Periodically collapsing bubbles in the US stock market?

The existence of periodically collapsing bubbles in stock markets, applying the Enders–Siklos momentum threshold autoregressive (MTAR) model, is empirically investigated in this paper. Using this nonlinear time series technique, we are now able to analyse bubble-driven run-ups in stock prices followed by a crash in a cointegration framework with asymmetric adjustment. Therefore, applying this technique makes possible a deeper insight into the behavior of stock prices than was previously possible using conventional cointegration tests. Although the results from the subsample 1871–1995 cannot be interpreted in favor of the existence of periodically collapsing bubbles in the US stock market, the findings from the 1871–2001 sample period indicate their presence.     

Does investor sentiment dynamically impact stock returns from different investor horizons? Evidence from the US stock market using a multi-scale method

This article uses the investor sentiment index to investigate the Granger causality between investor sentiment and stock returns for the US economy using a multi-scale method. To focus on the local analysis of different investor horizons, bivariate empirical mode decomposition is used to decompose time series of investor sentiment and stock returns at different timescales. We employ the linear and nonlinear integrated Granger causality method to examine the causal relationship of decomposed series on similar timescales. The results indicate both strong bilateral linear and nonlinear causality between longer-term investor sentiment and stock returns. However, there is no strong evidence for correlation of stock returns and investor sentiment on shorter timescales.     

Do political connections decrease the accuracy of stock analysts' recommendations in the Chinese stock market?

This paper studies the association between the accuracy of analysts' recommendations and political connections in the Chinese stock market. As most brokerage firms in China are state-owned, it raises concerns about conflicts of interest among their employed analysts issuing recommendations for Chinese state-owned enterprises. Based on 8469 analysts' recommendations with different ratings for both state-owned and non-state-owned enterprises from 74 brokerage firms, we document that analysts' recommendations are less accurate for Chinese state-owned enterprises, which supports the hypothesis that conflicts of interest create recommendation biases. Political connections encourage analysts to be more optimistic on SOEs and even to generate misleading “Buy” and “Hold” recommendations. Our results demonstrate the existence of an optimism bias among politically connected analysts on state-owned enterprises in China.     

Do speculative bubbles migrate in the Chinese stock market?

In this paper, a duration dependence test for speculative bubbles in the Chinese stock market is developed. It is found that bubbles in the aggregate stock price existed before the split share reform. After the reform, we observe the phenomenon of bubble migration across industries. In particular, bubbles migrate from the telecommunications industry to the health care industry. Moreover, we find that monetary policy used to have a significant impact on the bubble size before the reform but the impact diminished after the reform.

     

Does stock market performance affect the government satisfaction rating in the UK?

In this study, we attempt to answer the question of whether stock market performance affects the government satisfaction rating in the long run in a sample period spanning 1984:Q1 to 2013:Q2 in the UK. We examine both the equilibrium relationship and the causality relationship between stock market performance and government satisfaction rating. The results indicate that the voters are sensitive to the economic shocks and hold responsible for the government. The empirical results confirm the responsibility hypothesis.     

Is the stock market sticker shocked? A study of market response to recent CAFE regulations in the US

In response to increasing environmental concerns, to improve energy security and to conserve energy use, the US government has proposed a new round of Corporate Average Fuel Economy (CAFE) standards. Many studies have focused on how the CAFE standard can be met by various automakers that have sales in the US market, and the costs and benefits of the companies meeting the standard. However, the stock markets’ view on the impact of the standard on automakers’ profitability is largely absent. We study the more recent episode of the CAFE regulation in an effort to try to detect the market response using the standard event study method. Our empirical findings suggest that while the stock market had some responses to the regulation, the large-scale and systematic reaction to the regulation is absent. In addition, the market response pattern to the regulation appears to be tied to the individual company’s compliance condition if there is any significant response at all.     

Which types of commodity price information are more useful for predicting US stock market volatility?

