CIFEr 2012 Program


The program schedule posted is being subject to a number of changes. Information regarding the technical sessions will be available soon is now available.

Download program schedule (PDF) (last update March 28, 2012)

Download technical sessions schedule (PDF) (last update March 28, 2012)


Prof. Tomaso Poggio - "The Future of the Science and Engineering of Intelligenceā€

March 30, 17.15h-17.45h, Auditorium

Tomaso Poggio, Honorary Chair Short Bio: Tomaso Poggio is Eugene McDermott Professor in the Department of Brain and Cognitive Sciences and at the Artificial Intelligence Laboratory. He is also Co-Director of the Center for Biological and Computational Learning and was appointed Investigator immediately after the establishment of the McGovern Institute in 2000. He joined the MIT faculty in 1981, after ten years at the Max Planck Institute for Biology and Cybernetics in Tubingen, Germany. He received a Ph.D. in 1970 from the University of Genoa. Poggio is a Foreign Member of the Italian Academy of Sciences and a Fellow of the American Academy of Arts and Sciences. Source: Tomaso Poggio personal webpage.


Prof. Vladmir Vapnik

March 30, 11.30h-12.00h, Auditorium

CIFEr is delighted to host the 2012 IEEE Frank Rosenblatt Award presented to Prof. Vladmir Vapnik.

Prof. Vladmir Vapnik Short Bio: Vladimir Naumovich Vapnik is one of the main developers of Vapnik-Chervonenkis theory. He was born in the Soviet Union. He received his master's degree in mathematics at the Uzbek State University, Samarkand, Uzbek SSR in 1958 and Ph.D in statistics at the Institute of Control Sciences, Moscow in 1964. He worked at this institute from 1961 to 1990 and became Head of the Computer Science Research Department. At the end of 1990, he moved to the USA and joined the Adaptive Systems Research Department at AT&T Bell Labs in Holmdel, New Jersey. The group later became the Image Processing Research Department of AT&T Laboratories when AT&T spun off Lucent Technologies in 1996. Vapnik Left AT&T in 2002 and joined NEC Laboratories in Princeton, New Jersey, where he currently works in the Machine Learning group. He also holds a Professor of Computer Science and Statistics position at Royal Holloway, University of London since 1995 (link), as well as a position as Professor of Computer Science at Columbia University, New York City since 2003 (link). He was inducted into the U.S. National Academy of Engineering in 2006. He received the 2008 Paris Kanellakis Award. While at AT&T, Vapnik and his colleagues developed the theory of the support vector machine. They demonstrated its performance on a number of problems of interest to the machine learning community, including handwriting recognition. Source: Wikipedia.

Invited Award Talk - Prof. Vladimir Cherkassky

March 30, 12.00h-12.30h, Auditorium

Prof. Vladimir Cherkassky Short Bio: Vladimir Cherkassky is Professor of Electrical and Computer Engineering at the University of Minnesota. He received Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 1985. His current research is predictive learning from data, and he has co-authored a monograph Learning From Data published by Wiley in 1998 (first edition) and 2007(second edition). He served on the Board of Governors of INNS in 1996-1997. He serves / has served on editorial boards of many journals including Neural Networks, IEEE Transactions on Neural Networks, Neural Networks, Neural Processing Letters and Natural Computing. He served on the program committee of major international conferences on Artificial Neural Networks. He was Director of NATO Advanced Study Institute (ASI) From Statistics to Neural Networks: Theory and Pattern Recognition Applications held in France, in 1993. He presented numerous tutorials and invited talks on neural networks and predictive learning from data. Prof. Cherkassky was active in promoting applications of predictive learning and artificial neural networks since late 1980's. More recently, he organized and co-chaired several special sessions on Climate Modeling and Earth Sciences Applications at IJCNN 2005-2008. He was elected in 2007 as Fellow of IEEE for "contributions and leadership in statistical learning and neural networks", and in 2008 he received The A. Richard Newton Breakthough Research Award from Microsoft Research for development and application of new learning methodologies


Prof. Andrew W. Lo - "Rethinking Financial Regulation via Cryptography"

March 29, 12.00h-13.00h, Auditorium

Prof. Andrew W. Lo Short Bio: Andrew W. Lo is the Harris & Harris Group Professor at the MIT Sloan School of Management and director of the MIT Laboratory for Financial Engineering. He received his Ph.D. in economics from Harvard University in 1984. Before joining MIT's finance faculty in 1988, he taught at the University of Pennsylvania's Wharton School as the W.P. Carey Assistant Professor of Finance from 1984 to 1987, and as the W.P. Carey Associate Professor of Finance from 1987 to 1988.

He has published numerous articles in finance and economics journals, and has authored several books including The Econometrics of Financial Markets, A Non-Random Walk Down Wall Street, Hedge Funds: An Analytic Perspective, and The Evolution of Technical Analysis. He is currently co-editor of the Annual Review of Financial Economics and an associate editor of the Financial Analysts Journal, the Journal of Portfolio Management, and the Journal of Computational Finance.

