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R to common lisp translator
5 messages · Joshua Ulrich, Andres Susrud, Brian G. Peterson +1 more
Hi Andres,
On Tue, Jan 25, 2011 at 8:16 AM, Andres Susrud <andres.susrud at gmail.com> wrote:
---------- Forwarded message ---------- From: Andres Susrud <andres.susrud at gmail.com> Date: Tue, Jan 25, 2011 at 12:21 AM Subject: Re: [R-SIG-Finance] R to common lisp translator To: Paul Teetor <paulteetor at yahoo.com> Hi, Sorry to be a bit general in my question. But my concern is regarding packages such as ibroker, quantmod, ttr etc. BR Andres
Your question on Nuclear Phynance indicates you're trying to increase calculation speed. http://www.nuclearphynance.com/Show%20Post.aspx?PostIDKey=148722 What bottlenecks are you running into? Nearly all the heavy lifting in quantmod, TTR, xts, etc. is done in C, so moving to LISP probably wouldn't be much faster. Best, -- Joshua Ulrich | FOSS Trading: www.fosstrading.com
On Jan 24, 2011, at 11:34 PM, Paul Teetor <paulteetor at yahoo.com> wrote: Andres, Can you explain the connection between your question and finance? With a question such as this, you may have better luck using the general R-help mailing list. Paul Paul Teetor, Elgin, IL USA <http://quanttrader.info/public>http://quanttrader.info/public ------------------------------ *From:* Andres Susrud <andres.susrud at gmail.com> *To:* <r-sig-finance at stat.math.ethz.ch>r-sig-finance at stat.math.ethz.ch *Sent:* Mon, January 24, 2011 1:39:40 PM *Subject:* [R-SIG-Finance] R to common lisp translator Hi, just a question regarding common lisp translator, anyone know of a stable translator? <http://dan.corlan.net/R_to_common_lisp_translator/> http://dan.corlan.net/R_to_common_lisp_translator/ <http://common-lisp.net/project/rcl/>http://common-lisp.net/project/rcl/ <http://common-lisp.net/project/rclg/>http://common-lisp.net/project/rclg/ I found three sources. Any experience with it? ? ?[[alternative HTML version deleted]]
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On 01/25/2011 10:01 AM, Andres Susrud wrote:
The bottlenecks is when running backtests for larger datasets.I'm also looking at some other functions that are updated for every new timestep.
We run backtests in R on complex indicators on tick data where the indicator updates every tick. These complete backtests, including the path dependent trade generation rules run (for us) in seconds to a few minutes per day of tick data per instrument. All our code is R (mostly) or C/C++ (either implied, like with TTR, or specific to our proprietary indicators).
for(i in 1:length(dataset)){
function(dataset[1:i])}
This is a known performance bottleneck in R, and there is quite a lot of literature about either reworking this to a vectorized formulation, or moving such calculations which *must* be looped to C, Fortran, Java, or C++ (for which good integration options already exist in R).
When generating BM's also for comparisons, I also find the speed in R a bit slow, and that's why I'm looking for the bridge that gives more speed.
R-help would be a better place to see if people are doing Lisp in R in
any repeatable, scalable, manner.
Regards,
- Brian
Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock
One aside that Brian didn't mention is that 'quantstrat' (on R-forge, and discussed heavily on this list) is making serious strides in getting the backtesting times down. Coupled with further xts optimizations we've been making you are able to do many orders of magnitude better than na?ve loops in R. Vectorizing code isn't easy, but it generally means you are running in C at that point. One of the critical issues about 'faster than R' is that you are going to miss 'R'. You could code the fastest implementation in Fortran, but are you "able to" really --- from top to bottom? Fortran is the extreme case, but LISP is pretty close in terms of nowhere near complete. Plus you'll suffer from miserable adoption rates - no offense to the language or its enthusiasts (I am one), but if it hasn't met with success yet... I'm not putting much money or time into it. Use R for prototyping, spool up some more machines to backtest if need be, and if you really need to, write some faster bits in C/C++/Fortran2003 ;-). The idea of xts 'speed at all costs' is to make the bits we all use over and over as fast as possible, and to let the R-based logic have a bit more breathing room. Migrating to another language in search of the holy grail of speed isn't probably the best route at the end of the day. My 2c, Jeff
On Tue, Jan 25, 2011 at 10:09 AM, Brian G. Peterson <brian at braverock.com> wrote:
On 01/25/2011 10:01 AM, Andres Susrud wrote:
The bottlenecks is when running backtests for larger datasets.I'm also looking at some other functions that are updated for every new timestep.
We run backtests in R on complex indicators on tick data where the indicator updates every tick. ?These complete backtests, including the path dependent trade generation rules run (for us) in seconds to a few minutes per day of tick data per instrument. ?All our code is R (mostly) or C/C++ (either implied, like with TTR, or specific to our proprietary indicators).
for(i in 1:length(dataset)){
function(dataset[1:i])}
This is a known performance bottleneck in R, and there is quite a lot of literature about either reworking this to a vectorized formulation, or moving such calculations which *must* be looped to C, Fortran, Java, or C++ (for which good integration options already exist in R).
When generating BM's also for comparisons, I also find the speed in R a bit slow, and that's why I'm looking for the bridge that gives more speed.
R-help would be a better place to see if people are doing Lisp in R in any repeatable, scalable, manner. Regards, ? - Brian -- Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock
_______________________________________________ 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.
Jeffrey Ryan jeffrey.ryan at lemnica.com www.lemnica.com