This study aims to investigate which types of commodity price information are more useful for predicting US stock market realized volatility (RV) in a data-rich word. The standard predictive regression framework and monthly RV data are used to explore the RV predictability of commodity futures for the next-month RV on S&P 500 spot index. We utilize principal component analysis (PCA) and factor analysis (FA) to extract the common factors for each type and all types of commodity futures. Our results indicate that the futures volatility information of grains and softs has a significant predictive ability in forecasting the RV of the S&P 500. In addition, the FA method can yield better forecasts than the PCA and average methods in most cases. Further analysis shows that the volatility information of grains and softs exhibits higher informativeness during recessions and pre-crises. Finally, the forecasts of the five combination methods and different out-of-sample periods confirm our results are robust.     

Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market

Based on methods developed by Bollerslev et al. (2016), we explicitly accounted for the heteroskedasticity in the measurement errors and for the high volatility of Chinese stock prices; we proposed a new model, the LogHARQ model, as a way to appropriately forecast the realized volatility of the Chinese stock market. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. The better performance is also confirmed by the utility based economic value test through volatility timing.     

Do stock returns hedge inflation at long horizons?

We investigate the long-horizon relationship between market returns and inflation in the United States. Conventional tests for long horizon predictability may reject the null too frequently when the predictor variable is highly persistent and endogenous and there are overlapping observations. We use a recently developed econometric technique designed to overcome these problems. We find little to no evidence that securities are able to hedge inflation.     

How does leverage in stock market influence the margin of stock index futures?

In this article, we propose a margin-setting model under the assumption of extreme stock price changes. Specifically, extreme stock price changes are caused by the positive feedback effect of leverage and market impact. By introducing these factors into the futures price changes through a cost-of-carry model for setting the margin of stock index futures, we find that leverage and market impact in stock market are positively correlated with the margin.     

Is it China that leads the Asian stock market contagion in 2015?

This article examines the influence of China B-share aggregates on major Asian stock market aggregates during 2015 China crash. Results indicate the China market shows strong negative impact and is highly responsible for leading most markets down during the crash.     

Do national soccer results really impact on the stock market?

This study is a response to Klein et al. (2008), which was highly critical of earlier work by Ashton et al. (2003). This work considering the link between international soccer results and stock market returns was challenged by Klein et al. (2008), who reject the presence and importance of this link. In response, this work provides a reassessment of the link between international soccer results and stock market returns within Ashton et al. (2003). This new analysis extends the original work by using a larger dataset, employing an extended range of tests and allowing for outliers. It is reported that, contrary to the findings of Klein et al. (2008), the link between international soccer results and stock market prices does indeed exist particularly within the sample period 1984–2002 used by Ashton et al. (2003). After extending the dataset to include observations from 2002 until 2009, it is reported that the effect on stock market returns has declined in importance over this period, particularly the impact of wins.     

Does reference point matter in the leverage–return relationship? Evidence from the US stock market

The leverage–return relationship is supported by inconclusive empirical evidence in terms of its sign and significance. In this study, we argue that such a puzzling relationship can be understood by extending the traditional theoretical framework in a way that captures the reference dependence characteristics of prospect theory. We postulate that a firm’s leverage position relative to its reference point (i.e. target leverage) combined with market conditions places firms in either a gain or a loss domain, thereby resulting in different leverage–return relationships. Leverage and expected equity returns generally exhibit positive and negative relationships in gain and loss domains, respectively. Three hypotheses are derived and tested using 1998–2013 empirical data from the US stock market. This article contributes to the existing literature by confirming the applicability of prospect theory in explaining expected returns in the stock market.     

Do German renewable energy resources affect prices and mitigate market power in the French electricity market ?

Several empirical studies show that renewable energy sources such as wind and solar power, typically supplied at low marginal cost, can cause electricity market prices to fall. Recent theoretical research and simulations also highlight the link between the integration of renewable energy and market performance in an oligopolistic energy market. This article looks at these dynamics in the context of cross-border effects between two highly interconnected electricity markets, France and Germany. Using a rich panel dataset for hourly data from November 2009 to July 2015, I estimate the impact of German wind and solar power production on both prices and market power in the French wholesale market. The findings highlight the importance of coordinating energy policies via joint renewable energy support schemes among interconnected European electricity markets.     

