Stock market reactions to monetary policy surprises under uncertainty

This article investigates how uncertainty impacts the effect of monetary policy surprises on stock returns. Using high-frequency US data, we demonstrate that stock markets respond more aggressively to monetary policy surprises during periods of high uncertainty. We also show that uncertainty asymmetrically influences the transmission of positive and negative monetary policy surprises to stock market prices. The amplifying effect of uncertainty is found to be stronger for expansionary shocks than for contractionary shocks. Our robustness analysis confirms that financial uncertainty has a significant role in shaping the influence of monetary policy on the stock market.     

Price gap anomaly in the US stock market: The whole story

This paper analyses the price gap anomaly in the US stock market (comprised of the DJI, S&P 500 and NASDAQ) covering the period 1928 to 2018. This paper aims to investigate whether or not price gaps create market inefficiencies. Price gaps occur when the current day’s opening price is different from the previous day’s closing price due orders placed before the opening of the market. Several hypotheses are tested using various statistical tests (Student’s t-test, ANOVA, Mann-Whitney test), regression analysis, and special methods, that is, the modified cumulative returns and the trading simulation approaches. We find strong evidence in favour of abnormal price movements after price gaps. We observe that during a gap day prices tend to change in the direction of the gap. A trading strategy based on this anomaly was efficient in that its results were not random, indicating that this market was not efficient. The momentum effect was found to be temporary and no evidence of seasonality in price gaps was found. Lastly, our results were also contrary to the myth that price gaps tend to get filled.     

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.     

Unconventional monetary policy and stock repurchases: Firm-level evidence from a comparison between the United States and Japan

This paper is the first comparative study examining the determinants of stock repurchases during the period of unconventional monetary policy. By constructing a vast firm-level dataset of the U.S. and Japan and conducting multivariate Tobit and probit analyses, this paper presents evidence that during the period of unconventional monetary policy, in both the U.S. and Japan, firms with more free cash flow and lower borrowing costs are more likely to repurchase stock, firms with higher financial leverage are more likely to abstain from stock repurchases, and firms coordinate dividends and stock repurchases to please shareholders. I also find striking contrasts between the results of U.S. and Japanese firms, and show the importance of financial structure in explaining the contrasting results. From a micro perspective, this paper provides new insight and evidence to support the view that financial structure should be thought of as an important factor determining the effects of unconventional monetary policy.     

Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade

This paper examines the correlation and the dependence patterns of the Qatar stock market with other markets using copula statistical theory and exploiting new datasets covering the period August 1998 to June 2018. To examine the crisis –specific change in the average degree of dependence we decomposed the data into the time periods before and after oil price shocks and the 2017 political crisis among the Gulf Cooperation Council members (i.e. the Qatari blockade). Our findings from the static copula modelling show that the correlations between the Qatari and the other stock markets significantly change after the oil price and the blockade crisis as well. The degree of change in the correlation is time varying and differs from county-group to another. Moreover, our findings reveals that the 2008 global financial crisis has a stronger impact than the price shocks and political crisis. The findings of the paper are of interest and allow for formulating a reliable and dynamic portfolio design framework for investors and risk managers.     

Stock price crash risk and CEO power: Firm-level analysis

This study examines the impact of stock price crash risk on future CEO power. Using a large panel sample with 17,816 firm-year observations, we posit and find a significant negative impact of stock price crash risk on CEO power, suggesting that CEO power becomes smaller after stock price crashes. We also find that our results are stronger for firms with female CEOs and are largely driven by firms with shorter-tenure CEOs. In addition, we find that the significant negative impact of stock price crash risk on CEO power is diminished for firms with strong corporate governance. Our study responds to the call in Habib, Hasan, and Jiang (2018) by providing more empirical evidence on the consequences of stock price crash risk.     

The impact of forced divestments on parent company stock prices: Buy on the rumor,sell on the news?

We measure how warnings of expropriation and forced divestments of private property affect the stock prices of parent companies. We use a unique database of 116 events in 12 countries from 2005 to 2013. Our results show that different types of warnings have significant negative effects on stock prices, and the largest effect is from a warning that takes the form of a transitory permit revocation. In the case of forced divestments, we find a significant negative impact when a permit is permanently revoked. However, nationalizations are associated with a positive market reaction.     

Modelling the asymmetric linkages between spot gold prices and African stocks

We model the asymmetric linkages between returns of spot gold prices and African stock markets using wavelets and quantile regression techniques. The maximal overlap discrete wavelet transform technique was employed to decompose the returns into short-, medium-, and long-term series and the quantile regression was employed to explore the nexus by matching their conditional distributions along 0.05 quantile intervals. We find that the relationship between gold and African stocks is frequency-dependent and asymmetric in nature across the various timescales and quantiles. We find a mixture of negative and positive connections across the various quantiles in the short- and medium-terms. In the long-term, whereas the effect of gold is positive for Ghana, Mauritius, and Nigeria; it is negative for Egypt, Morocco, South Africa, and Tunisia. The results possess important implications for risk management as dependencies are not only studied over the entire conditional distribution at once but based on quantiles and further at different frequencies. Investors can make well-informed decisions to mitigate trade risks as they closely match the time heterogeneity in the markets.     

Forecasting Foreign Exchange Markets Using Google Trends: Prediction Performance of Competing Models

Abstract

Foreign exchange markets affect a variety of humans and businesses worldwide and there is a wide array of literature aimed at providing more accurate forecasts of their movement. In an attempt to quantify human expectations, Google query search terms related to foreign exchange markets are used to help explain and predict foreign exchange rates between the United States’ dollar and ten other currencies during the time period of January 2004 and August 2018. We find evidence that, while Google Trends can be helpful in prediction, it is necessary to implement some sort of shrinkage or sparsity scheme on the coefficients.