Browsing by Author "Chen, Ying"

Now showing items 1-12 of 12

2007-02-13Dissertation

Adaptive risk management

Chen, Ying

In den vergangenen Jahren ist die Untersuchung des Risikomanagements vom Baselkomitee angeregt, um die Kredit- und Bankwesen regelmäßig zu aufsichten. Für viele multivariate Risikomanagementmethoden gibt es jedoch ...
2015-04-22Buch

An Adaptive Approach to Forecasting Three Key Macroeconomic Variables for Transitional China

Niu, Linlin; Xu, Xiu; Chen, Ying

We propose the use of a local autoregressive (LAR) model for adaptive estimation and forecasting of three of China’s key macroeconomic variables: GDP growth, inflation and the 7-day interbank lending rate. The approach ...
2016-08-04Buch

Forecasting Limit Order Book Liquidity Supply Demand Curves with Functional AutoRegressive Dynamics

Chen, Ying; Chua, Wee Song; Härdle, Wolfgang Karl

Limit order book contains comprehensive information of liquidity on bid and ask sides. We propose a Vector Functional AutoRegressive (VFAR) model to describe the dynamics of the limit order book and demand curves and utilize ...
2006-11-16Buch

GHICA - Risk Analysis with GH Distributions and Independent Components

Chen, Ying; Härdle, Wolfgang Karl; Spokoiny, Vladimir

Over recent years, study on risk management has been prompted by the Basel committeefor regular banking supervisory. There are however limitations of some widely-used riskmanagement methods that either calculate risk ...
2009-01-22Buch

Localized Realized Volatility Modelling

Chen, Ying; Härdle, Wolfgang Karl; Pigorsch, Uta

With the recent availability of high-frequency Financial data the long range dependence of volatility regained researchers' interest and has lead to the consideration of long memory models for realized volatility. The long ...
2005-02-06Masterarbeit

Multivariate Risikomanagement

Chen, Ying

In this thesis we propose a risk management methodology to high-dimensional financial portfolios. Instead of estimating the joint density of the portfolios in a high-dimensional space, we are encouraged by using the ...
2004-10-27Buch

Nonparametric Risk Management with Generalized Hyperbolic Distributions

Chen, Ying; Härdle, Wolfgang Karl; Jeong, Seok-Oh

In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution ...
2005-12-15Buch

Portfolio Value at Risk Based on Independent Components Analysis

Chen, Ying; Härdle, Wolfgang Karl; Spokoiny, Vladimir

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks ...
2009-07-09Zeitschriftenartikel

Pre-transplant serum concentrations of anti-endothelial cell antibody in panel reactive antibody negative renal recipients and its impact on acute rejection

Han, Fei; Lv, Rong; Jin, Juan; Wu, Jianyong; Chen, Ying; Wang, Huiping; Chen, Jianghua

Background: Endothelial cell antigens are important targets in acute rejection (AR). Our goal was to measure the serum concentrations of pre-transplant anti-endothelial cell antibody (AECA) in panel reactive antibody (PRA) ...
2015-04-17Buch

Risk Related Brain Regions Detected with 3D Image FPCA

Chen, Ying; Härdle, Wolfgang Karl; Qiang, He; Majer, Piotr

Risk attitude and perception is re ected in brain reactions during RPID experiments. Given the fMRI data, an important research question is how to detect risk related regions and to investigate the relation between risk ...
2007-01-16Buch

Robust Risk Management

Chen, Ying; Spokoiny, Vladimir

In the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods ...
2011-08-19Buch

TVICA

Chen, Ray-Bing Chen; Chen, Ying; Härdle, Wolfgang Karl

Source extraction and dimensionality reduction are important in analyzing high dimensional and complex financial time series that are neither Gaussian distributed nor stationary. Independent component analysis (ICA) method ...