Processing time of backtests on a singlecomputer
I mean buy the maximum amount of memory your system allows, install it and see if that helps. Memory is cheap. On the expensive side, most quad core i7 CPU sockets can accept a six core i7 CPU upgrade. These were $1,000 the last time I checked. Frank Chicago, IL _____ From: Jersey Fanatic [mailto:jerseyfanatic1 at gmail.com] Sent: Friday, April 08, 2016 9:28 AM To: Frank Cc: Erol Biceroglu; r-sig-finance; Brian G. Peterson Subject: Re: [R-SIG-Finance] Processing time of backtests on a singlecomputer All info I could find was about setting the swap file size, not enabling Windows to max out memory, or disabling paging before like %90 memory usage. But will research further too see how its done. Thanks. 2016-04-08 16:22 GMT+03:00 Frank <frankm60606 at gmail.com>: Windows can start using the swap file long before 80% memory utilization. If speed is of the essence, you might want to max out the memory on your machine. If that doesn't help, return the memory. Frank Chicago, IL -----Original Message----- From: R-SIG-Finance [mailto:r-sig-finance-bounces at r-project.org] On Behalf Of Jersey Fanatic Sent: Friday, April 08, 2016 12:47 AM To: Erol Biceroglu Cc: r-sig-finance; Brian G. Peterson Subject: Re: [R-SIG-Finance] Processing time of backtests on a singlecomputer RAM is usually at 80% or so, but CPU is maxing out, I guess that means RAM is sufficient? 2016-04-07 23:23 GMT+03:00 Erol Biceroglu <erol.biceroglu at alumni.utoronto.ca
:
Hello, Only thing I can think of that might make it take longer, that affected me in the past, is RAM, especially in Windows. Is it maxing out at all? On Thursday, April 7, 2016, Jersey Fanatic <jerseyfanatic1 at gmail.com> wrote:
So I tried to see what effect trailing stop and stop loss rules have on the processing time. For the same dataset, only SL took 5 mins while only trailing SL took 10 mins, and trailing SL with normal SL took 13 mins. I guess it is processing it as fast as it should be. Thanks for all the help. 2016-04-07 20:45 GMT+03:00 Joshua Ulrich <josh.m.ulrich at gmail.com>:
On Thu, Apr 7, 2016 at 11:30 AM, Jersey Fanatic <jerseyfanatic1 at gmail.com> wrote:
Thanks for the insight. I did not know variations in processing time
of
20
minutes or so could happen between different parameter combinations. I ran the strategy with the same dataset with random parameters
without
Trailing SL, on single core and it took 5.15 minutes. The number of transactions were 7800. The amount of processing time seems too much compared to yours though. 5sec data of 3 years vs M5 data of just 1
year; 20
min vs 5 mins.
Again, the number of observations is not a good predictor of the amount of time it will take. You have 7800 transactions. My shortest (longest) run had 25 (1500) transactions. Seems reasonable to me that a strategy producing nearly 8000 transactions takes about 5 minutes; that's about 25 transactions a second.
2016-04-07 16:32 GMT+03:00 Joshua Ulrich <josh.m.ulrich at gmail.com>:
On Thu, Apr 7, 2016 at 8:10 AM, Jersey Fanatic <
jerseyfanatic1 at gmail.com>
wrote:
10 years of daily data makes about 2500 data points. So
extrapolating
from that to 58000 data points (assuming the relation is linear), it
should
take
Number of data points is not necessarily a good estimator for run
time
even if the strategies are the same. What matters more is the
number
of timestamps/observations that must be evaluated. That includes signals, moving orders, processing fills, etc.
about 12.2 secs for a single run with my dataset. For 144 runs
(total
number of parameter combinations), it should take about 30 mins. However, I
Again, the relationship is not linear. Different parameter combinations will produce differing amounts of signals, order movement, fills, etc. For example, I ran parameter optimization on ~3 years of 5-second data. Some parameter combinations took 1-2 minutes, some took >20 minutes.
ran apply.paramset() this morning (without trailing stops), it
took
4.5
hours. And the code is the one that I sent earlier with Trailing
stop
rules enabled=FALSE'd. Did you run the macd demo code with single core? If you did some parallel processing, did you use doSNOW package or something else? Maybe
that
is
the reason, I am not sure. Would deleting trailing stop rules speed things up, instead of
defining
them but setting enabled=FALSE? 2016-04-07 0:34 GMT+03:00 Brian G. Peterson <brian at braverock.com>:
On Wed, 2016-04-06 at 23:58 +0300, Jersey Fanatic wrote:
I will try running the same code without trailing stops and see
what
effect it has on the processing time. I will report back as soon as it
is
finished.
Running the macd demo code over 10 years of daily data on my
machine
(no trailing stops) takes 0.5262365 secs for a single run.
[[alternative HTML version deleted]]
_______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R
questions
should go.
-- Joshua Ulrich | about.me/joshuaulrich FOSS Trading | www.fosstrading.com R/Finance 2016 | www.rinfinance.com
-- Joshua Ulrich | about.me/joshuaulrich FOSS Trading | www.fosstrading.com R/Finance 2016 | www.rinfinance.com
[[alternative HTML version deleted]]
_______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.
-- Erol Biceroglu
*erol.biceroglu at alumni.utoronto.ca <erol.biceroglu at alumni.utoronto.ca>416-275-7970 <416-275-7970>*
_______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.