<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>The Research Kitchen</title>
	<atom:link href="http://www.theresearchkitchen.com/feed" rel="self" type="application/rss+xml" />
	<link>http://www.theresearchkitchen.com</link>
	<description>Rory Winston</description>
	<lastBuildDate>Mon, 28 Jan 2013 11:26:32 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>hourly</sy:updatePeriod>
	<sy:updateFrequency>1</sy:updateFrequency>
	<generator>http://wordpress.org/?v=3.5.1</generator>
		<item>
		<title>Plotting Tick Data with ggplot2</title>
		<link>http://www.theresearchkitchen.com/archives/934</link>
		<comments>http://www.theresearchkitchen.com/archives/934#comments</comments>
		<pubDate>Sun, 20 Jan 2013 10:48:57 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[kdb]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=934</guid>
		<description><![CDATA[Here are some examples of using ggplot2 and kdb+ together to produce some simple graphs of data stored in kdb+. I am using the qserver extension for R (http://code.kx.com/wsvn/code/cookbook_code/r/) to connect to a running kdb+ instance from within R. First, &#8230; <a href="http://www.theresearchkitchen.com/archives/934">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/934/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Rmathlib and kdb+ part 3: Utility Functions</title>
		<link>http://www.theresearchkitchen.com/archives/896</link>
		<comments>http://www.theresearchkitchen.com/archives/896#comments</comments>
		<pubDate>Fri, 11 Jan 2013 07:37:11 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[kdb]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=896</guid>
		<description><![CDATA[In the first two parts of this series, I looked at the basics of the interface I created between rmathlib and kdb+. In this post, I&#8217;ll go through some of the convenience functions I wrote to emulate some basic R &#8230; <a href="http://www.theresearchkitchen.com/archives/896">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/896/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Rmathlib and kdb+, part 2 &#8211; Probability Distribution Functions</title>
		<link>http://www.theresearchkitchen.com/archives/847</link>
		<comments>http://www.theresearchkitchen.com/archives/847#comments</comments>
		<pubDate>Fri, 11 Jan 2013 01:42:46 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[kdb]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=847</guid>
		<description><![CDATA[Following on from the last post on integrating some rmathlib functionality with kdb+, here is a sample walkthrough of how some of the functionality can be used, including some of the R-style wrappers I wrote to emulate some of the &#8230; <a href="http://www.theresearchkitchen.com/archives/847">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/847/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Integrating Rmathlib and kdb+</title>
		<link>http://www.theresearchkitchen.com/archives/835</link>
		<comments>http://www.theresearchkitchen.com/archives/835#comments</comments>
		<pubDate>Tue, 08 Jan 2013 16:28:20 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[kdb]]></category>
		<category><![CDATA[R]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=835</guid>
		<description><![CDATA[The R engine is usable in a variety of ways &#8211; one of the lesser-known features is that it provides a standalone math library that can be linked to from an external application. This library provides some nice functionality such &#8230; <a href="http://www.theresearchkitchen.com/archives/835">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/835/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Exporting Data From R to KDB</title>
		<link>http://www.theresearchkitchen.com/archives/776</link>
		<comments>http://www.theresearchkitchen.com/archives/776#comments</comments>
		<pubDate>Wed, 12 Dec 2012 11:04:39 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[kdb]]></category>
		<category><![CDATA[R]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=776</guid>
		<description><![CDATA[Here is the beginnings of a simple routine to convert R data frames to Q format (in this case a dictionary). It uses the S3 dispatch mechanism to handle the conversion of different data types. Extremely basic (I havent even &#8230; <a href="http://www.theresearchkitchen.com/archives/776">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/776/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Density Estimation of High-Frequency Financial Data</title>
		<link>http://www.theresearchkitchen.com/archives/761</link>
		<comments>http://www.theresearchkitchen.com/archives/761#comments</comments>
		<pubDate>Tue, 12 Jun 2012 12:21:27 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Finance]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=761</guid>
		<description><![CDATA[Frequently we will want to estimate the empirical probability density function of real-world data and compare it to the theoretical density from one or more probability distributions. The following example shows the empirical and theoretical normal density for EUR/USD high-frequency &#8230; <a href="http://www.theresearchkitchen.com/archives/761">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/761/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Binomial Pricing Trees in R</title>
		<link>http://www.theresearchkitchen.com/archives/738</link>
		<comments>http://www.theresearchkitchen.com/archives/738#comments</comments>
		<pubDate>Mon, 11 Jun 2012 07:23:50 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[Finance]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=738</guid>
		<description><![CDATA[Binomial Tree Simulation The binomial model is a discrete grid generation method from \(t=0\) to \(T\). At each point in time (\(t+\Delta t\)) we can move up with probability \(p\) and down with probability \((1-p)\). As the probability of an &#8230; <a href="http://www.theresearchkitchen.com/archives/738">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/738/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Statistical Arbitrage II : Simple FX Arbitrage Models</title>
		<link>http://www.theresearchkitchen.com/archives/710</link>
		<comments>http://www.theresearchkitchen.com/archives/710#comments</comments>
		<pubDate>Sun, 10 Jun 2012 05:14:03 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Finance]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=710</guid>
		<description><![CDATA[In the context of the foreign exchange markets, there are several simple no-arbitrage conditions, which, if violated outside of the boundary conditions imposed by transaction costs, should provide the arbitrageur with a theoretical profit when market conditions converge to theoretical &#8230; <a href="http://www.theresearchkitchen.com/archives/710">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/710/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Quasi-Random Number Generation in R</title>
		<link>http://www.theresearchkitchen.com/archives/700</link>
		<comments>http://www.theresearchkitchen.com/archives/700#comments</comments>
		<pubDate>Tue, 05 Jun 2012 21:41:39 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Coding]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=700</guid>
		<description><![CDATA[Random number generation is a core topic in numerical computer science. There are many efficient algorithms for generating random (strictly speaking, pseudo-random) variates from different probability distributions. The figure below shows a sampling of 1000 two-dimensional random variates from the &#8230; <a href="http://www.theresearchkitchen.com/archives/700">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/700/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>High-Frequency Statistical Arbitrage</title>
		<link>http://www.theresearchkitchen.com/archives/683</link>
		<comments>http://www.theresearchkitchen.com/archives/683#comments</comments>
		<pubDate>Tue, 05 Jun 2012 15:00:44 +0000</pubDate>
		<dc:creator>Administrator</dc:creator>
				<category><![CDATA[Finance]]></category>
		<category><![CDATA[Statistics]]></category>

		<guid isPermaLink="false">http://www.theresearchkitchen.com/?p=683</guid>
		<description><![CDATA[Computational statistical arbitrage systems are now de rigeur, especially for high-frequency, liquid markets (such as FX). Statistical arbitrage can be defined as an extension of riskless arbitrage, and is quantified more precisely as an attempt to exploit small and consistent &#8230; <a href="http://www.theresearchkitchen.com/archives/683">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://www.theresearchkitchen.com/archives/683/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
	</channel>
</rss>
