Reducing Asset Weights' Volatility by Importance Sampling in Stochastic Credit Portfolio Optimization

The objective of this paper is to study the effect of importance sampling (IS) techniques on stochastic credit portfolio optimization methods. I introduce a framework that leads to a reduction of volatility of resulting optimal portfolio asset weights. Performance of the method is documented in terms of implementation simplicity and accuracy. It is shown that the incorporated methods make solutions more precise given a limited computer performance by means of a reduced size of the initially necessary optimization model. For a presented example variance reduction of risk measures and asset weights by a factor of at least 350 was achieved. I finally outline how results can be mapped into business practice by utilizing readily available software such as RiskMetrics� CreditManager as basis for constructing a portfolio optimization model that is enhanced by means of IS. Dieser Beitrag soll die Auswirkung der Anwendung von Importance Sampling (IS) Techniken in der stochastischen Kreditportfoliooptimierung aufzeigen. Es wird ein Modellaufbau vorgestellt, der zu einer deutlichen Reduktion der Volatilität der Wertpapieranteilsgewichte führt. Durch eine Darstellung der verhältnismäßig einfachen Berücksichtigung der Importance Sampling Technik im Optimierungsverfahren sowie durch ein empirisches Beispiel wird die Leistungsfähigkeit der Methode dargelegt. In diesem Anwendungsbeispiel kann die Varianz der Schätzer sowohl für die Risikomaße als auch für die optimalen Anteilsgewichte um einen Faktor von mindestens 350 reduziert werden. Es wird somit gezeigt, dass die hier vorgestellte Methode durch eine Reduktion der Größe des ursprünglich notwendigen Optimierungs-problems die Genauigkeit von optimalen Lösungen erhöht, wenn nur eine begrenzte Rechnerleistung zur Verfügung steht. Abschließend wird dargelegt, wie die Lösungsansätze in der Praxis durch eine Ankopplung an existierende Softwarelösungen im Bankbetrieb umgesetzt werden können. Hierzu wird ein Vorgehen skizziert, das auf den Ergebnissen des Programms CreditManager von RiskMetrics ein Portfoliooptimierungsmodell aufbaut. Dieses wird um eine Importance Sampling Technik erweitert.Kreditrisiko ; Stochastische Optimierung; Varianzreduktion ; CVaR; CVaR ; credit risk ; stochastic portfolio optimization ; importance sampling ; CreditMetrics ; CreditManager

Understanding and predicting where people look in images

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 115-126).For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. This is a challenging task given that no one fully understands how the human visual system works. This thesis explores the way people look at different types of images and provides methods of predicting where they look in new scenes. We describe a new way to model where people look from ground truth eye tracking data using techniques of machine learning that outperforms all existing models, and provide a benchmark data set to quantitatively compare existing and future models. In addition we explore how image resolution affects where people look. Our experiments, models, and large eye tracking data sets should help future researchers better understand and predict where people look in order to create more powerful computational vision systems.by Tilke Judd.Ph.D

Apparent ridges for line drawing

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 69-72).Non-photorealistic line drawing depicts 3D shapes through the rendering of feature lines. A number of characterizations of relevant lines have been proposed but none of these definitions alone seem to capture all visually-relevant lines. We introduce a new definition of feature lines based on two perceptual observations. First, human perception is sensitive to the variation of shading, and since shape perception is little affected by lighting and reflectance modification, we should focus on normal variation. Second, view-dependent lines better convey the shape of smooth surfaces better than view-independent lines. From this we define view-dependent curvature as the variation of the surface normal with respect to a viewing screen plane, and apparent ridges as the locus points of the maximum of the view-dependent curvature. We derive the equation for apparent ridges and present a new algorithm to render line drawings of 3D meshes. We show that our apparent ridges encompass or enhance aspects of several other feature lines.by Tilke Judd.S.M

A Benchmark of Computational Models of Saliency to Predict Human Fixations

Many computational models of visual attention have been created from a wide variety of different approaches to predict where people look in images. Each model is usually introduced by demonstrating performances on new images, and it is hard to make immediate comparisons between models. To alleviate this problem, we propose a benchmark data set containing 300 natural images with eye tracking data from 39 observers to compare model performances. We calculate the performance of 10 models at predicting ground truth fixations using three different metrics. We provide a way for people to submit new models for evaluation online. We find that the Judd et al. and Graph-based visual saliency models perform best. In general, models with blurrier maps and models that include a center bias perform well. We add and optimize a blur and center bias for each model and show improvements. We compare performances to baseline models of chance, center and human performance. We show that human performance increases with the number of humans to a limit. We analyze the similarity of different models using multidimensional scaling and explore the relationship between model performance and fixation consistency. Finally, we offer observations about how to improve saliency models in the future

Nanomechanical resonators operating as charge detectors in the nonlinear regime

We present measurements on nanomechanical resonators machined from Silicon-on-Insulator substrates. The resonators are designed as freely suspended Au/Si beams of lengths on the order of 1 - 4 um and a thickness of 200 nm. The beams are driven into nonlinear response by an applied modulation at radio frequencies and a magnetic field in plane. The strong hysteresis of the magnetomotive response allows sensitive charge detection by varying the electrostatic potential of a gate electrode.Comment: 8 pages, 6 figure

Caledonian structure, metamorphism, geochronology, and tectonics of the Sitas-Singis area, Sweden

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1987.MICROFICHE COPY AVAILABLE IN ARCHIVES AND LINDGREN.8 maps in pocket of volume 1.Bibliography: leaves 215-223.by Peter Gerhard Tilke.Ph.D

Multi-core strategies for particle methods

This paper discusses the implementation of particle based numerical methods on multi-core machines. In contrast to cluster computing, where memory is distributed across machines, multi-core machine can share memory across all cores. Here general strategies are developed for spatial management of particles and sub-domains that optimize computation on shared memory machines. In particular, we extend cell hashing so that cells bundle particles into orthogonal tasks that can be safely distributed across cores avoiding the use of "memory locks" while still protecting against race conditions. Adjusting task size provides for optimal load balancing and maximizing cache hits. Additionally, the way in which tasks are mapped to execution threads has a significant influence on the memory footprint and it is shown that minimizing memory usage is one of the most important factors in achieving execution speed and performance on multi-core. A novel algorithm called H-Dispatch is used to pipeline tasks to processing cores. The performance is demonstrated in speed-up and efficiency tests on a smooth particle hydrodynamics (SPH) flow simulator. An efficiency of over 90% is achieved on a 24-core machine