I used volatility which is based on standard deviation and based on normality assumption. Any pointers to better risk measure taking into account of fat tails? I am asking here instead of asking on a Math forum because I am looking for practical and nice solutions, instead of current research papers... Thanks.
Volatility is the name given to how much a market moves in a given time period. Standard deviation of returns and average trading range are two possible ways to calculate a value for it. The normal distribution has nothing directly to do with it. To take account of fat tails, try using a Pareto distribution / approach once you have backtested your system. This just assumes that if an event (drawdown?) of magnitude x happens with probability p then one of kx will occur with probability p/(k^n). It's up to you to discover what your n is.
Read http://braverock.com/brian/R/PerformanceAnalytics/html/PerformanceAnalytics-package.html -- especially the section on VaR -- and then make use of his free, open-source Cornish-Fisher functionality, if you're so inclined.
you cant have simple trades and expect your risk to be controlled automatically. You need a variety of asset classes, timeframes, and non-directional trades in a portfolio of uncorrelated strategies to truly control risk. Its oversimplified to expect to just pop in some position sizer or something that tells you what your stop should be on the basis of volatility - atr, stdev, etc... thats just touching the surface.
Hi folks, Thanks for your replies... I guess for practical usage, I am just looking for a method to generate a variable and the variable can replace my current standard deviation. So hopefully, I can have a new variable named "Modified Standard Deviation" or "Modified Risk Measure" and plug it into my existing application and replace the currently used "standard deviation" ... Any thoughts? Thanks