Expanded BSADF test in the presence of breaks in time trend – a further analysis on the recent bubble phenomenon in China’s stock market

Under the framework of time trend breaks, the popular BSADF (backward Sup-ADF) test easily misidentifies the bubble processes. As an extending analysis, we construct a t-statistic to further identify the data feature of the detected bubble periods in BSADF test. For the sake of application, we examine the bubble phenomenon related to recent stock market activity in China. We find that a bubble period estimated by the BSADF test is spurious; the rapid rise of stock market on this period is driven by trend changes and has a solid foundation.     

Do mutual fund flows affect the French corporate bond market?

We study whether investors’ withdrawals from mutual funds affect corporate bond prices. As mutual funds have become major players in the financial markets, they are likely to exert downward pressures on asset prices when facing investors’ redemptions, particularly in the less liquid markets such as corporate bonds. We use a novel dataset on the French bond funds and show that both flows in and out of mutual funds lead to a significant effect on the corporate bond yields. This effect is asymmetric as redemptions provoke a change in yields of greater magnitude than inflows. Moreover, all corporate bonds are not equally affected by investors’ withdrawals from funds: The more a bond is detained by funds, the higher the impact of redemptions on its yield. These three results are robust to various changes in econometric specifications.     

Does the stock market affect investment by Chinese firms? Some new evidence

During the 1990s, the Chinese government increasingly relied on the stock market as the major tool for state‐owned enterprise (SOE) reform and for the allocation of investment resources. This paper investigates the impact of stock market development in China on firm‐level capital investment by using a panel data set constructed by the author of all Chinese listed firms for the period 1992 to 1999. The results show that stock market valuation, as measured by Tobin’s q, has a highly independent, significant and positive influence on listed firms’ investment decisions, particularly during the stock market boom from 1996 to 1999. Given the sizable real effects of the stock market, deviations of stock prices from fundamentals can have substantially negative consequences. As a result, this study suggests that sensible regulation of the Chinese stock market is needed in order to enhance the efficiency of stock prices and facilitate an effective channeling of investment funds.     

Did bubbles migrate from the stock to the housing market in China between 2005 and 2010?

The speculative nature of both stock and housing markets in China has attracted the attention of observers. However, while stock market data are easily available, the low frequency and low quality of publicly available housing price data hampers the study of the relationship between the two markets. We use original hedonic weekly resale housing prices of a major Chinese housing market and study them in conjunction with Shanghai's stock market index in the second half of the 2000s. The use of the Phillips et al. (2015 a,b) recursive explosive‐root test enables us to detect and date speculative episodes in both markets. We then implement the Greenaway‐McGrevy and Phillips (2016) methodology to detect the presence of migration between the two types of bubbles. We detect significant migration from the stock to the housing market bubble in 2009 and a temporary spillover in 2007.     

Brain waste? Educated immigrants in the US labor market

This paper investigates the occupational placement of immigrants in the US labor market using census data. We find striking differences among highly educated immigrants from different countries, even after we control for individuals' age, experience and level of education. With some exceptions, educated immigrants from Latin American and Eastern European countries are more likely to end up in unskilled jobs than immigrants from Asia and industrial countries. A large part of the variation can be explained by attributes of the country of origin that influence the quality of human capital, such as expenditure on tertiary education and the use of English as a medium of instruction. These findings suggest that “underplaced” migrants suffer primarily from low (or poorly transferable) skills rather than skill underutilization. The selection effects of US immigration policy also play an important role in explaining cross-country variation. The observed under-placement of educated migrants might be alleviated if home and host countries cooperate by sharing information on labor market conditions and work toward the recognition of qualifications.     

Brain waste? Educated immigrants in the US labor market

This paper investigates the occupational placement of immigrants in the US labor market using census data. We find striking differences among highly educated immigrants from different countries, even after we control for individuals' age, experience and level of education. With some exceptions, educated immigrants from Latin American and Eastern European countries are more likely to end up in unskilled jobs than immigrants from Asia and industrial countries. A large part of the variation can be explained by attributes of the country of origin that influence the quality of human capital, such as expenditure on tertiary education and the use of English as a medium of instruction. These findings suggest that “underplaced” migrants suffer primarily from low (or poorly transferable) skills rather than skill underutilization. The selection effects of US immigration policy also play an important role in explaining cross-country variation. The observed under-placement of educated migrants might be alleviated if home and host countries cooperate by sharing information on labor market conditions and work toward the recognition of qualifications.