I have built in a custom programming language a tool used to evaluate strategies (specific rules on when to enter and exit the market). There are many software programs out there like TradeStation that evaluate strategies, but in order to fully evaluate strategies you must (1) know what youâre doing, and (2) perform many , many tedious steps to arrive at the answer. Features of my Testing tool (if you don't feel like reading the technical jargon, skip to the part, "THIS IS WHY I'M TELLING YOU THIS") 1) My tool is built out of complied code, rather than interpretative code which means that itâll run about 100 x faster. What takes 1 hour to do in interpretative code takes about 45 seconds in complied code. (tradestation is interpretative) 2) My tool uses percentages rather than dollars amounts. When evaluating a strategy it is important to take values in terms of percentages rather than dollar amounts, or else youâll must more emphasis on the higher values. 3) If youâre doing a back test and get good results without knowing what the buy and hold or short and hold model is youâre fooling yourself. My tool doesnât evaluate the strategy on the actual performance, but rather takes into account of what a buy and hold or short and hold method model would have returned. 4) A measure of robustness that is commonly used is an in sample / out sample data test. What you have to do is test a strategy from say 2005 to 2006, find a set of parameters, then take those parameters and test them on data that is not seen, for example from 2006 to 2007. If the strategy returns nearly the same as it did from 2005 to 2006 this is considered a measure of robustness. In order to do this one has to plot the data into a surface plot in excel, and find a set of parameters. This however becomes a challenge when you are dealing with 3, 4, or 5 parameters. Doing this can become a cumbersome process, to do this youâd have to: 1) Do an optimization 2) Download the data into an excel surface plot,. 3) In the event that youâre only optimizating 2 parameters you can visually choose the best set of parameters, else I wouldnât know what to doâ¦ 4) Test the parameters on unseen data 5) Repeat sets 1 to 3 again. My Tool, will COMPLETELY, automate this process. 5) The robustness test doesnât stop there. My tool returns a value for each bar held, 3, 4, 5, 6â¦ etc bars. The value is an average of all the parameters in the strategy. The value is then compared to the buy and hold or short and hold model. A percentage of values that beat the buy and hold or short and hold model is displayed along with the average return with respect to the buy and hold or short and hold model of ALL parameters. 6) Then this process can be completed again and again for market after market. I can test hundreds, or maybe thousands or different markets with a click of the button go away and will have aâ¦ 1) In Sample optimization w/ my algorithm of searching for the best parameter combinations (This is not genetic for those interested, genetic is a great way to find a very fast way to overfit the data.) 2) Out Sample optimization w/ my algorithm of searching for the best parameter combinations 3) An out of sample data test 4) 2 other tests of robustness. Average of all the other parameters. All this can be done for as many markets as I want to test ALL AUTOMATED. Try doing all this in tradestationâ¦ youâll have carpel tunnel by the time youâre done, or try building this testing tool, another great way to get carpel tunnel. From the sample output Column A: This is the market tested. Column B: This is the 1st optimal Parameter Column C: This is the 2nd optimal parameter Column D: This is the 3rd optimal parameter Column E: This is the return of the optimal parameters. The value which I define is beat per bar. If a long strategy does .08% in 4 bars while the market does .06% in 4 bars. On average we are beating the market by .005%. The number is multiplied by 1000 for clarity reasons. Column F: Donât worry about this Column G: Trades Per symbol (sometimes I test in groups of stocks/ futures) Column H: Out of sample data test. This is the return tested on the out of sample data from the parameters of the in sample data. Column I: This is the average of every single parameter. Column J: My tool returns a value for each bar help, 3, 4, 5, 6â¦ etc bars. The value is an average of all the parameters in the strategy. The value is then compared to the buy and hold or short and hold model. A percentage of values that beat the buy and hold or short and hold model is displayed along with the average return with respect to the buy and hold or short and hold model of ALL parameters. THIS IS WHY IâM TELLING YOU THIS If you didnât have a clue as to what all the âstuffâ meant, basically I have built an excellent tool to help evaluate the performance of a strategy. With the all automation I have put into it, and the extra robustness tests, it makes actually evaluating a strategy fairly simple. What Iâm looking for is someone who has a winning strategy, a discretionary trader or a mechanical trader who would like to know how their strategy performs on hundreds of different markets. Currently I test about 550. I will write up your strategy and put it through my system. What youâll receive is a detailed description including all the features indicated above for every market you want to test. If you donât understand them, whatâs important is youâll receive every optimal parameter combination from every market you chose, along code so you can automate your strategy, along Iâll walk you through the results to better understand them. If interested Private Message Me or email me @ firstname.lastname@example.org â¢ My tool is not for sale â¢ I am not looking for people who want to test ideas, of which has happened in the past. Iâm looking individuals who have a winning model that are interested in obtaining what I can provide for them.