NEW YORK CITY / MARCH 5 JUNE Artificial Intelligence in Finance Institute.

Transcription

1 NEW YORK CITY / MARCH 5 JUNE Artificial Intelligence in Finance Institute

2 NEW YORK CITY / MARCH 5 JUNE

3 Mission The Artificial Intelligence Finance Institute s (AIFI) mission is to be the world s leading educator in the application of artificial intelligence to investment management, capital markets and risk. We offer one of the industry s most comprehensive and in-depth educational programs, geared towards investment professionals seeking to understand and implement cutting edge AI techniques. Taught by a diverse staff of world leading academics and practitioners, the AIFI courses teach both the theory and practical implementation of artificial intelligence and machine learning tools in investment management. As part of the program, students will learn the mathematical and statistical theories behind modern quantitative artificial intelligence modeling. Our goal is to train investment professionals in how to use the new wave of computer driven tools and techniques that are rapidly transforming investment management, risk management and capital markets 1

4 The Faculty Miquel Noguer i Alonso PhD Co-Founder & Chief Science Officer Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF. He worked for UBS AG (Switzerland) as Executive Director for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to He is professor of Big Data in Finance at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE in In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED Madrid Spain). Michael Oliver Weinberg CFA Co-Founder & Chief Executive Officer Michael has 25 years of experience investing directly at the security level and indirectly as an asset allocator in traditional and alternative assets. He is the Chief Investment Officer, and a Senior Managing Director of MOV37 and Protégé Partners. His portfolio management experience includes Soros Fund Management LLC, Credit Suisse First Boston, and Financial Risk Management (FRM). Michael is a published author and keynote speaker at conferences and universities. He received an M.B.A. from Columbia Business School, where he is now also an Adjunct Professor of Finance and Economics, and a B.S. in Economics from New York University. 2 Artificial Intelligence in Finance Institute

5 George Lentzas Professor George is a statistics expert with a decade of experience in applying quantitative models in the real world. He has worked in various capacities at leading financial institutions, such as Morgan Stanley, BNP Paribas, Citigroup, and Hutchin Hill Capital. He has also held faculty positions at Columbia University and NYU, where he has taught courses in machine learning and applied statistics and econometrics. His professional expertise includes the application of statistics, machine learning, and AI to finance and economics. He is currently the chief data scientist and manager of Springfield Capital Management. He holds a PhD, MPhil, and BA from Oxford University and an MPhil from Cambridge University. Igor Halperin Professor Igor Halperin is Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. Previously, he was an Executive Director of Quantitative Research at JPMorgan, and before that he worked as a quantitative researcher at Bloomberg LP. Igor has published articles in finance and physics journals, is a speaker at financial conferences and has co-authored the book Credit Risk Frontiers. Igor has a Ph.D. in theoretical high energy physics from Tel Aviv University, and a M.Sc. in nuclear physics from St. Petersburg State Technical University. He also advises fintech and data science start-ups and risk management firms. 3

6 Josh Joseph Professor Josh Joseph is the Chief Intelligence Architect of the Bridge, the application arm of MIT s Quest for Intelligence Initiative. Previously, Josh was the Chief Science Officer of Alpha Features, an alternative data distribution platform, and co-founded a proprietary trading company based on machine learning driven strategy discovery and fully autonomous trading. Additionally, he has done a variety of consulting work across finance, life sciences, and robotics. He has a Ph.D. in Aeronautics and Astronautics from MIT where his research focused on methods for learning models of complex systems for decision making. Mickey Atwal Professor Mickey Atwal is an associate professor at Cold Spring Harbor Laboratory where he undertakes machine learning research and builds tools to analyze vast datasets in cancer genomics and immunology. He was awarded the Winship Herr Award for Excellence in Teaching a record three times, developing courses at the interface of machine learning, molecular biology, and neuroscience. He has trained in theoretical physics from the University of Cambridge, Cornell University, and Princeton University. Larry Rudolph Professor Larry Rudolph is a researcher at the MIT Computer Science and Artificial Intelligence Laboratory. Larry received his PhD also in Computer Science in 1981 from the Courant Institute at NYU. He was on the faculty at University of Toronto, Carnegie-Mellon University, and The Hebrew University, before joining MIT as a principal research scientist, in Way back in 1978, he helped start the Ultracomputer, a high performance parallel computer architecture, many ideas of which can be found in current multi-core computer chips. VP (Member of Labs) at Two Sigma Investments. 4 Artificial Intelligence in Finance Institute