His awards include the Alfred P. Sloan Foundation Fellowship, the Paul A. Samuelson Award, the American Association for Individual Investors Award, the Graham and Dodd Award, the 2001 IAFE-SunGard Financial Engineer of the Year award, a Guggenheim Fellowship, the CFA Institute's James R. Vertin Award, the 2010 Harry M. Markowitz Award, and awards for teaching excellence from both Wharton and MIT. Source: Prof. Andrew W. Lo website.

Dr. Paul Wilmott - "What Quants Should Do"

March 30, 12.30h-13.00h, Auditorium

Dr. Paul Wilmott Short Bio: Paul Wilmott is a financial consultant, specializing in derivatives, risk management and quantitative finance. He has worked with many leading US and European financial institutions. Paul was born in the quaint little fishing village of Birkenhead and studied mathematics at St Catherine's College, Oxford, where he also received his D.Phil. He founded the Diploma in Mathematical Finance at Oxford University and the journal Applied Mathematical Finance. He is the author of Paul Wilmott Introduces Quantitative Finance (Wiley 2007), Paul Wilmott On Quantitative Finance (Wiley 2006), Frequently Asked Questions in Quantitative Finance (Wiley 2009) and other financial textbooks. He has written over 100 research articles on finance and mathematics. Paul Wilmott was a founding partner of the volatility arbitrage hedge fund Caissa Capital which managed $170million. His responsibilities included forecasting, derivatives pricing, and risk management. Dr. Wilmott is the proprietor of, the popular quantitative finance community website, the quant magazine Wilmott and is the Course Director for the Certificate in Quantitative Finance. Paul Wilmott was a professional juggler with the Dab Hands troupe. He also has three half blues from Oxford University for Ballroom Dancing. Source: Wilmott wiki webpage for Dr. Paul Wilmott.

Dr. Peter Carr - "Finanical Applications of PAY Martingales"

March 30, 14.00h-14.30h, Auditorium

Dr. Peter Carr Short Bio: Dr. Peter Carr is a Managing Director at Morgan Stanley with 15 years of experience in the derivatives industry. He was also a finance professor for 8 years at Cornell University, after obtaining his PhD from UCLA in 1989. He is presently the Executive Director of the Math Finance program at NYU's Courant Institute, the Treasurer of the Bachelier Finance Society, and a trustee for the Museum of Mathematics in New York. He has over 70 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and shared in the ISA Medal for Science in 2008. Last December, the International Association of Financial Engineers (IAFE) and Sungard jointly announced that they have selected Dr. Carr as its 2010 Financial Engineer of the Year. Source: Dr. Peter Carr website.

Invited Talk Abstract: We consider a subset of Azema Yor martingales which have positive support. Some applications of this subset to the pricing and hedging of derivative securities are given. We also consider the implications for portfolio insurance.

Industry Lightning Talk

Spencer Greenberg - "Stock Market Misconceptions Held Even By Professionals"

March 29, 9.30h-10.00h, Auditorium

Spencer Greenberg Short Bio: Spencer Greenberg is a mathematician with an education in applied mathematics and computer science from Columbia University's School of Engineering and NYU's Courant Institute of Mathematical Sciences. Spencer is co-founder and Chief Executive Officer of Rebellion Research, a quantitative fund that applies machine learning technology to investing. He has spoken about artificial intelligence and investing on Fox News, Bloomberg News, Bloomberg Radio, CNBC, Canada's Business News Network, China's Phoenix TV, in the Wall Street Journal, at Columbia Business School and at the Stern School of Business. Prior to founding Rebellion Research, Spencer was a computer programmer for Neuberger Berman, LLC, and developed software for a leading counter terrorism think tank.

Talk Abstract: Not all common knowledge is actually true. In this talk, Spencer Greenberg will discuss some beliefs held even by professional stock market investors that is challenged by empirical evidence. Commonly used computational concepts like beta, standard deviation and the risk-return tradeoff will be discussed. Do stock betas truly have predictive power? Does greater reward really come with greater risk? Is standard deviation a suitable measure of risk? Where do investment returns come from?.

Dr. Piero P. Bonissone - "Commercial and Industrial Applications of Computational Intelligence at GE"

March 29, 14.00h-14.30h, Auditorium

Dr. Piero Bonissone Short Bio: Dr. Bonissone is a Coolidge Fellow and a Chief Scientist at GE Global Research. He is also a Fellow of AAAI, IEEE, and IFSA. He has published over 150 articles in the area of soft computing, computational intelligence, expert systems, approximate reasoning, fuzzy sets, pattern recognition, decision analysis, and prognostics and health management (PHM). He has received 60 patents from the U.S. Patent Office (and 50+ are pending). In 2002, he was President of the IEEE Neural Networks Society (now IEEE Computational Intelligence Society). He was Editor-in-Chief for the International Journal of Approximate reasoning for 13 years, until 2005. In 2008, he received the II Cajastur International Prize for Soft Computing, from the European Centre of Soft Computing. Recently, he was bestowed the 2012 Fuzzy Systems Pioneer Award from the IEEE Computational Intelligence Society. Source: Dr. Piero P. Bonissone website.


