Previous Part In part A I brought up some basic ideas about how to measure a trading strategy effectiveness. The basic measurements were the delta between "buying point" and "daily max price" (in order to judge the buying decision), the delta between "Selling point" and "daily max price" ("holding methodology") and the delta between selling all at once versus in several phases ("Selling strategy"). Some readers suggested that these basic definitions are on hand obvious for professionals, and insufficient for beginners. I also received questions regarding trady, the multiple computing network that works for me. I tried to respond to all questions as soon as I got it, if I missed someone I would like to take this opportunity and express my apologizes. It is very hard to bring up a 3-years research and development sub-conclusions, in one article in a discussion forum. In the near future I plan to locate most information on a web site. At the meantime I'm using the forum platforms in order to share information and receive your feedback. What's in this part ? In Part B I will provide more information about TRADY, the system that I've developed for this research. I'm aware that part of my text may seem as obvious but in order to raise a theory it is essential to build a case, I hope it won;t be too boring. More about trady As explained in part A trady is a multiple computers servers ("pizza servers") that run a parallel software, in which the main purpose of it is to find, track, buy and sell, the best daily opportunities (currently long stock trading only). The logical structure consists of three major parts which I call (a) wide picking (b) narrow picking and (c) trading implementation. To understand the overall picture it is important to understand my personal day trading philosophy. My way of trading I'm a day trader for several years and engineer by background, education and experience for many years. That combination with a strong mathematical background lead me to develop a trading strategy and a system that implements it (called trady). Basically my fundamentals are: (1) I never hold positions overnight (always go to sleep with zero holdings whether I lost or made profit at that day), (2) I always buy long with a momentum (aligned with the trend, not against it) (3) My portfolio is dynamic and changed every day, every hour and nearly every 10 minutes and (4) In some models I use, budget is a key to control the statistical behavior (this will be explained in details later). Wide picking My computers network reads information from NYSE, NASDAQ and AMEX (through an on-line broker tdameritrade) and builds an automatic "preferred list" of about 1500-1800 tickers. The list is not permanents and it is built every 10 minutes until about 12 Noon EST. That list brings up the best tickers to watch in a day, based on numerical parameters and mathematical calculations. I call that list "wide picking" because it provides preliminary list of symbols to watch (clearly a human been is unable to do that watch but computers can). No one guarantees that tickers in this list will remain in list, I found that during a day, a 10 minutes refresh is good enough and about 80% of list remains permanent for the trading day. In the next day the list can be totally different. To complete that part I will specify that although TRADY picks symbols from $1 and above, I personally don't go below $10 (expect for SUNW from time to time if TRADY signals this one) and I never go with tickers above $80 (although GOOG is a very popular ticker on my screens). Narrow picking Out of the 1500-1800 tickers in list (which are assumed to be the best for that trading day or at least trading hours), about 180 tickers will get a tight watch by the network computers. It means that these chosen 180 tickers will be sampled by the network every 6 seconds (give or take) and the accumulated samples will be used to calculate and generate trading signals and decisions. I've been asked several questions at this point regarding the sampling rate and the effectiveness of this technological model, and I feel this is the place to reply. The whole idea is to be able to sample the price and volume charts and make some heavy floating point and int64 calculations in order to identify and verify a trend (for buying) and an exit point (selling). by sampling a symbol 10 times a minute I assume that drastic price/volume changes in a ticker chart are made slower than 5 times a minute, which in 99% of cases is true (for long stock trading, I wouldn't take the same assumption for options trading or currency). Between each and every sample the computer makes the backward calculations which are required to identify and verify the signals. From my experience this a good working point for the system. One asked me about reading every tick, which I wouldn't reject, however, for the purpose of this system, I found that there's no big different between sampling a symbol graph every 6 seconds or triggered by every market tick. The purpose of narrow picking Each computer can handle a certain number of symbols at once, therefore the number of computers servers in the rack is the number of symbols my network can track and control. Right now due to resources issues I use 16 computers servers to watch tightly about 160-200 symbols out of the 1500-1800 wide picking list. As explained, each and every symbol - out of the 160-200 watched ones - is sampled every 6 seconds. A sample includes the following parameters: price, change relative to last day close and volume. AV, WMA and EMA are calculated on the fly per each and every sample. Trading implementation Each and ticker in the narrow list is handled by two logical sub systems (a) sampling and (b) trading. The sampling sub system reads price, change to close, volume, computes AV,WMA and EMA per sample and stores data in a list which related to that specific ticker (by the way, data is stored forever and used later by TRADY data base for backward analysis and further research), the other sub system (the trading one) runs what I call "a trading program", which is a language I defined that helps me to apply a trading strategy. Each and every ticker can use a different trading program although it makes no sense to provide different trading strategies for randomly-picked symbols (I provide same program for all picked tickers). Infrastructure The described infra structure is eventually a parallel computing network that can signal, send buy order, sell order (of course change and cancel as well), and control many tickers very tightly. During the past years since I started that venture I built several trading models, as most of you may probably know, it takes a lot of time to define a model, to check it, to verify its consistency and to stabilize it. When you pass through these phases the so called "final" model is no longer identical to the initial one. That's why I had to build up a very flexible infrastructure (not that I knew it from the beginnig but at some point about 3 years ago I stopped everything and designed the system from scratch). Power, Recovery and other technical stuff I've been asked by readers about power control and recovery. TRADY was designed bottom up, from very basic infrastructure such as encryption and security, through data backup and recovery and power control. I use a chain of two UPS systems to provide a continues