7 Gordon Ritter Scientific Advisor Gordon Ritter completed his Ph.D. in mathematical physics at Harvard University in 2007, where he published in top international journals. Prior to that he earned his Bachelor s degree from the University of Chicago. Gordon is currently a senior portfolio manager at GSA. Prior to joining GSA, Gordon was a Vice President of Highbridge Capital Management and a core member of the firm s statistical arbitrage group. Concurrently with his positions in industry, Gordon teaches at three of the nation s leading MFE programs, including Baruch College and NYU. He has published articles, and is a speaker at the top industry conferences. Petter Kolm Scientific Advisor & Professor Petter Kolm is a Clinical Professor and the Director of the Mathematics in Finance Master s Program at Courant Institute of Mathematical Sciences, NYU. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management. Petter has coauthored numerous academic articles and four books. He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich. Petter is also on various Board of Directors, editorial and advisory boards. 7

8 Advisory Board Jeannette M. Wing Jeannette M. Wing is Avanessians Director of the Data Science Institute and a Professor Columbia University. From 2013 to 2017, she was at Microsoft Research. She is Consulting Professor of Computer Science at CarnegieMellon. From she was the Assistant Director of the Computer and Information Science and Engineering Directorate at the NSF. She received her S.B., S.M., and Ph.D. degrees in Computer Science, from the Massachusetts Institute of Technology. She has been chair and/or a member of many academic, government, and industry advisory boards and received various awards. Dr. Peter Carr Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He has won multiple prestigious Quant awards. Armando Gonzalez Armando Gonzalez is President & CEO of RavenPack, the leading provider of big data analytics for financial institutions. Armando is an expert in applied big data and artificial intelligence technologies. His commentary and research has appeared in leading business publications such as the Wall Street Journal, Financial Times, among many others. Armando holds degrees in Economics and International Business Administration from the American University in Paris and is a recognized speaker at academic and business conferences across the globe. Hein Hundal, Ph.D. Hein Hundal, Ph.D. Is the chief scientist at Random Order, Inc. He was a quantitative analyst for D.E. Shaw. Hein was a Principal Engineer for Raytheon and an Associate Research Engineer at the Pennsylvania State University (PSU), where he taught mathematics and earned an Honors B.S. degree. He served five years in the U.S. Navy as a Nuclear Engineer Officer and a Meteorology Division Officer. Hein has a Master s Degree in Computer Science and a Ph.D. in Mathematics from Penn State. Dr. Hundal has more than 15 peer-reviewed publications in mathematics journals and holds two U.S. patents. Emily L. Spratt Emily L. Spratt is an art historian, art technologist, and strategic advisor who has published extensively on the subjects of visual culture, aesthetic theory, vision technology, and machine learning in the arts. Emily has a B.A. from Cornell, an M.A. from UCLA, and an M.A. from Princeton. Her doctorate at Princeton is on Byzantine and Renaissance art. Emily has taught in the Department of Art History at Rutgers and has been the recipient of numerous international fellowships and awards. She is a consultant and fellow at The Frick Collection and Art Reference Library. 6 Artificial Intelligence in Finance Institute

9 Programme The Curriculum The course, globally offered online, expounds on the theory and implementation of artificial intelligence in finance. Students are expected to learn the mathematical and statistical theories behind modern quantitative artificial intelligence modeling. The course will provide education on the theory and practical application of artificial intelligence in finance through exposure to world leading practitioners and academics. Structure Artificial Intelligence in Investment Management Certificate 3 months program: March 5 June Lectures: New York City and globally offered online. Tuesday and Thursday pm. 75 hours: Lectures + Practice + Speakers. Evaluation: Exam + Project. Course Fee: $9,500 Ideal Candidates ⁰ Quantitative Analysts ⁰ Computer Scientists ⁰ Risk Managers ⁰ Traders ⁰ Portfolio Managers ⁰ Investment Managers ⁰ Data scientists We will give a Python Refresher and Mathematics Refresher/Primer at the beginning of the course. Apply online: 7