Xian Li - "Financial and Economic Data management using Semantic Web technologies"

March 29, 8.00h-9.00h, Auditorium

Xian Li Short Bio: Xian Li is a Ph.D student from the Cognitive Science department at Rensselaer Polytechnic Institute, where she is a member of the Tetherless World Constellation working with Dr. James Hendler. Her research interests include behavioral economics, collective dynamics of the social web, and efficient interacting with financial and economic data from heterogeneous sources using Semantic Web technologies. Xian has both B.S and M.S. degrees in Computer Science.

Tutorial Abstract: In domains of Finance and Economics, interacting with large amounts of data from heterogeneous sources is a common and critical task for both academic researchers and industrial practitioners. The increasing connectivity and interdependence of the world's markets, firms and financial instruments have posted significant challenges for efficiently managing relevant datasets which would be used to facilitate scientific discoveries and support business decisions. This tutorial proposes an approach to address the data interchange challenges with Semantic Web technologies. We first introduce a data model with Resource Description Framework (RDF) for describing business entities, financial markets, etc., and the related ontologies and vocabulary for managing metadata. In keeping with CIFEr's practical spirit, this tutorial will give participants hand-on experience using SPARQL to query large datasets in RDF form, and analyze the results with R.

Dr. Jan Dash - "Stressed Value-at-Risk"

March 30, 9.00h-10.00h, Auditorium

Dr. Jan Dash Short Bio: Jan Dash heads the Strategic Risk Research group at Bloomberg L.P. and previously managed quant/risk groups at Citigroup / Salomon Smith Barney and Merrill Lynch. He is also Adjunct Professor at the Courant Institute of NYU and Visiting Research Scholar at Fordham University. Jan invented Stressed Value at Risk, an advanced practical risk measure for financial crises. He introduced Feynman path integrals to finance. He co-invented the Macro-Micro Model that produces a practical realistic description of market variables at long and short time scales. He wrote the textbook Quantitative Finance and Risk Management, A Physicist's Approach. Previously he was Directeur de Recherche at the Centre de Physique Théorique (CNRS, Marseille, France) and published over 50 scientific papers. He holds a PhD in theoretical high-energy physics from UC Berkeley.

Tutorial Abstract: Stressed Value at Risk (Stressed VAR) in its advanced framework provides a realistic measure of market risk tailored for stressed market environments. The simpler regulatory version of Stressed VAR is a special case. Stressed VAR corrects various deficits of ordinary VAR in times of market stress. Stressed VAR incorporates scenario analysis in a VAR setting in a sophisticated and consistent fashion. The mathematical framework is familiar and simple, designed to be understandable in a practical way by risk managers, traders, and regulators. Specifically, the familiar Gaussian (normal) probability formalism is employed, but in a completely different way than for ordinary VAR, designed to account for tail risk and collective behavior. The two main ingredients for Stressed VAR are "fat-tail volatilities" that account for outlier events in the risk factors, and stressed correlations between risk factors that account for collective market participant behavior in stressed markets. This information is provided as input to standard Monte Carlo simulation to determine stressed market risks for a given portfolio. The VAR with the inputs of the fat-tail volatilities and the stressed correlations is the Stressed VAR. Bloomberg LP is implementing Stressed VAR in the PORT portfolio system.


Algo Trading Advancements through Computational Intelligence with Finance and Economics

March 29, 17.15h-18.15h, Auditorium

Algorithmic Trading has changed the world the way the Traders trade and Trade Support supports. There is a Brave New World happening with the "hands on" trading evolving into "hands off" algo trading. Not all trades need to be made in ultra low latency timing but the current trend has been an arms race to zero latency. Future trading will rely on a broader set of financial and economic data. Advancements will occur with Algo Trading through Computational Intelligence with intersections with Finance and Economics. The next generation of Algo Trading will encompass advanced and hybrid computational intelligence mechanisms.

Tentative questions

  • Q1: What is Computational Intelligence's role with our next generation of Algo Trading methods?
  • Q2: What are the main issues in integrating such systems with daily workflows with finance and economics in mind?
  • Q3: Which challenges in developing effective algorithms are the hardest to overcome with Computational Intelligence methods?
  • Q4: What types of algo trading systems work best with which types of buy-side strategies and are they ready for the next generation of CI based Algos?
  • Q5: How should such platforms be measured and benchmarked for efficacy?
  • Q6: What are the innovations on or just beyond the horizon?


