Quantitative Finance
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Quantitative Finance
News, Slides and various discussions about quant finance
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Tableau adds integration with R

Tableau adds integration with R | Quantitative Finance | Scoop.it
(This article was first published on Revolutions, and kindly contributed to R-bloggers)
Tableau, the popular interactive data visualization tool, is coming out with a new 8.1 update, and it will include integration with the R language.
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Sensitivity analysis for neural networks

Sensitivity analysis for neural networks | Quantitative Finance | Scoop.it
(This article was first published on R is my friend » R, and kindly contributed to R-bloggers) I’ve made quite a few blog posts about neural networks and some of the diagnostic tools that can be used to ‘demystify’ the information contained...
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Financial Data Accessible from R

Financial Data Accessible from R | Quantitative Finance | Scoop.it
(This article was first published on The R Trader » R, and kindly contributed to R-bloggers)
This post lists the sources and types of financial data that is accessible directly from R. I included here free and non free ressources.
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Perform a Function on Each File in R

Perform a Function on Each File in R | Quantitative Finance | Scoop.it
(This article was first published on Mollie's Research Blog, and kindly contributed to R-bloggers)
Sometimes you might have several data files and want to use R to perform the same function across all of them.
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Powerful set of chart functions for R

As mentioned in FOSS Trading post A New plot.xts yesterday

“The Google Summer of Code (2012) project to extend xts has produced a very promising new plot.xts function. Michael Weylandt, the project's student, wrote R-SIG-Finance to request impressions, feedback, and bug reports. The function is housed in the xtsExtrapackage of the xts project on R-Forge.

Please try xtsExtra::plot.xts and let us know what you think. A sample of the eye-candy produced by the code in Michael's email is below. Granted, this isn't a one-liner, but it's certainly impressive! Great work Michael!”

and as announced by author Michael Weylandt in https://stat.ethz.ch/pipermail/r-sig-finance/2012q3/010652.html

“As the community which makes the most heavy use of xts, I would like to draw your attention to a new set of plotting functions for xts objects available as part of Google Summer of Code 2012. This work represents a major overhaul of previously existing plot.xts and should provide you with the most comprehensive and flexible time series plotting available in R. Features include:

"automagic" layout construction and axis alignmentsmart argument recyclingpanel function abilitiesmore attractive candle and bar plots for OHLC objectsscatterplots to view the co-evolution of multiple seriesevent markersregime highlightingtime-oriented barplots via barplot.xts [based on code by Peter Carl]interoperability with all known R time series classes using the xts try/reclass paradigm
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Two presentations on Big Data Big Analytics with R

Two presentations on Big Data Big Analytics with R | Quantitative Finance | Scoop.it
(This article was first published on Revolutions, and kindly contributed to R-bloggers) Last week, Revolution Analytics' US Chief Scientist Mario Inchiosa gave a presentation on high-performance predictive analytics in R and Hadoop, showing...
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Creating publication quality graphs in R

Creating publication quality graphs in R | Quantitative Finance | Scoop.it

This tutorial was developped as part of a one-day workshop held within the Ecosystem Informatics PhD-programme at the Philipps University of Marburg. The contents of this tutorial are published under the creative commons license 'Attribution-ShareAlike CC BY-SA'.

Further information about this PhD programme can be found here

To see what we are usually up to I refer the interested reader to our homepage athttp://www.environmentalinformatics-marburg.de

Another resource for creating visualisations using R, more focussed on climatological/atmospheric applications can be found at http://metvurst.wordpress.com

I hope you find parts of this tutorial, if not all of it useful.

Comments, feedback, suggestions and bug reports should be directed to tim.appelhans {at} staff.uni-marburg.de

In this workshop we will

learn a few things about handling and preparing our data for the creation of meaningful graphsquickly introduce the two main ways of plot creation in R – base graphics and grid graphicsconcentrate on plot production using grid graphicsbecome familiar with the two main packages for highly flexible data visualisation in R – lattice & ggplot2 (biased towards lattice I have to admit)learn how to modify the default options of these packages in order to really get what we wantlearn even more flexibility using the grid package to create visualisations comprising multiple plots on one page and manipulate existing plots to suit our needssee how spatial data can be represented using the spatial packages available in Rlearn how to save our visualisations in different formats that comply with general publication standards of most academic journals

TIP: if you study the code provided in this tutorial closely, you will likely find some additional programming gems here and there which are not specifically introduced in this workshop… (such as the first two lines of code  )

In this workshop it is assumed that you

already know how to get your data into R (read.table() etc)have a basic understanding how particular parts of your data can be assessed ($, [ - in case you do not know what these special characters mean in an R sense, you might want to start at a more basic level, e.g. here)are familiar the notion of object creation/assignment ( <- )

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R vs Python Speed Comparison for Bootstrapping

R vs Python Speed Comparison for Bootstrapping | Quantitative Finance | Scoop.it
(This article was first published on Climate Change Ecology » R, and kindly contributed to R-bloggers)
I’m interested in Python a lot, mostly because it appears to be wickedly fast.
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Fantastic presentations from R using slidify and rCharts

