Blog Archives

ARMA Models for Trading, Part III

May 2, 2011
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ARMA Models for Trading, Part III

In the last post I showed how to pick the parameters for the ARMA model. The next step is to determine the position at the close. One way to do that is by a one day ahead prediction, if the prediction comes negative (remember the series we are operating on is the daily returns) then

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ARMA Models for Trading, Part II

April 20, 2011
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ARMA Models for Trading, Part II

We left the last post at the point of determining the best ARMA model. Before continuing the discussion, however, I would like to make a few points that might seem a bit questionable or unclear: We model the daily returns instead of the prices. There are multiples reasons: this way financial series usually become stationary,

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ARMA Models for Trading, Part I

April 14, 2011
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ARMA Models for Trading, Part I

Lately I have been testing trading models based on methods from various fields: statistics, machine learning, wavelet analysis and others. And I have been doing all that in R! In this series, I will try to share some of these efforts starting with the well-known from statistics Autoregressive Moving Average Model (ARMA). There is a

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Investing with the Odds

March 2, 2011
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Investing with the Odds

In this previous post, I showed that a look at the correlations in the daily returns of S&P 500 should have lead to a very profitable investing strategy. I also promised to show the results of this strategy in the 80s, but I am not going to do that, because MarketSci has done so in

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Open-sourcing some of my automation code

February 19, 2011
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Open-sourcing some of my automation code

To automate my trading I use a mix of scripts. Everything goes – R, Python, shell, C++, etc. For some time now I have been satisfied with the tools I have created. They run once a day, gather data from EODDATA, update the database, run some R magic to decide what needs to be done

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RSI(2) and the pre 80s Market

February 17, 2011
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RSI(2) and the pre 80s Market

In his detailed research on RSI(2) indicator, MarketSci emphasized several times that the contrarian strategies based on the RSI(2) indicator didn’t start working until the 80s. I remembered this observation recently when I observed another interesting anomaly … In statistics, an important initial step in studying time series data is to consider the auto correlation

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Tools

March 17, 2010
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Tools

All the tools I am using at the moment are free of charge. The one that comes to mind first is R. It’s a language for statistical computing which comes with a decent GUI. R comes with some time series support out of the box, but there are plenty of packages (R extensions are called

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Connecting to a DB2 database from R

January 16, 2010
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Connecting to a DB2 database from R

Unlike RMySQL and RSQLite there is no RDB2. However, I found it pretty straightforward connecting to a DB2 database using the JDBC driver and the RJDBC package. For all this to work, DB2 should be setup to use TCPIP, which is not used by default. You need to set the DB2COMM DB2 environment variable to

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