The effects of haze pollution on stock performances: evidence from China

Haze pollution has become the most important environmental issue in China in recent years. Using the data of PM_2.5 concentration and stocks of listed companies located in Beijing between 2010 and 2014, this article investigates the effects of haze pollution on stock performances. Empirical results indicate that haze pollution has significant negative effects on stock returns and significant positive effects on stock volatilities, through the channel of investors’ mood. Furthermore, the effects of haze pollution on stock returns emerge gradually and the effects of haze pollution on stock volatilities weaken gradually over time during a trading day.     

Dynamic linkages between Asian stock prices and exchange rates: new evidence from causality in quantiles

This article applies the Granger causality test in quantiles to investigate causal relations between stock returns and exchange rate changes for nine Asian markets over the period 1 January 1997 to 16 August 2010. Our empirical results indicate that the quantile causal relations vary across different quantiles and different periods. Although the causal effects of exchange rate changes on stock returns (or stock returns on exchange rate changes) are heterogeneous across quantiles, the overall evidence suggests that most stock and foreign exchange markets are negatively correlated. The result shows that there are more bidirectional causal relations in accordance with this method than the conventional least square (LS) estimation. The symmetry of these quantile causal effects (the ‘averaging effect’) helps to explain why conventional LS method usually obtains an insignificant result of causality.     

Causal relationship between stock returns and real economic growth in the pre- and post-crisis period: evidence from China

This article empirically examines the causality in mean and variance between stock returns and real economic growth in China before and after the outbreak of US subprime crisis. Using a nonuniform weighting cross-correlation approach and the multivariate generalized autoregressive conditional heteroscedasticity model, we found no causality in mean or variance between China’s stock returns and real economic growth for the period before the subprime crisis. Interestingly, however, in the period after the crisis, we detected unidirectional causality in mean from real economic growth to stock returns and unidirectional causality in variance from stock returns to real economic growth. These new findings imply that the linkage between China’s stock market and its real economy has become stronger in the post-crisis period. The implication of our results is that Chinese policymakers should continue the deregulation and improve the efficiency of the stock market to sustain high economic growth rate in the future.     

The effects of the Paris climate agreement on stock markets: evidence from the German stock market

We investigate the effects of the 2016 Paris Climate Agreement on the German stock market by considering the impact of 20 announcements pertaining to the Agreement on 17 industries. The event study methodology is used for this purpose, together with several robustness tests, such as the nonparametric rank test and non-parametric conditional distribution approach. The change in systematic risk following the announcements is captured by using various risk models. In general, we find that the Paris Climate Agreement is achieving its objectives in the short run. Our results show that the announcements affected polluting industries in terms of risk and return. Furthermore, we observe two distinct diamond risk structures when (1) Conference of the Parties (COP) 21 took place, and (2) the Agreement came into force.     

The stock market effect of air pollution: evidence from China

In financial studies, environmental stimuli such as sunshine, temperature, and daylight are often used as proxies for people’s collective mood swings to test their effects on the stock market. China has experienced serious air pollution problems in recent years, and Chinese public awareness of air pollution has soared. In this paper, we use China as a natural experiment to investigate the effect on stock returns of depressed moods induced by air pollution. Daily air-pollution data from 2005 to 2014 are analysed and the results obtained from the empirical research show that a contemporaneous negative and a two-day lagged positive relationship exists between air pollution levels and stock returns over this time period. The relationship is mediated by the influence of air pollution on investment decisions. The results also indicate that the effect is weakened for companies that protect air quality, but no stronger effect is detected for polluting companies. The findings imply that air pollution is a behavioural factor with some connection to stock returns in China.     

Measuring and testing the long-term impact of terrorist attacks on the US futures market

This study compares the accuracy and information content of economic forecasts for G7 countries made in the 1990s by the OECD and IMF. The benchmarks for comparison are the average forecasts of private sector economists published by Consensus Economics. With few exceptions, the private sector forecasts are less biased and more accurate in terms of mean absolute error and root mean square error. Formal tests show these differences are statistically significant for forecasts of real growth and production, less so for forecasts of inflation and unemployment. Overall, there appears little information in the OECD and IMF forecasts that could be used to reduce significantly the error in the private sector forecasts.     

