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A General Overview of Microsoft Treasury - From Investing $65 Billion in Assets to Managing the Associated Risks

Time
Speaker
George Zinn

Computational Finance Seminar As Corporate Vice President and Treasurer, George Zinn is responsible for overseeing Microsoft's corporate assets. He leads a group which manages the company's worldwide financial and corporate risk, investment portfolio, strategic portfolio, foreign exchange, corporate and structured project finance, dilution management, cash and liquidity, customer financing, and credit activities. In addition, Treasury has an important role in a range of initiatives across the spectrum from compensation through acquisitions and IP licensing.

Building
Room
295

Statistical Estimation From an Optimization Viewpoint

Time
Speaker
Lisa Korf

This lecture focuses on problems of density estimation (both parametric and nonparametric) and if there is time, time series estimation (no pun intended). When formulated as optimization problems, consistency of the estimators becomes a question of whether a sequence of optimization problems converge in an appropriate sense to the true problem. The tools of variational analysis are used to examine the question of consistency for these problems. In particular, an epigraphical ergodic theorem can be used to show consistency for a broad class of estimation problems.

Building
Room
389

Recidivism and Social Interactions

Time
Speaker
Sibel Sirakaya

Faced with overcrowded prisons, the courts have been increasingly passing probation sentences for adults convicted of felony crimes. Using a national sample, this paper identifies the risk factors for recidivism among Female, Male, Black, White and Hispanic felony probationers. Individual hazard function is assumed to depend on individual and neighborhood characteristics as well as social interactions among probationers. In selecting the covariates from a set of potential candidates, Bayesian model averaging is used both to account for model uncertainty and the subsequent inference.

Building
Room
389

What is the \'True Price\'? - State Space Models for High Frequency Financial Data

Time
Speaker
John Moody

Tick-by-tick interbank foreign exchange (FX) price series exhibit statistically- significant structures on various time scales. These include negative autocorrelations in tick-by-tick returns and positive autocorrelations (trends) on longer time scales. To account for the observed structures, we propose state space models for financial time series in which the observed price is a noisy version of an unobserved, less-noisy ``True Price\'\' process.

Building
Room
389

Considerations and Approaches Regarding the Deconvolution of an Unknown Function of One Variable From a Finite Set of Measurements

Time
Speaker
Brad Bell

Deconvolution of an unknown function of one variable from a finite set of measurements is an ill-posed problem. Placing a Bayesian prior on a function space is one way to extend the scientific model and obtain a well-posed problem. This problem can be well-posed even if the relationship between the unknown function and the measurements, as well as the function space prior, has unknown parameters. We present a method for estimating the unknown parameters by maximizing an approximation of the marginal likelihood where the unknown function has been integrated out.

Building
Room
389

Bayesian Analysis of Multi-Model Ensembles for Assessing Uncertainty in Climate Change Projections

Time
Speaker
Claudia Tebaldi

Different General Circulation Models (GCMs) produce different climate change projections, especially when evaluated at subcontinental (regional) scales. When it is time to try and combine their responses into a summary measure, and relative uncertainty bounds, it makes sense to weigh more the output of those GCMs that show better performance in reproducing present day climate (i.e. have smaller bias) and that agree with the majority (i.e. do not seem like outliers).

Building
Room
389

Stochastic Models That Separate Fractal Dimension and Hurst Effect

Time
Speaker
Tilmann Gneiting ARTICLE

Fractal behavior and long-range dependence have been described in an astonishing number of physical, biological, geological, and socio-economic systems. Time series, profiles, and surfaces have been characterized by their fractal dimension, a measure of roughness, and by the Hurst coefficient, a measure of long-memory dependence. Either phenomenon has been modeled and explained by self-similar random functions, such as fractional Gaussian noise and fractional Brownian motion.

Building
Room
389

Pragmatic Bayesian Designs For Clinical Trials

Time
Speaker
Lurdes Y.T. Inoue

In this talk we discuss the application of Bayesian methods in the design of clinical trials. In the first part of the talk we discuss sample size determination. A broad range of frequentist and Bayesian methods for sample size determination can be described as choosing the smallest sample that is sufficient to achieve some set of goals. An example for the frequentist is seeking the smallest sample size that is sufficient to achieve a desired power at a specified significance level.

Building
Room
389

Approximate Bayesian Computation Under Model Uncertainty, with Application to Protein Network Evolution

Time
Speaker
Sylvia Richardson

Data-generating stochastic processes arise naturally in many disciplines, for example biology, ecology or epidemiology. In many cases, because interesting models are highly complex, the likelihood f(xo | θ, M) of such implicit scientific models M is intractable. This hampers scientific progress in terms of iterative data acquisition, parameter inference, model checking and model refinement within a Bayesian framework. Nevertheless, given a value of θ, it is usually possible to simulate data from f(.|θ, M).

Building
Room
389

Tail Risk Budgeting

Time
Speaker
R. Douglas Martin

Risk budgeting is a methodology that has become increasingly popular over the last decade as a relatively transparent alternative to rebalancing portfolios via a black-box portfolio optimization method. We begin by briefly reviewing “classical” risk budgeting methodology based on volatility (standard deviation) of returns as the risk measure.

Building
Room
389