A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection

This paper develops a novel time-varying multivariate Copula-MIDAS-GARCH (TVM-Copula-MIDAS-GARCH) model with exogenous explanatory variables to model the joint distribution of returns. The model accounts for mixed frequency factors that affect the time-varying dependence structure of financial assets. Furthermore, we examine the effectiveness of the proposed model in VaR-based portfolio selection. We conduct an empirical analysis on estimating the 90%, 95%, 99% VaRs of the portfolio constituted of the Shanghai Composite Index, Shanghai SE Fund Index, and Shanghai SE Treasury Bond Index. The empirical results show that the proposed TVM-Copula-MIDAS-GARCH model is effective to investigate the nonlinear time-varying dependence among those three indices and performs better in portfolio selection.     

印花税率调整对A股市场波动性影响的实证分析

本文以印花税率变动日05年1月23号及07年5月30日前后三十天数据为样本,进行Brown-Forsythe、GARCH的检验和模拟。根据实际结果对沪市A股采取Brown-Forsythe结果,对深市A股采取GARCH结果,得出结论:税率上调对于股市波动性造成的影响要大于税率下调造成的影响,税率过高会增加市场波动性。     

Long-run equilibrium, short-term adjustment, and spillover effects across Chinese segmented stock markets and the Hong Kong stock market

This paper adopts a novel FIVECM-BEKK GARCH approach to examine the bilateral relationships among the A-share and B-share stock markets in China and the Hong Kong stock market. The evidence shows that these stock markets are fractionally cointegrated. Analyses of the spillover effects across these markets indicate that the A-share markets are most influential. The relaxation of government restrictions on the purchase of B shares by domestic residents accelerates the market integration process of A-share markets with the B-share and Hong Kong markets. The effects of the Asian crisis on the stock-return dynamic correlations vary across these markets.     

Conditional VaR using EVT - Towards a planned margin scheme

This paper constructs a robust Value-at-Risk (VaR) measure for the Indian stock markets by combining two well-known facts about equity return time series — dynamic volatility resulting in the well-recognized phenomenon of volatility clustering, and non-normality giving rise to fat tails of the return distribution. While the phenomenon of volatility dynamics has been extensively studied using GARCH model and its many relatives, the application of Extreme Value Theory (EVT) is relatively recent in tracking extreme losses in the study of risk measurement. There are recent applications of Extreme Value Theory to estimate the unexpected losses due to extreme events and hence modify the current methodology of VaR. Extreme value theory (EVT) has been used to analyze financial data showing clear non-normal behavior. We combine the two methodologies to come up with a robust model with much enhanced predictive abilities. A robust model would obviate the need for imposing special ad hoc margins by the regulator in times of extreme volatility. A rule based margin system would increase efficiency of the price discovery process and also the market integrity with the regulator no longer seen as managing volatility.     

The Role of U.S. Market on International Risk‐Return Tradeoff Relations

We study the intertemporal risk‐return tradeoff relations based on returns from 18 international markets. We find striking new empirical evidence that the inclusion of U.S. market returns significantly changes the estimated risk‐return tradeoff relations in international markets from mostly negative to predominantly positive. Our results are consistent with the lead‐lag effect between U.S. and international markets in the sense of Rapach, Strauss and Zhou.     

Risk forecasting in (T)GARCH models with uncorrelated dependent innovations

(G)ARCH-type models are frequently used for the dynamic modelling and forecasting of risk attached to speculative asset returns. While the symmetric and conditionally Gaussian GARCH model has been generalized in a manifold of directions, model innovations are mostly presumed to stem from an underlying IID distribution. For a cross section of 18 stock market indices, we notice that (threshold) (T)GARCH-implied model innovations are likely at odds with the commonly held IID assumption. Two complementary strategies are pursued to evaluate the conditional distributions of consecutive TGARCH innovations, a non-parametric approach and a class of standardized copula distributions. Modelling higher order dependence patterns is found to improve standard TGARCH-implied conditional value-at-risk and expected shortfall out-of-sample forecasts that rely on the notion of IID innovations.     

The dynamic interrelation between external finance and bank credit

This article studies the interrelation among the volumes of bonds and stocks issued by non-financial firms, and levels of industrial loans outstanding in the United States. These aggregates are co-integrated and characterized by asymmetric volatility. Their co-movements are driven by financial indicators such as the yield spread, size of loan market and market volatility. Bond and stock issuance are positively correlated, and even more so during the expansionary phase of the cycle. Loans outstanding and bond issuance are negatively correlated, and their substitutability increases in periods of economic downturn, highlighting the importance of bond markets to mitigate credit crunches.     

An investigation of the effects of exchange rate volatility on exports in East Asia

This study investigates the effects of the exchange rate volatility on the export flows of Indonesia, Malaysia, Republic of Korea, Singapore, Thailand, and the Philippines during 1974–2011. Towards this goal a trade weighted real effective (rather than the bilateral) exchange rate and three different measures of volatility, i.e. obtained from an ARCH model, a GARCH model and a moving-average standard deviation measure are used in this study. Specifically, the export flows between six Asian countries and the rest of the world are investigated rather than focusing on trade with only one country. Our findings reveal that the exchange rate volatility has a significant impact on export flows in the short run as well as in the long run for all the countries in the sample. The impact in the long run is predominantly negative with the exception of Singapore, but in the short run the impact varies across countries. Moreover, our results are robust to the alternative measures of volatility used and most of the findings in the long run and short run are also robust to the crisis period.     

Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia

Countries are becoming economically integrated and it is contended that this will also lead to their financial markets becoming integrated. This contention is important since international financial market integration diminishes portfolio diversification benefits and creates contagion risk. We test this contention in this article in the context of the Australasian region. Australia and Asia have experienced very significant economic integration through a rapid growth in their bilateral trade. We utilize a battery of econometric techniques – cointegration, asymmetric generalized dynamic conditional correlations and panel regression models. As expected, we find that trade intensity significantly drives the interdependence between their stock markets in both the short run and the long run. Thus, given the ever increasing economic integration in this region, this finding implies that their stock markets face the risk of contagion, and that investors in these markets would also be confronted with the prospect of lower diversification benefits.     

基于百度指数的碳交易市场波动率的实证研究

碳交易市场波动率研究主要基于成交量数据对收益率GARCH效应的解释作用。在互联网时代可以有更新更为有效的方法来衡量碳交易市场的波动性。基于“碳交易”词条的百度指数,以湖北碳交易市场中的收益率为样本,本文通过对比使用引入成交量和搜索量的IGARCH（1,1）模型,实证研究发现传统的量价方程的确没有解释力,而百度指数可以对收益率的GARCH效应做出部分合理的解释,这可以在某种程度上反映湖北碳交易市场的交易信息流。