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Portfolio Management interview preparation

Asset allocation, factor models, risk, attribution and implementation, on global and Indian portfolios. Every question is either traced to a named firm from a public candidate report, or tagged at desk level when we could not trace it, and answers lead with the point, then the mechanism, then the limitation.

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Question bank

100 questions, mapped to the firms that asked them

Questions
100
Traced to a firm
40
Firms
24
Updated
September 2026
Asked at
All firmsBLBlackRock4Vanguard4WMWellington Management4Amundi3ACAQR Capital Management3Neuberger Berman3SCSchroders3Man Group2MSCI2Northern Trust2AllianceBernstein1Apollo Global Management1Blackstone1BMBNY Mellon1Carlyle Group1Fidelity Investments1Goldman Sachs1Invesco1Millennium Management1MSMorgan Stanley1NUNuveen1PIMCO1SSState Street1TPTPG1
Topic
All topicsPortfolio theory5Factor models8Asset allocation11Rebalancing3Portfolio construction7Benchmarks and tracking error5Performance measurement8Risk management6Fixed income and LDI5Currency and global3Implementation and costs5Active versus passive6India markets7Brainteasers5Career and fit16
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Showing 1–2 of 2 · filtered from 100Clear filters
  1. 037How would you budget tracking error across a portfolio?Benchmarks and tracking errorHardsuperdayInstitutional asset managementRisk management

    Say this

    Treat it like a capital budget. The mandate gives you a total active risk allowance, and you allocate it to the decisions with the highest expected information ratio, remembering that risk adds in quadrature rather than linearly so diversified bets are cheap.

    Then walk it

    1. Start from the total: say the mandate allows 3 percent tracking error. Decompose the sources, asset allocation tilts, country and sector bets, stock selection, currency, and any manager selection risk if it is a fund of funds.
    2. Allocate by expected information ratio, not by conviction. If stock selection has a long-run IR of 0.4 and tactical allocation has 0.15, most of the budget belongs in stock selection, and that is an argument about process, not about this month's view.
    3. Use the quadrature point, because it is the technical content of the question. Three uncorrelated 1.5 percent sources give a total of about 2.6 percent, not 4.5 percent. So spreading the budget across genuinely independent decisions buys you more expected return per unit of total active risk.
    4. Which means correlation between active bets is the thing to police. An overweight to technology and an overweight to growth and an underweight to duration are one bet, and they will consume the budget three times over while delivering one payoff.
    5. Leave headroom. Run at perhaps 70 to 80 percent of the limit in normal conditions, because a volatility spike will raise your ex-ante tracking error without you trading, and being forced to cut positions to cure a breach is the worst possible reason to trade.
    6. Then monitor it prospectively and review the allocation, not just the level. If realised attribution says the 1 percent you spent on tactical asset allocation has produced nothing over five years, the right response is to move that budget to where the evidence is, not to try harder.

    Where candidates lose it

    Treating the budget as additive and dividing it up in straight lines. Risk adds in quadrature, so the diversification between active bets is the whole game. Also mention headroom, because breaching a tracking error limit on a volatility spike and being forced to trade is a real and unglamorous way to lose money.

    Expect next

    • How would you split the budget between allocation and selection?
    • What do you do when a volatility spike breaches the limit?
    • How do you measure correlation between active bets?
  2. 038What is the fundamental law of active management, and what does it tell you to do?Benchmarks and tracking errorHardsuperdayQuantitative asset managementAsset management

    Say this

    Information ratio is roughly skill times the square root of breadth. So a modest edge applied to many independent decisions beats a strong edge applied to a handful, and it tells you to industrialise breadth rather than hunt for a bigger insight.

    Then walk it

    1. Grinold's formula: IR equals the information coefficient times the square root of the number of independent bets per year. The generalised version multiplies by a transfer coefficient for constraints.
    2. Put numbers on it, because that is what makes it real. An information coefficient of 0.05, which is a barely detectable edge, applied to 1,000 independent decisions a year gives an IR of about 1.6. An IC of 0.2, a genuinely good stock picker, across 10 decisions gives about 0.63. The mediocre systematic process wins.
    3. That single comparison explains the existence of quantitative investing, and it also explains why concentrated fundamental funds have high dispersion of outcomes: low breadth means luck dominates over any realistic evaluation period.
    4. The word doing the work is 'independent'. Two hundred positions that all express one macro view have breadth of one. Overstating breadth is the most common abuse of the formula, and it is why a sector fund with 80 names is not diversified.
    5. The transfer coefficient is the second practical lesson. Long-only, position limits and turnover caps typically cut realised IR to half of theoretical, so relaxing the most binding constraint can be worth more than improving the signal.
    6. The limitations I would name: it assumes bets are independent and that IC is stable, it ignores costs, and breadth cannot be increased indefinitely because higher frequency means higher turnover and costs eat the gain. So it is a way of thinking about where to invest research effort, not a formula to trade off.

    Where candidates lose it

    Quoting the formula without the numerical comparison and without stressing independence. The insight only lands when you show that a tiny edge times high breadth beats a large edge times low breadth. And if you claim breadth of 500 for a portfolio with one macro theme, an interviewer will take the answer apart.

    Expect next

    • How would you count breadth for a macro fund?
    • So why do concentrated funds exist at all?
    • What limits how far you can push breadth?

Firm tags come from public, anonymous candidate reports on Wall Street Oasis: strong signal, not sworn testimony. Firms are named as the places a question was reported, not as partners of Fin Maverick. Answers are written for this page to show how to think out loud; they are not scripts to recite.

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