The effect of oil prices on stock prices: fresh evidence from asymmetric causality tests

This article investigates the causal impact of oil prices on stock prices in each G7 market as well as in the world market. An asymmetric causality test developed by Hatemi-J is used for this purpose. Since the underlying data appears to be non-normal with time-varying volatility, we use bootstrap simulations with leverage adjustments in order to produce more reliable critical values than the asymptotic ones. Based on symmetric causality tests, we find no causal effect of oil prices on the stock prices of the world market or any of the G7 countries. However, when we apply an asymmetric causality test, we find that increasing oil prices cause stock prices to rise in the world, the U.S. and Japan while decreasing oil prices cause stock prices to fall in Germany. This may imply that the world, the U.S. and Japanese stock markets consider increases in oil prices as an indicator of good news as this may mean that there is an increase in oil demand due to an expected growth in the economy while the German stock market treats decreasing oil prices as a signal of an expected contraction in the economy.     

Information in stock prices: the case of the 2016 U.S. presidential election

On the day before the 2016 U.S. presidential election, the odds of Hillary Clinton winning the presidency, according to political prediction markets, were above 90%. Surprisingly, Donald Trump won the Electoral College handily. In this study, we examine how movements in specific stock prices foreshadowed the eventual outcome. Specifically, we conduct a series of standard event-study tests focused on pharmaceutical companies, which became a focal point during the presidential campaign. Results show that while stocks of pharmaceutical companies significantly underperformed the market prior to the election, prices substantially increased beginning three days before the election outcome. This increase is both statistically significant and economically meaningful and robust to various event-study methodologies. These results suggest that some sectors of the stock market seemed to anticipate the election outcome.     

Asymmetric effects of oil price shocks on stock returns: evidence from a two-stage Markov regime-switching approach

The asymmetric effects of oil price shocks on stock returns have attracted the attention of many researchers in the past several decades. Most of these researchers’ studies, however, do not separate out the sources of oil price shocks when examining the asymmetric effects. In this article, we address this limitation using a two-stage Markov regime-switching approach. Our results indicate that oil supply and demand shocks have a null or minimal impact on stock returns in a low-volatility regime and a statistically significant impact in a high-volatility regime. We observe that oil demand shocks affect stock returns significantly more than oil supply shocks. A positive aggregate demand shock significantly increases stock returns, whereas a positive oil-specific demand shock markedly decreases stock returns. These results have important implications for policymakers and investors.     

On the forecastability of share prices on the Viennese stock exchange

In this paper the Viennese stock exchange data are analysed by using ARMA and GARCH technology. After using AIC and BIC for estimating the linear structure of the time series, to the resulting innovations a GARCH(1,1) model is fit. The resulting residuals are then tested for serial independence and constancy of its distribution to check whether the models are reasonable. Main result is that the residuals of this ARMA-GARCH(1,1)-model are reasonably iid (which is checked by BDS and classical independence tests) for index data and significantly less well-behaved for stock data. Second, there is considerable autocorrelation in the data (especially in the Viennese indices WBK and ATX) which can be exploited even with 1.25% transaction costs (which is checked by a posteriori analysis of a strategy which exploits an underlying time-varying AR(1) model), however, much higher profit can be made with 0.5% transaction costs. Furthermore, the same techniques are applied to US Standard & Poor 500 index and the results for both data sets are compared giving the result that the US-market looks much more mature than the Viennese one.Financial Support by the Institute for Advanced Studies, Vienna, and the Fonds zur Förderung der wissenschaftlichen Forschung, Vienna, Grant P 9176 is gratefully acknowledged. This paper is a slightly abbreviated version of the Research Report No. 135 by the same authors (see References), which contains many detailed plots of the results.     

