Prof David Donoho from Stanford University reviews some of Prof John Ioannidis' work on scientific findings and statistics on financial fund performance. He discusses a paper of his own (with co-authors), from the Journal of Portfolio Management, called 'Is Patience a Virtue?"
Free and open to the public. Seating is on a first-come first-served basis.
John Ioannidis of University of Ioannina School of Medicine has memorably claimed that over 50% of all published research findings are false. If this is what we think about scientific findings, what should we think about statistics on financial fund performance? The speaker will review some of Ioannidis' work and then discuss a paper of his own (with co-authors), from the Journal of Portfolio Management, called 'Is Patience a Virtue? The case for the long view in evaluating fund performance'.
About the speaker
Prof David Donoho received his PhD from Harvard University in 1983. From1984 to 1990, he was on the faculty of the University of California, Berkeley before moving to Stanford. He is currently Anne T and Robert M Bass Professor of the Humanities and Sciences, and Professor of Statistics at Stanford University.
Prof Donoho's is instrumental in the development of compressed sensing, a powerful technique which has wide applications in many fields such as medical imaging, oil exploration, physical chemistry and astronomy. His work also includes the development of effective methods for the construction of low-dimensional representations for high-dimensional data problems (multiscale geometric analysis) and development of wavelets for denoising.
Prof Donoho is a fellow of the American Academy of Arts and Sciences, a SIAM Fellow, a foreign associate of the French Academy of Sciences, and a member of the US National Academy of Sciences. He won the Shaw Prize in Mathematical Sciences 2013 for his profound contributions to modern mathematical statistics, and in particular the development of optimal algorithms for statistical estimation in the presence of noise and of efficient techniques for sparse representation and recovery in large data-sets.
Free and open to the public. Seating is on a first-come first-served basis.