Fantastic presentations from R using slidify and rCharts | Quantitative Finance | Scoop.it
(This article was first published on Data Community DC » R, and kindly contributed to R-bloggers)
Dr.
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Merging Data — SAS, R, and Python

Merging Data — SAS, R, and Python | Quantitative Finance | Scoop.it
(This article was first published on Adventures in Statistical Computing, and kindly contributed to R-bloggers) On analyticbridge, the question was posed about moving an inner join from Excel (which was taking many minutes via VLOOKUP()) to...
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Reproducing R: Scripts, Documents, and Packages

Reproducing R: Scripts, Documents, and Packages | Quantitative Finance | Scoop.it
(This article was first published on Trestle Technology » R, and kindly contributed to R-bloggers) I’m sharing the slides from the talk I’ll be giving at the Dallas R Users Group on creating R packages (and other techniques for reproducing...
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Not only CRAN downloads and Shiny … but also .. rCharts

Not only CRAN downloads and Shiny … but also .. rCharts | Quantitative Finance | Scoop.it
(This article was first published on PremierSoccerStats » R, and kindly contributed to R-bloggers)
I have been meaning for some time to get stuck into the rCharts package which provides
an interface to many Javascript graphic libraries.
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Announcing pqR: A faster version of R

Announcing pqR:  A faster version of R | Quantitative Finance | Scoop.it
(This article was first published on Radford Neal's blog » R Programming, and kindly contributed to R-bloggers)
pqR — a “pretty quick” version of R — is now available to be downloaded, built, and installed on Linux/Unix systems.
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rCharts goes Polar

(This article was first published on Timely Portfolio, and kindly contributed to R-bloggers) The new micropolar library from Chris Viau, author of   gives us reusable charts with polar coordinates for d3.js.  In testament to rCharts design,...
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Parallel Tempering in R with Rmpi

Parallel Tempering in R with Rmpi | Quantitative Finance | Scoop.it
(This article was first published on Lindons Log » R, and kindly contributed to R-bloggers)
My office computer recently got a really nice upgrade and now I have 8 cores on my desktop to play with.
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RStudio v0.98 Preview (Debugging Tools and More)

RStudio v0.98 Preview (Debugging Tools and More) | Quantitative Finance | Scoop.it
(This article was first published on RStudio Blog, and kindly contributed to R-bloggers)
We’re very pleased to announce that a preview release of RStudio IDE v0.98 is available for download now.
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Forecasting with R

Forecasting with R | Quantitative Finance | Scoop.it
(This article was first published on Hyndsight » R, and kindly contributed to R-bloggers)
The following video has been produced to advertise my upcoming course on Forecasting with R, run in partnership with Revolution Analytics.
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A technique for doing parametrized unit testing in R: Case study with stock price data analysis

A technique for doing parametrized unit testing in R: Case study with stock price data analysis | Quantitative Finance | Scoop.it
(This article was first published on Memo's Island, and kindly contributed to R-bloggers) Ensuring the quality and correctness of statistical or scientific software in general constitute as one fo the main responsibilities of scientific...
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Using Google maps API and R

Using Google maps API and R | Quantitative Finance | Scoop.it
(This article was first published on Jose Gonzalez » R, and kindly contributed to R-bloggers)
This post shows how to use Google Maps‘ API with R.
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Calendar-based Sector Strategy

Calendar-based Sector Strategy | Quantitative Finance | Scoop.it
(This article was first published on Systematic Investor » R, and kindly contributed to R-bloggers) I recently came across the Kaeppel’s Sector Seasonality Strategy which is described in Kaeppel’s Corner: Sector Seasonality and updated in...
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Date Formats in R

Date Formats in R | Quantitative Finance | Scoop.it
(This article was first published on Mollie's Research Blog, and kindly contributed to R-bloggers)
Importing DatesDates can be imported from character, numeric, POSIXlt, and POSIXct formats using the as.Date function from the base package.
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Tailor Your Tables with stargazer: New Features for LaTeX and Text Output

Tailor Your Tables with stargazer: New Features for LaTeX and Text Output | Quantitative Finance | Scoop.it
(This article was first published on R-statistics blog » RR-statistics blog, and kindly contributed to R-bloggers) Guest post by Marek Hlavac Since its first introduction on this blog, stargazer, a package for turning R statistical output...
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Learning Time Series with R

Learning Time Series with R | Quantitative Finance | Scoop.it
(This article was first published on Revolutions, and kindly contributed to R-bloggers)
by Joseph Rickert
Late last Saturday afternoon I was reading in my usual spot at the Dana Street Coffee House in Mt.
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Getting started with twitteR in R

Getting started with twitteR in R | Quantitative Finance | Scoop.it
(This article was first published on NERD PROJECT » R project posts, and kindly contributed to R-bloggers) I have asked by a few people lately to help walk them through using twitter API in R, and I’ve always just directed them to the blog post I...
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Parallel computation with helper threads in pqR

Parallel computation with helper threads in pqR | Quantitative Finance | Scoop.it
(This article was first published on Radford Neal's blog » R Programming, and kindly contributed to R-bloggers) One innovative feature of pqR (my new, faster, version of R), is that it can perform some numeric computations in “helper”...
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