Portfolio Backtesting Quant Interview Guide
Portfolio backtesting quant interview guide for rebalancing, costs, survivorship, constraints, risk metrics, examples, and validation.
Candidates evaluating allocation or portfolio strategy evidence.
Portfolio backtests need implementation detail
A portfolio backtest must specify weights, rebalancing, costs, liquidity, constraints, data availability, and corporate actions. The performance number alone is not enough.
Rebalancing changes results
Daily, monthly, and threshold-based rebalancing can produce different turnover, cost, and risk profiles. The rule should match the strategy and data timing.
Concrete example
A backtest that rebalances every day into illiquid names may look attractive before costs but fail when realistic trading assumptions are included.
Bias checks are mandatory
Survivorship bias, lookahead bias, stale prices, and benchmark changes can all distort portfolio evidence. Name the specific data issue you would check first.
Common mistakes
Candidates often discuss return and ignore portfolio mechanics. Strong answers include turnover, constraints, risk metrics, and whether the backtest could have been run live.
Practice the pattern
Use the LeetQuidity curriculum and calibration to turn this topic into a focused practice plan.