<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/tidyquant-new-tools-for-performing-financial-analysis-within-the-tidy-ecosystem/"></div></div><div></div></div><div></div></div>
<div>
(This article was first published on <strong><a href="http://www.business-science.io/technical-papers/2017/05/11/tidyquant-new-tools-financial-analysis.html"> business-science.io - Articles</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>In advance of upcoming <a target="_blank" rel="nofollow" href="http://www.business-science.io/"><em>Business Science</em></a> talks on <code>tidyquant</code> at R/Finance and EARL San Francisco, we are releasing a technical paper entitled <a target="_blank" rel="nofollow" href="https://github.com/business-science/reports/blob/master/new_financial_tools_tidy_ecosystem.pdf"><strong>“New Tools For Performing Financial Analysis within the ‘Tidy’ Ecosystem”</strong></a>. The technical paper covers an overview of the current R financial package landscape, the independent development of the “tidyverse” data science tools, and the <code>tidyquant</code> package that bridges the gap between the two underlying systems. Several usage cases are discussed. We encourage anyone interested in <strong>financial analysis and financial data science</strong> to check out the technical paper. We will be giving talks related to the paper at <a target="_blank" rel="nofollow" href="http://www.rinfinance.com/"><strong>R/Finance on May 19th in Chicago</strong></a> and <a target="_blank" rel="nofollow" href="https://earlconf.com/sanfrancisco/#speakersAnchor"><strong>EARL on June 7th in San Francisco</strong></a>. If you can’t make it, I encourage you to read the technical paper and to <a target="_blank" rel="nofollow" href="http://www.business-science.io/technical-papers/2017/05/11/tidyquant-new-tools-financial-analysis.html#social">follow us on social media to stay up on the latest <em>Business Science</em> news, events and information</a>.</p>
<h1>Technical Paper Abstract</h1>
<p>Financial analysis and data science in the R programming language have followed separate paths resulting in two important systems: “xts” and “tidyverse”. The advantage of the “xts” system is in the management of time series financial data. The advantage of the “tidyverse” system is in the ability to implement a set of packages that have a uniform structure and data representation to incorporate within the data science workflow. Because of the separation in development, the two systems are difficult to use together limiting the full potential of financial analysis within R. The <code>tidyquant</code> package solves this problem by integrating several of the best financial analysis packages with the “tidy” ecosystem. The integration unlocks the data science workflow, which enables modeling and scaling analyses in a “tidy” way.</p>
<p>Three usage cases are discussed to illustrate the benefits of <code>tidyquant</code>. The first example uses the scaling capabilities to provide an answer for how the financial market values risk versus reward. The second example builds on the first by visualizing the returns over time and illustrating how the <code>purrr</code> package can be used to apply functions to data frames. The third example evaluates methods to scale the performance analysis of multiple portfolios using combinations of weighted asset blends. These examples only scratch the surface of what is possible with <code>tidyquant</code>.</p>
<p><img alt="tidyquant Technical Paper Cover" src="https://i1.wp.com/www.business-science.io/assets/new_tools_report_cover.PNG?w=456" data-recalc-dims="1"></p>
<p><center><a target="_blank" rel="nofollow" href="https://github.com/business-science/reports/blob/master/new_financial_tools_tidy_ecosystem.pdf">Download the technical paper on GitHub!</a></center></p>
<h1>Announcements</h1>
<p>If you’re interested in meeting with the members of <a target="_blank" rel="nofollow" href="http://www.business-science.io/"><em>Business Science</em></a>, we’ll be speaking at the following upcoming conferences:</p>
<ul>
<li><a target="_blank" rel="nofollow" href="http://www.rinfinance.com/">R/Finance: Chicago, May 19-20</a></li>
<li><a target="_blank" rel="nofollow" href="https://earlconf.com/sanfrancisco/">Enterprise Applications of the R Language (EARL): San Francisco, June 5-7</a></li>
</ul>
<h1>Important Links</h1>
<p>If you are interested learning more about <code>tidyquant</code>:</p>
<ul>
<li><a target="_blank" rel="nofollow" href="https://business-science.github.io/tidyquant/">Visit our <code>pkgdown</code> site for detailed documentation</a></li>
<li><a target="_blank" rel="nofollow" href="https://github.com/business-science/">Visit our GitHub site for code updates</a></li>
<li><a target="_blank" rel="nofollow" href="http://www.business-science.io/">Visit our website for news and announcements</a></li>
</ul>
<h1>Follow Us on Social Media <a></a></h1>
<ul>
<li><a target="_blank" rel="nofollow" href="https://twitter.com/bizScienc">@bizScienc</a> is on <a target="_blank" rel="nofollow" href="https://twitter.com/bizScienc">twitter</a> and <a target="_blank" rel="nofollow" href="https://www.linkedin.com/company/business.science">LinkedIn</a>!</li>
<li>Sign up for <a target="_blank" rel="nofollow" href="http://www.business-science.io/">our insights blog</a> to stay updated!</li>
<li>If you like our software, <a target="_blank" rel="nofollow" href="https://github.com/business-science">star our GitHub packages</a> <img alt="🙂" class="wp-smiley" src="https://s.w.org/images/core/emoji/2/72x72/1f642.png"></li>
</ul>
<p>
<div>
<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://www.business-science.io/technical-papers/2017/05/11/tidyquant-new-tools-financial-analysis.html"> business-science.io - Articles</a></strong>.</div>
<hr>
<a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers.com</a> offers <strong><a rel="nofollow" href="https://feedburner.google.com/fb/a/mailverify?uri=RBloggers">daily e-mail updates</a></strong> about <a title="The R Project for Statistical Computing" rel="nofollow" href="https://www.r-project.org/">R</a> news and <a title="R tutorials" rel="nofollow" href="https://www.r-bloggers.com/search/tutorial">tutorials</a> on topics such as: <a title="Data science" rel="nofollow" href="https://www.r-bloggers.com/search/data%20science">Data science</a>, <a title="Big Data" rel="nofollow" href="https://www.r-bloggers.com/search/Big%20Data">Big Data, <a title="R jobs" rel="nofollow" href="https://www.r-users.com/">R jobs</a>, visualization (<a title="ggplot and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/search/ggplot2">ggplot2</a>, <a title="Boxplots using lattice and ggplot2 tutorials" rel="nofollow" href="https://www.r-bloggers.com/search/boxplot">Boxplots</a>, <a title="Maps and gis" rel="nofollow" href="https://www.r-bloggers.com/search/map">maps</a>, <a title="Animation in R" rel="nofollow" href="https://www.r-bloggers.com/search/animation">animation</a>), programming (<a title="RStudio IDE for R" rel="nofollow" href="https://www.r-bloggers.com/search/RStudio">RStudio</a>, <a title="Sweave and literate programming" rel="nofollow" href="https://www.r-bloggers.com/search/sweave">Sweave</a>, <a title="LaTeX in R" rel="nofollow" href="https://www.r-bloggers.com/search/LaTeX">LaTeX</a>, <a title="SQL and databases" rel="nofollow" href="https://www.r-bloggers.com/search/SQL">SQL</a>, <a title="Eclipse IDE for R" rel="nofollow" href="https://www.r-bloggers.com/search/eclipse">Eclipse</a>, <a title="git and github, Version Control System" rel="nofollow" href="https://www.r-bloggers.com/search/git">git</a>, <a title="Large data in R using Hadoop" rel="nofollow" href="https://www.r-bloggers.com/search/hadoop">hadoop</a>, <a title="Web Scraping of google, facebook, yahoo, twitter and more using R" rel="nofollow" href="https://www.r-bloggers.com/search/Web+Scraping">Web Scraping</a>) statistics (<a title="Regressions and ANOVA analysis tutorials" rel="nofollow" href="https://www.r-bloggers.com/search/regression">regression</a>, <a title="principal component analysis tutorial" rel="nofollow" href="https://www.r-bloggers.com/search/PCA">PCA</a>, <a title="Time series" rel="nofollow" href="https://www.r-bloggers.com/search/time+series">time series</a>, <a title="finance trading" rel="nofollow" href="https://www.r-bloggers.com/search/trading">trading</a>) and more...
<img height="1" alt="" width="1" src="http://feeds.feedburner.com/~r/RBloggers/~4/NOhJ4HP6FIs"></a></div>