The cross-section and time-series effects of individual stock sentiment on stock prices

In this article, we construct an individual stock sentiment index by using the principal component analysis method. We empirically study the cross-section and time-series effects of investor sentiment on the stock prices based on the panel data model with dummy variable. The results indicate that individual stock sentiment has greater impact on small-firm stock prices than big-firm stock prices, which presents obvious cross-section effect. Moreover, individual stock sentiment leads to much sharper ?uctuations of stock prices in the stock market downturn than in the stock market expansion, which shows obvious time-series effect. Specifically, the individual stock sentiment has the greatest impact on small-firm stock prices under the stock market downturn, exerting significant dual asymmetric effect. Our results are helpful to understanding the micro-mechanism of sentiment effect.     

Economic integration and stock market dynamic linkages: evidence in the context of Australia and Asia

Countries are becoming economically integrated and it is contended that this will also lead to their financial markets becoming integrated. This contention is important since international financial market integration diminishes portfolio diversification benefits and creates contagion risk. We test this contention in this article in the context of the Australasian region. Australia and Asia have experienced very significant economic integration through a rapid growth in their bilateral trade. We utilize a battery of econometric techniques – cointegration, asymmetric generalized dynamic conditional correlations and panel regression models. As expected, we find that trade intensity significantly drives the interdependence between their stock markets in both the short run and the long run. Thus, given the ever increasing economic integration in this region, this finding implies that their stock markets face the risk of contagion, and that investors in these markets would also be confronted with the prospect of lower diversification benefits.     

Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy

Using daily stock return data for individual stocks from an emerging economy, this article examines the relationship between return volatility and trading volume under the theoretical postulate of the mixture of distributions hypothesis. The results suggest that the contemporaneous trading volume as a proxy for latent information arrival to the market did not contribute to the removal of significant ARCH or Generalized Autoregressive Conditional Heteroscedasticity effects that are found in stocks at the first stage of the investigation. The same holds for the lagged volume except for one case. This, perhaps, suggests that the trading volume (contemporaneous or lagged) is not adequately conveying information to induce traders’ views of the desirability of trade and, therefore, points to the need for searching for other micro and macro variables to be used as potential proxy for information arrival to the stock market of the emerging economy.     

The effect of debt capacity on the long-term stock returns of debt-free firms

This article examines the long-term stock market performance of debt-free firms with high and low levels of debt capacity to see whether they are different. We use Fama and French’s (1993) three-factor and Carhart’s (1997) four-factor models to examine the subsequent 1, 2, 3, 4 and 5-year stock returns of firms that stayed debt free for 3- and 5-year periods. We measure debt capacity as the expected asset liquidation value of a firm, which is proxied by the firm-level tangibility measure defined by Berger, Ofek, and Swary (1996). We find that regardless of the level of debt capacity, zero-debt firms generate positive abnormal returns in the long run after controlling for key risk factors. We also find support for the notion that preserving debt capacity in the form of higher tangibility reinforces the positive abnormal returns over and above the effect of a zero-leverage policy.     

The sectoral effects of Brexit on the British economy: early evidence from the reaction of the stock market

We investigate the impact of the outcome of the EU referendum (Brexit) on various sectors of the British economy over the period June–July 2016. Using the event study methodology, we assess the effects of Brexit, relative to what had been anticipated, as measured by abnormal returns (ARs). The results show that the banking and travel and leisure sectors were affected negatively, with a cumulative AR of ?15.37% for the banking sector. We observe that Brexit has a mixed effect on ARs with apparent sector-by-sector differences.     

