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https://doi.org/10.21256/zhaw-24351| Publication type: | Bachelor thesis |
| Title: | A Python integration of practical asset allocation based on modern portfolio theory and its advancements |
| Authors: | Dubach, Philipp |
| Advisors / Reviewers: | Hilber, Norbert |
| DOI: | 10.21256/zhaw-24351 |
| Extent: | 83 |
| Issue Date: | 2021 |
| Publisher / Ed. Institution: | ZHAW Zürcher Hochschule für Angewandte Wissenschaften |
| Publisher / Ed. Institution: | Winterthur |
| Language: | English |
| Subject (DDC): | 005: Computer programming, programs and data 332.6: Investment |
| Abstract: | In 1990, Harry Markowitz was awarded with the Nobel Prize for his work on modern portfolio theory. To this day, the mean-variance framework is the preferred method to pick investments for many retail and institutional investors. Meanwhile, big data and the real-time economy have created new challenges and opportunities in the field of asset allocation. These developments are well documented, and portfolio management firms continuously implement the findings into sophisticated models. Nevertheless, only a few comprehensive software models are available publicly to use, study, or modify. We tackle this issue by engineering practical tools for asset allocation and implementing them in the Python programming language. With its clear syntax, efficient development, and usability, Python provides an ideal framework for this thesis. We turn to convex optimization to formulate specific portfolio optimization problems and incorporate different investment constraints. Even though convex optimization proves to offer a restricted class of optimization problems, its fundamental advantages become apparent throughout this thesis. We consistently examine our problems by solving them analytically or with numerical examples. The focus is to keep the tools simple enough for interested practitioners to understand the underlying theory yet provide adequate numerical solutions. For this reason, we provide code snippets of the accompanying routines as well as valuable visuals to describe the input data and the obtained results. We extend the original mean-variance model by going beyond the first two moments of the return distribution. Particularly we set up optimization problems with more advanced risk measures such as expected shortfall. We show how estimation errors in practical asset allocation can be reduced by combining the sample covariance matrix with a more structured estimator through a process called shrinkage. The effect of the implemented routines becomes apparent in the out-of-sample optimization results. Additionally, we provide a discussion on methods that did not demonstrate the anticipated improved results or did not meet our standard of efficiency and comprehensibility. We find that most optimization problems can be expressed in convex form and therefore be implemented and solved efficiently using available Python modules to create portfolios from real-world data. Finally, we demonstrate how even in an environment with high correlation, achieving a competitive return with a lower expected shortfall and lower excess risk than the given benchmark over multiple periods is possible. We underline this through various studies with historical data from the Swiss equity market. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/24351 |
| License (according to publishing contract): | CC BY-NC-ND 4.0: Attribution - Non commercial - No derivatives 4.0 International |
| Departement: | School of Management and Law |
| Appears in collections: | BSc Betriebsökonomie |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Bachelor_Thesis__Philipp_Dubach.pdf | 1.32 MB | Adobe PDF |  View/Open |
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Dubach, P. (2021). A Python integration of practical asset allocation based on modern portfolio theory and its advancements [Bachelor’s thesis, ZHAW Zürcher Hochschule für Angewandte Wissenschaften]. https://doi.org/10.21256/zhaw-24351
Dubach, P. (2021) A Python integration of practical asset allocation based on modern portfolio theory and its advancements. Bachelor’s thesis. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-24351.
P. Dubach, “A Python integration of practical asset allocation based on modern portfolio theory and its advancements,” Bachelor’s thesis, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, Winterthur, 2021. doi: 10.21256/zhaw-24351.
DUBACH, Philipp, 2021. A Python integration of practical asset allocation based on modern portfolio theory and its advancements. Bachelor’s thesis. Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Dubach, Philipp. 2021. “A Python Integration of Practical Asset Allocation Based on Modern Portfolio Theory and Its Advancements.” Bachelor’s thesis, Winterthur: ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-24351.
Dubach, Philipp. A Python Integration of Practical Asset Allocation Based on Modern Portfolio Theory and Its Advancements. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2021, https://doi.org/10.21256/zhaw-24351.
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