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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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Colog Asset Pricing, Evidence from Emerging Markets

NRU Higher School of Economics , 2013. No. WP BRP 26/FE/2013.
Dranev Y., Fomkina S.
We introduce a new asset pricing model to account for risk asymmetrically in a very natural way. Assuming asymmetric investor behavior we develop a utility function similar to a quadratic utility but include a colog measure for capturing risk attitude. Asymmetry in investor preferences follows the asymmetric relationships between asset and market returns in equilibrium. Moreover the local version of the model depends on the characteristics of domestic markets, which is reflected in the different relationship between asset and market returns. We test the model in the Russian and South African markets and show that market premium in the Russian market is higher than in the South African market. 
Priority areas: economics
Language: English
Full text
Text on another site
Keywords: asset pricingrisk measurerisk premiumintertemporal preferences
Publication based on the results of:
Research on Corporate Financial Decisions Made by Russian Companies and Companies of Other Emerging Capital Markets during the Global Transformation of Capital Markets and the Establishment of an Innovation Economy (2013)
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