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Optimizing Portfolios with Higher Moments: Insights from the Nordic Market

Ragnarsson, Anton LU (2025) NEKH03 20242
Department of Economics
Abstract
The traditional assumption of normally distributed returns in portfolio optimization often fails to capture real-world complexities. This thesis investigates how higher moments – skewness and kurtosis – enhance portfolio optimization by addressing these complexities. Using polynomial goal programming and Bayesian shrinkage estimators, the study constructs and evaluates portfolios optimized for higher moments, focusing on Nordic equities and commodities across various rebalancing strategies. Moreover, empirical results indicate that
incorporating skewness and kurtosis significantly improves risk-adjusted returns and tail risk mitigation, as measured by the Sharpe ratio, a higher moment adjusted Sharpe ratio, VaR, and CVaR. These findings... (More)
The traditional assumption of normally distributed returns in portfolio optimization often fails to capture real-world complexities. This thesis investigates how higher moments – skewness and kurtosis – enhance portfolio optimization by addressing these complexities. Using polynomial goal programming and Bayesian shrinkage estimators, the study constructs and evaluates portfolios optimized for higher moments, focusing on Nordic equities and commodities across various rebalancing strategies. Moreover, empirical results indicate that
incorporating skewness and kurtosis significantly improves risk-adjusted returns and tail risk mitigation, as measured by the Sharpe ratio, a higher moment adjusted Sharpe ratio, VaR, and CVaR. These findings provide practical insights for Nordic investors, highlighting the value of higher moments in managing real-world risks and maximizing returns. (Less)
Please use this url to cite or link to this publication:
author
Ragnarsson, Anton LU
supervisor
organization
course
NEKH03 20242
year
type
M2 - Bachelor Degree
subject
keywords
Higher moments, Nordic market, Polynomial goal programming, Portfolio optimization
language
English
id
9184226
date added to LUP
2025-05-16 10:51:37
date last changed
2025-05-16 10:51:37
@misc{9184226,
  abstract     = {{The traditional assumption of normally distributed returns in portfolio optimization often fails to capture real-world complexities. This thesis investigates how higher moments – skewness and kurtosis – enhance portfolio optimization by addressing these complexities. Using polynomial goal programming and Bayesian shrinkage estimators, the study constructs and evaluates portfolios optimized for higher moments, focusing on Nordic equities and commodities across various rebalancing strategies. Moreover, empirical results indicate that 
incorporating skewness and kurtosis significantly improves risk-adjusted returns and tail risk mitigation, as measured by the Sharpe ratio, a higher moment adjusted Sharpe ratio, VaR, and CVaR. These findings provide practical insights for Nordic investors, highlighting the value of higher moments in managing real-world risks and maximizing returns.}},
  author       = {{Ragnarsson, Anton}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Optimizing Portfolios with Higher Moments: Insights from the Nordic Market}},
  year         = {{2025}},
}