Ram Ahluwalia

Winged Foot Capital

Ram Ahluwalia Short Bio: Winged Foot Capital is a quantitative investment management firm. Winged Foot Capital applies a systematic, multi-disciplinary, hypothesis-based approach to generating alpha across market regimes. Previously, Ram was a Senior Vice President at Bank of America-Merrill Lynch and member of the Cards & Deposits executive management team responsible for investment decisioning a $120 Bn credit portfolio. Prior to this role, Ram was responsible for business development in the Merrill Lynch Global Bank Group where he developed strategic partnerships in the airline, hotel, and retail segments. As a management consultant at Inductis, Ram advised Fortune 50 financial services firms on best-in-class decision-making frameworks for acquisition and risk modeling. At the Cato Institute Ram performed threat-matrix and operating cost-structure analysis for the Defense & National Security policy team. Ram received a B.A. in Economics-Philosophy from Columbia College.

Matthew Butler

Faculty of Computer Science
University of York

Ram Ahluwalia Short Bio: I grew up in Bedford, Nova Scotia, Canada and attended Dalhousie University for my undergraduate degree in Finance. After finishing my degree I embarked on a two year trip where I lived and worked in Scotland and Australia. I was living in Edinburgh Scotland for 1.5 years where I worked for HSBC in their personal banking division. From there it was on to Sydney Australia to work for the Hubb Financial Group a developer for trading and investment analysis software. This was my first introduction to computer programming and the inspiration for my research in Machine Learning. I completed my Masters of Electronic Commerce at Dalhousie University in 2009 and my thesis title was "An Artificial Intelligence Approach to Financial Forecasting using Improved Data Representation, Multi-objective Optimization, and Text Mining". I am currently a 2nd year PhD Student at the University of York in York England. My current research is with the Artificial Intelligence Group and is focused on Financial Modeling with the aid of artificial intelligence techniques. Source: Matthew Butler website

Richard Labs, CPA, CFA

Co-Chair FIX Protocol Algorithmic Trading Working Group
Managing Member, CL&B Capital Management, LLC

Richard Labs Short Bio: Rick is a portfolio manager at his Registered Investment Advisory firm CL&B Capital Management, LLC where he directly oversees investments for a handful of private clients. In 1995 he became involved in the FIX Algorithmic Trading Working group, which subsequently developed and maintains the FIX algorithmic trading definition language (FIXatdl). During the last six years he has overseen the launch of FIXatdl version 1.0, and the major update, version 1.1 in 2010.
Rick's prospective on the capital markets is long-term, analytical, and multidimensional. He started in 1981 as a CPA auditor of Fortune 500 firms. From there he worked extensively as an executive in the marketing, advertising, and investor relations industry. In 1991 he became a Chartered Financial Analyst and began working directly as a portfolio manager. He's therefore been involved in every phase from creating the books, auditing the books, promoting the books, reading and interpreting the books, pulling the trigger on the buy/hold/sell decisions, and actually executing the trades. In 1998 he formed his Registered Investment Advisory firm serving individual clients. He's a lifetime analytical researcher and maintains significant ongoing interest in psychology (including perception, communication, attachment and bonding), behavioral finance, artificial intelligence, market research, muli-factor fundamental financial analysis, and algorithmic trading. Most recently he's been following market structural changes brought on by the 2008 crisis and regulatory aftermath. He's a graduate of Syracuse University with a BA in Psychology, and has an MBA from the University of San Diego.

Murray Ruggiero Jr.

V.P. of research and development TradersStudio Inc.,
Chief Systems Designer and Market Analyst for Tuttle Wealth Management, LLC

Murray Ruggiero Short Bio: Murray Ruggiero is Vice President of research and development for TradersStudio Inc. and Chief Systems Designer and Market Analyst for Tuttle Wealth Management, LLC. At TradersStudio Inc. Murray developed a cutting edge software program that is used worldwide by institutional and retail investors to create automated systems for trading in futures, currency, stock, and ETF markets. Murray's expertise has also helped Tuttle Wealth Management, LLC become one of the nation's top Tactical Asset Allocation money managers.
He is a sought-after speaker at IEEE engineering conventions and symposiums on artificial intelligence. IEEE, the Institute of Electrical and Electronics Engineers, is the largest professional association in the world advancing innovation and technological excellence for the benefit of humanity. Due to his work on mechanical trading systems, Murray has also has been featured on John Murphy's CNBC show Tech Talk , proving John's chart-based trading theories by applying backtested mechanical strategies. (Murphy is known as the father of inter-market analysis.)
After earning his degree in astrophysics, Murray pioneered work on neural net and artificial intelligence (AI) systems for applications in the investment arena. He was subsequently awarded a patent for the process of embedding a neural network into a spreadsheet.
Murray's first book, Cybernetic Trading , revealed details of his market analysis and systems testing to a degree seldom seen in the investment world. Reviewers were universal in their praise of the book, and it became a best seller among systems traders, analysts and money managers. He has also co-written the book Traders Secrets , interviewing relatively unknown but successful traders and analyzing their trading methodologies. Murray has been a contributing editor to Futures magazine since 1994, and has written over 160 articles.

