Publications
2022
Technical analysis, spread trading, and data snooping control
Psaradellis, I., Laws, J., Pantelous, A. A., & Sermpinis, G. (2022). Technical analysis, spread trading, and data snooping control. INTERNATIONAL JOURNAL OF FORECASTING, 39(1), 178-191. doi:10.1016/j.ijforecast.2021.10.002
2019
Internal capital market mergers in weak external market environment: An emerging market evidence
Huang, W., Zhang, H., Goyal, A., & Laws, J. (2019). Internal capital market mergers in weak external market environment: An emerging market evidence. International Journal of Finance and Economics, 24(4), 1486-1505. doi:10.1002/ijfe.1739
2018
Performance of technical trading rules: evidence from the crude oil market
Psaradellis, I., Laws, J., Pantelous, A. A., & Sermpinis, G. (2018). Performance of technical trading rules: evidence from the crude oil market. The European Journal of Finance, 25(17), 1793-1815. doi:10.1080/1351847X.2018.1552172
Cross-border exchanges and volatility forecasting
Goyal, A., Kallinterakis, V., Kambouroudis, D., & Laws, J. (2018). Cross-border exchanges and volatility forecasting. QUANTITATIVE FINANCE, 18(5), 789-799. doi:10.1080/14697688.2017.1414512
Special Issue of <i>Quantitative Finance</i> on the ‘23rd Forecasting Financial Markets Conference’
Laws, J., & Sermpinis, G. (2018). Special Issue of <i>Quantitative Finance</i> on the ‘23rd Forecasting Financial Markets Conference’. Quantitative Finance, 18(5), 723-724. doi:10.1080/14697688.2018.1429723
2016
PROFITABILITY OF A SIMPLE PAIRS TRADING STRATEGY: RECENT EVIDENCES FROM A GLOBAL CONTEXT
MIAO, J. I. A., & LAWS, J. (2016). PROFITABILITY OF A SIMPLE PAIRS TRADING STRATEGY: RECENT EVIDENCES FROM A GLOBAL CONTEXT. International Journal of Theoretical and Applied Finance, 19(04), 1650023. doi:10.1142/s0219024916500230
PROFITABILITY OF A SIMPLE PAIRS TRADING STRATEGY: RECENT EVIDENCES FROM A GLOBAL CONTEXT
MIAO, J., & LAWS, J. (2016). PROFITABILITY OF A SIMPLE PAIRS TRADING STRATEGY: RECENT EVIDENCES FROM A GLOBAL CONTEXT. International Journal of Theoretical and Applied Finance, 19(04), 1-18.
Derivatives and Hedge Funds
Satchell, S. (Ed.) (2016). Derivatives and Hedge Funds. In . Palgrave Macmillan UK. doi:10.1057/9781137554178
2015
Modelling commodity value at risk with Psi Sigma neural networks using open–high–low–close data
Sermpinis, G., Laws, J., & Dunis, C. L. (2015). Modelling commodity value at risk with Psi Sigma neural networks using open–high–low–close data. The European Journal of Finance, 21(4), 316-336. doi:10.1080/1351847x.2012.744763
Trading and hedging the corn/ethanol crush spread using time-varying leverage and nonlinear models
Dunis, C. L., Laws, J., Middleton, P. W., & Karathanasopoulos, A. (2015). Trading and hedging the corn/ethanol crush spread using time-varying leverage and nonlinear models. The European Journal of Finance, 21(4), 352-375. doi:10.1080/1351847x.2013.830140
2014
Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms
Karatahansopoulos, A., Sermpinis, G., Laws, J., & Dunis, C. (2014). Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms. Journal of Forecasting, 33(8), 596-610. doi:10.1002/for.2290
Computational Intelligence Techniques for Trading and Investment
Dunis, C., Likothanassis, S., Karathanasopoulos, A., Sermpinis, G., & Theofilatos, K. (Eds.) (n.d.). Computational Intelligence Techniques for Trading and Investment. In . Routledge. doi:10.4324/9780203084984
Derivative products and innovation in Islamic finance
Kiong Kok, S., Giorgioni, G., & Laws, J. (2014). Derivative products and innovation in Islamic finance. International Journal of Islamic and Middle Eastern Finance and Management, 7(3), 242-257. doi:10.1108/imefm-07-2013-0084
2013
NONLINEAR FORECASTING OF THE GOLD MINER SPREAD: AN APPLICATION OF CORRELATION FILTERS
Dunis, C. L., Laws, J., Middleton, P. W., & Karathanasopoulos, A. (2013). NONLINEAR FORECASTING OF THE GOLD MINER SPREAD: AN APPLICATION OF CORRELATION FILTERS. Intelligent Systems in Accounting, Finance and Management, 20(4), 207-231. doi:10.1002/isaf.1345
Investor Sentiment and Forecasting Ability: Evidence from COT Reports in Precious Metal Futures Markets
Zhang, Y., & Laws, J. (2013). Investor Sentiment and Forecasting Ability: Evidence from COT Reports in Precious Metal Futures Markets.
