What is the best tool(s) to analyze data progammatically?

[narafa]

I need some advice on the best programming languages to analyze tons of price & volume data. The aim is to run certain programmed algorithms on the data and gather outputs in a proper format (csv would do).

I am comparing R, Python and VBA (Because it can easily work with data in excel directly).

Any advice on pros and cons of those (among others) from a practical perspective?

The objective is as mentioned, to run algorithms on large amounts of price & volume data which look for certain conditions/patterns and produce me with proper format output. This cycle can literally run hundreds of times with multiple tweaks to the algorithms.

I have to say that this is NOT a backtesting exercise, so all the well known backtesting software packages are ruled out (Metastock, NinjaTrader, eSignal, AmiBroker, etc...). I need a programming tool for larger flexibility.

Thoughts & inputs are appreciated

 

[Girija]

Whichever one you know better. Among the three Python will have more open source libs for reference.

 

[Atikon]

I need some advice on the best programming languages to analyze tons of price & volume data. The aim is to run certain programmed algorithms on the data and gather outputs in a proper format (csv would do).

I am comparing R, Python and VBA (Because it can easily work with data in excel directly).

Any advice on pros and cons of those (among others) from a practical perspective?

The objective is as mentioned, to run algorithms on large amounts of price & volume data which look for certain conditions/patterns and produce me with proper format output. This cycle can literally run hundreds of times with multiple tweaks to the algorithms.

I have to say that this is NOT a backtesting exercise, so all the well known backtesting software packages are ruled out (Metastock, NinjaTrader, eSignal, AmiBroker, etc...). I need a programming tool for larger flexibility.

Thoughts & inputs are appreciated

R is used widely in the Finance Industry. If you want to market your skill some day, I would go with R

 

[gaussian]

I need some advice on the best programming languages to analyze tons of price & volume data. The aim is to run certain programmed algorithms on the data and gather outputs in a proper format (csv would do).

I am comparing R, Python and VBA (Because it can easily work with data in excel directly).

Any advice on pros and cons of those (among others) from a practical perspective?

The objective is as mentioned, to run algorithms on large amounts of price & volume data which look for certain conditions/patterns and produce me with proper format output. This cycle can literally run hundreds of times with multiple tweaks to the algorithms.

I have to say that this is NOT a backtesting exercise, so all the well known backtesting software packages are ruled out (Metastock, NinjaTrader, eSignal, AmiBroker, etc...). I need a programming tool for larger flexibility.

Thoughts & inputs are appreciated

The one you can use most effectively.

 

[trader99]

Both R and Python are good tools for data analyses, analytics, machine learning, and modeling.

 

[MarvelousMarvinH]

To me, it is ultimately that Pandas has surpassed R dataframes by quite a bit.
The reason to still use R is all the statistical knowledge of CRAN
https://cran.r-project.org/web/packages/available_packages_by_name.html
It is an insane resource.

 

[narafa]

To me, it is ultimately that Pandas has surpassed R dataframes by quite a bit.
The reason to still use R is all the statistical knowledge of CRAN
https://cran.r-project.org/web/packages/available_packages_by_name.html
It is an insane resource.

Thanks for your feedback, appreciated.

 

[xappppp]

R is quick, easy and powerful in terms of pure statistical analysis, but the thought process is pretty linear. Python is a safe bet if your analytic tool tend to grow into a system and being complicated.

 

[Atikon]

R is quick, easy and powerful in terms of pure statistical analysis, but the thought process is pretty linear. Python is a safe bet if your analytic tool tend to grow into a system and being complicated.

How do you mean that? Machine Learning is available in R, and that surely isn't linear

 

[xappppp]

what I mean the analytic thought flow. If your analysis is just take 10 steps in sequential order, and running stats package I think R is sufficient and quick.

Lets say if your analytics becoming ver complex and you want to make them your own tool box or even a package, I think R is kinda limited in that way. Python seems have more potential to expand.