Ronald Yager

IEEE Fellow
Director of Machine Intelligence Institute
Professor of Iona College, USA

Ron Yager, General Chair Short Bio: Ronald R. Yager is a fellow of the IEEE, the New York Academy of Sciences and the Fuzzy Systems Association. He has served at the NSF as program director in the Information Sciences program. He was a NASA/Stanford visiting fellow as well as a research associate at the University of California, Berkeley. He has served as a lecturer at NATO Advanced Study Institutes. He received his undergraduate degree from the City College of New York and his Ph. D. from the Polytechnic University of New York. Currently, he is Director of the Machine Intelligence Institute and Professor of Information and Decision Technologies at Iona College. He is editor and chief of the International Journal of Intelligent Systems. He serves on the editorial board of a number of journals including the IEEE Transactions on Fuzzy Systems, Neural Networks, Data Mining and Knowledge Discovery, IEEE Intelligent Systems, Fuzzy Sets and Systems, the Journal of Approximate Reasoning and the International Journal of General Systems. He is one of the co_founders of the conference on Information Processing and the Management of Uncertainty (IPMU). He has published over 500 articles and fifteen books. In addition to his pioneering work in the area of fuzzy logic he has made fundamental contributions in decision making under uncertainty and the fusion of information. His current research interests include the development of technologies for a more intelligent internet (E-Commerce, data mining, information retrieval) aggregation theory, decision making under uncertainty and higher order information fusion.

Panel Moderator

Robert Golan

DBmind Technologies Inc.

Robert Golan, Program ChairShort Bio: DBmind Technologies Inc. specializes in Data Base Mining through Artificial Intelligence techniques while integrating Business Intelligence and Data Warehousing. Robert Golan, President of DBmind, has been involved in many AI based projects beginning with a LEVEL5 development and rollout of a rule based expert system which was used to diagnose printer hardware and software problems. Robert Golan earned a Masters Degree in Computer Science from the University of Regina. Robert's initial startup of Rough Knowledge Discovery Inc. in 1995 was later renamed to DBmind Technologies Inc. in 1997. In collaboration with DBintellect/EDS a proposal was made for a prospect profiling project via data mining for Fidelity Investments. Robert has been working with Wall Street firms since 1996 and has promoted AI/CI through CIFEr and other forums.

Technical Sessions

Download Technical Sessions Schedule (PDF) (last update March 28, 2012)

Thursday March 29, 2012

Session 1A "Fuzzy Decision models in Financial Engineering - I"

10.30AM-12 Noon, Ante Room. Chair: Uzay Kaymak

(86) A Multi-Covariate Semi-Parametric Conditional Volatility Model Using Probabilistic Fuzzy Systems. Rui Jorge Almeida, Nalan Basturk, Uzay Kaymak and Viorel Milea

(81) A Mean-Reverting Strategy based on Fuzzy Transform Residuals. Luigi Troiano and Pravesh Kriplani

(16) Modeling principles in fuzzy time series forecasting. Okan Duru and Shigeru Yoshida

(89) Linguistic Decision Making with Probabilistic Information and Induced Aggregation Operators. José M. Merigó and Montserrat Casanovas

Session 1B "Advanced Algorithmic Trading - I"
Special Session (Philip Yu, Chenghui Cai, Daniel Paraschiv)

10.30AM-12 Noon, Club Room. Chair: Chenghui Cai

(25) The Use of Neural Networks for Modeling Nonlinear Mean Reversion: Measuring Efficiency and Integration in ADR Markets. Eugenio Suarez, Farzan Aminian and Mehran Aminian

(53) A Learning Adaptive Bollinger Band System. Matthew Butler and Dimitar Kazakov

(41) Complex Stock Trading Strategy Based on Particle Swarm Optimization. Fei Wang, Philip L.H. Yu and David W. Cheung

(71) Limit Order Placement Across Multiple Exchanges. Raymond Yim and Andrew Brzezinski

Session 2A "Asset Pricing / Pricing of Structured Securities"

2.30PM-4.00PM, Ante Room. Chair: Aman Kumar

(31) A New Approach to Asset Pricing with Rational Agents Behaving Strategically. Alain Bretto and Joël Priolon

(22) Bio-Inspired Optimization of Fuzzy Cognitive Maps for their Use as a Means in the Pricing of Complex Assets. Lars Krueger, Ralf Salomon and Peter Heydebreck

(9) A Multi-Phase, Flexible, and Accurate Lattice for Pricing Complex Derivatives with Multiple Market Variables. Chuan-Ju Wang, Tian-Shyr Dai and Yuh-Dauh Lyuu

