| Forecasting and trading the EUR/USD exchange rate with stochastic Neural Network combination and time-varying leverage G Sermpinis, C Dunis, J Laws, C Stasinakis Decision Support Systems 54 (1), 316-329, 2012 | 117 | 2012 |
| Hedging effectiveness of stock index futures J Laws, J Thompson European Journal of Operational Research 163 (1), 177-191, 2005 | 90 | 2005 |
| Higher order and recurrent neural architectures for trading the EUR/USD exchange rate CL Dunis, J Laws, G Sermpinis Quantitative Finance 11 (4), 615-629, 2011 | 89 | 2011 |
| Statistical arbitrage and high-frequency data with an application to Eurostoxx 50 equities CL Dunis, G Giorgioni, J Laws, J Rudy Liverpool Business School, Working paper, 2010 | 74 | 2010 |
| Performance of Shariah-compliant indices in London and NY stock markets and their potential for diversification S Kok, G Giorgioni, J Laws International Journal of Monetary Economics and Finance 2 (3-4), 398-408, 2009 | 74 | 2009 |
| Forecasting and trading the EUR/USD exchange rate with gene expression and psi sigma neural networks G Sermpinis, J Laws, A Karathanasopoulos, CL Dunis Expert systems with applications 39 (10), 8865-8877, 2012 | 72 | 2012 |
| Modelling and trading the gasoline crack spread: A non-linear story CL Dunis, J Laws, B Evans Derivatives Use, Trading & Regulation 12 (1), 126-145, 2006 | 54 | 2006 |
| Modelling and trading the EUR/USD exchange rate at the ECB fixing CL Dunis, J Laws, G Sermpinis The European Journal of Finance 16 (6), 541-560, 2010 | 50 | 2010 |
| The use of market data and model combination to improve forecast accuracy CL Dunis, J Laws, S Chauvin Developments in forecast combination and portfolio choice, 45-80, 2001 | 49 | 2001 |
| Applied quantitative methods for trading and investment CL Dunis, J Laws, P Na John Wiley & Sons, 2004 | 48 | 2004 |
| Trading futures spreads: An application of correlation and threshold filters CL Dunis, J Laws, B Evans Applied Financial Economics 16 (12), 903-914, 2006 | 43 | 2006 |
| Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: a comparative analysis CL Dunis, J Laws, B Evans Artificial Higher Order Neural Networks for Economics and Business, 348-366, 2009 | 42 | 2009 |
| Trading and hedging the corn/ethanol crush spread using time-varying leverage and nonlinear models CL Dunis, J Laws, PW Middleton, A Karathanasopoulos The European Journal of Finance 21 (4), 352-375, 2015 | 34 | 2015 |
| Trading futures spread portfolios: applications of higher order and recurrent networks CL Dunis, J Laws, B Evans The European Journal of Finance 14 (6), 503-521, 2008 | 34 | 2008 |
| Performance of technical trading rules: evidence from the crude oil market I Psaradellis, J Laws, AA Pantelous, G Sermpinis The European Journal of Finance 25 (17), 1793-1815, 2019 | 29 | 2019 |
| Derivative products and innovation in Islamic finance: A hybrid tool for risk-sharing options S Kiong Kok, G Giorgioni, J Laws International Journal of Islamic and Middle Eastern Finance and Management 7 …, 2014 | 29 | 2014 |
| Modelling and trading the Greek stock market with gene expression and genetic programing algorithms A Karatahansopoulos, G Sermpinis, J Laws, C Dunis Journal of forecasting 33 (8), 596-610, 2014 | 28 | 2014 |
| Modelling commodity value at risk with higher order neural networks CL Dunis, J Laws, G Sermpinis Applied Financial Economics 20 (7), 585-600, 2010 | 24 | 2010 |
| The efficiency of financial futures markets: Tests of prediction accuracy J Laws, J Thompson European Journal of Operational Research 155 (2), 284-298, 2004 | 23 | 2004 |
| Modelling and trading the realised volatility of the FTSE100 futures with higher order neural networks G Sermpinis, J Laws, CL Dunis The European Journal of Finance 19 (3), 165-179, 2013 | 21 | 2013 |
