Department of Mathematics & Statistics Calendar Week of November 20 - 26, 2006 Monday, November 20, 2006 Tuesday, November 21, 2006 Wednesday, November 22, 2006 THANKSGIVING BREAK BEGINS - NO CLASSES - OFFICES OPEN Thursday, November 23, 2006 HAPPY THANKSGIVING - THANKSGIVING BREAK CONTINUES NO CLASSES - OFFICES CLOSED Friday, November 24, 2006 THANKSGIVING BREAK CONTINUES - NO CLASSES - OFFICES CLOSED Saturday, November 25, 2006 Sunday, November 26, 2006 ******************************************************* Department of Mathematics & Statistics Calendar Week of November 27 - December 3, 2006 Monday, November 27, 2006 Tuesday, November 28, 2006 Wednesday, November 29, 2006 11:30 AM UGrad Stats Courses/Programs Discussion Group 400 MSc 2:30 PM Frame Theory Seminar 459 MSc Professor Wolf Iberkleid, BGSU Visiting Professor 3:30 PM Calculus Seminar 459 MSc Semester Wrap-Up 3:30 PM Statistics Seminar 445 MSc Dr. Wei NING, BGSU "Fitting Mixture Distributions Using Generalized Lambda Distributions (GLD’s): Examples, Comparisons with Normal Mixtures, and Computational Considerations" Thursday, November 30, 2006 1:30 PM Analysis Seminar 459 MSc George TURCU, BGSU "Hypercyclic Operators Which Do Not Satisfy the Hypercyclicity Criterion" 2:30 PM Foundational Math Committee 447 MSc Friday, December 1, 2006 11:30 AM Algebra Seminar 400 MSc Greg OMAN, Ohio State University "TBA" **12:00 Noon Calendar Information Due to Cyndi** for the next month's worth of calendar info **Dec. 4th (2006) - January 8th (2007)** 12:30 PM Undergraduate Committee Meeting 400 MSc 2:30 PM Graduate Student Seminar 400 MSc 3:30 PM Refreshments served prior to the colloquium--Coffee Lounge 3:45 PM Colloquium 459 MSc Dr. Gordon WADE, BGSU "Stock Price Covariance Estimation Incorporating Intraday Extremal Data" ABSTRACT: The correlation of the changes in stock prices over time is a fundamentally important ingredient in market analysis. Most conventional estimators for the correlation are based on historical records of end-of-day prices (which are publicly and widely available). The include the usual sample estimator, and variation ``weighted'' versions thereof. In addition to end-of-day price data, beginning-of-day and intraday extremal price data are also widely available, e.g., one may readily obtain historical records of the daily open, high, low, and closing prices for essentially any publicly traded stock. Our goal is to develop an estimator which incorporates this additional data, on the belief that such an estimator could be significantly more efficient than estimators based only on close-of-day prices. Toward this end, we derive the joint probability density function (PDF) for the normalized pairs of daily high, low, and closing prices for a pair of stocks (six variables in all), based on modeling the pair of prices as a vector-valued geometric Brownian motion with drift and absorbing boundary conditions. This PDF may then be used in the context of maximum likelihood estimation. The PDF thus derived is given in terms of the solution of an anisotropic diffusion equation posed on rectangular domain. A significant portion of the effort, then, lies in understanding and obtaining solutions to this diffusion equation. Thus this talk lies at the intersection of mathematical finance, stochastic differential equations, and partial differential equations. Numerical results will be presented. NAME="C"> Saturday, December 2, 2006 Preview Day OPEN HOUSE Sunday, December 3, 2006
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