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  • EQUITY MARKETS PRICING AND CENTRAL BANK INTERVENTIONS: A PANEL DATA APPROACH
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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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EQUITY MARKETS PRICING AND CENTRAL BANK INTERVENTIONS: A PANEL DATA APPROACH

P. 99–99.
Rincon C. J.

This paper analyses the effects of central bank interventions on the pricing of stock market indices. The study confirms that the large-scale purchases of government debt securities in response to the Great Recession and Covid-19 crises by the Fed, influence the pricing of equity markets via its effect on the pricing of treasury bonds. The instrumental variables three-stage model approach is used to determine the impact of the Fed?s balance sheet size on the equity market indices as a measure of its price levels. Under this approach, this study examines the effects of changes in the size of the Fed?s balance sheet in three intervention scenarios: during the 2008-2013, the 2020-2021 periods, and throughout. Moreover, the study compares the results from two statistical strategies: time series and panel data. The results of this study lead to conclude that the 3SLS for time series is recommended over the panel data strategy when analyzing indices that share stocks in common. Use of the 3SLS panel data strategy is left for analyzing the effects of instruments on international indices that do not share stocks in common.

Language: English
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Keywords: instrumental variablesquantitative easingGreat RecessionCOVID-19TaperingFed’s Balance Sheet

In book

World Finance & Banking Symposium, 2022 E-Proceedings
Florida International University, 2022.
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