We show that along with being a superior risk measure, Stable Expected Tail Loss (SETL) enables an elegant approach to portfolio optimization via convex optimization. We show that SETL portfolio optimization yields superior risk adjusted returns relative to Markowitz portfolios. Finally, we introduce an alternative investment performance measurement tools: the Stable Tail Adjusted Return Ratio (STARR), which is a generalization of the Sharpe ratio in the Stable Distribution Framework. Asset pricing and hedging models require the proper modeling of the return distribution of financial assets. In this course we propose the class of the GARCH tempered stable processes as appropriate model for financial return time series. We empirically test those processes and show their superiority over the classical Gaussian pricing models. Studying the impact of transaction costs the participants will learn how to mathematically model transaction costs, including slippage, taxes and costs, incorporate transaction costs into the Markowitz framework to select portfolios, gain an understanding of the impact of variable trading costs and trade size on rebalancing decisions, interpret the “no trade region”, expose hidden expected returns from differential portfolio selection performance.

There are some suggested criterion for audiences:

1. Working experience in financial industry
2. Laptop should be taken by audiences
3. Background of math
4. Software, such as Matlab

To be added

Professo Dr. Svetlozar (Zari) Rachev
Dr. Rachev is Professor in the Department of Applied Mathematics at Stony Brook University in New York. In addition, he will hold the title of Frey Family Foundation Professor in Quantitative Finance. Dr. Rachev is one of the world’s foremost authorities in the application of heavy-tailed distributions in finance. His 30 years of research culminated in three recently awarded patents at FinAnalytica, where he serves as Chief Scientist. He was a co-founder and President of Bravo Risk Management Group, originator of the Cognity methodology, acquired by FinAnalytica. In addition to his Chair-Professorship at Karlsruhe Institute of Technology, he is Professor Emeritus at the University of California, Santa Barbara in the Department of Statistics and Applied Probability. Rachev is the author of 14 books and over 300 published articles on finance, econometrics, probability, statistics and actuarial science.

Professor Dr. Andrew P. Mullhaupt
Dr. Mullhaupt is Research Professor at the Center for Quantitative Finance at Stony Brook University. His original research interests involved partial differential equations and linear algebra. Prior to joining the faculty at Stony Brook he worked for over 20 years on Wall Street designing mathematically based trading systems, first at Morgan Stanley, then at Renaissance Technologies, and most recently at SAC Capital Management, where he recently retired from his position as Director of Research for the SAC Meridian Fund.

Dr Boryana Racheva-Iotova
Ms. Boryana Racheva-Iotova is President of FinAnalytica. She leads FinAnalytica's Research & Development team and product development of the Cognity platform that offers risk and portfolio construction analytics for funds of funds, hedge funds and asset managers. She was co-founder and CEO of the Bravo Risk Management Group - the originator of the Cognity product suite, which was later acquired by FinAnalytica. She holds M. Sci. in Probability and Statistics at the Faculty of Mathematics and Informatics, Sofia University,and Ph.D. from the Faculty of mathematics, Informatics and Statistics at Ludwig-Maximilians-University, Munich, Germany. Her many articles have recently appeared in premier scientific journals and her forthcoming book will appear in Wiley-Finance. She has nearly 10 years of experience in building risk management solutions and utilizing the latest analytical advancements to meet the needs of financial industry practitioners.

To be added