Conditional value-at-risk: Aspects of modeling and estimation

This paper considers flexible conditional (regression) measures of market risk. Value-at-Risk modeling is cast in terms of the quantile regression function – the inverse of the conditional distribution function. A basic specification analysis relates its functional forms to the benchmark models of returns and asset pricing. We stress important aspects of measuring the extremal and intermediate conditional risk. An empirical application characterizes the key economic determinants of various levels of conditional risk. Received: September 30, 1999/Revised version: November 20, 2000     

Markets liquidity risk under extremal dependence: Analysis with VaRs methods

Value-at-Risk (VaR) is a widely used tool for assessing financial market risk. In practice, the estimation of liquidity extreme risk by VaR generally uses models assuming independence of bid–ask spreads. However, bid–ask spreads tend to occur in clusters with time dependency, particularly during crisis period. Our paper attempts to fill this gap by studying the impact of negligence of dependency in liquidity extreme risk assessment of Tunisian stock market. The main methods which take into account returns dependency to assess market risk is Time series–Extreme Value Theory combination. Therefore we compare VaRs estimated under independency (Variance–Covariance Approach, Historical Simulation and the VaR adjusted to extreme values) relatively to the VaR when dependence is considered. The efficiency of those methods was tested and compared using the backtesting tests. The results confirm the adequacy of the recent extensions of liquidity risk in the VaR estimation. Therefore, we prove a performance improvement of VaR estimates under the assumption of dependency across a significant reduction of the estimation error, particularly with AR (1)-GARCH (1,1)-GPD model.     

Random dynamical systems: a review

Summary. This paper provides a review of some results on the stability of random dynamical systems and indicates a number of applications to stochastic growth models, linear and non-linear time series models, statistical estimation of invariant distributions, and random iterations of quadratic maps.Received: 16 August 2002, Revised: 9 January, 2003, JEL Classification Numbers: C1, C6, D8, D9. Correspondence to: Mukul MajumdarThanks are due to A. Goswami and B.V. Rao for their detailed comments on an earlier version.     

Return threshold model analysis of two stock markets： Evidence study of Italy and Germany＇s stock returns

This paper discusses the model construction and the association between the Italy and the Germany＇s stock markets. The period of study data is from January 3, 2000 to June 30, 2008. This paper also utilizes Student＇s t distribution to analyze the proposed model. The empirical results show that the two stock markets are mutually affected each other, and the dynamic conditional correlation （DCC） and the bivariate asymmetric-GARCH （1, 2） model is appropriate in evaluating the relation between them. The empirical result also indicates that Italy and Germany＇s stock markets show a positive relationship. The average value of correlation coefficient equals to 0.8424, which implies that the two stock markets return volatility have a synchronized influence on each other. In addition, the empirical result also shows that there is an asymmetrical effect between Italy and the Germany＇s stock markets, and demonstrates that the good news and bad news of the stock returns＇ volatility will produce the different variation risks for Italy and the Germany＇s stock price markets.     

中国通货膨胀率及其波动关系分析

有关通货膨胀率和通货膨胀率波动影响关系,存在F riedm an-B a ll和Cuk ierm an-M e ltzer两种假说,即存在通货膨胀率及其波动的相互影响关系。使用GARCH和TGARCH模型,选择中国1993~2004年月度通货膨胀率数据,检验结果表明F riedm an-B a ll假说成立,稳健的货币政策对经济发展有积极作用。     

Non-causality: The role of the omitted variables

In this paper a proof is offered that if a variable Y₃ does not cause a variable Y₁ in the bivariate system (Y₁, Y₃) and Y₃ causes a variable Y₁ in higher-order system (Y₁, Y₂, Y₃), then the omitted variable Y₂ must cause the variable Y₁ in the bivariate system (Y₁, Y₂) and in the trivariate system (Y₁, Y₂, Y₃).     

Modeling crime in Japan

This study aims at identifying the factors of aggregate and disaggregate crime categories in Japan over the period 1964–2009. All crime categories are related to police outlays, police numbers, unemployment, divorce and urbanization rates. Bounds testing approach to cointegration is implemented to test the existence of a long-run relationship amongst the variables. Cointegration analysis yields that the main deterrent effect on crime is the police presence and this factor is further confirmed by the real police outlays. As for the essential cause of crime, urbanization stands as the leading factor which is followed by divorce and unemployment rates. Policy implications are discussed.     

我国银行同业拆借市场利率波动特征分析

利用ARMA—GARCH族模型对上海银行同业拆借市场隔夜折借利率进行了实证分析,得出如下几点结论:(1)银行同业拆借利率存在尖峰厚尾特征,非正态分布更适合描述隔夜拆借利差的厚尾特征;(2)银行同业隔夜拆借利差存在着波动的集聚性;(3)同业拆借利差波动存在着杠杆效应或不对称性,非预期的正的利差抖动引起的波动上升大于同幅度的非预期负的利差抖动引起的波动的上升,即利率上升引起的波动高于同幅度利率下降引起的波动。     

