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Financial Analysis with HeuristicLab

One application that I've been interested in lately is financial analysis.

Recently I've looked at interest rate swaps in more detail. Interest rate swaps are an important financial instrument for controlling risk, but are also used for speculative purposes. Using the genetic programming capabilities of HeuristicLab it is relatively easy to generate a regression model to estimate the interest rate swap yield. The result for the European 10-year interest rate swap (monthly data) in the time span from April 1991 until August 2011 can be seen in the next figure.

In the last section from index 582 onwards (July 2007 - August 2011) the output of the model (red line) deviates very strongly from the actually observed values.

To get a better idea of the underlying relations found by GP it is interesting to study variable impacts. The most important variables for the 10-year European interest rate swap yield found through the genetic programming runs are:

Most relevant variables Hold out set
US M1, US Mortgage Market Index March 1991 - April 1995
Eurozone Employment qq, US M1, US Corporate Profits April 1995 - May 1999
US Corporate Profits, Eurozone Employment qq, US U Michigan Expectations Prelim. May 1999 - June 2003
US Corporate Profits, Eurozone Employment qq June 2003 - July 2007
US Existing Home Sales July 2007 - August 2008

Interestingly the most important variables differ for different time spans. Only the corporate profits and the number of employed persons in the Euro zone are detected as relevant over a larger time span.

The following table shows the variable impact calculation results for the first fold in greater detail. It can be clearly seen that money supply M1 in the US and the US mortgage market index are used repeatedly in all models. This is a strong indicator that there is a strong correlation of these variables and the interest rate swap yield for the time span from April 1995 until August 2011 which was used as training set for these models. As can be seen in the previous chart the output on the hold out set (March 1991 - April 1995) is relatively accurate.

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