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Dr. Qian, CFA and chief investment officer of the multi asset group at PanAgora Asset Management
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| Title: To Rebalance or Not to Rebalance: A Statistical Comparison of Terminal Wealth of Fixed-Weight and Buy-and-Hold Portfolios |
| Abstract: We carry out statistical analysis under a variety of return assumptions and portfolio settings. For long-only portfolios, we show buy-and-hold approach leads to higher expected terminal wealth but also higher variance of terminal wealth. When there are serial correlations in asset returns, we demonstrate quantitatively that for long-only portfolios mean-reverting returns are relatively more favorable to fixed-weight portfolios whereas trending returns are relatively more favorable to buy-and-hold portfolios. For long-short portfolios, however, the effects of portfolio rebalancing are markedly different from long-only portfolios, mainly due to portfolio leverage. For example, we prove that fixed-weight approach often leads to higher expected value of terminal wealth. But it may also lead to higher variance of terminal wealth although it is not always the case. Furthermore, the effects of serial return correlations on long-short portfolios could be opposite of the effects on long-only portfolios. The overall results suggest that fixed-weight portfolios with portfolio rebalancing are more likely to have better risk-adjusted terminal wealth than buy-and-hold portfolios. |
AUTHOR
Michael Grabchak
Wed. April 9 at 3:30-4:30pm in Fretwell 306
Categories: Spring 2022
Wed, Feb 19 at 11:00am in the conference room
Categories: Spring 2022
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Dr. JaEun Ku, Oklahoma State University
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| Title: Solver-friendly hybrid mixed finite element methods |
| Abstract:
A new hybrid mixed finite element method to compute the flux variable
accurately and efficiently will be introduced. The method is a two–step method, based on a system of first-order equations for second-order elliptic partial differential equations. On a coarse mesh, the primary variable is approximated by a standard Galerkin method. Then, on a fine mesh, an H(div) projection is sought as an accurate approximation for the flux variable. The computation on a finer mesh can be carried out very efficiently using well developed preconditioners for the H(div) projection. Also, it will be shown that the mesh size h for the finer mesh can be taken as a square of the coarse meshsize H. This is a joint work with Dr. Young Ju Lee and Dr. Dongwoo Sheen. |
Friday, Nov 15 at 3:00pm in the conference room
Categories: Spring 2022
| Xiaoyu Fu, Sichuan University, China |
| Title: A unified treatment for controllability and observability of PDEs and its application |
| Abstract:
The purpose of this talk is to present a unified treatment on controllability/observability problems for PDEs. The starting point is some fundamental weighted identities for partial differential operators, via which one can derive suitable global Carleman estimates. Meanwhile, based on this weighted identity, we will give its application in the stability of inverse acoustic wave problems.
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Friday, Nov 1 at 2:00pm in the conference room
Categories: Past Talks
| Annie (Peiyong) Qu, University of Illinois, Urbana-Champaign |
| Title: Time-varying networks estimation and dynamic model selection |
| Abstract: In many biomedical and social science studies, it is very important to identify and predict the dynamic changes of associations among network data over time. We propose a varying-coefficient model to incorporate time-varying network data, and impose a piecewise penalty function to capture local features of the network associations. The advantages of the proposed approach are that it is nonparametric and therefore flexible in modeling dynamic changes of association for network data problems, and capable of identifying the time regions when dynamic changes of associations occur. To achieve local sparsity of network estimation, we implement a group penalization strategy involving overlapping parameters among different groups. However, this imposes great challenges in the optimization process for handling large-dimensional network data observed at many time points. We develop a fast algorithm, based on the smoothing proximal gradient method, which is computationally efficient and accurate. We illustrate the proposed method through simulation studies and children’s attention deficit hyperactivity disorder fMRI data, and show that the proposed method and algorithm efficiently recover the dynamic network changes over time. The proposed approach works especially well when networks are sparse. This is joint work with Xinxin Shu. |
Friday, Nov 8 at 2:00pm in Fretwell 205
Categories: Past Talks
| (Tony) Jianguo Sun, University of Missouri, Columbia MO |
| Title: Regression Analysis of Longitudinal Data with Informative Observation Times and Application to Medical Cost Data |
Abstract: The analysis of longitudinal data with informative observation processes has recently attracted a great deal of attention and some methods have been developed. However, most of those methods treat the observation process as a recurrent event process, which assumes that one observation can immediately follow another. Sometimes, this is not the case, as there may be some delay or observation duration. Such a process is often referred to as a recurrent episode process. One example is the medical cost related to hospitalization, where each hospitalization serves as a single observation. For the problem, we present a joint analysis approach for regression analysis of both longitudinal and observation processes and a simulation study is conducted that assesses the finite sample performance of the approach. The asymptotic properties of the proposed estimates are also given and the method is applied to the medical cost data that motivated this study. |
Wednesday, Aug 21 at 11:00am in the conference room
Categories: Past Talks
| Jae Woo Jeong, Miami University, Hamilton Ohio |
| Isogeometric analysis of plates with cracks |
| ABSTRACT: The mapping techniques for isogeometric analysis, introduced by Jeong et al. (2013), is an effective method for dealing with crack singularities of elliptic boundary value problems. In some sense, the mapping techniques is similar to the Method of Auxiliary Mapping(MAM), introduced by Babuska and Oh (1990), for conventional Finite Element Methods(FEM). However, unlike MAM, the mapping techniques make it possible to independently control the radial and angular direction of the function to be approximated as far as the point singularities are concerned.The vertical displacement of a thin plate is governed by a fourth order elliptic equation and thus the approximation functions for numerical solutions are required to have continuous partial derivatives. Hence, the conventional FEM has difficulties to solve the fourth order problems. In order to deal a plate problem with crack effectively, the approximation functions must be smooth except at the crack tip and have singularity at the crack. In this talk, I will discuss recent results and ongoing works on isogeometric analysis, including a way to construct such approximation functions. |