Before rushing in analyzing and predicting the Financial Markets (and actually anything else) it is essential that we get an idea about the data at hand. So after data collection (ie getting values of different market indices) i wanted to understand first what is going on to the markets. And a correlation Matrix tells us just that. Let's see what happens on the Greek Stock Exchange :
By looking at the matrix we can immediately see some interesting things :
1) There is a high correlation (=0.847) between DAX index and the Greek stock exchange index (marked as aseStockExchangeIndex)
2) The Insurance index sector (xaaInsurance) and the Media sector (xaaMedia) have a low correlation with the aseStockExchangeIndex. Consider the following scatter chart that shows the poor correlation between Insurance sector stocks and the aseStockExchangeIndex :
Those two facts alone can help significantly in trading: For example if an investor's trading decision is heavily based on aseStockExchangeIndex then the investor should also keep a close look on the DAX Index as opposed to other European indices (such as FTSE,CAC40,etc).
A lot of problems later in the analysis can be prevented if one pays attention to the "Data Understanding" phase. Plus, we also get an insight as to what kind of results should we expect from the learning algorithms.
By looking at the matrix we can immediately see some interesting things :
1) There is a high correlation (=0.847) between DAX index and the Greek stock exchange index (marked as aseStockExchangeIndex)
2) The Insurance index sector (xaaInsurance) and the Media sector (xaaMedia) have a low correlation with the aseStockExchangeIndex. Consider the following scatter chart that shows the poor correlation between Insurance sector stocks and the aseStockExchangeIndex :
Those two facts alone can help significantly in trading: For example if an investor's trading decision is heavily based on aseStockExchangeIndex then the investor should also keep a close look on the DAX Index as opposed to other European indices (such as FTSE,CAC40,etc).
A lot of problems later in the analysis can be prevented if one pays attention to the "Data Understanding" phase. Plus, we also get an insight as to what kind of results should we expect from the learning algorithms.
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