抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

计量经济分析 = Econometric analysis

In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Forecasting, Structural Time Series Models and the Kalman Filter

Econometric policy evaluation: A critique

Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

Modelling Financial Time Series

This paper reexamines Asian stock market contagion by applying a dynamic multivariate GARCH model to daily stock-return data in nine Asian countries and the United States during the period from 1996 to 2003. The empirical results find supportive evidence of a contagion effect. By analyzing the correlation-coefficient series, this paper identifies two phases of the Asian crisis. The first phase shows an increase in correlation (contagion) and the second phase shows continued high correlation (herding). Statistical analysis of the correlation coefficients shows shifts in the level as well as in the variance of the correlation coefficients during the crisis period, casting some doubt on the benefit of international portfolio diversification. This study finds that international rating agents play significant role in shaping the structure of dynamic correlations in the Asian markets.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1052661_code365382.pdf?abstractid=1052661&type=2

Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Countries

http://www.pages.drexel.edu/~chiangtc/JIMF_Paper_Chiang_Jeon_Li_11_28_2005.pdf

Dynamic correlation analysis of financial contagion: Evidence from Asian markets

This paper examines herding behavior in global markets. By applying daily data for 18 countries from May 25, 1988, through April 24, 2009, we find evidence of herding in advanced stock markets (except the US) and in Asian markets. No evidence of herding is found in Latin American markets. Evidence suggests that stock return dispersions in the US play a significant role in explaining the non-US market’s herding activity. With the exceptions of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. Evidence suggests that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. During crisis periods, we find supportive evidence for herding formation in the US and Latin American markets.

An empirical analysis of herd behavior in global stock markets

This study examines herding behavior in dual-listed Chinese A-share and B-share stocks. We find evidence of herding within both the Shanghai and Shenzhen A-share markets that are dominated by domestic individual investors, and also within both B-share markets, in which foreign institutional investors are the main participants. Herding occurs in both rising and falling market conditions. Herding behavior by A-share investors in the Shanghai market is more pronounced under conditions of rising markets, high trading volume, and high volatility, while no asymmetry is apparent in the B-share market.

Thomas C. Chiang

Papers

Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Countries

Dynamic correlation analysis of financial contagion: Evidence from Asian markets

An empirical analysis of herd behavior in global stock markets

Herding behavior in Chinese stock markets: An examination of A and B shares

Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis