Imperial College London > Talks@ee.imperial > Control and Power Seminars > Topics in Financial Data Science Part II

Topics in Financial Data Science Part II

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  • UserGiuseppe Calafiore, Politecnico di Torino
  • ClockWednesday 27 March 2019, 10:00-12:00
  • House408.

If you have a question about this talk, please contact Giordano Scarciotti.

Abstract: Data science finds a natural field of application in finance, a domain in which an abundance of data is available. In this short course we shall discuss some selected topics related to the analysis of market data, the effective estimation of key quantities of interest in investment decisions and in risk analysis, and their use in optimization for financial decision making.

Program: Tue. March 26 (1.5 hrs): Introduction. Financial price and return series. Making sense of high dimensional data. Projections. Principal Component Analysis. Factor Models. Sparse PCA . Covariance estimation. Shrinkage. Sparse precision models. Wed. March 27 (1.5 hrs): Return/risk tradeoff models. Portfolio optimization. Transaction costs, market impact, diversification. Robustness.

Biography: Giuseppe C. Calafiore, is a full professor at DET , Politecnico di Torino, where he coordinates the Systems and Data Science lab, and an associate fellow of the IEIIT -CNR. Dr. Calafiore held several visiting positions at international institutions: at the Information Systems Laboratory (ISL), Stanford University, California, in 1995; at the Ecole Nationale SupĆ©rieure de Techniques AvanceĆ©s (ENSTA), Paris, in 1998; and at the University of California at Berkeley, in 1999, 2003, 2007, 2017 and 2018. He was a Senior Fellow at the Institute of Pure and Applied Mathematics (IPAM), University of California at Los Angeles, in 2010. Dr. Calafiore is the author of more than 180 journal and conference proceedings papers, and of eight books. He is a Fellow of the IEEE . He received the IEEE Control System Society ``George S. Axelby’’ Outstanding Paper Award in 2008. His research interests are in the fields of convex optimization, randomized algorithms, identification, and control of uncertain systems, with applications ranging from finance and economic systems to robust control, machine learning, and robotics. Dr. Calafiore currently teaches a MS course on Convex Optimization and MS course on Optimization for Machine Learning at PoliTo, and a Master course on Financial Data Science at the Berkeley Haas Business School.

This talk is part of the Control and Power Seminars series.

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