4,145 research outputs found
Dynamic evolution of cross-correlations in the Chinese stock market
We study the dynamic evolution of cross-correlations in the Chinese stock
market mainly based on the random matrix theory (RMT). The correlation matrices
constructed from the return series of 367 A-share stocks traded on the Shanghai
Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a
moving window with a size of 400 days. The evolutions of the statistical
properties of the correlation coefficients, eigenvalues, and eigenvectors of
the correlation matrices are carefully analyzed. We find that the stock
correlations are significantly increased in the periods of two market crashes
in 2001 and 2008, during which only five eigenvalues significantly deviate from
the random correlation matrix, and the systemic risk is higher in these
volatile periods than calm periods. By investigating the significant
contributors of the deviating eigenvectors in different moving windows, we
observe a dynamic evolution behavior in business sectors such as IT,
electronics, and real estate, which lead the rise (drop) before (after) the
crashes
Bloch's cycle complex and coherent dualizing complexes in positive characteristic
Let be a separated scheme of dimension of finite type over a perfect
field of positive characteristic . In this work, we show that Bloch's
cycle complex of zero cycles mod is quasi-isomorphic to
the Cartier operator fixed part of a certain dualizing complex from coherent
duality theory. From this we obtain new vanishing results for the higher Chow
groups of zero cycles with mod coefficients for singular varieties.Comment: 62 pages. Accepted for publication in Tran AMS. Compared to v2: Due
to an update of arXiv:1703.02269 concerning the normality condition (more
specifically, Thm. 8.6), Cor. 8.12 in our article is now changed. (The
statement in Cor. 0.2(6) remains valid.
Performance improvements of automobile communication protocols in electromagnetic interference environments
Electromagnetic Interference (EMI) is frequently encountered in automobile communication systems due to a large number of inductive nodes used in these systems. This thesis investigates the effects of EMI on two types of automobile communication systems, the Controller Area Network (CAN) and the FlexRay. It also proposes a modified Automatic Repeat reQuest (ARQ) scheme to improve the communication performances in EMI environments --Abstract, page iii
Hardware emulation of wireless communication fading channels
This dissertation investigates several main challenges to implementing hardware-based wireless fading channel emulators with emphasis on incorporating accurate correlation properties. Multiple-input multiple-output (MIMO) fading channels are usually triply-selective with three types of correlation: temporal correlation, inter-tap correlation, and spatial correlation. The proposed emulators implement the triply-selective fading Channel Impulse Response (CIR) by incorporating the three types of correlation into multiple uncorrelated frequency-flat Rayleigh fading waveforms while meeting real-time requirements for high data-rate, large-sized MIMO, and/or long CIR channels. Specifically, mixed parallel-serial computational structures are implemented for Kronecker products of the correlation matrices, which makes the best tradeoff between computational speed and hardware usage. Five practical fading channel examples are implemented for RF or underwater acoustic MIMO applications. The performance of the hardware emulators are verified with an Altera Field-Programmable Gate Array (FPGA) platform and the results match the software simulators in terms of statistical and correlation properties. The dissertation also contributes to the development of a 2-by-2 MIMO transceiver testbench that is used to measure real-world fading channels. Intensive channel measurements are performed for indoor fixed mobile-to-mobile channels and the estimated CIRs demonstrate the triply-selective correlation properties --Abstract, page iv
PUBLIC MENTAL HEALTH IN POST-COVID-19 ERA
Transmission of the 2019 novel coronavirus (COVID-19) has now rapidly spread around the world, which has alarming implications for individuals and communities, in particular for public mental health. Significant progress has been made in the prevention and control of the COVID-19 pandemic in China, but the psychological crisis caused by the epidemic is still not over and may continue to exist. The public mental health in the post-COVID-19 era should not be ignored. This article provides early warning for the public\u27s mental health in the post-COVID-19 era by listing the characteristics and duration of the public mental health crisis following the SARS outbreak. In addition, based on the current situation, specific methods and measures are proposed in order to provide effective reference for the prevention and control of psychological crisis caused by the COVID-19 epidemic
Dynamic structure of stock communities: A comparative study between stock returns and turnover rates
The detection of community structure in stock market is of theoretical and
practical significance for the study of financial dynamics and portfolio risk
estimation. We here study the community structures in Chinese stock markets
from the aspects of both price returns and turnover rates, by using a
combination of the PMFG and infomap methods based on a distance matrix. We find
that a few of the largest communities are composed of certain specific industry
or conceptional sectors and the correlation inside a sector is generally larger
than the correlation between different sectors. In comparison with returns, the
community structure for turnover rates is more complex and the sector effect is
relatively weaker. The financial dynamics is further studied by analyzing the
community structures over five sub-periods. Sectors like banks, real estate,
health care and New Shanghai take turns to compose a few of the largest
communities for both returns and turnover rates in different sub-periods.
Several specific sectors appear in the communities with different rank orders
for the two time series even in the same sub-period. A comparison between the
evolution of prices and turnover rates of stocks from these sectors is
conducted to better understand their differences. We find that stock prices
only had large changes around some important events while turnover rates surged
after each of these events relevant to specific sectors, which may offer a
possible explanation for the complexity of stock communities for turnover
rates
Robust Bayesian Variable Selection for Gene-Environment Interactions
Gene-environment (G×E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G×E studies have been commonly encountered, leading to the development of a broad spectrum of robust penalization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a robust Bayesian variable selection method for G×E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects. An efficient Gibbs sampler has been developed to facilitate fast computation. The Markov chain Monte Carlo algorithms of the proposed and alternative methods are efficiently implemented in C++
- …