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Talks in Financial and Insurance Mathematics
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This is the regular weekly research seminar on Insurance Mathematics and Stochastic Finance.
Spring Semester 2017
Note: The highlighted event marks the next occurring event.
Date / Time | Speaker | Title | Location | |
---|---|---|---|---|
23 February 2017 17:15-18:15 |
Mathias Beiglböck TU Wien |
Brenier-type results in Martingale Optimal Transport | HG G 43 | |
Abstract: A seminal result in optimal transport is Brenier's theorem on the structure of the optimal plan for squared distance costs. We briefly review related results on the martingale version of the transport problem and connections with robust finance and the Skorokhod embedding problem. We then introduce a continuous time Brenier-type theorem for the martingale transport problem which exhibits a particularly simple functional form. Finally, we explain a link of this result with the local vol model. | ||||
2 March 2017 17:15-18:15 |
Anthony Réveillac INSA de Toulouse |
A Black-Scholes type formula for the pricing of some reinsurance contract | HG G 43 | |
Abstract: In this talk we will derive, using the Malliavin calculus, a new formula which can be thought as a counterpart for some reinsurance contracts of the celebrated Black-Scholes formula in Finance. Our approach allows one for instance to consider claims that may depend on the intensity of the underlying counting process defining the risk process. This constitutes a joint work with Caroline Hillairet (ENSAE - Paris) and Ying Jiao (ISFA - Lyon). | ||||
9 March 2017 17:15-18:15 |
Juan-Pablo Ortega Universität Sankt Gallen |
Time-delay reservoir computers: nonlinear stability of functional differential systems and optimal nonlinear information processing capacity. Applications to stochastic nonlinear time series forecasting | HG G 43 | |
Abstract: Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus on a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This talk addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional link between the reservoir parameters and its performance. This function is used to explore various properties of the device and to choose the optimal reservoir architecture, thus replacing the tedious and time consuming parameter scannings used so far in the literature. | ||||
23 March 2017 17:15-18:15 |
Walter Schachermayer University of Vienna |
Title T.B.A. | HG G 43 | |
30 March 2017 17:15-18:15 |
Fred Espen Benth University of Oslo |
Title T.B.A. | HG G 43 | |
6 April 2017 17:15-18:15 |
Lisa R. Goldberg Berkeley |
Identifying Financial Risk Factor with Sparse and Low-Rank Decompositions | HG G 43 | |
Abstract: We show how to use sparse and low-rank (SLR) matrix decompositions based on convex optimization to extract financial risk factors from a sample return covariance matrix. We provide an example that highlights the difference between this approach and the academic standard for financial factor identification, principal component analysis (PCA), which makes systematic errors. Using finance-oriented metrics, we analyze the accuracy of SLR and PCA on equally weighted portfolios and minimum variance portfolios in a simulated global equity market. Finally, we discuss non-convex programming formulations that show promise in identifying numerous sparse factors (industries, counties, etc) at various scales. A preprint that gives some background on what we’re up to is linked here: https://papers.ssrn.com/sol3/papers2.cfm?abstract_id=2800237 and more information can be found ion this page: http://cdar.berkeley.edu/research/risk-factors-and-low-rank-sparse-decompositions/ | ||||
20 April 2017 17:15-18:15 |
Tom Hurd McMaster University |
Title T.B.A. | HG G 43 | |
27 April 2017 17:15-18:15 |
Scott Robertson Boston University |
Title T.B.A. | HG G 43 | |
4 May 2017 17:15-18:15 |
Ari-Pekka Perkkiö LMU-Münich |
Title T.B.A. | HG G 43 | |
11 May 2017 17:15-18:15 |
Chris Rogers University of Cambridge |
Title T.B.A. | HG G 43 | |
18 May 2017 17:15-18:15 |
Felix Kübler University of Zürich |
Title T.B.A. | HG G 43 | |
25 May 2017 |
Ascension day | |||
1 June 2017 17:15-18:15 |
Hanspeter Schmidli University of Cologne |
Title T.B.A. | HG G 43 |
Archive: SS 17 AS 16 SS 16 AS 15 SS 15 AS 14 SS 14 AS 13 SS 13 AS 12 SS 12 AS 11 SS 11 AS 10 SS 10 AS 09