Explicit formulas for optimal hedging stratergies for European contingent claims

Chellaboina, VijaySekhar; Bhatia, Anil; Bhat, Sanjay P.

doi:10.1109/cifer.2013.6611707

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…and Chellaboina et al (2013) applying both these approaches to hedged option portfolios. The next two topics in this category -volatility modelling, forex forecasting -have elements of similarity with their focus on forecasting asset pricing and volatility.…”

Section: Asset Modelling and Forecasting Topicsmentioning

confidence: 99%

Machine Learning and Finance

Khatib¹

2021

Int J Innov Educ Res

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The aim of this paper is provide a first comprehensive structuring of the literature applying machine learning to finance. We use a probabilistic topic modelling approach to make sense of this diverse body of research spanning across the disciplines of finance, economics, computer sciences, and decision sciences. Through the topic modelling approach, a Latent Dirichlet Allocation Technique (LDA), we can extract the 14 coherent research topics that are the focus of the 6,148 academic articles during the years 1990-2019 analysed. We first describe and structure these topics, and then further show how the topic focus has evolved over the last two decades. Our study thus provides a structured topography for finance researchers seeking to integrate machine learning research approaches in their exploration of finance phenomena. We also showcase the benefits to finance researchers of the method of probabilistic modelling of topics for deep comprehension of a body of literature, especially when that literature has diverse multi-disciplinary actors.

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Section: Asset Modelling and Forecasting Topicsmentioning

confidence: 99%