中国风险投资网络结构特性及其演化

根据1999～2018年中国风险投资事件,构建了5年移动时间窗的联合风险投资网络,从复杂网络角度研究中国风险投资网络结构、特性及其动态演化规律.研究发现:在网络关系属性方面,中国风险投资网络规模在不断增大,机构之间网络能力差异性大,不利于网络的均衡发展;在网络结构层次方面,中国风险投资网络存在局部紧密性,并且,随着规模...     

混合型模糊聚类分析方法及其应用

在动态聚类方法和模糊ISODATA方法的基础上,提出了混合型模糊聚类分析方法.该方法首先利用传统的传递闭包方法得到1个初始分类,并在此基础上提出初始分划矩阵,根据考虑权重因子的模糊ISODATA方法对相关数据进行迭代计算,从而对数据进行有效分类.以股票分类为例对该方法进行实证分析,分析结果表明,应用该方法可以对股票进行有效分类优选.     

中国股市的拓扑结构及其复杂性质研究

在计算中国股市各股票之间的关联函数的基础上,利用最小生成树方法构建了股市的拓扑结构,从而验证了股市板块内部的共振效应,并发现股市的拓扑结构的连通性分布满足幂律关系。为此,本文从自组织临界性的角度研究了股市的复杂性质,其所得到的股市整体结构的分形性,将成为股市复杂系统鲁棒性研究的基础。     

Randomized unit root processes for modelling and forecasting financial time series: Theory and applications

This paper considers the problems of statistically analysing the levels of financial time series rather than their differences, which are often equivalent to returns and which are traditionally analysed in econometric modelling. This focus on differences is a consequence of the inherent nonstationarity of the levels, and hence analysing the latter requires introducing an alternative framework for modelling nonstationary behaviour. We do this by considering randomized unit root processes, arguing that these can have a natural interpretation in the financial context. The paper thus develops methods for testing for randomized unit roots and for modelling such processes. It then applies these techniques to various financial time series, so as to ascertain their potential usefulness, particularly for forecasting.     

Forecasting stock volatility in the presence of extreme shocks: Short-term and long-term effects

This paper introduces a novel generalized autoregressive conditional heteroskedasticity–mixed data sampling–extreme shocks (GARCH-MIDAS-ES) model for stock volatility to examine whether the importance of extreme shocks changes in different time ranges. Based on different combinations of the short- and long-term effects caused by extreme events, we extend the standard GARCH-MIDAS model to characterize the different responses of the stock market for short- and long-term horizons, separately or in combination. The unique timespan of nearly 100 years of the Dow Jones Industrial Average (DJIA) daily returns allows us to understand the stock market volatility under extreme shocks from a historical perspective. The in-sample empirical results clearly show that the DJIA stock volatility is best fitted to the GARCH-MIDAS-SLES model by including the short- and long-term impacts of extreme shocks for all forecasting horizons. The out-of-sample results and robustness tests emphasize the significance of decomposing the effect of extreme shocks into short- and long-term effects to improve the accuracy of the DJIA volatility forecasts.     

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR

As a representative emerging financial market, the Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conducts a comparative study about the predictive performance of artificial neural network, support vector regression (SVR) and autoregressive integrated moving average and selects SVR to study the asymmetry effect of investor sentiment on different industry index predictions. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed of young companies with high growth and high operative pressure and there are a great number of investment bubbles in those companies.     

A decision rule to minimize daily capital charges in forecasting value‐at‐risk

Under the Basel II Accord, banks and other authorized deposit‐taking institutions (ADIs) have to communicate their daily risk estimates to the monetary authorities at the beginning of the trading day, using a variety of value‐at‐risk (VaR) models to measure risk. Sometimes the risk estimates communicated using these models are too high, thereby leading to large capital requirements and high capital costs. At other times, the risk estimates are too low, leading to excessive violations, so that realized losses are above the estimated risk. In this paper we analyze the profit‐maximizing problem of an ADI subject to capital requirements under the Basel II Accord as ADIs have to choose an optimal VaR reporting strategy that minimizes daily capital charges. Accordingly, we suggest a dynamic communication and forecasting strategy that responds to violations in a discrete and instantaneous manner, while adapting more slowly in periods of no violations. We apply the proposed strategy to Standard & Poor's 500 Index and show there can be substantial savings in daily capital charges, while restricting the number of violations to within the Basel II penalty limits. Copyright © 2009 John Wiley & Sons, Ltd.     

要素资源错配对企业创新的作用机制及实证检验——基于制造业上市公司的经验分析

本文构建理论模型分析了要素资源错配对企业创新的作用机理,并采用2012-2016年中国制造业上市公司数据实证检验了要素资源错配对企业创新的影响效果.研究发现:企业创新存在循环累积效应,要素资源错配是影响企业创新的重要因素,但劳动力和资本资源错配对企业创新具有不同的影响,整体而言,劳动力资源错配显著促进了企业创新.分地区来看,劳动力资源错配对企业创新的作用效果存在中东西部依次递减趋势,中部地区资本资源错配显著抑制了企业创新;分股权性质来看,国有企业和民营企业劳动力资源错配促进了企业创新,民营企业和外资企业资本资源错配抑制了企业创新;分行业来看,不同要素资源错配对企业创新存在行业差异.此外,企业规模、资本密集度、企业年龄和市场集中度也在不同程度上影响了企业创新.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

欧美股票市场对我国股票市场的传染效应研究——基于次贷与欧债危机背景

近年来,金融危机频频爆发且易表现出传染性,这使得金融传染引起国内外学者的高度关注.本文选取合适的动态条件相关模型研究欧美市场与A股、港股市场的条件相关性,结合内生多重结构突变模型与T检验方法划分危机传染期与平稳期,选用考虑外部影响的CCK模型研究A股、港股市场的羊群行为,随后,引入收益率分散度指标,研究两次危机的羊群行为传染渠道.研究结果表明:港股市场受两次危机传染的速度均快于A股市场,受传染的持续时间均长于A股市场,但受传染的程度均弱于A股市场:次贷危机传染程度强于欧债危机的传染程度,但传染的持续时间短于欧债危机:羊群行为传染渠道是两次危机对A股、港股市场的传染渠道之一.