(33) Pricing Discrete Asian Barrier Options on Lattices. William W.Y. Hsu, Cheng-Yu Lu, Ming-Yang Kao, Jan-Ming Ho and Yuh-Dauh Lyuu

(18) Improving Non-parametric Option Pricing during the Financial Crisis. Dragan Kukolj, Nikola Gradojevic and Camillo Lento

(57) Closed-Form Mortgage Pricing Formula with Outstanding Principal as Prepayment Value. Yi-Cheng Tsai, Zheng-Hui Chen, Jan-Ming Ho, Ming-Yang Kao, Szu-Lang Liao and Chin-Laung Lei

Session 2B "Fuzzy Decision models in Financial Engineering - II"

2.30PM-4.00PM, Club Room. Chair: Aderemi Adewumi

(37) Exponential Length of Intervals for Fuzzy Time Series Forecasting. Emrah Bulut, Okan Duru and Shigeru Yoshida

(91) Decision Making in Complex Environments with Generalized Aggregation Operators. José M. Merigó

(54) MIMO Evolving Functional Fuzzy Models for Interest Rate Forecasting. Leandro Maciel, Fernando Gomide and Rosangela Ballini

(77) Group Decision Making in fuzzy environment. Mahima Gupta

Session 3A "Advanced Algorithmic Trading- II"
Special Session (Philip Yu, Chenghui Cai, Daniel Paraschiv)

4.15PM-5.15PM, Auditorium. Chair: Xian Li

(39) Behavior Based Learning in Identifying High Frequency Trading Strategies. Steve Yang, Mark Paddrik, Roy Hayes, Andrew Todd, Andrei Kirilenko, Peter Beling and William Scherer

(44) Hierarchical Temporal Memory-Based Algorithmic Trading of Financial Markets. Patrick Gabrielsson, Rikard König and Ulf Johansson.

(43) Robust Stock Trading Using Fuzzy Decision Trees. Carlo Noel Ochotorena, Cecille Adrianne Yap and Elmer Dadios.

Session 3B "Risk Management"

4.15PM-5.15PM, Ante Room. Chair: Roy S. Freedman

(72) Optimal Selection of Simulated Years of Catastrophe Activity for Improved Efficiency in Insurance Risk Management. Guillermo Franco

(11) Event-Based Historical Value-at-Risk. Frederik Hogenboom, Michael De Winter, Milan Jansen, Alexander Hogenboom, Flavius Frasincar and Uzay Kaymak

(50) Online Estimation of Stochastic Volatility for Asset Returns. Ivette Luna and Rosangela Ballini

(78) Liquidity Risk Spillover: Evidence from cross-country analysis. William Cheung and Siu Lo

Session 3C "Behavioral Analysis and Decision Support - I"
Special Session (Ronald R Yager, Antoaneta Serguieva, Edward Tsang, Robert Golan)

4.15PM-5.15PM, Club Room. Chair: Murray Ruggiero Jr.

(10) Intermarket Divergence, a method for generating robust signals for a wide range of markets. Murray Ruggiero Jr

(40) A Study on the Reversal Mechanism for Large Stock Price Declines Using Artificial Markets. Isao Yagi, Takanobu Mizuta and Kiyoshi Izumi

(90) A New Approach to Risk Management Using Soft Information. Ronald Yager and Rachel Yager

(21) A Comparison of Feed-forward and Recurrent Neural Networks in Time Series Forecasting. Danko Brezak, Tomislav Bacek, Dubravko Majetic, Josip Kasac and Branko Novakovic

Friday March 30, 2012

Session 4X "Behavioral Analysis and Decision Support - II"
Special Session (Ronald R Yager, Antoaneta Serguieva, Edward Tsang, Robert Golan)

10.30AM-11.30AM, Auditorium. Chair: JosJosé M. Merigo

(38) Modeling the Term Structure of Government Bond Yields with a Differential Evolution Algorithm. Leandro Maciel, Fernando Gomide and Rosangela Ballini

(36) Three decision making levels in trading portfolio. Sarunas Raudys and Aistis Raudys

(49) The Development of a Real-time Valuation Service of Financial Derivatives. Hsin-Tsung Peng, Chi-Fang Chang, Szu-Lang Liao, Ming-Yang Kao, Feipei Lai and Jan-Ming Ho

(24) A New Solution Method for Customer Grading Problem With Multi-factor Constraint. Jie Yang and Yimin Chen

Session 4Y "Agent based Computational Economics"
Special Session (Herbert Dawid)

10.30AM-11.30AM, Ante Room. Chair: Jie Du

(83) An Agent-based Modeling Approach to Study Price Impact Wei Cui and Anthony Brabazon

(59) Testing Implications of the Adaptive Market Hypothesis via Computational Intelligence Matthew Butler and Dimitar Kazakov

(68) An Agent Based Model of the E-Mini S&P 500: Applied to Flash Crash Analysis Mark Paddrik, Roy Hayes, Andrew Todd, Steve Yang, Peter Beling and William Scherer

