焦点企业知识存量对联盟组合分裂断层的影响：知识转移效率的中介作用

运用断层理论，从知识获取和关系治理角度，分析焦点企业知识存量如何影响联盟组合分裂断层及分裂断层形成机理。基于焦点企业知识存量、分裂断层、知识转移效率、情景嵌入性之间的关系理论模型框架，认为焦点企业知识存量能够影响联盟组合分裂断层，其中，知识转移效率在这一过程中发挥中介效应，情景嵌入性发挥调节效应。结果发现：焦点企业知识存量与分裂断层之间存在显著负相关关系；知识转移效率能够部分中介焦点企业知识存量与分裂断层之间的关系；情景嵌入性能够正向调节焦点企业知识存量与知识转移效率之间的关系。     

How have the dependence structures between stock markets and economic factors changed during the COVID-19 pandemic?

This study investigates how the dependence structures between stock markets and economic factors have changed during the COVID-19 pandemic using the dynamic model averaging approach. A series of economic factors such as commodity markets, cryptocurrency, monetary policy, international capital flows, and market uncertainty indices are considered. We find that the importance of economic variables and the sign and size of their coefficients are significantly different from those before the COVID-19 pandemic. The stock markets are most influenced by economic factors during the COVID-19 outbreak.     

Extendible stock loan

In this paper, the model of extendible stock loan with forbearance is proposed. The loan is extendible, so as to prevent immediate losses or to prevent subsequent price drop; while the forbearance is granted only when the pledged share’s value is above threshold, so as to mitigate the risk-taking behavior induced by the extension. The non-synchronization of the liquidation of insolvent stock loans also alleviates the downward leverage spiral in a market downturn. Numerical analysis shows that fair extendible stock loan rates increase with the forbearance level as well as extension period, and loan rates are quite sensitive to the change of asset volatility and debt ratio. For lenders waiving the interest rates during extension period, their burden grows with extension rapidly when they grant looser forbearance and when asset volatility or loan-to-value is higher. Some suggestions are made accordingly. First, lenders offering uniform extendible loan rate can let borrowers choose between looser forbearance with shorter extension, or tighter forbearance with longer extension. Second, if the loan rate is priced fairly, lower margin requirement can only be accomplished with tighter forbearance. More looser forbearance worth higher rates.     

IFRS adoption and stock misvaluation: Implication to Korea discount

Analyzing publicly traded stocks in Korea surrounding IFRS adoption in 2011, we find that the gap between stock price and firm value, value-to-price (V/P) ratio, narrows following the IFRS adoption and that this narrowed gap is observed only for higher V/P firms. We further find that the return predictability of V/P decreases in the post-IFRS period. Using a path analysis, we report further evidence that mandatory IFRS adoption decreases idiosyncratic volatility and improves trading volume and market liquidity, thereby contributing to the narrowed gap between value and price. We conclude that IFRS adoption contributes to resolution of Korea discount.     

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.     

Does Investor Sentiment Affect the Value Relevance of Accounting Information?

We investigate whether investor sentiment affects the relationships between accounting variables and contemporaneous stock returns. Using price-relevant accounting variables identified by Chen and Zhang (2007) and the investor sentiment index constructed by Baker and Wurgler (2006), we find that the value relevance of accounting variables is collectively lower in high sentiment periods than in low sentiment periods. More importantly, earnings yield appears to be more related to contemporaneous stock returns in high sentiment periods, while other accounting variables are more related to stock returns in low sentiment periods. The effect of investor sentiment on the value relevance of accounting information is stronger for firms that are more difficult to value and to arbitrage.     

The capital market spillover effect of product market advertising: Evidence from stock price synchronicity

We analyze whether product market advertising has a spillover effect on stock price synchronicity by transmitting firm-specific information to the capital market and attracting more investor attention. Using a sample of Chinese listed firms from 2009 to 2017, we find that firms with greater advertising expenditures have lower stock price synchronicity. The results are robust after we address endogeneity concerns. In accord with our hypothesis that product market advertising increases the amount of firm-level information capitalized into stock prices through the information channel, we find that the impact of advertising on synchronicity is more pronounced for firms with a higher degree of information asymmetry and firms in the consumer-product industry. Further tests show that product market advertising enhances the ability of current period returns to reflect future earnings, and thus rules out that the negative relationship between advertising and synchronicity is driven by noise trading. Our results imply that product market advertising plays an informative role and improves information efficiency in a capital market.     

Wage returns to education in Ethiopia

ABSTRACT

In this paper, we aim to provide robust estimates of wage returns to education in Ethiopia. Previous estimates vary widely based on the scope and size of the study sample, variables employed, and estimation method. We use two recent rounds of national labour force survey data and a pseudo- (or synthetic) panel framework to address the well-known potential endogeneity of schooling in wage regressions. Birth-year cohort based pseudo-panel estimate of the return to an additional year of education is between 14 percent and 16 percent, 4 to 5 percentage points higher than that from ordinary least squares (OLS). The significant downward bias in OLS is further confirmed by two-year pseudo-panel estimates and remains robust, to a large extent, as we use an alternate model, change the estimation sample, and address selection bias concurrently with endogenous schooling using a novel approach. We discuss some possible explanations in the context of Ethiopia.     

Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration

Given that the United States is an engine of global stock market while China is the largest emerging market with a cornucopia of anomalies in particular, it is vital to investigate the risk-return relationship in the two markets. This paper brings new insights not only into risk-return tradeoff, but also to the leverage effect, with the application of the fractionally co-integrated vector auto-regression (FCVAR) model capturing the fractional cointegrated relationship and long memory property. Results show that China stock markets own the property of double long memory but the US markets don’t. Most of all, in the US market, a positive risk-return tradeoff exists for the whole sample while after the crisis, even we find the negative relation, it’s not a volatility feedback effect but low risk and high returns. However, there is only a volatility feedback effect in China stock markets. Besides, there is a leverage effect in the US market, while Chinese market exhibits a reverse one, another anomaly, indicating significant difference in the two markets again.