Trading with the momentum transformer: an interpretable deep learning architecture
An attention-based deep learning model for trading is presented
CLICK HERE TO DOWNLOAD THE PDF
Kieran Wood, Sven Giegerich, Stephen Roberts and Stefan Zohren introduce the ‘momentum transformer’, an attention-based deep-learning architecture that outperforms benchmark time series momentum and mean-reversion trading strategies. Unlike state of-the-art long short-term memory architectures, which are sequential in nature and tailored to local processing, an attention mechanism provides our architecture with a direct connection to all previous time steps
Time
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
More on Cutting Edge
Volatility shape-shifters: arbitrage-free shaping of implied volatility surfaces
Manipulating implied volatility surfaces using optimal transport theory has several applications
Georgios Skoufis on RFRs, convexity adjustments and Sabr
Bloomberg quant discusses his new approach for calculating convexity adjustments for RFR swaps
Infrequent MtM reduces neither value-at-risk nor backtesting exceptions
Frequency of repricing impacts volatility and correlation measures
Dynamic margining long/short equity trading strategies
A repo haircut model extends a previous solution for long-only strategies
SABR convexity adjustment for an arithmetic average RFR swap
A model-independent convexity adjustment for interest rate swaps is introduced
Joint S&P 500/VIX smile calibration in discrete and continuous time
An arbitrage-free model for exotic options that captures smiles and futures is presented
The carbon equivalence principle: minimising the cost to carbon net zero
A method to align incentives with sustainability in financial markets is introduced
The cost of mis-specifying price impact
Expected returns can be significantly affected by the wrong use of impact models
Most read
- Top 10 operational risks for 2024
- Japanese megabanks shun internal models as FRTB bites
- LCH issued highest cash call in more than five years