10 Course Timetable Module Contents Date (all 6 9pm) Professor 1 Artificial Intelligence in Finance Landscape Tues, March 05, 2019 Dr Miquel Noguer i Alonso 2 Alternative data Thurs, March 07, 2019 Dr Petter Kolm 3 Econometrics and financial modeling review Tues, March 12, 2019 Dr Petter Kolm a. Univariate and Multivariate modeling b. Continuous and Discrete models c. Time Series Models d. Linear Factor Models e. Portfolio Allocation f. Exercises Thurs, March 14, 2019 Dr Petter Kolm 4 Python and coding - Primer Tues, March 19, 2019 Dr Gilberto Batres Estrada a. Python basics b. Sci-kit Learn c. XgBoost d. Keras and Tensorflow e. NLTK f. Exercises Thurs, March 21, 2019 Dr Gilberto Batres Estrada 5 DataRobot Tues, March 26, 2019 Dr John Boersma 6 Machine Learning Modeling and Metrics Thurs, March 28, 2019 Dr Georges Lentzas a. Preprocessing i. Features scaling and selection ii. Dimensionality Reduction iii. Sampling b. Learning i. Model Selection ii. Cross-Validation iii. Performance Metrics iv. Hyperparameter optimization c. Evaluation d. Prediction e. Exercises and Code Tues, April 02, 2019 Dr Georges Lentzas 7 Supervised Learning Thurs, April 04, 2019 Dr Georges Lentzas a. Classification i. Logistic and Softmax Regression ii. K-Nearest Neighbors iii. Classification and Regression Trees iv. Support Vector Machines v. Exercises and Code Tues, April 09, 2019 Dr Georges Lentzas b. Ensemble models Thurs, April 11, 2019 Dr Miquel Noguer i Alonso 8 Artificial Intelligence in Finance Institute

11 i. Bagging: Random Forests ii. Boosting Adaboost and XGBoost iii. Exercises and Code Tues, April 16, 2019 Dr Miquel Noguer i Alonso c. Regression Thurs, April 18, 2019 Dr Josh Joseph i. Linear Regression ii. Penalized Linear Regression: Lasso and Ridge iii. Non-Linear Regressions iv. Deep Regressions Tues, April 23, 2019 Dr Josh Joseph 8 Unsupervised Learning Thurs, April 25, 2019 Dr Mike Atwal a. Principal Component Analysis b. Clustering c. Exercises and Code Tues, April 30, 2019 Dr Mike Atwal 9 Deep Learning Thurs, May 02, 2019 Dr Larry Rudolph a. The mathematics of deep learning i. Mathematical definition ii. Optimization iii. Drop out b. Feedforward Neural Networks c. Recurrent Neural Networks d. Long Short Term Memory Networks e. Convolutional Neural Networks f. Generative Adversarial Networks g. Interpretability h. Exercises and Code Tues, May 07, 2019 Dr Larry Rudolph 10 Reinforcement Learning Thurs, May 09, 2019 Dr Igor Halperin a. Markov decision Processes b. Deep Reinforcement Learning c. Inverse Reinforcement Learning Tues, May 14, 2019 Dr Igor Halperin 11 Artificial Intelligence Thurs, May 16, 2019 Dr Miquel Noguer i Alonso a. Natural Language Processing i. Theory ii. Deep Learning for NLP iii. Applications iv. Exercises and Code Tues, May 21, 2019 Dr Miquel Noguer i Alonso 12 Practical Cases I Thurs, May 23, 2019 All professors a. AI and Investing b. AI and Risk and Banking Tues, May 28, 2019 All professors 13 Final Exam Tues, June 04, 2019 Faculty 14 Artificial Intelligence in Finance Project Tues, June 11,

12 Registration Form Start date: Tuesday March Regular Course Fee Full Course Fee: $9, Early Bird Discount 25% Discount until Friday February Discount code VOLUME DISCOUNT: If 2 or more people from your institution wish to take the course please contact us. To register, please fax or scan and the completed booking form to: info@aifinanceinstitute.com DELEGATE DETAILS NAME: FLEXIBLE PAYMENT OPTIONS: Option 1: Pay in full on Registration Option 2: Pay 50% on registration and 50% by April ORGANISATION: JOB TITLE: DEPARTMENT: ADDRESS: ZIPCODE: TELEPHONE: NATIONALITY: DATE: SIGNATURE: info@aifinanceinstitute.com / Tel:

13 69 Charlton St, New York, NY 10014