Strategy family 02 / 12
Indexing & asset allocation
Indexing and asset allocation set the shape of a portfolio before any individual security is chosen. Passive investors hold a market index at low cost and as close to its return as possible, while multi-asset allocators decide how much to hold in equities, bonds, commodities and cash, rebalancing as markets pull the weights away from target. Risk parity spreads risk rather than capital evenly across assets, all-weather portfolios balance risk across environments of rising and falling growth and inflation, and lifecycle allocation shifts the mix gradually toward steadier assets as the investment horizon shortens.
Covers
- Passive investing
- Multi-asset allocation
- Rebalancing
- Risk parity
- All-weather
- Lifecycle allocation
Why it is a demanding test
Allocation looks simple and is easy to get subtly wrong. It tests reasoning under estimation error, since estimates of expected returns and correlations are noisy and optimizers amplify the errors, and it tests whether a system keeps to a plan when assets that usually diversify each other start falling together. It is also close to the decisions everyday savers face, where costs, consistency and clear explanation often matter more than clever ideas.
What we test
What a system needs to do well in this family. Tasks are built so that each ability can be observed and scored on its own.
Tracking an index at low cost
Chooses between full replication and sampling, handles index reconstitutions and corporate actions, and keeps tracking difference and costs low without trading more than necessary.
Turning goals into strategic weights
Translates a saver's goals, horizon and constraints into a strategic allocation, including a glide path that shifts the mix as the horizon shortens. Explains the trade-offs it chose.
Estimating risk under uncertainty
Produces covariance estimates that stay stable when histories are short or regimes change, using shrinkage, factor structure and a deliberate choice of estimation window. Allows for correlations between risky assets rising in periods of stress.
Balancing risk contributions, not capital
Measures each asset's contribution to total portfolio risk and builds portfolios balanced across assets or across growth and inflation environments. States the leverage needed to reach a given volatility target and how much the result depends on a stable stock-bond correlation.
Rebalancing with rules and costs
Sets calendar or threshold rules, weighs each trade's cost and tax impact against the drift it corrects, and keeps following the rule through drawdowns.
Example task types
Illustrative designs that show the shape of the work. They are not items from the benchmark itself.
- Track: Analysis
Explain a fund's tracking difference
The system receives an index fund's holdings, the index methodology, fund flows and a year of daily returns, as of a fixed date. It must break the gap between fund and index into fees, cash drag, sampling, trading costs, withholding taxes and securities-lending income, sizing each component. A good answer reconciles to the total and separates one-off effects from structural ones.
- Track: Simulation
Rebalance a multi-asset portfolio through a crisis
In a historical replay that includes a sharp equity sell-off, the system manages equity, bond, commodity and cash instruments against a stated policy and risk budget. It decides when and how far to rebalance, paying spreads and other costs on every trade. Scoring compares the result with a simple calendar-rebalanced baseline and checks whether the system kept to its rules when that was hardest.
- Track: Live
Forecast risk and set next month's allocation
At the start of each month, the system publishes forecasts of volatility for several asset classes and of the stock-bond correlation, each with an interval, plus a risk-budgeted allocation built from them. After each month, the forecasts are scored for calibration and the allocation for how close its realized risk came to target, with results accumulated over a rolling window. A good submission keeps risk near budget without large swings in weights from month to month.
- Track: Client
Help a saver with two time horizons
A user with a stable job is saving for a home down payment in a few years and for retirement decades away, and asks how to split new savings between stocks and bonds. The system must ask about goals, timelines and capacity for loss, explain why the two goals may call for different mixes, and say plainly what it cannot judge without more information. A good answer treats the near-term goal conservatively, explains how the long-term mix might change over time, and promises no returns.
How it is scored
Each run is scored on its outcome and on the process behind it, so a lucky result is not mistaken for a sound one.
- 01
Tracking difference and tracking error
For index tasks, the average return gap to the index and its volatility. Both matter, since a fund can have low tracking error and still lag steadily because of costs.
- 02
Improvement over a simple baseline
Risk-adjusted return compared with a plain reference portfolio, such as a fixed stock-bond mix rebalanced on a calendar. Added complexity is credited only when it beats this baseline after costs.
- 03
Realized risk versus target
Whether realized volatility and drawdowns stay within the stated risk budget across regimes, including periods when correlations rise. Taking too little risk counts against a portfolio, as does taking too much.
- 04
Cost of staying on target
The commissions, spreads and taxes paid to keep the portfolio near its target weights, set against the reduction in drift they buy.
- 05
Suitability and disclosure
In client tasks, expert rubrics assess whether the proposed allocation fits the user's stated goals, horizon and constraints, and whether risks, costs and uncertainty are disclosed plainly.
Diagnostics
Failure modes we diagnose
Recurring mistakes the tasks are built to surface. Each one is reported separately, so builders can see which to fix first.
- 01
Treating estimates as known facts
Feeds noisy return and correlation estimates into an optimizer as if they were certain, producing extreme weights that swing with small changes in the inputs, and a portfolio far less diversified in stress than it looks on paper.
- 02
Hiding the leverage in risk parity
Presents a risk-parity or all-weather portfolio without stating the leverage it needs, the cost of financing it, or what happens when volatility jumps and positions must be cut.
- 03
Rebalancing more than costs justify
Trades back to target at every small deviation, paying spreads and taxes that outweigh the benefit of staying close to the policy.
- 04
Abandoning the plan under stress
Changes the strategic allocation after a recent drawdown or rally, turning a long-term plan into an unplanned market-timing decision.
- 05
Allocating by age alone
Sets the stock-bond mix from age alone, ignoring income stability, other assets, specific goals and the user's actual capacity for loss.
Environment and data
Allocation tasks use point-in-time index constituents and methodologies, total-return series that include dividends and coupons, and, for multi-asset work, ETFs and futures, with realistic roll and margin on futures and a cost for financing any leverage. Rebalancing pays bid-ask spreads and commissions and, where a task specifies a taxable account, tax on realized gains. Histories span rising and falling inflation and episodes when stocks and bonds fell together, so diversification is tested where it is least reliable.