Statistical arbitrage trading with implementation of machine learning : an empirical analysis of pairs trading on the Norwegian stock market

The main objective of this thesis is to analyze whether there are arbitrage opportunities on\nthe Norwegian stock market. Moreover, this thesis examines statistical arbitrage through cointegration\npairs trading. We embed an analytic framework of an algorithmic trading model\nwhich includes principal component analysis and density-based clustering in order to extract\nand cluster common underlying risk factors of stock returns. From the results obtained we\nstatistically prove that pairs trading on the Oslo Stock Exchange Benchmark Index does not\nprovide excess return nor favorable Sharpe ratio. Predictions from our trading model are also\ncompared with an unrestricted model to determine appropriate stock filtering tools, where we\nfind that unsupervised machine learning techniques have properties which are beneficial for\npairs trading.