Why risk is hard to measure
April 25, 2015
Regulators and financial institutions increasingly depend on statistical risk forecasting. This column argues that most risk modelling approaches are highly inaccurate and confidence intervals should be provided along with point estimates. Two major approaches, value-at-risk and expected shortfall are compared, and while the former is found to be superior in practice, it is also easier to be manipulated by forecasters.åÊ
Published on VoxEU.org
Models and risk
Bloggs and appendices on artificial intelligence, financial crises, systemic risk, financial risk, models, regulations, financial policy, cryptocurrencies and related topics© All rights reserved, Jon Danielsson,