政府主导还是市场主导--我国转轨金融运行机制的评价研究

转轨过程中,我国金融运行机制是采取政府主导还是市场主导模式是经济学界争论的焦点,文章应用ARCH类模型对我国金融运行机制进行实证研究,结果表明我国金融运行机制与西方市场经济国家存在显著区别。在我国转轨的特定阶段,金融系统无法依靠自身的力量达到稳定状态,只有靠外部力量的非市场干预才能实现金融系统的平稳运行。目前在金融系统自身不具备自我稳定的功能条件下,政府的外部干预是金融系统平稳运行的前提,否则会导致金融系统陷入剧烈的波动之中。     

Generalized runs tests to detect randomness in hedge funds returns

The major contribution of this paper is to make use of generalized runs tests (Cho and White, 2011) to analyze the randomness, i.e. the lack of persistence, in both absolute and relative returns of hedge funds. We find that about 42% of the HFR universe exhibit iid absolute returns over the period spanning 2000 to 2012. These funds are mainly found in proportions within the Macro and Equity Hedge strategies. A similar result holds for relative returns. We also find that funds having non-iid returns often exhibit ARCH effects and structural breaks, with largest breaks located within financial crises. Also, only a small percentage displays persistence in their relative performance, 8.2% to 16.7% of the universe, mainly found in proportions within the Relative Value and Event-Driven strategies. The robustness of results is challenged by implementing the tests on a crisis-free period. We find similar results for absolute returns. For relative ones, differences appear across strategies and benchmarks, but still both ARCH and breaks are present. Our work contributes to the hedge fund literature in terms of methodology, portfolio allocation, and performance measurement.     

人民币兑美元汇率的风险测量

风险价值 (VaR)是一种计算金融市场风险的综合方法。基于ARCH模型的方差—协方差法计算VaR的基本原则 ,选取人民币 /美元的每日汇率为研究对象 ,测度了人民币兑美元汇率的风险轨迹。     

汇率与股价波动研究——基于中国与日本高频数据的ARCH检验

次贷危机发生前，汇率与股指存在ARCH效应，且均有不对称信息的冲击，波动存在持续性的影响；次贷危机发生后，汇率与股价都不存在ARCH效应，系统性风险和非系统性风险暴露出来使得汇率对股市的波动影响降低，从而促进投资者风险得到有效对坤。     

On the (nonlinear) relationship between exchange rate uncertainty and trade — An investigation of US trade figures in the group of seven

In this paper bilateral models formalizing monthly growth of US imports and exports are employed to investigate the potential of nonlinear relationships linking exchange rate uncertainty and trade growth. Parametric linear and nonlinear as well as semiparametric time series models are evaluated in terms of fitting and ex ante forecasting. The overall impact of exchange rate variations on trade growth is found to be weak. In periods of large exchange rate variations, trade growth forecasts gain from conditioning on volatility. Empirical results support the view that the relationship of interest might be non-linear and, moreover, lacks homogeneity across countries and imports vs. exports. JEL no. C14, C22, F31, F41     

Quantile cointegrating regression

Quantile regression has important applications in risk management, portfolio optimization, and asset pricing. The current paper studies estimation, inference and financial applications of quantile regression with cointegrated time series. In addition, a new cointegration model with quantile-varying coefficients is proposed. In the proposed model, the value of cointegrating coefficients may be affected by the shocks and thus may vary over the innovation quantile. The proposed model may be viewed as a stochastic cointegration model which includes the conventional cointegration model as a special case. It also provides a useful complement to cointegration models with (G)ARCH effects. Asymptotic properties of the proposed model and limiting distribution of the cointegrating regression quantiles are derived. In the presence of endogenous regressors, fully-modified quantile regression estimators and augmented quantile cointegrating regression are proposed to remove the second order bias and nuisance parameters. Regression Wald tests are constructed based on the fully modified quantile regression estimators. An empirical application to stock index data highlights the potential of the proposed method.     

A robust VaR model under different time periods and weighting schemes

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable.

Heterogeneity effects from market interventions

The aim of this paper is to test whether the European Commission activities generate a heterogeneity effect on the merging parties. A sample of 74 firms involved in 45 contested merger and acquisition operations during the years 1990 to 1999 is used. The methodology is based on the GARCH framework. The main result is that, globally, the DGC interventions seem not to reduce significantly the heterogeneity among investors, except for the operations where it takes strong decisions like prohibition. In these last cases, the signal coming from the DGC encompasses valuable information and is well understood by market participants.     

我国沪、深股市的波动性研究——基于GARCH族模型

金融市场的波动性不仅是投资者关注的焦点之一,而且也是被研究的热点之一。中国股市还非常年轻,股票市场的价格常常表现出大幅波动的特征。本研究以上证综合指数和深圳成分指数为研究对象,分别运用GARCH模型、TARCH模型和EGARCH模型同时拟合,并对比分析了中国股市日收益率波动的动态特征;结果显示,EGACH模型能更有效拟合股市的波动性。