The impact of environmental regulations on international competitiveness of textile industry in China

A greater focus of environmental protection is directed toward environmental regulations in China. This paper focuses on environmental regulations and their impact on textile industry. The academic circle does not reach a consensus on the relationship between environmental regulations and international competitiveness. Some hold the view that environmental regulations lower international competitiveness while others think that environmental regulations improve both environment and economic performance. This paper aims to analyze the impact of the environmental regulations on the international competitiveness of textile industry in China. This study starts with theories relative to this subject; the second part, based on the impact mechanism of environmental regulations on competitiveness, analyzes the environmental impact on textile from the perspective of cost and market. The conceptual exploration comes to the conclusion that environmental regulations make a negative impact on the international competitiveness on the cost side and improve it by means of innovation and product differentiation on market side; the third part gives time series evidence to examine the impact. In this part the Pearson Correlation Analysis is conducted based on the data of China＇s textile industry of the period from 1991 to 2005. It turns out to prove that the negative environmental impact on cost side exceeds the positive environmental impact on market side, namely, environmental regulations deteriorate the international competitiveness in textile industry as a whole during the inspected period.     

The effect of quantitative easing on stock prices: a structural time series approach

A structural time series model is estimated and tested to examine the effect of quantitative easing (QE) on US stock prices. The model is estimated by maximum likelihood in a Time-varying parametric (TVP) framework, using the S&P 500 index as the dependent variable and the Fed’s balance as an explanatory variable in addition to the unobserved components accounting for the behaviour of variables that do not appear explicitly in the equation. The results show that QE had a sizeable, but not exclusive, effect on stock prices and that stock prices were also affected by other missing variables and cyclical movements. Several explanations are presented for the rise of the US stock market in the post-QE period, particularly since the election of Donald Trump.     

The impact of electricity prices on foreign direct investment: evidence from the European Union

We examine the impact of electricity price variation on net FDI (%GDP) inflows in countries of the European Union. We use panel data of 27 EU countries for a period of 2003 – 2013. We show that electricity prices of south-western and north-eastern EU countries did not converge to one price until now. Dynamic panel data analysis using system GMM shows that besides unit labour costs, tax rates and competitive disadvantage in secondary education, also higher electricity prices reduce countries’ ability to attract FDI. The immediate effects are statistically significant across both sub-regions analysed: in the short run, a 10% increase in electricity prices leads to a decrease in net FDI inflows as a share of GDP by 0.4 percentage points for the south-western and 0.33 for the north-eastern region. In the long run, the response is 0.60 percentage points for south-western and 0.48 for north-eastern regions. Policies should aim at reducing electricity market price differences on the European level through investment in transborder transmission capacity; reductions in FDI, when environmental policy increases after-tax electricity prices, should be countered by other tax reductions as well as harmonization of property rights, absence of corruption and labour market regulations at best-practice level.     

The influence of cultural distance on the volatility of the international stock market

Along with the development of cultural dimensions and cultural distance, the influence of cultural variables on the stock market is attracting more and more attention. In this study, we propose an improved gravity model to examine the relationship between culture and the volatility of the international stock market. Firstly, based on Hofstede's cultural dimensions theory, a model of the impact of cultural dimensions on the volatility of the national stock market is presented. Secondly, cultural distance is incorporated into the extended gravity model. Then, models of the impact of cultural distance on fluctuations in the international stock market and on foreign securities investment are proposed. Finally, the results of case studies using samples of national stock market indices indicate that different cultural dimensions have different influences on the volatility of national stock markets. The smaller the cultural distance between countries, the more similar the level of volatility in those countries' stock markets. Greater cultural similarity promotes increased securities investment between countries.     

The impact of news,oil prices,and global market developments on Russian financial markets1

This paper analyses the impact of news, oil prices, and international financial market developments on daily returns on Russian bond and stock markets. First, regarding returns, energy news affects returns, while news from the war in Chechnya is not significant. Market volatility does not appear to be sensitive to either type of news. Second, a significant effect of the growth in oil prices on Russian stock returns is detected. Third, the international influence on Russian financial markets depends upon the degree of financial liberalization. The higher the degree of financial liberalization, the stronger is the impact of US stock returns on Russian financial markets. In addition, banking reform and interest rate liberalization efforts seem to dictate the globalization of Russian stock markets, while it is the progress in liberalizing securities markets and non‐bank financial institutions that matters more for the globalization of Russian bond markets.