Way to go getting that coded so fast, looks like we have a few people getting excited about this project. Can you post the code as it is when you get a chance so that others don't have to start from the beginning? I was thinking about Vultures talk of different time frames and thought maybe we could add a 13sma in uptrend which would be almost equivalent to checking to see if the 5sma on a 5min chart was moving up, or maybe there is a different way to code that. Keep up with the good ideas all wdbaker
Oh yeah...duh! Here it is....Tradestation 6 EasyLanguage: sorry can't figure out to get it in here. I have cut and pasted and typed by hand and it won't take. It must be me.
OK what's going on... whether I copy and paste or enter by hand I get this lame thing... oooh I think I see, I bet ET's VB code is reading my input as Vb code. I wonder if I put quotes around the whole thing, otherwise I don't know what to do. nope...
Just out of morbid curiousity, someone program this into their intraday analysis program and tell me the results. Purchase at 9:50 Sell at 10:10 Past 50 days -- there are no short sides. aphie
Maybe you can get by your problem of including TS code by enclosing it between "code" and "\code" (each of these need to be enclosed in [ and ] (without the quotes)). If that doesn't work, it's probably because of a character in TS that is being interpreted as HTML code. Just alter this by, for example, puting a space between offending characters. Looking forward to seeing your code. Thanks for taking the initiative. Richard
There are two main types of systems in my opinion: a) Generality Systems b) Specific Systems What is being suggested here, in my opinion, is a more general system. Suppose we researched historical data and found that, statistically speaking, Wednesdays had a 1.2% greater probability of closing higher than the open. We then statistically find that, between the times of 2:15 and 2:37, statistically the price will be greater at 2:37. We then say to ourselves, "Hmm, I can make a better system by only buying on Wednesdays at 2:15!" In effect, we are trying to capitalize on statistical edges from price-data which will, over a very long course of time, generally prove to approach an almost random distribution (Perhaps the past year Wednesday was the best day to buy, but over the course of 20 years, we might find that Wednesday is no better than any other day -- and if it is found to still be so, it may only be a .001% difference). I've looked over some of Larry Williams systems in his book, "Daytrading Futures Online" and have to say a lot of his systems fall under a general system. There is nothing wrong with this in my opinion (as his performance speaks for itself), but again, over a large sampling of time and data, all generalities will eventually seek a random distribution. .... However, in a specific system, we wouldn't concern ourselves so much with past events but a system that works directly from the data as it exists in the hear and now. Data from a day ago or today could certainly be used, but this type of system would not be concerned with past performance of variables existing over a long time period. Simple systems that follow trends, if used correctly and with discipline, can and are quite profitable. This is the part of "keep it simple." Give a 7 year old a chart and he'll probably make the observation by noon that it is a "strong up day." So buy, right? Why not? Why are we going to fight the trend -- why are we building these complex systems that exist off past data that is no longer relevent in our timeframe of the present? Instead, the best system is simply the one that uses whatever simple tools are necessary to trade into however major market trends exist together at any one point in time, holding that position until profitable, and selling it. I have never backtested a system, nor will I ever do so with a computer. I look at each graph and I try to observe what things happen before, during and after a trend shift. These things include: a) Changes in price action (speed of price change, direction of price change, volatility of price action). b) Changes in volume levels c) Changes in volatility d) Moving averages to understand general directional bias Running simulations through a computer may find profitable results, but only if you then take the next step to let the computer trade that system and not yourself. If you want a human to trade a system, you better have a human manually ascertain if that system can be profitable. If you want a computer to trade a system, then use a computer to backtest a mechanical system, boot it up and go drink coffee. Either approach could work, but don't mix and match these together or you are setting yourself up for dissappointment. aphie
I see where you are coming from, the main reason for using the first two and the last hour was just to stay out of the chop that takes place during the middle of the day and usually is not good for trend systems. Maybe you could come up with a good way to trade the chop for us that is simple, in any case we will probably test with out the time constraints also just to see what it looks like, big experiment you know. thanks for your input wdbaker
The best trading systems I have seen over the years have the following characteristics: (1) A small number of indicators (2) Consider trends over various timeframes and produce predictive comparisons / correlations of the various time scales (3) For model based systems, there is an allowance for adjustable parameters based upon an experienced traders reading of market conditions. Another point that I would make - and its just my observation - is that it is easy to get caught up in producing ever more complex mathematical models, incorporating the latest buzzword technique. For example, Wavelets - mentioned in another thread - are a useful modern approach for some calculations but for most things the pre-wavelets methods work just fine and in fact have some advatages. Increasing the complexity of things does not IMHO mean that your approach will be more profitable. In fact, there may be an inverse relationship between profitability and complexity of approach.