Essays on novel methods and applications of portfolio optimization

Julkaisun otsikon käännös: Essays on novel methods and applications of portfolio optimization

Tutkimustuotos: Doctoral ThesisCollection of Articles

Abstrakti

This dissertation advances the methods and applications of portfolio optimization and consists of two parts. The first part focuses on developing new portfolio optimization methods using drawdown measures. The second part utilizes existing portfolio optimization methods in novel application areas. The first method developed in the dissertation is designed to minimize portfolio drawdown duration, an important criterion institutional investors use. The drawdown duration measure has been discussed in several academic and white papers, but no models that allow for minimizing or controlling drawdown duration in a decision support model are present in the literature. Thus, we cover that research and practice gap and present a new family of portfolio selection models: minimizing maximum drawdown duration, average drawdown duration and tail drawdown duration. The model testing reveals that none of the traditional alternative methods achieve drawdown duration levels close to optimal ones. The second new method, drawdown stochastic dominance, allows for portfolio choice based on comparing random drawdown profiles of investments. Portfolio optimization models exist to minimize drawdown as a single value in the objective function with simplifying assumptions, but no methods account for the whole drawdown distribution. Therefore, we introduce a new variant of the drawdown measure, the corresponding optimization method, and the new dominance rule for portfolio selection in the spirit of second-degree stochastic dominance. Both new methods can readily utilize historical data because they are formulated based on scenarios with discrete returns. The first novel application demonstrates how previously established portfolio optimization models and Monte Carlo simulation methods can be utilized to support portfolio choice in venture capital (VC) markets. The second application study investigates performance enhancements in mixed-asset portfolios (MAPs) by including direct real estate investments (DREIs) in the traditional stock and bond portfolios. Third-degree stochastic dominance (TSD) is applied in the analysis to account for different risk-attitudes. Both DREIs and VC investments may represent an attractive option for investors to diversify risks, but scant studies are available in the literature dedicated to portfolio optimization applications, specifically in these markets.
Julkaisun otsikon käännösEssays on novel methods and applications of portfolio optimization
AlkuperäiskieliEnglanti
PätevyysTohtorintutkinto
Myöntävä instituutio
  • Aalto-yliopisto
Valvoja/neuvonantaja
  • Liesiö, Juuso, Vastuuprofessori
  • Seppälä, Tomi, Ohjaaja
Kustantaja
Painoksen ISBN978-952-64-1359-4
Sähköinen ISBN978-952-64-1360-0
TilaJulkaistu - 2023
OKM-julkaisutyyppiG5 Artikkeliväitöskirja

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