In this study, we address the ambiguity in portfolio optimization, particularly focusing on the uncertainty related to the statistical parameters governing asset returns. We propose a novel method that combines robust optimization with artificial neural networks (ANNs). Our approach effectively...

This research examines the challenges of issuing green bonds due to a lack of established benchmarks. We compare regional differences between the U.S. and the E.U., hypothesizing that issuers of green bonds stand to benefit from comparing them to conventional (black) bonds. As most investors...

This study examines whether portfolio optimization can be effectively based on annual changes in the harmonized index of consumer prices (HICP) data. Specifically, we assess whether asset allocation based on consumer expenditure can generate superior returns compared to static or equal-weighted...

This study explores an innovative approach to incorporating option strategies into equity portfolios. It presents an alternative direction that institutional investors could take to overcome their current challenges, in a context where traditionally diversified portfolios of only equity and...

Drawdown is an important risk measure in both theory and practice. Most drawdown measures use the running peak as the reference point from which to calculate the drawdown. Instead, the start-to-low drawdown (SLD), which references the start of the period, is firstly proposed as a relevant...

In this paper, we propose a novel optimization model for portfolio selection that integrates the classical mean-variance criterion with a second-order Tsallis entropy term. This approach enables a trade-off between expected return, risk, and diversification, extending Markowitz's theory to...

Portfolio optimization, which is performed while investing in any asset, is an important issue for all investors and finance researchers. In this study, the Artificial Hummingbird Optimization Algorithm (AHA), which has been proposed in recent years, was implemented for portfolio optimization by...

This article combines the traditional definition of portfolio risk with minimum-spanning-tree-based "interconnectedness risk" to improve equal risk contribution portfolio performance. We use betweenness centrality to measure an asset's importance in a market graph (network). After filtering the...

In this paper, we consider the inclusion of the solvency capital requirement (SCR) into portfolio optimization by the use of a quadratic proxy model. The Solvency II directive requires insurance companies to calculate their SCR based on the complete loss distribution for the upcoming year. Since...

The cryptocurrency market offers attractive but risky investment opportunities, characterized by rapid growth, extreme volatility, and uncertainty. Traditional risk management models, which rely on probabilistic assumptions and historical data, often fail to capture the market's unique dynamics...

Recent trends in portfolio management emphasize the importance of reducing carbon footprints and aligning investments with sustainable practices. This paper introduces Sensitivity Value-at-Risk (SensitivityVaR), an advanced distortion risk measure that combines Value-at-Risk (VaR) and Expected...

This study explores an innovative approach to portfolio optimization, bridging traditional Modern Portfolio Theory (MPT) with advanced Machine Learning techniques. We start by recognizing the significance of Markowitz's model in MPT and quickly proceed to focus on the Hierarchical Risk Parity...

Over the last century, the passenger airline industry has undergone a series of transformations, with Lufthansa being a key player not only in Europe, but also worldwide. This case study traces Lufthansa's development, from its origins up until its current status, and outlines its expansion by...

This study addresses market concentration among major corporations, highlighting the utility of relative entropy for understanding diversification strategies. It introduces entropic value at risk (EVaR) as a coherent risk measure, which is an upper bound to the conditional value at risk (CVaR),...

We explore the performance of mixed-frequency predictive regressions for stock returns from the perspective of a Bayesian investor. We develop a constrained parameter learning approach for sequential estimation allowing for belief revisions. Empirically, we find that mixed-frequency models...

Portfolio optimization is a pertinent topic of significant importance in the financial literature. During the portfolio construction, an investor confronts two important steps: portfolio selection and portfolio allocation. This article seeks to investigate portfolio optimization based on the...

This paper investigates the consumption and investment decisions of an individual facing uncertain lifespan and stochastic labor income within a Black-Scholes market framework, A key aspect of our study involves the agent's option to choose when to acquire life insurance for bequest purposes, We...

We explore a multi-asset jump-diffusion pricing model, combining a systemic risk asset with several conditionally independent ordinary assets. Our approach allows for analyzing and modeling a portfolio that integrates high-activity security, such as an exchange trading fund (ETF) tracking a...

We study the effects of low short-term interest rates on the optimal portfolio allocation in Markowitz portfolios and Risk parity portfolios. We propose a measure of Portfolio Instability, gauging the amount of optimal portfolio shifts needed to respond to exogenous shocks to the expected risk...

This paper proposes a new method for financial portfolio optimization based on reducing simultaneous asset shocks across a collection of assets. This may be understood as an alternative approach to risk reduction in a portfolio based on a new mathematical quantity. First, we apply recently...

The present note provides an initial theoretical explanation of the way norm regularizations may provide a means of controlling the non-asymptotic probability of False Dominance classification for empirically optimal portfolios satisfying empirical Stochastic Dominance restrictions in an iid...

We solve an expected utility-maximization problem with a Value-at-risk constraint on the terminal portfolio value in an incomplete financial market due to stochastic volatility. To derive the optimal investment strategy, we use the dynamic programming approach. We demonstrate that the value...

We document that compared to all other investor groups investment funds exhibit a distinctly procyclical behavior when financial-market beliefs about the probability of a euro-related, institutional rare disaster spike. In response to such euro disaster risk shocks, investment funds shed...