Constraint-directed Search in Computational Finance and Economics Edward Tsang + Centre for Computational Finance and Economic Agents (CCFEA)CCFEA University of Essex

Sunday, 10 January 2016Edward Tsang (Copyright)2 Use The Force  Constraints brought the problem here  They also guide us to solutions  Experts will follow the lead by constraints  E.g. –Constraint propagation, learning no goods –Guided Local Search (GLS) –Guided Genetic Algorithm (GGA) –The Incentive Method (used in financial forecasting and bargaining) forecastingbargaining

Constraints in financial forecasting EDDIE Use constraints to reflect market expectation or risk preference 10 January 2016All Rights Reserved, Edward Tsang

Constraints in Bargaining The Incentive Method Use constraints to focus the search in promising areas 10 January 2016All Rights Reserved, Edward Tsang

Conclusions  Constraints could guide us to solutions  Forecasting: –Repeated patterns were found  Bargaining: –Evolutionary computation provides an alternative approach to approximate subgame equilibrium  In both applications, constraints-directed search is crucial 10 January 2016All Rights Reserved, Edward Tsang

10 January 2016All Rights Reserved, Edward Tsang Centre for Computational Finance and Economic Agents 2010  Computing & Maths  Economics –Interdisciplinary; ~ 57 Master & PhD Students –City links: Olsen Ltd, HSBC, Old Mutual, Ionic Sharescope, etc  CCFEA Qingfu Zhang Optimisation Edward Tsang EDDIE / GP Monaghan Software Sheri Markose Economics Winglon Ng Hi-frequency Richard Olsen Forex Olsen Ltd  EBS Constantinou Banking HSBC John O’Hara Risk Steve Phelps Agents Maria Fasli Agents John Foster Alg. trading Abhinay Muthoo Game Theory Warwick Alex Dupuis Forex Olsen Ltd