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.     

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.     

股票流动性与中国企业创新策略:流水不腐还是洪水猛兽？

中国情境下股票流动性对企业创新的影响是激励机制还是压力机制占主导地位？本文基于上市公司分类专利的申请、授权、终止数据研究发现:一方面,股票流动性使企业发明专利申请显著增加,但能通过实质审查的授权增长极少,说明申请质量明显下滑;另一方面,股票流动性使创新含量较低的实用新型与外观设计授权显著增加,且这些专利拖累了企业盈利表现,法律效力提前终止的数量也明显更多,揭示企业实际上是以“策略性创新”来应对资本市场压力,加剧了“专利泡沫”问题。分样本检验发现,“重数量轻质量”的创新策略集中体现于民营、传统行业及长期机构投资者持股较少的企业。稳健性检验替换关键指标构造和模型估计方法、构造工具变量克服潜在内生性问题,前述结论仍然成立。本文启示,金融制度设计应防范资本市场压力对企业创新的“意外伤害”,更好地实现“以金融助实体、以改革促发展”的目标。     

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.     

World equity markets and COVID-19: Immediate response and recovery prospects

Following the spread of the COVID-19 pandemic, most global equity market indices experienced significant falls. Recognizing the severe economic impacts of the pandemic, starting from mid-March, many governments announced unprecedented economic rescue packages, which appear to restore investors’ confidence, given the recoveries recorded in most stock markets. However, the recovery performance significantly varies across countries. This paper provides an empirical analysis on what may explain this variation in the recovery performance observed in equity markets across countries. We find that among different types, fiscal stimulus supports seem to be strongly and positively associated with higher recovery that may justify more targeted fiscal supports for the real sector firms to restore investors’ confidence. We also find that the severity of the outbreak, reliance more on natural resource and tourism revenues are negatively associated with countries’ stock market recovery performance.     

Nonlinear tail dependence in cryptocurrency-stock market returns: The role of Bitcoin futures

We investigate the median and tail dependence between cryptocurrency and stock market returns of BRICS and Developed countries using a newly developed nonparametric cumulative measure of dependence over the period January 4, 2016 – December 31, 2019 as well as before and after the introduction of Bitcoin futures on December 17, 2017. The new measure is model-free and permits measuring tail risk. The results highlight the leading role of S&P500, Nasdaq and DAX 30 in predicting BRICS and developed countries’ stock market returns. Among BRICS countries, BVSP shows a starring role in predicting stock market returns. BSE 30 is the most predictor of cryptocurrencies, which have a little predictability on stock market returns. Ethereum has the leading role in predicting cryptocurrencies and stock market returns followed by Bitcoin. Tail dependence shows substantial role of S&P500, Nasdaq and BVSP in predicting stock market returns. Subsample analysis show the role of Bitcoin futures in reshaping the mean and tail dependence between cryptocurrency and stock market returns. Our results have important policy implications for portfolio managers, hedge funds and investors.     

Structural breaks in the mean of dividend-price ratios: Implications of learning on stock return predictability

In their out-of-sample predictions of stock returns in the presence of structural breaks, Lettau and Van Nieuwerburgh (2008) implicitly assume that economic agents’ perception of the regime-specific mean for the dividend-price ratio is time-invariant within a regime. In this paper, we challenge this assumption and employ least squares learning with constant gain (or constant-gain learning) in estimating economic agents’ time-varying perception for the mean of dividend-price ratio. We obtain better out-of-sample predictions of stock returns than in Lettau and Van Nieuwerburgh (2008) for both the U.S. and Japanese stock markets. Our empirical results suggest that economic agents’ learning plays an important role in the dynamics of stock returns.     

Trump’s Effect on the Chinese Stock Market

U.S. President Donald J. Trump tweets frequently to communicate his thoughts to the public. We quantitatively evaluate the impact of Trump's China-related tweets on the Chinese stock market. We find that following Trump’s inauguration, his tweets with a positive sentiment significantly increase abnormal returns for the manufacturing industry in the Chinese stock market. Furthermore, an increase in the absolute value of his positive sentiment increases both the trading volume and volatility of the market. The positive effect is more pronounced for those subindustries with high exposure to international trade and stronger business relations with the United States than for other subindustries. The results are robust for various sensitivity tests.     

Contagion between real estate and financial markets: A Bayesian quantile-on-quantile approach

We study contagion between Real Estate Investment Trusts (REITs) and the equity market in the U.S. over four sub-samples covering January, 2003 to December, 2017, by using Bayesian nonparametric quantile-on-quantile (QQ) regressions with heteroskedasticity. We find that the spillovers from the REITs on to the equity market has varied over time and quantiles defining the states of these two markets across the four sub-samples, thus providing evidence of shift-contagion. Further, contagion from REITs upon the stock market went up during the global financial crisis particularly, and also over the period corresponding to the European sovereign debt crisis, relative to the pre-crisis period. Our main findings are robust to alternative model specifications of the benchmark Bayesian QQ model, especially when we control for omitted variable bias using the heteroskedastic error structure. Our results have important implications for various agents in the economy namely, academics, investors and policymakers.     

股票价格波动的信息渠道影响研究——基于媒体报道和分析师预测的视角

文章手工收集、整理了2006-2015年中国A股上市公司的媒体报道倾向数据，实证研究了媒体报道正向倾向与分析师乐观预测偏差对上市公司负收益偏态系数的影响。研究表明，虽然媒体报道正向倾向、分析师乐观预测均分别对上市公司股价负收益偏态系数产生显著的负向影响，但是两者的交互项对股价负收益偏态系数的影响则是显著为正，即当媒体报道正面倾向与分析师乐观预测两者共同作用时，将会触发"信息过度关注偏差"机制，从而降低了上市公司股票收益。文章研究还发现，媒体报道、分析师预测和"信息过度关注偏差"机制的作用强度，在市场化程度高地区要明显大于市场化程度低地区，可能的原因是市场化程度高地区的企业更加容易被媒体报道和分析师关注，进而产生更强的关注效应。