HKU ELEC7082 Artificial Intelligence in Finance, 2022-23
Notes:
- No single source covers the whole module. The field is developing very fast. Following are useful material.
- Not all of the material below will be included in the syllabus; they are included because they are relevant to the subject.
- Attending the lectures is the quickest way to learn the subject.
Introductory text:
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This book covers some of the topics in this module, but misses all the technical contents:
Tsang, E.P.K.,
AI for Finance, CRC Press, June 2023
Core Material:
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On Rationality:
Tsang, E.P.K.,
Computational intelligence determines effective rationality,
International Journal on Automation and Control, Vol.5, No.1, January 2008, 63-66
(pdf)
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On Computation in finance:
Tsang, E.P.K., Computation in finance: potentials and limitations,
Working Paper WP047-10,
Centre for Computational Finance and Economic Agents (CCFEA),
University of Essex, November 2010
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Book on Directional Change:
J. Chen & E.P.K.Tsang,
Detecting Regime Change in Computational Finance, Data Science, Machine Learning and Algorithmic Trading,
CRC Press, 2021
- Why Directional Change is better than time series for handling tick-to-tick data:
E.P.K.Tsang,
Directional change for handling tick-to-tick data,
Journal of Chinese Economic and Business Studies, 2021
(DOI: 10.1080/14765284.2021.1989883)
(early version)
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Nowcasting directional change:
E.P.K.Tsang, S. Ma & V.L. Raju Chinthalapati,
Nowcasting directional change in high frequency FX markets,
Intelligent Systems in Accounting, Finance and Management, Wiley, March 2024
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Portfolio optimisation:
Modern Portfolio Theory, Wikipedia
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Forecasting:
Tsang, E.P.K. & Li, J.,
EDDIE for financial forecasting,
in S-H. Chen (ed.),
Genetic Algorithms and Programming in Computational Finance,
Kluwer Series in Computational Finance, 2002, Chapter 7, 161-174 (pdf)
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Bargaining:
Jin, N. & Tsang, E.P.K.,
Bargaining strategies designed by evolutionary algorithms,
Applied Soft Computing, Vol. 11, Issue 8, December 2011, 4701-4712
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Agent-based modelling application:
B. Alexandrova-Kabadjova, E.P.K. Tsang & Krause, A,
Market structure and information in payment card markets,
International Journal of Automation and Control (IJAC), Vol.8, No.3, 2011, 364-370
Specialized computational techniques:
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Major discovery in Directional Change:
Glattfelder, J.B., Dupuis, A. & Olsen, R. Patterns in high-frequency FX data: discovery of 12 empirical scaling laws, Quantitative Finance, Volume 11 (4), 2011, 599-614
(pdf / early version)
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GP in machine learning:
Jin, N., Tsang, E. & Li, J.,
A constraint-guided method with evolutionary algorithms for economic problems,
Applied Soft Computing, Vol.9, Iss.3, June 2009, 924-935
(mirror)
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PBIL (Population-based incremental learning):
Baluja, S.,
Population-Based Incremental Learning:
A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning,
Technical Report CMU-CS-94-163,
School of Computer Science, Carnegie Mellon University, 1994
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GPBIL (Generalised population-based incremental learning):
Kern, M.,
Parameter Adaptation in heuristic search - a population-based approach,
PhD Thesis, University of Essex, 2005
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Artificial market:
Martinez-Jaramillo, S. & Tsang, E.P.K.,
An heterogeneous, endogenous and co-evolutionary GP-based financial market,
IEEE Transactions on Evolutionary Computation, Vol.13, No.1, 2009, 33-55 (early version)
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Discovering stylized facts:
S. Masry, A. Dupuis, R.B.Olsen & E.P.K. Tsang,
Time Zone Normalisation of FX Seasonality,
Quantitative Finance, Vol.13, No.7, 2013, 1115-1123
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Market analysis in Directional Change:
Tsang, E.P.K., Tao, R., Serguieva, A. & Ma, S.,
Profiling High-Frequency Equity Price Movements in Directional Changes,
Quantitative Finance, Vol.17, Issue 2, 2017, 217-225
(early version)
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Alpha Engine: trading with DC properties:
Golub, Anton and Glattfelder, James and Olsen, Richard B.,
