I meet dilemmas when I'm developing futures trading system,they are problems of data proceeding. We all know that each futures contract has a starting date and a expiring date,for example,Cu contract usually starts in July and expires in Jan.when we chain all the contracts with the same starting and expiring month in the same market,there is always a big gap between this starting price and previous expiring price,it's not suitable for a indicator troughout the whole period of the contract,so how to test a mediun/long term system on several markets. A suggestion is to test on index data,that's,create an open interest-weighted index from all the contracts in the same market,regards the results from it as the performance of a system on the whole market.But when a long/short signal occurs on index data with this system,the operator have to check whether this signal could be performed on contracts in this market,there are too many unstable factors in this period,so the performence between test and reality would be very huge. Another suggestion is to create some continuous contracts from a market,a case is picking the most active sections of contracts in a market to compound an index data.So new problems of adjusting contract comes: 1. should I back-adjust or forward-adjust? back-adjusting data could keep the data in the most recent section the same as the data in the most active real contract,but the absolute value of data in the older sections would be distorted ( althouth there is no change to their relative relationship ),but with date going,the contract with the most active data changes,and new 'most active data' is added,the new absolute value of data in previous sections would change,too.So the value of some indicators,which are base on the price of data (not on the relationship),would change accordingly,probably the signals for trading(entry price/exit price) would change,the results of a system in this data proceeding rules may not be stable,how can I believe this system? If I decide to forward-adjust data,that's,letting the absolute value of starting data be,and revise the data in the following sections,in this way,once the data is revised,they will not be changed any more,the result of test on them would be constant,but the absolute value of data in the most recent section are different from their relating real market data completely,althought their relationship between the data are the same.The direct effect is,the position sizing rules in test may be different from those in real trading on real market data completely--the entry / exit price are not the same,also the result of risk measuring. 2. in order to eliminate the gap between different sections,should I adjust them with add/subtract rule or multiply/divide rule? with add/subtract rules,probably many data's change originally in the limit-day range,but not after being added / subtracted,for example,two close price originally are: 8341 and 8123,the change% in real market is (8123-8341)/8341*100=2.64%,which is in the 3% limit day range,in order to eliminate the gap between two sections,that are subtract 3000 to 5341 and 5123,the change% in this state is 4.08% > 3% limit day rule. How to sovle these problem please? regards.
In order to eliminate the gaps,at first,I planned to build an index data from those basic real market futures data,that's,multiplied price with open interest each bar,the result are every bar's open capital -- capital stored in market in each bar,then sum all contracts in the same market up each bar(there are 12 contracts in this market),also added their open interest up each bar,then divided total open capital by total open interest each bar,by this mean,a weighted bar is built,I repeated this procedure again and again,a series of weighted data is built. I then run systems on this weighted data,and got an acceptable result,but I found a new problem:when a signal is occured with my system on this data,I don't know which contract should I take,and I don't know how to set rules to pick corresponding contract,it's really a big problem. then I want to tried another way to eliminate gaps.after studying,I found some contracts' (active) main period are continuous,so I divided 12 contracts into 4 groups.the periods and groups are shown in the following snap: <img src=http://imageserver1.textamerica.com/user.images.x/5/IMG_490505/_1003/TZ201003105526720.jpg> firstly,I picked the first group including contracts expired in Jan,May,and Sep.for each contract,in order to avoid liquidity risk,I cut the data in the first 2 months and last 1 month,the rest data in 4 months in 3 contracts could be joint.but gaps are still be. <img src=http://imageserver1.textamerica.com/user.images.x/5/IMG_490505/_1003/TZ201003110737849.jpg> but at least,now if the system sent a signal to entry or exit,I could immediately know which contract should I operate on. but now,the big problem for me is: in order to eliminate gaps,should I adjust data from the most recent part back to the older part(back adjust),or from the oldest part to the recent part(forward adjust)?should I add/subtract something to eliminate gaps or multiply/divide factors to do so?