the JOIM

Vol. 23, No. 3, 2025 By Christoph Reschenhofer and Josef Zechner This paper demonstrates that portfolio performance can be substantially enhanced by simultaneously utilizing historical factor return volatilities and option-derived market volatilities to optimize factor exposures. The improvements are particularly pronounced in regimes where option-implied market returns exhibit high volatility and right-skewness. Further gains in… Read more

Vol. 23, No. 3, 2025 By Andrew Chin, Che Guan, Promod Rajaguru, Qifeng Sun and Yuning Wu We use large language models (LLMs) and natural language processing (NLP) to extract environmental, social and governance (ESG) insights from real-time news, creating an expert-annotated dataset to evaluate ESG classification, firm relevance, and sentiment. Our fine-tuned models outperform… Read more

Vol. 23, No. 3, 2025 By Gong Cheng, Eric Jondeau and Benoît Mojon We propose a method for creating a sovereign securities portfolio that gradually reduces its carbon footprint, in line with the Paris Agreement. This allows passive investors to achieve netzero (NZ)targets while maintaining risk-adjusted returns similar to a business-as-usual benchmark. From 2015 to… Read more

Vol. 23, No. 3, 2025 By Megan Czasonis, Mark Kritzman and David Turkington Many prediction tasks in economics and finance involve complicated relationships that lie beyond the reach of linear regression analysis. Neural networks can capture these complex dynamics, but they are notoriously opaque and difficult to implement. We show that an alternative model-free prediction… Read more