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·3 min read·BestFolio Research Team

Do strategy risk labels match realized drawdowns?

Do strategy risk labels match realized drawdowns?

BestFolio's conservative, moderate, and aggressive labels separate the catalog medians in the expected order. The gaps are large enough to be useful and still too coarse for sizing a portfolio.

A risk label compresses years of returns into one word. That is convenient for browsing and dangerous for allocation. Aggressive can refer to leverage, equity concentration, a deep historical drawdown, or some combination. Conservative can still include a loss that changes an investor's plan.

These are manually assigned categories at the strategy level. They are navigation labels rather than fixed thresholds. Auditing them against the primary variants shows whether the words at least point in the same direction as the measured outcomes.

The medians line up

The usable sample included 22 aggressive, 54 moderate, and 11 conservative primary strategies. Full-period histories have different start dates, so this is a catalog description rather than a controlled experiment.

Primary strategies; robustness snapshot uses 217 tracked trials
Full-period medianConservative, n=11Moderate, n=54Aggressive, n=22
CAGR8.38%10.25%14.41%
Sharpe1.121.040.86
Maximum drawdown-18.90%-24.03%-46.59%
Volatility6.82%9.95%18.99%
Annual one-way turnover0.802.141.79
Share flagged fragile0%7.41%31.82%
Grouped bars showing median CAGR and maximum drawdown across conservative, moderate, and aggressive strategy labels
Median CAGR rises steadily across the labels. Maximum drawdown makes the larger jump, especially from moderate to aggressive.

The aggressive median earned 14.41% CAGR, 6.03 percentage points above the conservative median. Its maximum drawdown was also 27.69 points deeper. Median volatility nearly tripled from 6.82% to 18.99%.

Risk-adjusted return moved in the opposite direction. Median Sharpe declined from 1.12 for conservative to 1.04 for moderate and 0.86 for aggressive. A higher-return category did what its label promised, but the average unit of historical volatility received less return.

Fragility rises with the category

BestFolio flags a strategy as fragile when its Deflated Sharpe result falls below the catalog threshold. The calculation at this snapshot used 217 tracked trials. Among primary strategies, 31.82% of the aggressive group was flagged, compared with 7.41% of moderate and 0% of conservative.

That ordering has a plausible mechanical source. Aggressive strategies often combine leverage, shorter live fund histories, or more concentrated rules. Each can make a high headline result more dependent on the chosen sample. The group result identifies an audit priority, not the cause for any specific strategy.

Turnover refuses to follow the simple ladder

Median turnover was 0.80 for conservative, 2.14 for moderate, and 1.79 for aggressive. The middle category traded more than the aggressive category. Risk level and trading burden are separate dimensions.

This matters when labels become portfolio filters. An investor may be able to tolerate an aggressive historical drawdown inside a small sleeve while lacking the time or tax setting for a moderate strategy with frequent rotations. A single word cannot encode those constraints.

The label is a starting point

A useful risk card needs the category plus the measurements that can break the plan:

  • Maximum drawdown depth and the date it occurred.
  • Longest recovery time.
  • Worst month and worst calendar year.
  • Gross leverage and the assets that remain leveraged in defense.
  • Turnover, execution schedule, and expected friction.
  • Robustness after the full research trial count.

The audit supports keeping the labels. The conservative, moderate, and aggressive medians are meaningfully different on CAGR, volatility, drawdown, Sharpe, and fragility. It also supports treating them as shelf signs. The number that determines position size should come from the strategy's own failure record, not the category name above it.

Data sources

Past performance does not guarantee future results. Backtested results are hypothetical and do not represent actual trading.

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Data and method

Study dates and assumptions are documented in the article and its revisions. Our current methodology explains the platform's data sources, proxy histories, trade timing and inflation treatment.

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