arrow-right host location public time type
25
Nov 2020

Seminario DIIIO: “Hedging with linear regressions and neural networks”

Santiago y Viña del Mar
Tipo de Evento: Seminario
Organiza: Facultad de Ingeniería y Ciencias
Dónde: Online, vía Zoom
Público: Académicos
Horario: 12:00:00 hr

El propósito del Seminario DIIIO es permitir que investigadores y profesionales de todo el mundo presenten investigaciones de vanguardia en todas las áreas de Investigación de Operaciones, Ingeniería Industrial y Ciencias de la Gestión a una amplia audiencia, incluidos profesores, estudiantes y cualquier persona interesada.

Title: Hedging with linear regressions and neural networks | Johannes Ruf (LSE)

Abstract: We study the use of neural networks as nonparametric estimation tools for the hedging of options. To this end, we design a network, named HedgeNet, that directly outputs a hedging strategy given relevant features as input. This network is trained to minimise the hedging error instead of the pricing error. Applied to end-of-day and tick prices of S&P 500 and Euro Stoxx 50 options, the network is able to reduce the mean squared hedging error of the Black-Scholes benchmark significantly. We illustrate, however, that a similar benefit arises by a simple linear regression model that incorporates the leverage effect. Finally, we argue that outperformance of neural networks previously reported in the literature is most likely due to a lack of data hygiene. In particular, data leakage is sometimes unnecessarily introduced by a faulty training/test data split, possibly along with an additional ‘tagging’ of data. Joint work with Weiguan Wang.

Bio: Johannes Ruf is a full Professor at the London School of Economics (LSE) and a leading academic in mathematical finance. Prior to LSE, he was a Senior Research Fellow at the Oxford-Man Institute of Quantitative Finance and a Senior Lecturer at the University College London (UCL). Johannes was awarded his Ph.D. in Statistics at Columbia University in New York.

Johannes’ research interests include machine learning and portfolio theory. His work received several industry prizes including the ‘Morgan Stanley Prize for Excellence in Financial Markets’ and a Savvy Investor recognition for the ‘Best Factor Investing Papers of 2018.’ Johannes’ research was covered by Risk Magazine. He was a Fulbright scholar and won several teaching prizes at Columbia University and LSE. He coauthored numerous published research articles with practitioners and academics from different fields including Finance, Economics, and Operations Research.

Johannes is also an associated member at the UCL Centre for Blockchain Technologies and an associate editor of Applied Mathematical Finance and Stochastic Models. He served on the Expert Council for the ‘Pilot Project on Environmental Stress Testing – Testing Corporate Loan Portfolios for Drought Scenario,’ launched by the United Nations Environmental Programme. Johannes also served as the director of the MSc programme in Financial Mathematics at LSE.

Contacto: Diego Morán | diego.moran@uai.cl

Actividad vía Zoom

Redes Sociales

Instagram