Quantitative Finance
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# Minimum Correlation Algorithm Example

Today I want to follow up with the Minimum Correlation Algorithm Paper post and show how to incorporate the Minimum Correlation Algorithm into your portfolio construction work flow and also explain why I like the Minimum Correlation Algorithm.
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# Quantitative Finance

News, Slides and various discussions about quant finance
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(This article was first published on Systematic Investor » R, and kindly contributed to R-bloggers) David Varadi has published two excellent posts / ideas about cooking with momentum: VIX-Adjusted Momentum Error-Adjusted Momentum I just...
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## Quantitative Finance applications in R – 8

(This article was first published on Revolutions, and kindly contributed to R-bloggers) The latest in a series by Daniel Hanson Introduction Correlations between holdings in a portfolio are of course a key component in financial risk...
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## Optimizing with R expressions

(This article was first published on Odd Hypothesis, and kindly contributed to R-bloggers) I recently discovered a powerful use for R expression()’s Say you are trying to fit some experimental data to the following nonlinear equation:...
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## magrittr: Simplifying R code with pipes

(This article was first published on Revolutions, and kindly contributed to R-bloggers)
R is a functional language, which means that your code often contains a lot of ( parentheses ).
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## Constructing a Continuous Futures Series From Quandl

(This article was first published on Revolutions, and kindly contributed to R-bloggers)
by Ilya Kipnis
In this post, I will demonstrate how to obtain, stitch together, and clean data for backtesting using futures data from Quandl.
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## IEEE ranks R #9 amongst all languages

(This article was first published on Revolutions, and kindly contributed to R-bloggers) IEEE — the world's largest professional association for the language of technology — recently published its ranking of the popularity of programming...
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## Introducing RcppParallel: Getting R and C++ to work (some more) in parallel

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers) A common theme over the last few decades was that we could afford to simply sit back and let computer (hardware) engineers take care of...
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## Data Preparation – Part I

(This article was first published on Flavio Barros » r-bloggers, and kindly contributed to R-bloggers)
The R language provides tools for modeling and visualization, but is still an excellent tool for handling/preparing data.
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## Forbes on putting R-based analytics in the hands of business analysts

(This article was first published on Revolutions, and kindly contributed to R-bloggers) Forbes has published an article today on the integration between Alteryx and Revolution R Enterprise, which gives business analysts the ability to drag...
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## High resolution graphics with R

(This article was first published on mages' blog, and kindly contributed to R-bloggers)
For most purposes PDF or other vector graphic formats such as windows metafile and SVG work just fine.
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## Beginner's Guide to Quantitative Trading

n this article I'm going to introduce you to some of the basic concepts which accompany an end-to-endquantitative trading system. This post will hopefully serve two audiences. The first will be individuals trying to obtain a job at a fund as a quantitative trader. The second will be individuals who wish to try and set up their own "retail" algorithmic trading business.

Quantitative trading is an extremely sophisticated area of quant finance. It can take a significant amount of time to gain the necessary knowledge to pass an interview or construct your own trading strategies. Not only that but it requires extensive programming expertise, at the very least in a language such as MATLAB, R or Python. However as the trading frequency of the strategy increases, the technological aspects become much more relevant. Thus being familiar with C/C++ will be of paramount importance.

A quantitative trading system consists of four major components:

Strategy Identification - Finding a strategy, exploiting an edge and deciding on trading frequencyStrategy Backtesting - Obtaining data, analysing strategy performance and removing biasesExecution System - Linking to a brokerage, automating the trading and minimising transaction costsRisk Management - Optimal capital allocation, "bet size"/Kelly criterion and trading psychology

We'll begin by taking a look at how to identify a trading strategy.

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## Classification using neural net in r

(This article was first published on Analytics , Education , Campus and beyond, and kindly contributed to R-bloggers)
This is mostly for my students and myself for future reference.
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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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## Thanks to R Markdown: Perhaps Word is an option after all?

(This article was first published on mages' blog, and kindly contributed to R-bloggers)
In many cases Word is still the preferred file format for collaboration in the office.
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## A Hammer Trading System — Demonstrating Custom Indicator-Based Limit Orders in Quantstrat

So several weeks ago, I decided to listen on a webinar (and myself will be giving one on using quantstrat on Sep.
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## R vs MATLAB (Round 3)

(This article was first published on Eran Raviv » R, and kindly contributed to R-bloggers)
At least for me, R by faR. MATLAB has its own way of doing things, which to be honest can probably be defended from many angles.
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## How to update and backup a MySQL database under version control and all within Rstudio

(This article was first published on Bartomeus lab » Rstats, and kindly contributed to R-bloggers) I am trying to have better workflows to ensure data quality and two important things for me are first, scripting as much as posible the data...
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## Shiny cheat sheet

(This article was first published on RStudio Blog, and kindly contributed to R-bloggers)
Shiny v0.10 comes with a quick, handy guide. Use the Shiny cheat sheet as a quick reference for building Shiny apps.
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## Consistent naming conventions in R

(This article was first published on Robin Lovelace - R, and kindly contributed to R-bloggers)
Naming conventions in R are famously anarchic, with no clear winner and multiple conventions in use simultaneously in the same package.
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## Compile R and OpenBLAS from Source Guide

(This article was first published on Lindons Log » R, and kindly contributed to R-bloggers)
This guide is intended to aid any R and Linux user who desires a threaded version of BLAS.
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## Réflexions du soir sur la solvabilité et la mesure des risques...

Les évolutions récentes du dispositif prudentiel européen conduisent à passer d'une logique dans laquelle l'exigence de marge est calculée de manière très forfaitaire, cette simplicité s'accompagnant d'un certain nombre de contraintes imposées par...
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I create supporting pages for two projects I have collaborated with David Varadi in 2013: Proportional Minimum Variance Algorithm Adaptive Shrinkage Method Please check the links to get more info, including supporting blog posts, back-tests, R...
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## R and my divorce from Word

(This article was first published on Ecology in silico, and kindly contributed to R-bloggers)
Being in grad school, I do a lot of scholarly writing that requires associated or embedded R analyses, figures, and tables, plus bibliographies.
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## RProtoBuf & HistogramTools: Statistical Analysis Tools for Large Data Sets

(This article was first published on Google Open Source Blog, and kindly contributed to R-bloggers) At Google, building, managing and safely securing some of the world’s largest storage systems requires complex analysis of filesystem...
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## Tableau adds integration with R

(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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