather than risk management hygiene?
打开 →A live manager panel shows 27 low-leverage funds and 18 high-leverage funds. Survival rates for those groups were 90% and 60%, respectively. Suppose low-leverage funds average 1.2x gross leverage and high-leverage funds average 2.4x gross leverage. What was the average gross lev
打开 →A vendor offers two hedge-fund datasets. Dataset A contains only funds that are currently reporting, but it includes long backfilled histories for those funds. Dataset B stores monthly reporting snapshots and preserves closed funds in the historical archive. Which dataset is be
打开 →Suppose 50 genuinely null standardized t-statistics are approximately independent N(0,1). What is the probability the largest of them exceeds 2.4?
打开 →A researcher wants the 2016-2025 average return of all funds launched in 2016. Which data pull is least exposed to survivorship bias? A. Keep only funds that are still alive in 2025, then use their full back history. B. Keep funds alive on each evaluation date, but retroactively
打开 →A live database shows 28 small-capacity funds and 42 large-capacity funds. Survival rates for those groups were 40% and 70%, respectively. Suppose small-capacity funds average $1.0$ billion of capacity and large-capacity funds average $3.0$ billion. By how much does the displaye
打开 →A live fund panel shows 45 low-turnover funds and 15 high-turnover funds. Historical survival rates were 90% for low-turnover funds and 30% for high-turnover funds. By how many percentage points does the displayed live panel understate the original share of high-turnover launche
打开 →A research platform runs 200 null strategies. Only strategies with in-sample p-value below 15% are promoted, and each promoted strategy must then pass a fresh 5% confirmation test. Assuming independence under the null, what is the expected number of false strategies that survive
打开 →You test 40 independent noise strategies. A strategy is launched only if it passes an in-sample screen at level 1/20 and then passes a second independent validation at level 1/10. Under the global null, what is the probability that at least one noise strategy still gets launched?
打开 →A 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
打开 →A researcher generates 240 heavily correlated strategy variants but argues they amount to only 24 effectively independent families. If the desk still flags any family with p-value below 8%, what is the approximate probability of at least one false family-level winner under the nu
打开 →A researcher produced 120 parameter variants, but they cluster into roughly 6 effectively independent families. Using a 5% per-family threshold as a rough approximation, what is the probability of at least one false winner across the 6 families?
打开 →A signal becomes public at Tuesday 4:15pm ET. A daily strategy may only trade after all input data are known. What is the earliest tradable session?
打开 →A signal becomes public at Wednesday 8:10am ET. A daily strategy may only trade after all input data are known. What is the earliest tradable session?
打开 →A signal becomes public at Thursday 6:00pm ET. A daily strategy may only trade after all input data are known. What is the earliest tradable session?
打开 →A signal becomes public at Friday 3:55pm ET. A daily strategy may only trade after all input data are known. What is the earliest tradable session?
打开 →At end-2026, a live panel contains 18 funds launched in 2017 and 24 funds launched in 2021. The survival rates for those vintages were 30% and 80%, respectively. What was the average launch year across all original launches?
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