(15) Continuous Variable Based Bayesian Network Structure Learning from Financial Factors. Jianjun Yang, Zitian Wang, Bingwu Liu and Shaohua Tan

Session 4Z "Energy Markets"
Special Session (Wolf Ketter)

10.30AM-11.30AM, Club Room. Chair: Svetlana Borokova

(27 A Self-Organizing Neural Fuzzy System to Forecast the Price of Ecopetrol Shares Jose Alejandro Avellaneda Gonzalez, Cynthia María Ochoa Rey and Juan Carlos Figueroa García

(6) Financing for Rural Electrification Najib Altawell

(58) News analytics for energy futures Svetlana Borovkova

Session 5X "Portfolio Optimization"
Special Session (Dietmar Maringer, Garnett Wilson, Sandra Paterlini)

12.30 PM-4.00 PM, Auditorium. Chair: Richard Labs

(73) Rebalancing A Two-Asset Markowitz Portfolio: A Fundamental Analysis Sujit Das and Mukul Goyal

(28) Portfolio optimization using a parallel multi-objective risk-adjusted optimization algorithm Phil Maguire, Donal O' Sullivan and Philippe Moser

(45) Discrete-Time Log-Optimal Portfolio Rebalancing: A Scalable Efficient Algorithm Sujit Das and Mukul Goyal

(26) Comparative Results of Heuristics for Portfolio Selection Problem Aderemi Adewumi and Annalisa Moodley

(14) Analytical Factor Stochastic Volatility Modeling for Portfolio Allocation Nikolay Nikolaev and Evgueni Smirnov

Session 5Y "Business Intelligence and Knowledge Management"
Special Session (Suash Deb and Xin-She Yang)

2.30 PM-4.00 PM, Ante Room. Chair: V. L. Raju Chinthalapati

(55) On behavior of Malaysian equities through Fractal analysis. Farhad Pourkalbassi, Alireza Bahiraie and Aishah Hamzah

(56) Fuzzy linguistic summaries: where are we, where can we go? Bernadette Bouchon-Meunier and Gilles Moyse

(65) Parallelization of Artificial Neural Network Training Algorithms: A Financial Forecasting Application. Augusto Casas

(69) A Pattern Recognition Approach to Automated XBRL Extraction. Hassan Alam, Aman Kumar, Cheryl Lee and Yuliya Tarnikova

(42) Volatility Forecast in FX Markets using Evolutionary Computing and Heuristic Technique. V.L. Raju Chinthalapati

(67) Knowledge-guided Genetic Algorithm for Financial Forecasting. Jie Du and Roy Rada

Session 5Z "Advanced Algorithmic Trading- III"
Special Session (Philip Yu, Chenghui Cai, Daniel Paraschiv)

2.30 PM-4.00 PM, Club Room. Chair: Rui J. Almeida

(19) A Naïve Model to Forecast the Probability Distribution of Excess Returns in the U.S. Stock Market . Reza Khosravani

(66) Optimal leverage and stop loss policies for futures investments. Rainer Schuessler

(62) Stock Trading System Based on Portfolio Beta and Evolutionary Algorithms. Yan Chen

(79) Order Aggressiveness of Option Market: Evidence from the 2008 Credit Crisis. William Cheung and Conrad Cheng


Friday March 30, 2012

Poster Session

4.00PM-5.15PM, Reception Area

(60) An analytic environment for systemic risk- Risk modeling support for financial policy makers. Charles Worrell

(87) Input Output Table Updating based on Agent-Responses Equilibrium Model Wei Duan, Zhaoguang Hu, Yuhui Zhou and Xiao Xiao

(5) Incorporating Statistical Distribution in Loss and Gain Functions in CVaR Robust Mean-variance Portfolios. Mahnaz Manteqipour

(35) Common Data and Controlling General Ledger Paradigm of Banking Data Services. Josef Langmayer and Pavel Pešout

(51) Solving the Winner Determination Problem by a Distributed Genetic Algorithm Approach. Terje Kristensen and Mauricio Rojas

(61) Comparison of data classification methods for predictive ranking of banks exposed to risk of failure. Charles Worrell

(12) Forecasting of Return of Stocks Portfolio Based in Fuzzy c-Means Algorithm and Fuzzy Transform. Renato Aguiar

(32) FX trading: an empirical study. Gerda Cabej, Manfred Gilli, Jonela Lula and Enrico Schumann

(70) An Integrated System Approach For Cash Management System Internal Control. Kuan Chen and Carin Chuang

Special Sessions

Aims and Scope

In the spirit of our the Computational Finance and Economics Technical Committee (CFETC) with its task forces, we at CIFEr would like to jointly organize special sessions aligning with their initiatives. By organizing these sessions, we are able to promote the missions of CFETC, as declared in the IEEE Computational Finance and Economics TC