The Alpha Engine: Designing an Automated Trading Algorithm, High Performance Computing in Finance, Chapman & Hall/CRC Series in Mathematical Finance, April 2017
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DC properties in Chinese market:
J. Ma, X. Xiong, F. He & W Zhang,
Volatility measurement with directional change in Chinese stock market: Statistical property and investment strategy,
Physica A: Statistical Mechanics and its Applications, 2017, vol. 471, issue C, 169-180
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On AlphaGo (great success in machine learning):
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel & Demis Hassabis,
Mastering the game of Go without human knowledge,
Nature 550, 19 October 2017, 354-359
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On AlphaGo (great success in machine learning):
David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel & Demis Hassabis,
Mastering the game of Go with deep neural networks and tree search,
Nature 529, 2016, 484-489
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Forecasting:
Tsang, E.P.K., Yung, P. & Li, J., EDDIE-Automation, a decision support tool for financial forecasting, Journal of Decision Support Systems, Special Issue on Data Mining for Financial Decision Making, Vol.37, No.4, 2004, 559-565
(pdf)
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Forecasting:
Tsang, E.P.K., Markose, S. & Er, H., Chance discovery in stock index option and future arbitrage, New Mathematics and Natural Computation, World Scientific, Vo.1, No.3, 2005, 435-447
(pdf)
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Forecasting:
Tsang, E.P.K., Forecasting -- where computational intelligence meets the stock market,
Frontiers of Computer Science in China, Springer, 2009, 53-63
(mirror)
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Modelling:
Tsang, E.P.K., Olsen, R. & Masry, S.
A Formalization of Double Auction Market Dynamics,
Quantitative Finance, Vol.13, Iss.7, July 2013, 981-988
WP038-10,
Centre for Computational Finance and Economic Agents (CCFEA),
University of Essex, October 2012)
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On multi-objective optimization:
[Li 2021]
Li, K., Decomposition Multi-Objective Evolutionary Optimization: From State-of-the-Art to Future Opportunities, 2021, https://arxiv.org/abs/2108.09588
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On multi-objective optimization:
[Zhang & Li 2007]
Q. Zhang and H. Li, MOEA/D: A Multi-objective Evolutionary Algorithm Based on Decomposition, IEEE Transactions on Evolutionary Computation, vol.11, no. 6, 2007, 712-731
General references:
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On portfolio optimisation:
Modern Portfolio Theory, Wikipedia
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On portfolio optimisation:
Zhang, Q., Li, H., Maringer, D. & Tsang, E.P.K.,
MOEA/D with NBI-style Tchebycheff approach for Portfolio Management,
Proceedings, Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010, 3008-3015
(IEEE Explore)
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On portfolio optimisation:
Alentorn, A., Moraglio, A. & Johnson, C.,
Heuristic Portfolio Optimisation for a Hedge Fund Strategy using the Geometric Nelder-Mead Algorithm,
UK Workshop on Computational Intelligence, Colchester, UK, 8-10 September 2010
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Application to central banking policies:
B. Alexandrova-Kabadjova, S. Martinez-Jaramillo, A. L. Garcia-Almanza & E. Tsang (ed.),
Simulation in Computational Finance and Economics: Tools and Emerging Applications,
IGI Global, 2012
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Computational Finance: Brabazon, A. & O'Neill, M.,
Biologically inspired algorithms for Financial Modelling, Springer-Verlag 2006
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On high-frequency finance:
Dacorogna, M.M., Gencay, R., Muller, U., Olsen, R.B. & Pictet, O.V.,
An introduction to high-frequency finance, Academic Press 2001
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New results on high-frequency finance:
Bisig, T., Dupuis, A., Impagliazzo, V & Olsen, R.B., The scale of market quakes,
Quantitative Finance Vol.12, No.4, 2012, 501-508
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Betting as trading:
Butler, J.,
Betfair Trading Techniques: Trading Models, Money Management, Machine Learning & Algo-Trading,
CreateSpace Independent Publishing Platform, 2016
(ISBN-10: 1514286629; ISBN-13: 978-1514286623)
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Forecasting application: Garcia Almanza, A.L., Martinez Jaramillo, S., Alexandrova-Kabadjova, B. & Tsang, E.P.K.,
Using genetic programming systems as early warning to prevent bank failure, Chapter 14, in Yap, A.Y.
