There are several arguments against using the Sharpe ratio. First is that the Sharpe ratio can be gamed by managers:
Illiquid stocks or infrequent marking-to-market raises the sharpe ratio. An example of this is using the NACREF appraisal index to measure the return & volatility of real-estate assets as opposed to the NAREIT index which is marked-to-market much more frequently.
Lengthening the measurement interval (to monthly instead of daily returns, for example). This lowers the estimated volatility. Longer holding periods increase the ratio by approximately the square root of time. Digression: This practice is quite pervasive. Whenever I see a strategy tear-sheet I immediately flip to the definition of sharpe ratio and often find that the manager uses monthly sharpe ratios instead of daily.
Several strategies such as buy-write have high sharpe ratios that mask severe downside risk for several years. For example, writing out of the money puts and calls generates premium which has a high sharpe in good times. Similarly, strategies that take on default risk, liquidity risk, have the ability to bias upwards the sharpe ratio in normal times (see Long-Term Capital Management)
Engage in a return swap with a broker dealer to eliminate the highest returning and lower returning months in the portfolio will increase Sharpe by eliminating extreme returns
Smoothing of returns with derivatives
The Sharpe ratio can be gamed by adjusting the universe of analysis. For example, a manager with a Sharpe ratio of 1.5 performing security selection the S&P 500 universe has better active management skill than a manager who achieves the same Sharppe ratio on the Russell 5000.
To use Sharpe ratio to compare manager performance across strategies there is an assumption that i) investors care about the 1st two moments of returns, and ii) that when the Sharpe ratio is used to compare across strategies that strategy returns are normally distributed.
There are various non-parametric and monte carlo techniques that can improve upon the limitations identified above. Also there are other measures such as Sterling Ratio, Return over Max Drawdown (RAMOD), that can inform one's perspective when used in concert with the Sharpe ratio.
Also, attached is a paper by Andrew Lo that is a nice critique of the Sharpe ratio. His conclusion:
The results presented in this article provide one way to gauge the
accuracy of these estimators, and it should come as no surprise that
the statistical properties of Sharpe ratios depend intimately on the
statistical properties of the return series on which they are based.
This suggests that a more sophisticated approach to interpreting
Sharpe ratios is called for, one that incorporates information about
the investment style that generates the returns and the market
environment in which those returns are generated. For example, hedge
funds have very different return characteristics from the
characteristics of mutual funds; hence, the comparison of Sharpe
ratios between these two investment vehicles cannot be performed
As mentioned above, the R Performance Analytics package has a number of performance measurement tools.