Multivariate volatility forecasts for stock market indices

Volatility forecasts aim to measure future risk and they are key inputs for financial analysis. In this study, we forecast the realized variance as an observable measure of volatility for several major international stock market indices and accounted for the different predictive information present in jump, continuous, and option-implied variance components. We allowed for volatility spillovers in different stock markets by using a multivariate modeling approach. We used heterogeneous autoregressive (HAR)-type models to obtain the forecasts. Based an out-of-sample forecast study, we show that: (i) including option-implied variances in the HAR model substantially improves the forecast accuracy, (ii) lasso-based lag selection methods do not outperform the parsimonious day-week-month lag structure of the HAR model, and (iii) cross-market spillover effects embedded in the multivariate HAR model have long-term forecasting power.     

How does news sentiment affect the states of Japanese stock return volatility?

This paper examines the impact of public news sentiment on the volatility states of firm-level returns on the Japanese Stock market. We firstly adopt a novel Markov Regime Switching Long Memory GARCH (MRS-LMGARCH), which is employed to estimate the latent volatility states of intraday stock return. By using the RavenPack Dow Jones News Analytics database, we fit discrete choice models to investigate the impact of news sentiment on changes of volatility states of the constituent stocks in the TOPIX Core 30 Index. Our findings suggest that news occurrence and sentiment, especially those of macro-economic news, are a key factor that significantly drives the volatility state of Japanese stock returns. This provides essential information for traders of the Japanese stock market to optimize their trading strategies and risk management plans to combat volatility.     

Do stock market returns predict changes to output? Evidence from a nonlinear panel data model

Recent empirical work suggests a predictive relationship between stock returns and output growth. We employ quarterly data from a panel of 27 countries to test whether stock returns as useful in predicting growth. Unlike previous research, our approach allows for the possible non-linear effect of recessions on the growth-return relationship. There is strong evidence to suggest that a linear model would be misspecified and provide potentially misleading inference. Using a switching regression approach, we find evidence that returns are most useful in predicting growth when the economy is in recession.First version received: November 2002/Final version received: April 2003This paper benefited greatly from discussions with Kalvinder Shields, Mark Harris, Pete Summers, and Vance Martin. Two anonymous referees provided useful comments on an earlier version of the paper for which we are grateful. The usual disclaimer applies to any errors and omissions. Funding from The University of Melbourne greatly assisted in the completion of this paper.     

股票市场的货币政策传导分析

货币政策的传导机制不是唯一的，金融市场的种种特征造成了货币政策传导的多样性，股票市场中的货币政策传导就具有独特的规律，在不与银行信贷的创造机制相连的前提下，信贷资金和股市资金的沟通是合理的，目前中国信贷市场和股票市场之间千丝万缕的关系，并没有为货币政策传导创造更加有效的机制基础，股票市场还不能成为货币政策的有效传导渠道。     

浙江省科技型中小企业的产业发展特征与股权激励模式的选择

主要根据浙江省科技民营企业的产业发展特征，对实施企业股权激励机制的模式选择问题进行深入研究与探讨。首先，分析论述了企业产业发展特征对企业激励模式选择的影响；在此基础上，对浙江省科技民营企业实施股权激励机制几个理论问题进行分析与探讨。     

股权结构与公司绩效实证研究的发现及其评价

对中国国有企业改革的研究,主要有“委托—代理”“、法定产权与事实产权不一致”“、产业定位与产权特性相对称”等三个理论框架。对股权结构与公司绩效的实证研究,为这三个理论框架的逻辑分析提供了有力的经验证据,也为深化国有企业改革提供了明确的、有益的指导。     

股权分置改革前后上市公司绩效变化的研究

选取了177家股改公司,通过对股改前后绩效的分析发现:每股净资产在股改前后不存在显著差异;每股收益、资产利润率、净资产收益率均表现为股改后第一季度指标值显著高于股改前的指标值、股改后第二和三季度的指标值显著低于股改前的指标值、股改后第四季度的指标值与股改前的指标值没有显著差异,并对该结论进行了简单分析。     

Does the Company Lawyer Have Your Back? A Brief Look at the Need for Personal Private Liability Insurance

There are four traditional uses of private personal liability insurance dating from the 1970s to the present (Hayes 1979; Sommers 2005) which pertain either to individuals or corporations. There is insurance to cover damage to rental cars, umbrella insurance to cover any injury to a guest at one’s home, insurance bought by corporations to cover potential corporate responsibility for actions of company representatives and insurance including misadventures with financial information and morally hazardous behavior as well as corporate required actions which are later deemed to be wrong or inappropriate. Employees need to find out if the employee manual provides for coverage for legal liabilities resulting out of performing job responsibilities. Due to a need to reduce company costs, many companies are reducing or eliminating coverage for employees for many types of actions. Private personal liability insurance gives you the peace of mind to know what you are covered for and for how long. Employee rights versus corporate budgets are at the core of this discussion.     

Building the Knowledge Stock: Lags,Depreciation, and Uncertainty in R&D Investment and Link with Productivity Growth

The search for an appropriate methodology to investigate the relation between R&D investment, knowledge stock and productivity growth is the main purpose of the paper. In analogy with physical assets, we present a model of knowledge capital formation which allows the calculation of the relevant user cost, as well. The proposed model accumulates R&D investment based on a stochastic gestation lag and a geometric depreciation of the stock. The basic parameters underlying the lag structure differ according to the types of research expenditure. The approach is applied to public R&D investment in Italian agriculture; the results provide interesting information about the economic structure of public research effort in Italian agriculture and plausible estimates of its internal rate of return.     

中国股票市场市盈率的检验分析

市盈率高低是我国股市的关注焦点之一。本文在比较国外证券市场的市盈率之后认为我国的市盈率偏高。这种推测得到我们理论研究和模型结论的支持,我国股市市盈率由于系统风险的掩藏、股票初始发行价偏高和股市投机性等因素而呈现较高的倍数。从2004年我国股市市盈率开始下降,逐渐接近我们模型的估计值。此外,我们实证分析认为,市盈率的高低与GDP增长、股票收益波动和国有股比重等因素不存在严格的变动关系,市盈率呈现出一种随机游走的态势,市盈率不是稳定的区间值,而是一系列的动态的时间序列变量值。