GP algorithm versus hybrid and mixed neural networks
Dunis, C. L., Laws, J., & Karathanasopoulos, A. (2013). GP algorithm versus hybrid and mixed neural networks. The European Journal of Finance, 19(3), 180-205. doi:10.1080/1351847x.2012.679740
Modelling and trading the realised volatility of the FTSE100 futures with higher order neural networks
Sermpinis, G., Laws, J., & Dunis, C. L. (2013). Modelling and trading the realised volatility of the FTSE100 futures with higher order neural networks. The European Journal of Finance, 19(3), 165-179. doi:10.1080/1351847x.2011.606990
2012
Forecasting and trading the EUR/USD exchange rate with stochastic Neural Network combination and time-varying leverage
Sermpinis, G., Dunis, C., Laws, J., & Stasinakis, C. (2012). Forecasting and trading the EUR/USD exchange rate with stochastic Neural Network combination and time-varying leverage. Decision Support Systems, 54(1), 316-329. doi:10.1016/j.dss.2012.05.039
Kalman Filters and Neural Networks in Forecasting and Trading
Sermpinis, G., Dunis, C., Laws, J., & Stasinakis, C. (2012). Kalman Filters and Neural Networks in Forecasting and Trading. In Unknown Conference (pp. 433-442). Springer Berlin Heidelberg. doi:10.1007/978-3-642-32909-8_44
Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks
Sermpinis, G., Laws, J., Karathanasopoulos, A., & Dunis, C. L. (2012). Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks. Expert Systems with Applications, 39(10), 8865-8877. doi:10.1016/j.eswa.2012.02.022
Currency trading in volatile markets: Did neural networks outperform for the EUR/USD during the financial crisis 2007–2009?
Dunis, C. L., Laws, J., & Schilling, U. (2012). Currency trading in volatile markets: Did neural networks outperform for the EUR/USD during the financial crisis 2007–2009?. Journal of Derivatives & Hedge Funds, 18(1), 2-41. doi:10.1057/jdhf.2011.31
Modelling and Trading the Greek Stock Market with Hybrid ARMA-Neural Network Models
Dunis, C. L., Laws, J., & Karathanasopoulos, A. (2012). Modelling and Trading the Greek Stock Market with Hybrid ARMA-Neural Network Models. Unknown Journal, 103-127. doi:10.1007/978-1-4614-3773-4_4
2011
Modelling and trading the Greek stock market with mixed neural network models
Dunis, C. L., Laws, J., & Karathanassopoulos, A. (2011). Modelling and trading the Greek stock market with mixed neural network models. Applied Financial Economics, 21(23), 1793-1808. doi:10.1080/09603107.2011.577008
Cointegration-based optimisation of currency portfolios
Dunis, C. L., Laws, J., & Shone, A. (2011). Cointegration-based optimisation of currency portfolios. Journal of Derivatives & Hedge Funds, 17(2), 86-114. doi:10.1057/jdhf.2011.11
Profitable mean reversion after large price drops: A story of day and night in the S&P 500, 400 MidCap and 600 SmallCap Indices
Dunis, C. L., Laws, J., & Rudy, J. (2011). Profitable mean reversion after large price drops: A story of day and night in the S&P 500, 400 MidCap and 600 SmallCap Indices. Journal of Asset Management, 12(3), 185-202. doi:10.1057/jam.2011.15
Higher order and recurrent neural architectures for trading the EUR/USD exchange rate
Dunis, C. L., Laws, J., & Sermpinis, G. (2011). Higher order and recurrent neural architectures for trading the EUR/USD exchange rate. Quantitative Finance, 11(4), 615-629. doi:10.1080/14697680903386348
Mean Reversion Based on Autocorrelation: A Comparison Using the S&P 100 Constituent Stocks and the 100 Most Liquid ETFs
Dunis, C., Laws, J., & Rudy, J. (2011). Mean Reversion Based on Autocorrelation: A Comparison Using the S&P 100 Constituent Stocks and the 100 Most Liquid ETFs.
2010
Profitable Pair Trading: A Comparison Using the S&P 100 Constituent Stocks and the 100 Most Liquid ETFs
Rudy, J., Dunis, C., & Laws, J. (2010). Profitable Pair Trading: A Comparison Using the S&P 100 Constituent Stocks and the 100 Most Liquid ETFs.
