This new test is in response to an inquiry concerning the average holding period for trades by my systems. I knew the answer in general terms but had not collected the data in the past and since I was also curious I too wanted a better view of the statistics; I decided to make a new test. I did not want to repeat an old simulation just to get this particular data and since I was designing new enhancements in an effort to keep on improving my methods, the choice was simple: do the new test and collect the data.
The following graph is taken from my latest test on my modified version of the Myst’s XDev script:
What this graph says is that in general, stop losses are taken quite early; in 10 cases within a week’s time and in over 2/3 of the cases in less than 14 weeks. The number of bars held for losing positions decreases exponentially over the tested group with an R-square of 0.96, a pretty close fit. It should be noted that the small group of stocks having been held with losses for the longest time have a high probability of still being in the portfolio and are simply unrealized losses with the potential to maybe, in time, recuperate somewhat.
The unsorted version of the above graph does not show as well the loss concentration in just a few of the stocks or the concentration of very small losses at the other end of the spectrum:
The average number of bars held was 564 for profitable trades with a minimum average of 225 and a maximum of 812 out of the possible 1500 bars. I find this quite reasonable as all the early trades are either stop out will a small lost or are being sold with a profit to finance the acquisition procedures. It’s like a rolling profit window which feeds back cash in the system to acquire more shares. This is why the high number of trades (on average about 2 600 per stock) and at the portfolio level 110 000+ trades over the life of the portfolio (5.83 years). This is also why my trading methods need to be automated and fortunately that is what my scripts are designed to do.
Overall, the performance metrics were very interesting as can be seen below:
One other interesting aspect of this test is that when you sum up all the losses for all the stocks in the portfolio they represent about 2% of total profits generated and a lot of it in still opened positions. Almost as if you are being charged a small fee for doing business. Also, the method has an 88% hit rate which is very impressive. The system traded over 98,000 profitable trades with an average profit of over 6,000 per trade; while the some 13,000 losing trades averaged a loss of about 500 each, a 12:1 profit factor. It might not be an orthodox method, it misbehaves at times, but then I do like the numbers
Created on ... July 16, 2011 © Guy R. Fleury. All rights reserved.