Backtesting speed
Python is probably even a better agile language than Perl at this point. Its database connectivity is nonesuch, and the RPy interface provides the capabilities to combine both R and Python functionality in a single program. For more information, check out "Poor Man's BI", an article I wrote for the June 2006 DM Review Extended Edition. http://www.dmreview.com/ee/ Steve Miller -----Original Message----- From: r-sig-finance-bounces at stat.math.ethz.ch [mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of eric larson Sent: Wednesday, July 19, 2006 5:07 PM To: R-sig-finance Subject: Re: [R-sig-Finance] Backtesting speed
roger bos wrote:
Yeah reading the link above, I would summarize it as this: If someone is good at/and likes C/C++, you will never be able to convince them that an interpretted language is as good. Most proponents of interpretted
languages
just figure the processor speed and memory improvements will allow them to carry on without using compilers. When I profile my R code, the vast majority of the time is usually in read.table and write.table, so I figure there is not much I can do to improve my code. While using Perl & C & R together could bring some speed imporovement, there is also a downside to learning and maintaining code in different langues and putting all the pieces together. But then again, I work with monthly data, so its not really a concern of mine. Most hedge funds that work with tick data use Perl to process the data and then maybe R to analyze it. Basically, the volume is too great
to
do in R. Of course linking to a database to a nice plus in R, I don't know if Perl can do that.
Actually Perl has excellent database connectivity. The DBA's I work with tend to use Perl more than anything else to write DB maintenance and data transformation tools because the combination of Perl's db connectivity and text manipulation capabilities is very hard to beat. As far as interpreted vs. compiled code the gap is narrowing every day. C doesn't map directly to machine instructions as in the past as CPUs become more sophisticated, and languages like Java are using techniques like run-time optimization that are not available to statically compiled languages. _______________________________________________ R-SIG-Finance at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance