<story><title>An Introduction to Stock Market Data Analysis with R – Part 1</title><url>https://ntguardian.wordpress.com/2017/03/27/introduction-stock-market-data-r-1/</url></story><parent_chain><item><author>ktta</author><text>I don&amp;#x27;t have much experience with any kind of stock market analysis&amp;#x2F; HFT programming.&lt;p&gt;I&amp;#x27;ve seen people use python (or R) a lot in online tutorials and courses (there&amp;#x27;s one on coursera[1] check it out). It&amp;#x27;s understandable that python is preferred since it&amp;#x27;s an easy language to get started with, but I&amp;#x27;ve never really seen C&amp;#x2F;C++ used by people online (Although I&amp;#x27;ve heard about the use of FPGAs by the hardcore guys)&lt;p&gt;Is the only reason C++ isn&amp;#x27;t recommended because it is difficult? The performance difference seems rather large to me. And especially if you&amp;#x27;re doing lots of number crunching, it would really benefit using C&amp;#x2F;C++ wouldn&amp;#x27;t it?&lt;p&gt;Do people use them but I don&amp;#x27;t hear about them because anyone above &amp;#x27;tutorial level&amp;#x27; doesn&amp;#x27;t share their code or talk about it?&lt;p&gt;Or are the R and Python Computational libraries close to the performance of C&amp;#x2F;C++ that it&amp;#x27;s a viable compromise?&lt;p&gt;[1]: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.coursera.org&amp;#x2F;learn&amp;#x2F;computational-investing&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.coursera.org&amp;#x2F;learn&amp;#x2F;computational-investing&lt;/a&gt;</text></item></parent_chain><comment><author>ryankennedyio</author><text>I don&amp;#x27;t think any retailer can trade on the scale and speed that would require C&amp;#x2F;C++ over Python. With lower capital and significantly higher transaction costs, retail traders (mostly) need to have holding periods for at least hours, so speed isn&amp;#x27;t really an issue. It&amp;#x27;s more about finding longer term anomalies to deploy maybe at most a few dozen positions, as opposed to reacting to billions of quotes over any trading day.&lt;p&gt;I think Python is a great tool for finance, particularly with libraries like Pandas, Numpy, etc. Most of the work in those libraries is C&amp;#x2F;Fortan&amp;#x2F;etc anyway. Great community. For more &amp;#x27;academic&amp;#x27; style work&amp;#x2F;exploration, I think R might have an edge, but I personally find it more difficult to write and maintain high quality code in R.&lt;p&gt;I&amp;#x27;d like to just throw a quick plug in for an open source project I&amp;#x27;m working on [1]. It&amp;#x27;s an event-driven trading library written in Python.  We&amp;#x27;re pretty close to having live trade execution ready in an alpha state.&lt;p&gt;The motivation is that you can put together a pretty simply strategy in ~40 lines of code. The codebase is designed to be pretty flexible &amp;amp; modular.  Mike from &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;quantstart.com&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;quantstart.com&lt;/a&gt; has some great resources &amp;amp; many of his recent articles use the same library.&lt;p&gt;[1]: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;mhallsmoore&amp;#x2F;qstrader&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;github.com&amp;#x2F;mhallsmoore&amp;#x2F;qstrader&lt;/a&gt;</text></comment>
<story><title>An Introduction to Stock Market Data Analysis with R – Part 1</title><url>https://ntguardian.wordpress.com/2017/03/27/introduction-stock-market-data-r-1/</url></story><parent_chain><item><author>ktta</author><text>I don&amp;#x27;t have much experience with any kind of stock market analysis&amp;#x2F; HFT programming.&lt;p&gt;I&amp;#x27;ve seen people use python (or R) a lot in online tutorials and courses (there&amp;#x27;s one on coursera[1] check it out). It&amp;#x27;s understandable that python is preferred since it&amp;#x27;s an easy language to get started with, but I&amp;#x27;ve never really seen C&amp;#x2F;C++ used by people online (Although I&amp;#x27;ve heard about the use of FPGAs by the hardcore guys)&lt;p&gt;Is the only reason C++ isn&amp;#x27;t recommended because it is difficult? The performance difference seems rather large to me. And especially if you&amp;#x27;re doing lots of number crunching, it would really benefit using C&amp;#x2F;C++ wouldn&amp;#x27;t it?&lt;p&gt;Do people use them but I don&amp;#x27;t hear about them because anyone above &amp;#x27;tutorial level&amp;#x27; doesn&amp;#x27;t share their code or talk about it?&lt;p&gt;Or are the R and Python Computational libraries close to the performance of C&amp;#x2F;C++ that it&amp;#x27;s a viable compromise?&lt;p&gt;[1]: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.coursera.org&amp;#x2F;learn&amp;#x2F;computational-investing&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.coursera.org&amp;#x2F;learn&amp;#x2F;computational-investing&lt;/a&gt;</text></item></parent_chain><comment><author>rampage101</author><text>People use Python for finance and time series because of how easy it to read in the data. There is a library called pandas which allows you to read in a txt, csv, or excel file easily and do any type of array manipulation you want. The pandas library is written in C++, so it&amp;#x27;s basically a python wrapper.&lt;p&gt;Conversely I don&amp;#x27;t think C++ has this same type of library for reading in data in a single line.&lt;p&gt;While C++ is faster than Python overall, for most financial simulations Python is definitely fast enough.</text></comment>