Ask two quants to compare a bond fund against a crypto strategy using the Sharpe ratio, and you will get a number that looks objective, feels scientific, and is quietly lying to both of them. The annualisation step — that innocent-looking multiplication at the end — is where comparability goes to die. This question matters enormously because performance fees, capital allocation, and career outcomes all hinge on it.

Here is the direct answer: multiplying by the square root of the number of periods is only mathematically valid when returns are independently and identically distributed with no autocorrelation. In practice, almost no asset class satisfies that assumption cleanly, and different practitioners use different period counts — 252 for equities, 365 for crypto, 12 for monthly funds — making the resulting ratios structurally incomparable even before a single trade is examined.

CONCEPTSharpe annualisation assumes i.i.d. returns — a condition real markets routinely violate.
WARNINGComparing a daily-scaled equity Sharpe against a monthly-scaled bond Sharpe is like comparing kilometres to nautical miles and calling it a fair race.
KEY IDEAAlways state your annualisation convention explicitly — a Sharpe ratio without it is a meaningless number dressed in a suit.

Think of it like converting currencies mid-transaction without telling anyone the exchange rate. A crypto strategy sampled at daily frequency and scaled by √365 will produce a structurally higher Sharpe than an identical risk-adjusted bond fund scaled by √252, purely because of the denominator choice. The ratio has not changed because the strategy got better — it changed because someone picked a different calendar.

Same Strategy, Different Annualisation Convention√252√260√365√12 mo1.411.431.691.47Sharpe rises with larger multiplier — same underlying returns

The autocorrelation problem compounds this further. Fixed income strategies often exhibit positive return autocorrelation — momentum in bond prices — which makes volatility appear lower at monthly frequency than daily, artificially inflating the Sharpe. Trend-following systems have a similar quirk. Researchers like Lo (2002) documented this formally, showing annualised Sharpes can be overstated by 65% or more when autocorrelation is ignored. For a thorough grounding in the ratio's mechanics, the Investopedia Sharpe ratio explainer is worth bookmarking, while the Wikipedia entry on the Sharpe ratio covers the statistical assumptions candidly. The broader category of risk-adjusted return metrics also shows why no single ratio tells the whole story.

The practical takeaway is brutally simple: before trusting any Sharpe comparison, demand the annualisation convention, the sampling frequency, and whether autocorrelation adjustment was applied. Without those three numbers, you are comparing apples to submarines.

A Sharpe ratio without a stated convention is not a metric — it is a opinion wearing a calculator's clothing.

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