Forecasting stock price volatility: New evidence from the GARCH-MIDAS model

This paper introduces a combination of asymmetry and extreme volatility effects in order to build superior extensions of the GARCH-MIDAS model for modeling and forecasting the stock volatility. Our in-sample results clearly verify that extreme shocks have a significant impact on the stock volatility and that the volatility can be influenced more by the asymmetry effect than by the extreme volatility effect in both the long and short term. Out-of-sample results with several robustness checks demonstrate that our proposed models can achieve better performances in forecasting the volatility. Furthermore, the improvement in predictive ability is attributed more strongly to the introduction of asymmetry and extreme volatility effects for the short-term volatility component.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

Terrorism,country attributes,and the volatility of stock returns

This study investigates the interplay between terrorism and finance, focusing on the stock return volatility of American firms targeted by terrorist attacks. We find terrorism risk is an important factor in explaining the volatility of stock returns, which should be taken into account when modelling volatility. Using a volatility event-study approach and a new bootstrapping technique, we find volatility increases on the day of the attack and remain significant for at least fifteen days following the day of the attack. Cross-sectional analysis of the abnormal volatility indicates that the impact of terrorist attacks differs according to the country characteristics in which the incident occurred. We find that firms operating in wealthier, or more democratic countries, face greater volatility in stock returns relative to firms operating in developing countries. Firm exposure varies with the nature of country location, with country wealth and level of democracy playing an important role in explaining the likelihood of a terrorist attack. Our results show that despite significant terrorist events this past decade, stock markets in developed countries have not taken terrorist risk into sufficient consideration.     

Speculative dynamics and price behavior in the Shanghai Stock Exchange

This article examines the extent to which the trading behavior of heterogeneous investors manifests in stock price changes of asset portfolios which constitute the Shanghai Stock Exchange. There are three major findings that materialize. Firstly, reliable statistical evidence of a negative relation between the conditional first and second moments of the return distributions of stock prices lends support to the volatility feedback effect. Secondly, ‘feedback’, or momentum-type investors, are not present in this market as is often detected from the daily price changes of other industrialized markets. Finally, trade volume as a proxy for ‘information-driven’ trading suggests that such investors play a statistically significant role in stock price movements. Parameter estimates from this latter group of investors imply that a rise in stock prices from a high volume trading day is more likely than a rise resulting from a low volume trading day.     

Resurrecting the size effect: Evidence from a panel nonlinear cointegration model for the G7 stock markets

Firm size is known to be an important factor affecting stock returns. This study proposes a panel threshold cointegration model to investigate the impact of the size effect on stock returns for the panel of G7 countries: Canada, France, Germany, Italy, Japan, the U.K., and the U.S. over the period 1991:1–2012:12. The empirical analysis is based upon the nonlinear cointegration framework using the asymmetric ARDL cointegration methodology (Shin et al., 2011). This methodological approach permits a much richer degree of flexibility in the dynamic adjustment process toward equilibrium, than in the classical linear model. Our findings indicate the presence of asymmetric adjustment around a unique long-run equilibrium. In particular, the empirical analysis provides evidence of asymmetric effects between stock returns and the size effect, while controlling for the book-to-market ratio and the price-to-earnings ratio.     

Impact of the Financial Crisis on Banking Acquisitions: A Look at Shareholder Wealth

This paper examines the influence of the 2007–08 financial crisis on value creation for acquirer’s shareholders in the banking industry using a sample of 883 deals over 2004–12. Applying an exploratory and top-down approach, banking acquisitions are considered at the global level, narrowing the analysis step by step to consider domestic versus cross-border acquisitions. Then cross-border deals are split based on the economic development of the acquirer and target countries. It is observed that only acquisitions involving emerging-economy acquirers and developed-economy targets generate positive and significant returns to shareholders after the crisis. Major changes in the global acquisition landscape are also observed since 2007, with emerging-economy banks increasing their acquisition activity, both nationally and internationally.     

通胀预期与货币需求:实际调整与名义调整机制检验

货币存量调整机制一般可分为两类设定方式:实际调整过程和名义调整过程.在实际调整机制下,预期通胀对货币需求没有独立的影响,而在名义调整机制下,通胀预期自然成为货币需求的一个解释变量.通胀预期在货币需求函数中显著可能并不意味着通胀预期直接影响了货币需求,而是表明了部分调整机制的误设.本文根据预期通胀率在货币需求函数中的显著性,比较了货币持有量名义调整和实际调整机制假说对我国的解释能力,认为名义机制比实际机制更好地描述了中国的经验.我们在一个状态空间中联合估计预期通胀以及货币需求方程,避免了传统"两步法"的不足.     

我国二板市场实施做市商制度的障碍与对策研究

在建立我国二板市场的讨论中 ,关于借鉴纳斯达克市场 ,采用做市商制度的呼声正日益高涨。在中国将要推出的“按新体制运行”的二板市场微观结构设计中 ,是否引入做市商制度 ?针对国情 ,当前我国应大力培育和发展柜台市场 ,建立多层次的资本市场体系 ;应制定有利于做市商制度实施的规则、法律条款及其监督落实的一系列制度 ,提高二板市场的效率。     

资本永续盘存法及其国内应用

资本存量数据是宏观经济运行政策研究的重要决定因素。资本存量核算比较复杂，在理论与技术两个层面都存在诸多问题难以厘清。我国资本统计十分薄弱，数据可得性成为资本存量估算的严重制约。在我国经济增长研究中，如何准确估算资本存量一直是困扰研究者的难题。学术界需要使用这方面数据，又促使很多学者基于各自的研究目的对我国资本存量进行估算。这些研究分别利用不同的假设和处理方法，这使我国资本存量数据出现了差异很大的众多版本。本文在对资本存量估算方法进行梳理之后，对我国资本估算现有研究进行了回顾和评论。