Sökning: "Mean-variance"
Visar resultat 1 - 5 av 152 uppsatser innehållade ordet Mean-variance.
1. Robust Portfolio Optimization with Correlation Penalties
Master-uppsats, KTH/Matematisk statistikSammanfattning : Robust portfolio optimization models attempt to address the standard optimization method's high sensitivity to noise in the parameter estimates, by taking an investor's uncertainty about the estimates into account when finding an optimal portfolio. In this thesis, we study robust variations of an extension of the mean-variance problem, where an additional term penalizing the portfolio's correlation with an exogenous return sequence is included in the objective. LÄS MER
2. Analysing the Optimal Fund Selection and Allocation Structure of a Fund of Funds
Master-uppsats, KTH/Matematik (Avd.)Sammanfattning : This thesis aims to investigate different types of optimization methods that can be used when optimizing fund of fund portfolios. Moreover, the thesis investigates which funds that should be included and what their respective portfolio weights should be, in order to outperform the Swedish SIX Portfolio Return Index. LÄS MER
3. Portfolio Optimization Problems with Cardinality Constraints
Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : This thesis analyzes the mean variance optimization problem with respect to cardinalityconstraints. The aim of this thesis is to figure out how much of an impact transactionchanges has on the profit and risk of a portfolio. We solve the problem by implementingmixed integer programming (MIP) and solving the problem by using the Gurobi solver. LÄS MER
4. The Impact of Quantum Computing on the Financial Sector : Exploring the Current Performance and Prospects of Quantum Computing for Financial Applications through Mean-Variance Optimization
Master-uppsats, Linköpings universitet/ProduktionsekonomiSammanfattning : Many important tasks in finance often rely on complex and time-consuming computations. The rapid development of quantum technology has raised the question of whether quantum computing can be used to solve these tasks more efficiently than classical computing. LÄS MER
5. Personalized Investment Recommendations Using Recommendation Systems
Magister-uppsats, Lunds universitet/Nationalekonomiska institutionenSammanfattning : This paper presents a Deep Learning-based Hybrid Recommendation System (DLHR) designed specifically for institutional investors with public portfolio holdings on the Stockholm Stock Exchange. The objective is to provide personalized investment recommendations, complement existing portfolios, and explore untapped cross-selling opportunities. LÄS MER