power feeding, and most of data is distributed and duplicated over network. The software was written by me over the past two+ years, and right now it is about 600,000 Pascal code lines of EXE and about 200,000 code lines of extension programs and utilities. Buying signal Professional traders will acknowledge the "price breakthrough" term. In general a price breakthrough is a point where the demand grows faster than supply and therefore a price goes high. The challenge is to distinguish between temporary strong demand (in which you may buy but lose) and a "real" demand (where you can buy and exit later with some profit). There are many mathematical tests and indicators that were plan to signal a real demand trend. In TRADY the system is "programmed" to identify a demand by a combination of pattern recognition and price/volume acceleration. Over 233 trading days (since the system is so called "stabilized") and more than 35000 tickers which were picked by TRADY due to their daily/hourly behavior, about 88% of triggered symbols generated a price growth for more than 10 minutes since trigger and more than 75% of triggered symbols generated a daily higher price for more than an hour since the trigger time. Ad by the way, I forgot to point out, TRADY will never pick a symbol which its volume is below 100000 shares at 10 AM, 130000 at 10:30 AM, 200000 shares at 11:00 aM and so on (this is also a configurable parameter). I also forgot to point out that all selections and signals were made at real time on my real money and nit a back simulation or regression. In part C In the next part I will expand about the buying decision and start "talking" about the "holding methodology"'. I will also introduce more information about TRADY project. Your comments and feedback is important and welcomed. Please feel free to comment either through he forum or my direct email TradySupport @ Trady1.Com
I find your results highly suspect... In the context of very efficient markets for liquid stocks. You may be a great programmer... But you seem totally out of your depth... In terms of designing trading systems that will work in the Real World. You should partner will an experienced pro trader... And build something that will actually make a lot of money in the Real World. There is a lot more money to be made trading... Than flogging more software that alledgedly does this or that... When viewed restrospectively.
Dear HoundDogOne Let me tell you about me in few words. I'm a day trader since 2002 (not for living at that time), and does it for living from 2003 end. I work on my research - both mathematical and computerized - since 2003 end and still does. Everything I do is done with my real money and not on paper. My system is operational since 2004 mid. and I'm using it since then (although diff math models are developed all the time) In year 2005 I made about 120% on my above $120K budget (which was leveraged up to $480K daily budget through TDAmeritrade) and this year it seems I'm going to reach the same results, give or take. And just for the record, In year 1998 I established a startup company and raised more than $30M from US and European VC firms, I sold my holdings in the company in about 2003 end and since then I'm dedicated for day trading. I plan to build up together with other investors a fund, based on the results generated by the system. And for that matter a professional feedback from pro traders will be essential. I receive feedback about technology and computers and power but the real feedback I'm looking for will be about the trading decisions made by the system and for that purpose I'm publishing a set of "articles" that will explain the core of it without disclosing the internals. At some point I'm going to allow free access - not for any charge - to the system for a chosen group of pro traders, I'm sure they will be able to explore and appreciate the daily results generated by it. If you are a pro trader that you can join to that group, when door will be opened. And yes, these are the actual results, and I'm sure that you will be the first to admit if you join that club at that time been...Anyway, what do you have to lose ? By the way, from your experience, what is the profit rate made by private pro traders in a year ? Trady 1
Hi, I am just getting started -- I have a good theoretical understanding of economics and a degree in pure mathematics but have very little practicle experience. I am trying to set up a system for automated trading as well - I was wondering which online brokerage would you recommend (what do you use yourself?) to place automatic orders? I would think they would have to have fast and reliable executions and low commissions, and an easy way to place trades automatically - maybe an API? Another question I have is: Which data providers do you use? Being a private investor with quite a limited amount of money, where can I get real-time financial data (and historical data) -- preferably in an easily accessible format - perhaps as a Relational Database? I do have moderate web programming background - a relic from 6 years ago. I know that the above are at their core technical hurdles - but they are highly important and i find it impossible to test my trading algorithms without it. Your help is very much appreciated. - dynamicaxiom
I do > 200 trades/day... and have made about 350,000 trades over 12-13 years... So I am very experienced... and I have a Computer Science degree. I have been building real-time trading systems for > 10 years... And my total code is about 100,000 lines... About 40,000 lines of legacy Pascal code that only crunches number overnite... About 30,000 lines of VB6 code that is all real-time systems... And about another 30,000 equivalent in extensive Excel systems... That act as front end or do very specialized hedge fund accounting. That's 100,000 lines of code. When I was pro programmer 15 years ago... Rough standard for production for corporate application programmer... Was about 50 lines of debugged, documented code/day in production. Let's double that... so average corporate programmer today can do 100 lines of code/day. You are claiming 1,300 lines of code/day... An order of magnitude higher than average software engineer. Why would you need 800,000 lines of code anyway for this? 16 computers to follow a few 100 stocks sounds ludicrous. If you had the kind of financing to you talk about... Why in the world would you be coming to this place? Why do you not even have a web site... If you can churn out 800,000 lines of code in 2+ years??? Any 16 year old can put up a decent web site in days.
I too find the idea of 800K lines of code in 2 years to be not credible. I may have turned out 1300 lines of code in a day on occasion but whether it worked properly is another issue entirely. On the other hand I may have spent a whole day or more tracking down a particularly intractable bug. To do this consistantly with a quality outcome would be near super human. Another sobering thought. Despite the best of intentions with modular design, well designed interfaces and whatever, as the number of lines of code increases, so does the effort required to add more lines, the time to do regression testing and on and on. The largest individual project I have worked on was about 200K lines of fairly complex cross platform C. It took three of us two years and we weren't sitting on our hands.