Mathematical Finance Internal Seminar
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Thu, 29/04/2010 13:00 |
Zhongmin Qian (Oxford) |
Mathematical Finance Internal Seminar  |
DH 1st floor SR |
| This talk I present a study of BSDEs with non-linear terms of quadratic growth by using Girsanov's theorem. In particular we are able to establish a non-linear version of the Cameron-Martin formula, which can be for example used to obtain gradient estimates for some non-linear parabolic equations. | |||
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Thu, 13/05/2010 13:00 |
Jose Martinez (SBS) |
Mathematical Finance Internal Seminar |
DH 1st floor SR |
| Using a large panel data set of Swedish pension savers (75,000 investors, daily portfolios 2000-2008) we show that active investors outperform inactive investors and that there is a causal effect of fund switches on performance. The higher performance is earned not by market timing, but by dynamic fund picking (within the same asset class). While activity is positive for the individual investor, there are indications that it generates costs for other investors. | |||
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Thu, 27/05/2010 13:00 |
Vincent Crawford (Economics) |
Mathematical Finance Internal Seminar |
DH 1st floor SR |
| The talk concerns experiments that study strategic thinking by eliciting subjects’ initial responses to series of different but related games, while monitoring and analyzing the patterns of subjects’ searches for hidden but freely accessible payoff information along with their decisions. | |||
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Thu, 10/06/2010 13:00 |
Junna Bi (Oxford) |
Mathematical Finance Internal Seminar |
DH 1st floor SR |
| A behavioral mean-variance portfolio selection problem in continuous time is formulated and studied. Based on the standard mean-variance portfolio selection problem, the cumulative distribution function of the cash flow is distorted by a probability distortion function. Then the problem is no longer a convex optimization problem. This feature distinguishes it from the conventional linear-quadratic (LQ) problems. The stochastic optimal LQ control theory no longer applies. We take the quantile function of the terminal cash flow as the decision variable. The corresponding optimal terminal cash flow can be recovered by the optimal quantile function. Then the efficient strategy is the hedging strategy of the optimal terminal cash flow. | |||
