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Meetup video on Use of R core scripting to eliminate ‘NA’ and other common issue

Meetup video on Use of R core scripting to eliminate ‘NA’ and other common issue

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Use of R core scripting to eliminate ‘NA’ and other common issue

Tuesday, Jun 10, 2014, 6:00 PM

GotoMeeting Webinar online
GotoMeeting Webinar online Toronto, ON

9 Researching Traders Went

Meetup Webinar Tues Jun 10 at 6 PM EST: Use of R core scripting to eliminate ‘NA’ (“and other common recycled value problems”?)Body of presentation: I Use of rm() inside of source codeThis following portion is still under construction as I haven’t gotten as much feedback as would be helpful from core R team yet…II Manually coding a ‘divisor proc…

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Use of R core scripting to eliminate ‘NA’ and other common issue

Tuesday, Jun 10, 2014, 6:00 PM

10 Members Went

Check out this Meetup →

Presentation material:

Manuscript of Intended Presentation:

 

 

The Use of     a<-a[-(i)]   can lead to NA’s

 

Argument is that a<-a[-is.na(a)] would then suffice to clean this up, but what are the costs if, say, a is a resultant vector from a sorting algorithm which recursively shortens the vector?

 

The reality is that removing individual elements by referring to their index can be difficult on data integrity after the remaining indices are then restructured.  Perhaps this is dependent on the cluster or R environment you are loading from.      The reality is that NA’s are a commonly recurring problem in R.

 

Since there are many precompiled functions in R, it seems logical to make use of them.  What isn’t so obvious is the usage of them for non-vector arguments.   For example,  typically rm() is a function which can be used to clean up a directory prior to inputting or after outputting a file from a program.   However, rm() can also be used for the same purposes as a<-a[-(i)], and therefore bypassing the need to subsequently call a<-a[-is.na()] afterwards,  and the risk for loss of data integrity.

 

 

More along the lines of data integrity is the loss of precision in arithmetic operations as you get close to your assigned machine precision.  What then happens is dependent on, again, your own system and which version of R you are utilizing.  Apparently 3.0.0  seems to be set up now with the idea of allowing data to just drop digits as precision is maxed out.     To quote the current developers blog:

The following function is due for release:

 

digitloss=c(“allow”, “warn”, “forbid” )

 

 

C developers can deal with this by implementing their own arithmetic procedures, keeping in mind the underlying algorithm of each.   e.g.   Division can be viewed as the inverse operation of multiplication, which in turn can be viewed as a “convolution” of two floating point integers.

 

So what does this mean..  ?     Maybe for the purposes of speeding up your system and avoiding the abovementioned data loss, converting your division problem to a multiplication by the inverse of your divisor, and then in order to convert your base 10 number to decimal formatting-  either calling strtoll()  or incorporating your own division algorithm.

 

At this point you would be ready to perform the “convolution” portion of  your multiplication formula.   Warning:   convolve() in R (as in C’s numerical recipes) incorporates  the Fourier transform, adding a full      N*logN     to your computational complexity.   So it may be best to code up your own if you think time is of importance.

 

 

 

 

 

Examples of code  demonstrating the above topics can be available upon request.  Thanks for your attendance.

 

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How to use SQL Database for Algo Trading with HFT Potential with SQL Server MYSQL NOSQL MongoDB Redis Cassandra R Java

How to use SQL Database for Algo Trading with HFT Potential with SQL Server MYSQL NOSQL MongoDB Redis Cassandra R Java

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Notes and Video Demos of SQL Database for Algo Trading with HFT Potential with SQL Server MYSQL NOSQL MongoDB Redis Cassandra R Java

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New video of details for a volunteer to help interpret quant analysis trading strategies and model research for potential HFT use

New video of details for a volunteer to help interpret quant analysis trading strategies and model research for potential HFT use

I am keeping a running list of those interested here:

http://quantlabs.net/academy/forum/careers-jobs-forum/any-volunteers-who-want-to-help-out-trading-strategy-performance/

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Q&A on automated historical back testing, cheap tick data help, use of models, and technical vs quant analysis

Q&A on automated historical back testing, cheap tick data help, use of models, and technical vs quant analysis

More questions from Meetup members:

Hey Bryan

 

Would you be kind to point to where I can understand what these models are about,

what they can do and what possible pitfalls with such modeling (especially in these politicized markets)?

 

–> I have a general how to a be a quant as these models are part of this picture

I am unsure of your question on: with such modeling. All I can say 80% of all trades in NYSE are done using algo which are driven by these models

 

Context for asking: My main goal is to become a good discretionary trader and only second to be a quant (for the above reason).

–> technical and funamental trading is becoming old school. I think algos will get the better fills on smaller retail/discretionary traders

But would love to know what quant models can do specifically – if I had a better idea I’d refocus my efforts maybe

–> this is an ongoing process as I am starting with ARIMA followed by GARCH model types

 

Also, I heard you mention about availability of historical tick data.

Where can I find 2-3 years worth of currencies and futures please??

–>http://www.youtube.com/watch?v=Ry7igGVN1uQ&feature=plcp

I have some serious backtesting to do and need to do market replay in NinjaTrader and can find no

affordable data so far back.

–> You can use other automated ways of doing this through other open source trading platforms

 

Please advise

 

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What RDMS or NOSQL Database should a R user focus on? This helps us develop our future integrated trading platform with R analytics.

What RDMS or NOSQL Database should a R user focus on? This helps us develop our future integrated trading platform with R analytics. Thanks for the input.

Which database do R users? Commercial vs open source vs NOSQL?

Go here to take it.

http://quantlabs.net/surveys/2012/06/19/what-rdms-or-nosql-database-should-a-r-user-focus-on/

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