股权分置改革对股票市场吸收冲击能力的影响分析

根据经济学理论,股权分置改革最主要的意义在于解决影响中国股市发展的委托一代理问题。从改革后市场的反应看,2005年开始的股权分置改革较为成功地解决了这一问题。如此,改革后市场的运作应该比之前更加规范和理性,消化冲击能力更强。然而运用GARCH模型对此进行分析,得到的实证结果与提出的观点却相反。最后,对此现象进行了分析。     

城市产业转型升级与空间规模演化的经济学分析

城市化是由要素边际生产率变化导致产业结构变化,致使劳动力由农业部门向工业和服务业部门的流动,大量地在城市中的聚集。通过构建数理模型,我们发现在产业转型升级的过程中,技术进步起到了至关重要的作用。技术进步直接决定了城市的人口密度和规模,因而引导着城市化的发展方向和速度。由于产业分布在空间的相互排斥,促使产业转型推动了城市地租的新一轮上涨。产业转型决定着城市必然走向内涵式发展的道路,大、中、小城市呈现空间组团化格局。     

人民币NDF与即期汇率的动态关联性研究

文章以2005年7月25日~2006年6月13日间人民币NDF和即期汇率为研究对象,以MA(1)-GARCH(1,1)模型分析人民币NDF市场和即期市场间均值和波动的溢出效应。分析结果表明,两个市场的波动没有相互溢出效应,即期市场对人民币NDF市场没有报酬溢出效应,而人民币NDF市场对即期市场具有报酬溢出效应。可见,我国汇制改革后,境外因素已开始影响人民币即期市场。     

Volatility in productivity and the impact on unemployment

Volatility, and the uncertainty it creates, has long been recognized as a factor in economic decision making. Since hiring occurs before shocks to productivity are realized, firms’ investment in new labour is inherently risky. How large a role uncertainty in productivity has on aggregate unemployment is an empirical question that we attempt to answer. In this paper we measure the impact of higher volatility in labour productivity on the unemployment rate in the U.S. economy using a SVAR-GARCH-M model. Using the conditional standard deviation of productivity innovations from a multivariate GARCH model to measure uncertainty, we provide compelling evidence that unemployment increases with volatility. This estimated relative effect is actually larger for positive productivity shocks leading to unemployment declines only 60% as large as would have occurred using models that exclude uncertainty.     

基于FIGARCH模型的中国房地产指数的实证分析

在T分布和正态分布假设下采用GARCH模型和FIGARCH模型对上证地产股指数日收益率序列进行建模分析,结果表明,上证地产股指数日收益率序列的波动具有显著的长记忆性,表明外部冲击对波动有着长期的影响。因此,采用FIGARCH模型建模的效果优于采用GARCH模型建模的效果,并且在T分布假设下拟合模型,其效果优于在正态分布假设下拟合的模型。     

中国开放式基金业绩持续性研究

分别采用七类业绩评价基准及三类基金业绩持续性检验方法,对中国偏股型开放式基金的短期及中期业绩持续性进行了检验分析,并利用多元logit回归模型,对基金业绩持续性的影响因素进行了检验分析。研究结果表明,中国开放式基金在半年间业绩存在着比较显著的持续性,但季度间业绩持续性不显著。同时,业绩评价基准及业绩持续性检验方法的不同对检验结果有较大影响,但前者对业绩持续性检验结果的影响大于后者。相对于其他因素,基金的选股及选时能力对业绩持续性的影响最为显著。     

机构投资者对我国股市波动的影响研究

基于修正的GARCH事件模型,本文选取五个关键时间点作为事件窗口,通过事件研究考察机构投资者对我国股市波动的影响。研究发现,机构投资者进入与股权分置改革试点加剧了我国股市的波动性。在上海证券市场上,股权分置改革对股市波动性的影响最大;在深圳证券市场上,开放式基金的进入对股市波动性的影响最大。保险公司的进入对沪深两市波动性的影响最小,发挥着积极的作用。     

Sustainability of Austrian public debt: a political economy perspective

Sustainability of Austrian public debt is investigated in the context of political objectives such as stabilizing the business cycle, increasing chances for being re-elected and implementing the ideologies of political parties. Several tests indicate that Austrian fiscal policies were sustainable in the period 1960–1974, while from 1975 on, public debt grew much more rapidly. The development of public debt in Austria seems to be driven not primarily by ideology, but by structural causes and a shift in the budgetary policy paradigm. We find some empirical evidence that governments in Austria dominated by one party run higher deficits than coalition governments. There are no indications of a political business cycle.     

Are residual economic relationships normally distributed? Testing an assumption of neoclassical economics

In both theoretical and applied contexts, neoclassical economics typically assumes that residual economic relationships are mean-zero, finite-variance, normally distributed random variables. However, many have challenged this view, from various perspectives. The Austrian economists, specifically in the tradition of Mises and Rothbard, reject outright the effort to mathematically model human choices. This Austrian view is often derided as unscientific. However, some of the most mathematically sophisticated work in financial economics also rejects the orthodox bell curve. In this paper, we test Benoit Mandelbrot’s “stable Paretian” hypothesis on ten major macroeconomic data sets and reject the normal distribution in nine of them. We further argue that the stable Paretian hypothesis (and, more generally, the field of “chaos theory”) is far more compatible with the Austrian position than one might initially suspect.