(ed.), Information systems for global financial markets, IGI Global, 2012, 369-382
- Agent-based Economics:
The economy needs agent-based modelling
J.D.Farmer & D.Foley, Nature, Vol.460, 6 August 2009 (cache)
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On agent technology:
M.Fasli, Agent technology for e-commerce, John Wiley and Sons, 2007
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On evaluating trading strategy:
Jorge M. Faleiro Jr & Edward P.K. Tsang,
Black Magic Investigation Made Simple: Monte Carlo Simulations and Historical Back Testing of Momentum Cross-Over Strategies Using FRACTI Patterns,
Working paper WP078-16, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, November 2016
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On artificial intelligence:
Russell, S. & Norvig, P., Artificial Intelligence, A Modern Approach, Prentice Hall, Third Edition, 2011
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On constraint satisfaction:
Tsang, E.P.K., Foundations of constraint satisfaction, Academic Press, London, 1993
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Application of EDDIE:
Kampouridis, M., Computational Intelligence in Financial Forecasting and Agent-Based Modeling: Applications of Genetic Programming and Self-Organizing Maps,
PhD Thesis, University of Essex, 2011
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Application of EDDIE:
M. Kampouridis, S-H. Chen & E.P.K. Tsang, Microstructure dynamics and agent-based financial markets: can dinosaurs return? Advances in Complex Systems, Vol.15, No.5, 2012
(early version)
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Application of EDDIE:
M. Kampouridis, S-H. Chen & E.P.K. Tsang,
Market fraction hypothesis: a proposed test,
International Review of Financial Analysis, Vol.23, 2012, 41-54
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On heuristic search:
Gendreau, M. & Potvin, J-Y. (ed.),
Handbook of Metaheuristics, Springer-Verlag, 2011
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On machine learning: Mitchell, T.,
Machine Learning, McGraw Hill, 1997
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On machine learning and optimization: Battiti, R. & Brunato, M.,
The LION Way, LIONlab, University of Trento, 2014
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On machine learning with Neural Network: Bishop, C.,
Pattern Recognition and Machine Learning, Springer-Verlag 2007
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On portfolio optimization: Maringer, D.,
Portfolio management with heuristic optimization, Springer-Verlag 2005
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Computational Intelligence and its applications: Kordon, A.K.
Applying Computational Intelligence, Springer-Verlag 2010 (new book, useful for practitioners, see
Tsang's review)
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VBA Implementations: Webber, N., Implementing models of financial derivatives, object oriented applications with VBA,
Wiley Finance, 2011
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Fractal in finance:
Mandelbrot, B. & Hudson, R.L.,
The (Mis)Behavior of Markets: A Fractal View of Risk, Ruin, and Reward, Basic Books, 2004
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Alternative view to Money:
Rothbard, M., What has Government Done to Our Money?, Ludwig von Mises Institute, fifth edition, 2005
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Schweitzer, F., Fagiolo, G., Sornette, D., Vega-Redondo, F., Vespignani, A., and White, D. R.,
Economic Networks: The New Challenges,
Science Vol.325, Issue 5939, 24 July 2009, 422-425
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Opinions that are well worth reading:
Willem Buiter's blog on FT.COM (Professor Buiter has moved on in 2010)
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Games, background reading (EDDIE mentioned):
Epstein, R.,
The theory of gambling and statistical logic,
Academic Press 2009
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Trading strategies:
Robert Krausz,
W.D. Gann Treasure Discovered, Marketplace Books, 2005
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Zig-zag charting (related to DC):
Sklarew, A., Techniques of a Professional Commodity Chart Analyst. New York: Commodity Research Bureau, 1980
Page maintained by Edward Tsang;
Last updated: 2023.02.01
(My reference: HKU/AIF.www.index.html)