December

I have recently been busy writing my thesis, and now that it has been graded and published I would like to do a short review about the subject. 

The quantitative research was carried out by first introducing concepts of technical analysis and by studying historical price data from a five-year time frame. The price data of the instruments was selected randomly from four different samples of asset classes. These segments included then 18 different derivative instruments. The price charts were then studied form a market technique- based strategy’s viewpoint: The strategy aims to find spots in the market, where movement will appear probably. The periods, through which the prices were studied, were also selected randomly from a 20-year timeframe. These fictitious order executions were obtained by entering the buying and selling signals into a table.  From these prices could then be the instruments behavior describing statistics derived.

 The results of the different instruments can be seen in the following pictures.

 In the first two columns we can see how many bullish, bearish and neutral periods each instrument had. Then we have columns with the signals given by the tested strategy,

Where the yellow highlighted cells represent numbers that are sums and the grey areas averages.

The quantitative results of the research showed that technical analysis can be used to some extent to gain continuously positive returns. As the research showed that instruments behave differently, the measure of profitability depends highly on the perspective from which the results are examined. Altogether, the scope of this study was to investigate, analyze and develop the field of technical analysis. As we can see in the tables, the commodities and index derivatives were clearly the most profitable instruments on average. The presented strategy represents a simple trend detection method that can easily be enhanced by adding terms and conditions.