How to annualize Sharpe Ratio?

Question

I have a basic question about annualized Sharpe Ratio Calculation: if I know the daily return of my portfolio, the thing I need to do is multiply the Sharpe Ratio by $\sqrt{252}$ to have it annualized.

I don't know why is that, can any body explain?

Answer 1

Actually, that is not always the case. Here is a great paper by Andy Lo, "The Statistics of Sharpe Ratios". He shows how monthly Sharpe ratios "cannot be annualized by multiplying by $\sqrt{12}$ except under very special circumstances". I expect this will carry over to annualizing daily Sharpe Ratios.

Answer 2

@RYogi's answer is definitely far more comprehensive, but if you're looking for what the assumptions behind the common rule of thumb are, they are:

1. The returns of the portfolio are a Wiener process, in which volatility scales with the square-root of time.
2. There are 252 trading days in a year.

As Lo's paper points out, assumption #1 is somewhat suspect.

Answer 3

You often see various financial metrics scale with the square root of time This stems from the process that drives the lognornmal returns in stock prices which is the Ito process $dS = \mu Sdt + \sigma SdZ$.

The Wiener process assumes that each dt is IID and has constant $\mu$ and $\sigma^2$, therefore the same expected value and variance at each increment. Because: $$\operatorname{Var}\left(\ln\left(\frac{S(T)}{S(T_0)} \right) \right) = \operatorname{Var}\left(\ln\left(\frac{S(t_n)}{S(t_{n-1})} \right) \right) + \operatorname{Var}\left(\ln\left(\frac{S(t_{n-1})}{S(t_{n-2})} \right) \right) + \dots + \operatorname{Var}\left(\ln\left(\frac{S(t_1)}{S(t_0)} \right) \right)$$ $$ = ns^2 = s^2\frac{(T-T_0)}{dt}$$ $$\text{where } n = \frac{(T-T_0)}{dt}$$ It follows that $s^2(T-T_0)$. Because the variance should be finite, in the $\lim_{dt \rightarrow 0}$, variance should be proportional to $dt$. Since $s^2$ is 1 for a lognormally distributed process, the variance is $(T-T_0)$, the standard deviation is therefore $\sqrt{T-T_0}$ or $\sqrt{T}$.

The reason you see financial metrics scaled to the square root of time is because the metrics are usually calculated using stock returns, which are assumed to be lognormally distributed. Whether it's right or wrong really has to do with your assumption of how stock returns are really distributed.

Answer 4

Here's the idea of where that comes from:

To annualize the daily return, you multiply by 252 (the number of observations in a year).

To annualize the variance, you multiply by 252 because you are assuming the returns are uncorrelated with each other and the log return over a year is the sum of the daily log returns.

So the annualization of the ratio is 252 / sqrt(252) = sqrt(252).

Answer 5

The units of Sharpe ratio are 'per square root time', that is, if you measure the mean and standard deviation based on trading days, the units are 'per square root (trading) day'. It should be obvious then, how to re-express Sharpe ratio in different units. For example, to get to 'per root month', multiply by $\sqrt{253/12}$.

The reason why Sharpe has these units is because the drift term has units of 'return per time', while variance is 'returns squared per time'.