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This paper investigates the relationship between news sentiment and corporate bond yield spreads, including assymmetry and sentiment-based bond investing.
Tag Archive for: Svetlana Borovkova
In this paper, we investigate the interaction between Refinitiv ESG scores of firms and the performance of corporate bonds issued by these firms. We provide a rather straight-forward analysis of the relationship between ESG scores and corporate bond yields.
Svetlana Borovkova’s column in the Financial Investigator is about climate risk assessment for NGFS and portfolio climate risk.
Svetlana Borovkova’s column in the Financial Investigator is about the ML application of pricing and hedging financial derivatives and reinforcement learning.
Svetlana Borovkova’s column in the Financial Investigator is about machine learning for market risk, neural networks, and the use of autoencoders as proposed by Prof. John Hull.
Svetlana Borovkova’s column in the Financial Investigator is about the value of alternative data, backtesting for assessing the value and returns versus costs.
This white paper addresses the question of the value of alternative data in the investment process with the Refinitiv News Analytics Data.
Svetlana Borovkova’s column about machine learning applications in finance, including banks, derivatives, market risk and quant investing.
At RiskMinds 2021, three important themes were discussed: climate risk, credit risk and market risk. Furthermore, CROs worry about cybersecurity and operational risk.
This EBA discussion paper provides a good and comprehensive overview of the use of machine learning for credit applications.