Zidrina Pabarskaite

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We analyze portfolio creation techniques in a high frequency trading domain and randomly changing environments. We aim to create the best risk/reward portfolio based on thousands of profit histories of automated trading robots. We show that the effectiveness of standard portfolio weight calculation rules depends on the dimensionality, N, and the sample(More)
Markowitz's mean-variance portfolio optimisation is not suitable for a large number of assets due to the unacceptably slow quadratic optimisation procedure involved. This is particularly important in systematic/algorithmic/automated trading applications where instead of assets, automated trading systems are used. We propose a much faster heuristic approach(More)
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