Results 11 to 20 of about 139 (68)
, 2023 This paper investigates the optimal selection of portfolios for power utility maximizing investors in a financial market where stock returns depend on a hidden Gaussian mean reverting drift process.
Gabih, Abdelali, Wunderlich, Ralf
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On Adaptive Portfolio Management with Dynamic Black-Litterman Approach
, 2023 This paper presents a novel framework for adaptive portfolio management that combines a dynamic Black-Litterman optimization with the general factor model and Elastic Net regression. This integrated approach allows us to systematically generate investors'
Hsieh, Chung-Han, Li, Chi-Lin
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, 2022 As the COVID-19 pandemic restrictions slow down, employees start to return to their offices. Hence, the discussions on optimal workplaces and issues of diversity and inclusion have peaked.
Bax, Karoline
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Could ChatGPT have earned abnormal returns? A retrospective test from the U.S. stock market [PDF]
This paper attempts to assess the ability of OpenAI’s ChatGPT to provide high-quality recommendations for a casual investor looking to beat the market. Going back to 1985 and instructing the GPT-4 model to restrict its knowledge to only what could have ...
LoGrasso, Marc
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Portfolio diversification with varying investor abilities
, 2023 We introduce new mathematical methods to study the optimal portfolio size of investment portfolios over time, considering investors with varying skill levels. First, we explore the benefit of portfolio diversification on an annual basis for poor, average
James, Nick, Menzies, Max
core +1 more source
Analysis of Optimal Portfolio Management Using Hierarchical Clustering
, 2023 Portfolio optimization is a task that investors use to determine the best allocations for their investments, and fund managers implement computational models to help guide their decisions. While one of the most common portfolio optimization models in the
Panda, Kapil
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Portfolio Selection via Topological Data Analysis
, 2023 Portfolio management is an essential part of investment decision-making. However, traditional methods often fail to deliver reasonable performance.
Kuznetsov, Kristian +3 more
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Regression techniques for portfolio optimisation using MOSEK [PDF]
, 2013 Regression is widely used by practioners across many disciplines. We reformulate the underlying optimisation problem as a second-order conic program providing the flexibility often needed in applications.
Andersen, ED +3 more
core +1 more source
High order universal portfolios
, 2023 The Cover universal portfolio (UP from now on) has many interesting theoretical and numerical properties and was investigated for a long time. Building on it, we explore what happens when we add this UP to the market as a new synthetic asset and ...
Turinici, Gabriel
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Black-Litterman, Bayesian Shrinkage, and Factor Models in Portfolio Selection: You Can Have It All
, 2023 Mean-variance analysis is widely used in portfolio management to identify the best portfolio that makes an optimal trade-off between expected return and volatility.
Chong, Kwong Yu
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