360 search results for "quantmod"

2013 Summary

January 6, 2014
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2013 was a tough year. Trading was tough, with one of my strategies experiencing a significant drawdown. Research was tough – wasted a lot of time on machine learing techneques, without much to show for it. Also made some expensive mistakes, so all in all – it was a year I’d prefer I had avoided.

Quantitative Finance Applications in R

December 27, 2013
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by Daniel Hanson, QA Data Scientist, Revolution Analytics Extracting Financial Data from Internet Source Using R (first in a series) Earlier this month, a colleague and I attended a presentation on Computational Finance in R, given by Guy Yollin of the University of Washington Applied Mathematics faculty, at a meeting of the Seattle useR Group. The first among several...

Financial Data Accessible from R – part IV

December 13, 2013
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DataMarket is the latest data source of financial data accessible from R I came across. A good tutorial can be found here. I updated the table and the descriptions below. Source R Package Free Access Available on CRAN Provider url Yahoo, FRED, Oanda, Google Quantmod Yes Yes Quantmod Quandl Quandl Yes Yes Quandl TrueFX TFX

December 6, 2013
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Mebane Faber posted another interesting blog post: Building a Simple Sector Rotation on Momentum and Trend that caught my interest. Today I want to show how you can test such strategy using the Systematic Investor Toolbox: Mebane thank you very much for sharing your great ideas. I would encourage readers to play with this strategy

Averaged Input Assumptions and Momentum

December 4, 2013
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Today I want to share another interesting idea contributed by Pierre Chretien. Pierre suggested using Averaged Input Assumptions and Momentum to create reasonably quiet strategy. The averaging techniques are used to avoid over-fitting any particular frequency. To create Averaged Input Assumptions we combine returns over different look-back periods, giving more weight to the recent returns,

Analyzing the DVI Indicator

November 30, 2013
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The DVI indicator is a well-known indicator, created by David Varadi from CSS Analytics. It was introduced in 2009 as a good predictor for the S&P 500 over the past 30 years. Its performance on the S&P 500 has been studied in the blogosphere comprehensively. None of these studies, however, contained everything I was looking

Fast Threshold Clustering Algorithm (FTCA) test

November 27, 2013
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Today I want to share the test and implementation for the Fast Threshold Clustering Algorithm (FTCA) created by David Varadi. This implementation was developed and contributed by Pierre Chretien, I only made minor updates. Let’s first replicate the results from the Fast Threshold Clustering Algorithm (FTCA) post: The clusters are stable and match David’s results

getSymbols Extra

November 25, 2013
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The getSymbols function from the quantmod package is an easy and convenient way to bring historical stock prices into your R environment. You need to specify the list of tickers, the source of historical prices and dates. For example following commands will download historical stock prices from yahoo finance for ‘RWX’, ‘VNQ’, ‘VGSIX’ symbols: Now,

Financial Data Accessible from R – part III

November 8, 2013
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I came across a new source of data which I think is really worth sharing: ThinkNum. It gathers around 2,000 sources of data but more importantly it allows the user to manipulate this data via functions and graphics and there is an R package available on CRAN. Interested readers can find a very good post

Today, I want to explain the commission’s functionality build in to Systematic Investor Toolbox(SIT) “share” back-test. At each re-balance time the capital is allocated given the weight such that For example, if weight is 100% (i.e. fully invested) and capital = $100 and price =$10 then The period return is equal to The total