Χρήστου-Βαρσακέλης, ΔημήτριοςΜπανάτας, ΙωάννηςΔιπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2022.This thesis proposes a stock portfolio optimization method that is simple, scalable, and efficient compared to other proposed strategies from the literature, while significantly outperforming the market. We discuss the survivor bias effect that affects datasets composed of historical information on stock prices and how that can distort results and hinder the proper evaluation of any portfolio optimization strategy. Our approach uses a screening tool to select stocks out of a large pool. The screener’s parameters are optimized on a training dataset. We then construct a portfolio which weights stocks so as to minimize the correlation of the selected stocks. We also incorporate a "trigger" mechanism for identifying downturns in stock prices in a way that informs our trading decisions. Using multiple testing periods of 14, 17 and 20 years, our strategy surpassed the S&P500 index and outperformed many similar studies. Overall, this work shows that a simpler, more fundamental approach can oftentimes perform better than complex models.Submitted by ΙΩΑΝΝΗΣ ΜΠΑΝΑΤΑΣ (aid20007@uom.edu.gr) on 2022-09-04T10:03:55Z No. of bitstreams: 2 license_rdf: 1031 bytes, checksum: 934f4ca17e109e0a05eaeaba504d7ce4 (MD5) BanatasIoannisMsc2022.pdf: 1455482 bytes, checksum: 856a1efdbfe64cfe5a4381215f55f21c (MD5)Approved for entry into archive by Κυριακή Μπαλτά (balta@uom.gr) on 2022-09-05T09:51:39Z (GMT) No. of bitstreams: 2 license_rdf: 1031 bytes, checksum: 934f4ca17e109e0a05eaeaba504d7ce4 (MD5) BanatasIoannisMsc2022.pdf: 1455482 bytes, checksum: 856a1efdbfe64cfe5a4381215f55f21c (MD5)Made available in DSpace on 2022-09-05T09:51:40Z (GMT). No. of bitstreams: 2 license_rdf: 1031 bytes, checksum: 934f4ca17e109e0a05eaeaba504d7ce4 (MD5) BanatasIoannisMsc2022.pdf: 1455482 bytes, checksum: 856a1efdbfe64cfe5a4381215f55f21c (MD5) Previous issue date: 2022-09-04http://dspace.lib.uom.gr/handle/2159/27419Πανεπιστήμιο ΜακεδονίαςΑναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 4.0 Διεθνέςhttp://creativecommons.org/licenses/by-nc-sa/4.0/Stock market simulationOptimizatonSurvivor biasMachine learningScreenerStock portfolioStock marketmarkowitzA simple stock screener framework for portfolio optimizationElectronic Thesis or DissertationText2022-09-05T09:51:40ZΤεχνητή νοημοσύνηArtificial Intelligenceisi - Computer Science, Artificial Intelligence covers resources that focus on research and techniques to create machines that attempt to efficiently reason, problem-solve, use knowledge representation, and perform analysis of contradictory or ambiguous information. This category includes resources on artificial intelligence technologies such as expert systems, fuzzy systems, natural language processing, speech recognition, pattern recognition, computer vision, decision-support systems, knowledge bases, and neural networks.Μεταπτυχιακή εργασίαMaster thesisΠανεπιστήμιο ΜακεδονίαςGreek Aggregator OpenArchives.gr | National Documentation Centre (EKT)