Proposed Special Session Topics:

  • Agent-based Computational Economics
  • Advanced Algorithm Trading
  • Energy Markets
  • Portfolio Optimization
  • Business Intelligence & Knowledge Management
  • Behavioral Analysis and Decision Support

More specifically, the subjects of the above tracks include:

Agent-based Computational Economics (Herbert Dawid)
  • Agent-based computational modeling of markets (financial markets, labor markets, electricity markets, energy markets, agriculture markets, commodity markets, auctions, etc)
  • Agent-based computational modeling of social interactions and social and economic networks (cultural formation, social network formation, migration, technology spillover and adoption, etc)
  • Agent-based computational modeling of organizations (firms, networks of firms, networks of banks, etc)
  • Agent-based modeling of behavioral economics (behavioral game experiments, human-subject experiments, neuroeconomic experiments)
  • Agent-based computational macroeconomics, international economics and financial crisis
  • Spatial agent-based economic models (urban dynamics, new economic geography, etc.)
  • Other related Agent-based computational economic models: Computable General Equilibrium, Input-Output Table and Social Accounting Matrices, Statistical Physics, and Dynamic Stochastic General Equilibrium Models.
Advanced Algorithmic Trading (Philip Yu, Chenghui Cai, Daniel Paraschiv)
  • Trading Methods and Algorithms
  • Automated Trading Systems
  • Evaluation and Optimization of Trading Strategies
  • Market Microstructures and Designs
  • Order Placement Decisions
  • Execution Tactics
  • High-Frequency Trading
  • Volatility Trading
  • Portfolio Trading
  • Multi-Asset Trading Strategies (Hedging, Arbitrage, etc)
  • Statistical Arbitrage
  • Computerized News Handling Techniques
  • Automated News Handling
Energy Markets (Wolf Ketter)
  • Power Trading Agent Competition
  • Intelligent Systems in Power Systems (Power Generation, Transmission, and Distribution)
  • Intelligent Systems in Energy Markets
  • Energy Load and Price Forecast
  • Deregulated Electric Power Systems
  • Smart Electric Grids
  • Smart Energy Networks
  • Renewable energy
Portfolio Optimization (Dietmar Maringer, Garnett Wilson, Sandra Paterlini)
  • Computational Intelligence in Portfolio Optimization and Risk Management
  • Algorithmic Portfolio Management
  • Stock Selection
  • Monte-Carlo Methods for Portfolio Optimization
  • Dynamic Programming Approaches for Portfolio Optimization
  • Mutli-Objective Portfolio Optimization
  • Constrianed Portfolio Optimization
  • Real Estate Portfolio Optimization
  • Large-Scale Portfolio Optimization
Business Intelligence & Knowledge Management (Suash Deb and Xin-She Yang)
  • Data driven strategies, optimization, applications, solutions or experimentation
  • Search engine marketing and optimization
  • Online auctions
  • High Performance Computing for BI
  • Personalization and Recommendation Systems
  • Customer segmentation or profiling
  • Active learning and imbalanced data handling
  • OLAP and Data Warehousing
  • Text Mining and Web Mining
  • Semantic Web and Ontology-based Methods for BI
  • Service oriented and cloud architecture for data mining
  • Business models based on user-generated content
  • Information privacy
  • Supply Chain Integration through BI
  • Knowledge discovery from social or complex networks
Behavioral Analysis and Decision Support (Ronald R. Yager, Antoaneta Serguieva, Edward Tsang, Robert Golan)
  • Advanced risk measurement and decisions on capital adequacy for banks
  • Algorithmic trading and risk analysis environments as decision support systems
  • Behavioral aspects in systemic risk modeling
  • Empirical study of trader behavior
  • Evaluation of impacts of trading decisions
  • Evolutionary risk management in sequential trading models
  • Financial wind tunnels in facilitation of policy making
  • Hybrid knowledge-based systems in decision support
  • Market-based decision support systems
  • Market stylized facts based on trader behavior
  • Modeling of trader behavior
  • Regional and global interdependence in market behavior
  • Trade decision-taking and model optimization in algorithmic trading
  • Trader behavior and contagion in crisis propagation

Social Events

Welcome Reception

Thursday, March 29, 2012, 6.30PM, Reception Area

A wine and cheese reception will take place on the Reception Area of Credit Suisse.


Thursday, March 29, 2012, 7.00AM-8.00AM, Reception Area

Friday, March 30, 2012, 8.00AM-9.00AM, Reception Area

To kick-off the day, in the mornings starting an hour before the day's sessions there will be a continental breakfast in the Reception Area of Credit Suisse.


1.00PM-2.00PM, Reception Area

Lunch will be served in the Reception Area of Credit Suisse.

Coffee Breaks

Reception Area

All coffee breaks will take place in the Reception Area of Credit Suisse.

All social events are open to all attendees including registered students.