Since you posted this I've investigated further. If I understand things correctly, you do not have to divulge your system, but can just post trades to them.
The main issue is not the system but the possibility of back charges in excess of what you have made in fees and charged to your cc. Regardless, one a fool would post the trades of a system that works and not take advantage of it himself.
That is precisely what happens...C2 hold up payouts for 60 days... Users can 'rent' the system and regardless of the outcome after one month they can demand a refund ...no questions asked...reason saves C2 from getting into litigation... Sounds ludicrous....FACT. Incidently, no one can telll how the subscriber traded the system.And some people have no morals.... NiN
If you have to ask if you a system is good enough to sell, chances are that you have much to learn about the math behind testing and developing systems. Consequently, your system will most likely fail. This is not being said to discourage you, but rather to encourage you to learn more before proceeding. Also, much of the past 15 months presented market conditions that were not faced for many years before. Sampling the system during other time periods is a must. Test statistics such as profit ratio and sharp ratio assume that your system's success is based on factors that are causing the market to move. More likely, your system made its profits in the back-test due to correlations between different conditions (IE: Different indicators working together to give a trade). Such systems are poorly evaluated in terms of profit ratio, sharpe ratio and such since correlation between factors can change dramatically over time. It looks like you are trying to take a systematic approach to trading which shows that you are going in the right direction. My advice: Pick up some textbooks on statistical analysis and study them thoroughly while doing practice projects along the way reflecting the topic you are studying. Topics such as probability distributions, correlation testing, and hypothesis testing with mean and variation should be emphasized. Entering the trading game means you are competing with some of the most intelligent and knowledgeable people in the world. Do not for one second think that "winging it" is good enough. A good book is "An Introduction to Statistical Methods and Data Analysis" by R. Lymann Ott which can be found at : http://www.amazon.com/Introduction-...=sr_1_1?s=books&ie=UTF8&qid=1288640834&sr=1-1 Reading this book won't make you an expert at trading. It is however a good start to developing an objective approach and testing method. If you do take this route, one piece of advice: Do not assume that samples of market data are normally distributed or even come from normal distributions. This makes a huge difference in the accuracy of your tests (If you are unsure what this means, you will understand it after looking into that book). I am sure this post will result in replies saying "you don't need math" to be good at trading. Perhaps they are right. However, you don't have to be more than 6 feet tall to play basketball in the NBA, but it sure makes a huge difference.
None. Forgot to mention it in my first post, the test data doesn't include the market data for May 6, 2010 and May 7, 2010. The market volatility for May 6, 2010 was unusually high, so the test result of May 6, 2010 was un-normal; even the following day, May 7, 2010 was unusual. I've decided to drop off May 6 and May 7's data from my test data set. But my trading system did handle "the flash crash" days very well. Followings are the test results for May 6, 2010 and May 7, 2010: ES: May 6, 2010 Trades: 30 Net Profit: 3130 May 7, 2010 Trades: 42 Net Profit: 2694 NQ: May 6, 2010 Trades: 32 Net Profit: 3412 May 7, 2010 Trades: 77 Net Profit: 2392 YM: May 6, 2010 Trades: 47 Net Profit: 1462 May 7, 2010 Trades: 45 Net Profit: -1455
Ok, cool. Yeah, I actually did the same, otherwise the flash crash skewed the parametrization too much. Can you give us some insights into the concepts on which your strategies are built?