Event(s) on June 2009

• 4/6/2009

  題目:	Fractional differential equations and continuous time random walk model
  講員:	Prof. Kazufumi ITO, Department of Mathematics, North Carolina State University, USA
  時間/地點:	11:30  -  12:30 FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
  摘要:	In this talk we discuss the wellposedness of time and space fractional power equations in a Hilbert space. Our analysis is based on the semigroup approach and we derive the solution property and numerical approximations. Application of such equation include the continuous time random walk (CTRW) process modeling of ground water flow and mathematical finance.

  
  

• 15/6/2009

  題目:	SRCC DLS: Seeking Interpretable Models for High Dimensional Data
  講員:	Prof. Bin Yu, University of California, Berkeley, USA
  時間/地點:	11:00  -  12:30 (Preceded by Reception at 10:30am) LT3, Ho Sin Hang Campus, Hong Kong Baptist University
  摘要:	Extracting useful information from high-dimensional data is the focus of today's statistical research and practice. After broad success of statistical machine learning on prediction through regularization, interpretability is gaining attention and sparsity has been used now as its proxy. With the virtues of both regularization and sparsity, Lasso L1 penalized L2 minimization) has been very popular recently. In this talk, I would like to discuss the theory and practice of sparse modeling. First, I will give an overview of recent research on model selection consistency property of l1 penalized minimization including Lasso and explain what useful insights have been learned. Second I will present collaborative research on building nonparametric sparse hierarchical models that describe fMRI responses in primary visual cortex area V1 to natural images.

  
  

• 24/6/2009

  題目:	JRIAM DLS: A Unified Framework for Dynamic Pari-Mutuel Information Market Design: A Case of On-Line Optimization
  講員:	Prof. Yinyu Ye, Department of Management Science and Engineering, Stanford University, USA
  時間/地點:	11:00  -  12:00 (Preceded by Reception at 10:30am) LT2, Cha Chi-Ming Science Tower, HSH Campus, Hong Kong Baptist University
  摘要:	Recently, several pari-mutuel mechanisms have been introduced to organize prediction markets, such as the logarithmic scoring rule, the cost function formulation, and sequential convex pari-mutuel mechanism (SCPM). In this work, we develop a unified framework that bridges these seemingly unrelated models for centrally organizing contingent-claim markets. Our framework establishes necessary and sufficient conditions for designing mechanisms with many desirable properties such as proper scoring, truthful bidding (in a myopic sense), efficient computation, controllable risk-measure, and guarantees on the worst-case loss. As a result, we develop the very first proper, truthful, risk-controlled, loss-bounded, and polynomial-time scoring rule, which neither of the previous proposed mechanisms possesses simultaneously. Thus, in addition to providing a general framework that unifies and explains all the existing mechanisms, our work would be an effective and instrumental tool in designing new market mechanisms. We also discuss applications of our framework to general open markets for dynamic resource pricing and allocation. This is a joint work with Shipra Agrawal, Erick Delage, Mark Peters, Anthony So, and Zizhuo Wang.

  
  

• 30/6/2009

  題目:	CDO Pricing with Multifactor and Copulae Models
  講員:	Prof. Hardle Wolfgang, Center for Applied Statistics and Econometrics (CASE), Institute for Statistics and Econometrics, Humboldt-Universitat zu Berlin, Germany
  時間/地點:	11:30  -  12:30 FSC1217, Fong Shu Chuen Library, HSH Campus, Hong Kong Baptist University
  摘要:	Modeling the portfolio credit risk is one of the crucial issues of the last years in the financial problems. We propose the valuation model of Collateralized Debt Obligations based on a one- and two-parameter copula and default intensities estimated from market data. The presented method is used to reproduce the spreads of the iTraxx Europe tranches. The two-parameter model incorporates the fact that the risky assets of the CDO pool are chosen from six different industry sectors. The dependency among the assets from the same group is described with the higher value of the copula parameter, otherwise the lower value of the parameter is ascribed. Our approach outperforms the standard market pricing procedure based on the Gaussian distribution.