Realised Volatility Forecasting: Machine Learning via Financial Word Embedding

44 Pages Posted: 29 Jul 2021

See all articles by Eghbal Rahimikia

Eghbal Rahimikia

University of Manchester - Alliance Manchester Business School

Stefan Zohren

University of Oxford - Oxford-Man Institute of Quantitative Finance

Ser-Huang Poon

Alliance Manchester Business School, University of Manchester; Alan Turing Institute

Date Written: July 28, 2021

Abstract

We develop FinText, a novel, state-of-the-art, financial word embedding from Dow Jones Newswires Text News Feed Database. Incorporating this word embedding in a machine learning model produces a substantial increase in volatility forecasting performance on days with volatility jumps for 23 NASDAQ stocks from 27 July 2007 to 18 November 2016. A simple ensemble model, combining our word embedding and another machine learning model that uses limit order book data, provides the best forecasting performance for both normal and jump volatility days. Finally, we use Integrated Gradients and SHAP (SHapley Additive exPlanations) to make the results more 'explainable' and the model comparisons more transparent.

Keywords: Realised Volatility Forecasting; Machine Learning; Natural Language Processing; Word Embedding; Explainable AI; Dow Jones Newswires; Big Data

JEL Classification: C22; C45; C51; C53; C55; C58

Suggested Citation

Rahimikia, Eghbal and Zohren, Stefan and Poon, Ser-Huang, Realised Volatility Forecasting: Machine Learning via Financial Word Embedding (July 28, 2021). Available at SSRN: https://ssrn.com/abstract=3895272 or http://dx.doi.org/10.2139/ssrn.3895272

Eghbal Rahimikia (Contact Author)

University of Manchester - Alliance Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

HOME PAGE: http://www.rahimikia.com

Stefan Zohren

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Ser-Huang Poon

Alliance Manchester Business School, University of Manchester ( email )

Alliance Manchester Business School
Booth Street West
Manchester, Manchester M15 6PB
United Kingdom
+44 161 275 4031 (Phone)
+44 161 275 4023 (Fax)

HOME PAGE: http://www.manchester.ac.uk/research/Ser-huang.poon/

Alan Turing Institute ( email )

British Library, 96 Euston Road
London, NW12DB
United Kingdom

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