Publikation:

Out-of-Sample Performance of Modern Portfolio Strategies

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Haudek_2-oh87zvw235qb5.pdf
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2023

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Masterarbeit/Diplomarbeit
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This paper evaluates the out-of-sample performance of four modern portfolio strategies, which are the minimum-variance portfolio, the Jorion’s Bayes-Stein minimum-variance portfolio, the 1/N portfolio, and the Equity Market Neutral portfolio implemented by a Convolutional Neural Network. The out-of-sample performance is tested on two time horizons (2010 -2019 and 2010 -2022) on the German stock market using Return, Volatility, Sharpe Ratio, and Drawdown as performance measurements. The empirical results show the minimum-variance portfolio has on average the lowest annual volatility and max drawdown for both time horizons. Whereas the Equity Market Neutral portfolio has the highest average annual return and Sharpe Ratio in both time horizons. However, these results need to be verified in further investigations, for example adding transaction costs to each portfolio strategy, which can result in drastically different performance.

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Fachgebiet (DDC)
330 Wirtschaft

Schlagwörter

Portfolio Optimization, Investment Strategies, Modern Portfolio Theory, Minimum-Variance Portfolio, Bayesian Portfolio Optimization, 1/N Portfolio Strategy, Convolutional Neural Network, Performance Evaluation, DAX Index, Out-of-Sample Testing, Benchmark Comparison, Rolling Window Approach, German Stock Market, Stock Market Analysis, Long-Term Investment, Asset Management

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ISO 690HAUDEK, Marlon, 2023. Out-of-Sample Performance of Modern Portfolio Strategies [Master thesis]. Konstanz: Universität Konstanz
BibTex
@mastersthesis{Haudek2023Outof-67894,
  year={2023},
  title={Out-of-Sample Performance of Modern Portfolio Strategies},
  address={Konstanz},
  school={Universität Konstanz},
  author={Haudek, Marlon}
}
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Konstanz, Universität Konstanz, Masterarbeit/Diplomarbeit, 2023
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