Modelling and trading the EUR/USD exchange rate at the ECB fixing
Dunis, C. L., Laws, J., & Sermpinis, G. (2010). Modelling and trading the EUR/USD exchange rate at the ECB fixing. The European Journal of Finance, 16(6), 541-560. doi:10.1080/13518470903037771
Modelling commodity value at risk with higher order neural networks
Dunis, C. L., Laws, J., & Sermpinis, G. (2010). Modelling commodity value at risk with higher order neural networks. Applied Financial Economics, 20(7), 585-600. doi:10.1080/09603100903459873
Trading and filtering futures spread portfolios: Further applications of threshold and correlation filters
Dunis, C. L., Laws, J., & Evans, B. (2010). Trading and filtering futures spread portfolios: Further applications of threshold and correlation filters. Journal of Derivatives & Hedge Funds, 15(4), 274-287. doi:10.1057/jdhf.2009.24
2009
The robustness of neural networks for modelling and trading the EUR/USD exchange rate at the ECB fixing
Dunis, C. L., Laws, J., & Sermpinis, G. (2009). The robustness of neural networks for modelling and trading the EUR/USD exchange rate at the ECB fixing. Journal of Derivatives & Hedge Funds, 15(3), 186-205. doi:10.1057/jdhf.2009.10
Performance of Shariah-Compliant Indices in London and NY Stock Markets and their potential for diversification
Kok, S., Giorgioni, G., & Laws, J. (2009). Performance of Shariah-Compliant Indices in London and NY Stock Markets and their potential for diversification. International Journal of Monetary Economics and Finance, 2(3/4), 398. doi:10.1504/ijmef.2009.029071
2008
Modelling and Trading the Soybean-Oil Crush Spread with Recurrent and Higher Order Networks
Dunis, C. L., Laws, J., & Evans, B. (2009). Modelling and Trading the Soybean-Oil Crush Spread with Recurrent and Higher Order Networks. In Artificial Higher Order Neural Networks for Economics and Business (pp. 348-366). IGI Global. doi:10.4018/978-1-59904-897-0.ch016
Trading futures spread portfolios: applications of higher order and recurrent networks
Dunis, C. L., Laws, J., & Evans, B. (2008). Trading futures spread portfolios: applications of higher order and recurrent networks. The European Journal of Finance, 14(6), 503-521. doi:10.1080/13518470801890834
2006
Trading futures spreads: an application of correlation and threshold filters
Dunis, C. L., Laws, J., & Evans, B. (2006). Trading futures spreads: an application of correlation and threshold filters. Applied Financial Economics, 16(12), 903-914. doi:10.1080/09603100500426432
Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis
Dunis, C. L., Laws, J., & Evans, B. (2006). Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis. Neural Network World, 16(3), 193-214.
Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis
Dunis, C. L., Laws, J., & Evans, B. (2006). Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: A comparative analysis. Neural Network World, (3), 192-213.
2005
Modelling with recurrent and higher order networks: A comparative analysis
Dunis, C. L., Laws, J., & Evans, B. (2005). Modelling with recurrent and higher order networks: A comparative analysis. Neural Network World, 15(6), 509-523.
Hedging effectiveness of stock index futures
Laws, J., & Thompson, J. (2005). Hedging effectiveness of stock index futures. European Journal of Operational Research, 163(1), 177-191. doi:10.1016/j.ejor.2004.01.007
Modelling and Trading the Gasoline Crack Spread: A Non-Linear Story
Duns, C. L., Laws, J., & Evans, B. (2005). Modelling and Trading the Gasoline Crack Spread: A Non-Linear Story. Derivatives Use Trading and Regulation, 12(1/2), 1-20.
Trading with Higher Order and Recurrent Networks: A Comparative Analysis
Duns, C. L., Laws, J., & Evans, B. (2005). Trading with Higher Order and Recurrent Networks: A Comparative Analysis. Neural Network World, (6), 509-523.
2004
The efficiency of financial futures markets: Tests of prediction accuracy
Laws, J., & Thompson, J. (2004). The efficiency of financial futures markets: Tests of prediction accuracy. European Journal of Operational Research, 155(2), 284-298. doi:10.1016/s0377-2217(03)00087-0
2003
Applied Quantitative Methods for Trading and Investment
Dunis, C. L., Laws, J., & Naïm, P. (Eds.) (2003). Applied Quantitative Methods for Trading and Investment. Wiley. doi:10.1002/0470013265
Portfolio Analysis Using Excel
Laws, J. (2003). Portfolio Analysis Using Excel. In Unknown Book (pp. 293-311). Wiley. doi:10.1002/0470013265.ch9
FX volatility forecasts and the informational content of market data for volatility
Dunis, C., Laws, J., & Chauvin, S. (2003). FX volatility forecasts and the informational content of market data for volatility. The European Journal of Finance, 9(3), 242-272. doi:10.1080/13518470210151100
2000
FX volatility forecasts: A fusion-optimization approach
Dunis, C. L., Laws, J., & Chauvin, S. (2000). FX volatility forecasts: A fusion-optimization approach. Neural Network World, 10(1), 187-202.
1995
Business cycle analysis and forecasting with a structural vector auto regression model for wales
Ioannidis, C., Laws, J., Matthews, K., & Morgan, B. (1995). Business cycle analysis and forecasting with a structural vector auto regression model for wales. Journal of Forecasting, 14(3), 251-265. doi:10.1002/for.3980140308