An examination of the dynamic behavior of aggregate bond and stock issues

Using a vector autoregressive (VAR) model, this article examines the dynamic behavior of aggregate bond issues and aggregate stock issues and how interest rates, stock market returns, and aggregate capital expenditures influence them. We find that an increase in stock market returns causes an increase in stock issues that persists over one quarter, while a decrease in interest rates leads to an increase in bond issues that persists over a full year. Aggregate capital expenditures have an immediate effect, but not a long-term effect, on bond issues. We also find that the financing process spreads over a period of at least 1 year. In the short run, an increase in aggregate bond issues leads to a decrease in aggregate stock issues, but in the long run (6 months to 1 year), an issue of either stocks or bonds makes subsequent financing by either stocks or bonds more likely.     

The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey

This paper investigates the effects of interest rate and foreign exchange rate changes on Turkish banks' stock returns using the OLS and GARCH estimation models. The results suggest that interest rate and exchange rate changes have a negative and significant impact on the conditional bank stock return. Also, bank stock return sensitivities are found to be stronger for market return than interest rates and exchange rates, implying that market return plays an important role in determining the dynamics of conditional return of bank stocks. The results further indicate that interest rate and exchange rate volatility are the major determinants of the conditional bank stock return volatility.     

Asymmetric effect of advertising on the Chinese stock market

In this paper, we investigate whether investor attention to advertising has an asymmetric effect on Chinese stock returns by using a multivariate Markov switching model with time-varying regime transition probabilities. Using the Chinese stock market as a setting, we obtain lagged conditional volatility from generalized autoregressive conditional heteroskedasticity (GARCH) for modelling the time-varying transition probabilities of the regime-switching process to capture changes in the market regime. Our evidence documents that the high advertising portfolio does earn higher abnormal return than the low advertising portfolio in low-volatility periods. In high-volatility periods, however, the abnormal return is insignificant when the firm increases advertising spending. Our results support the behavioural model argument that in high-volatility period, advertising information diffuses slowly due to cognitive dissonance. Thus, the effect of advertising on stock returns is asymmetric, and it shows statistical significance in low-volatility periods.     

Asymmetric spillover effects between the Shanghai and Hong Kong stock markets: evidence from quantile lagged regression

This article surveys the asymmetric spillover effects between the mainland China-based Shanghai Composite Index (SCI) and the Hong Kong based Hang Seng Index (HSI) using a quantile lagged regression model. Compared to previous studies, this article, based on data before and after the 2008 global financial crisis, presents a more detailed analysis, as we investigate the spillovers in terms of returns, volatilities and exchange rates between the renminbi (RMB) and the Hong Kong dollar (HKD) throughout the entire conditional return distribution, including the central quantiles, which are closely related to the normal circumstances, and the extreme quantiles, which correspond to the bear and bull markets. First, we find that the return spillovers from its lagged returns or from the other index not only vary across time but also depend on stock state. Second, while return volatility may boost the stock market in a bull market, it accelerates the decline in a bear market. Third, the depreciation of the RMB relative to the HKD does not significantly affect current returns for the HSI, while it negatively affects current returns for the SCI in a bad state after the crisis. The findings presented in this article will facilitate investors’ understanding of the two stock markets.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.     

Value at risk estimation by threshold stochastic volatility model

This article proposes a threshold stochastic volatility model that generates volatility forecasts specifically designed for value at risk (VaR) estimation. The method incorporates extreme downside shocks by modelling left-tail returns separately from other returns. Left-tail returns are generated with a t-distributional process based on the historically observed conditional excess kurtosis. This specification allows VaR estimates to be generated with extreme downside impacts, yet remains empirically widely applicable. This article applies the model to daily returns of seven major stock indices over a 22-year period and compares its forecasts to those of several other forecasting methods. Based on back-testing outcomes and likelihood ratio tests, the new model provides reliable estimates and outperforms others.     

Asset prices and economic fluctuations: The implications of stochastic volatility

This paper investigates whether the multi-factor stochastic volatility of stock returns is related to economic fluctuations and affects asset prices. We address these issues in a dynamic Fama-French three-factor volatility model framework. Consistent with the ICAPM with stochastic volatility (Campbell et al., 2017), we find that the conditional volatility of the size and value factors is significantly related to economic uncertainty. These volatilities are also significant pricing factors. The out-of-sample forecasting analysis further reveals that the conditional volatility can predict stock returns and deliver economic gain in asset allocation. Our analysis sharpens the understanding on the link between the stock market and economic fundamentals.     

Modelling conditional moments and correlation with the continuous hidden-threshold-skew-normal distribution

A key issue in modelling conditional densities of returns of financial assets is the time-variation of conditional volatility. The classic econometric approach models volatility of returns with the generalized autoregressive conditional heteroscedasticity (GARCH) models where the conditional mean and the conditional volatility depend only on historical prices. We propose a new family of distributions in which the conditional distribution depends on a latent continuous factor with a continuum of states. The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. The distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. We show empirically that this distribution outperforms its main competitor, the mixed normal conditional distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.     

股利政策稳定性对股票长期收益影响的实证研究

本文以1997—2007年中国A股市场上分红次数多于5次的股票为样本,以分红波动分组,采用日历时间回归方法研究了股利政策稳定性对股票长期收益的影响。为了更好地比较股利政策的影响,修正了Fama-French三因子模型。通过实证研究发现:分红股票相对于不分红股票存在超额收益,高股利股票较低股利股票有较高的超额收益。据此提出如下建议:监管机构应出台更为有效的政策来引导和管理上市公司进行股利分配,使股利支付趋于稳定,从而引导投资者理性投资。     

Tail risk in emerging markets of Southeastern Europe

This article examines the left-tail behaviour of returns on stocks in Southeastern Europe (SEE). We apply conditional extreme value theory (EVT) approach on daily returns of six stock market indices from SEE between 2004 and 2013. Predictive performance of value-at-risk (VaR) and expected shortfall (ES) based on EVT is compared against several alternatives, such as historical simulation and analytical approach based on GARCH with a single conditional distribution. Model backtesting with daily returns shows that EVT-based models provide more reliable VaR and ES forecasts than the alternative models in all six markets. Unlike the alternatives, the EVT-based models cannot be rejected as VaR confidence level is increased. This emphasizes the importance of extreme events in SEE markets and indicates that the ability of a model to capture volatility clustering accurately is not sufficient for a correct assessment of risk in these markets.     

An information theoretic analysis of stock returns,volatility and trading volumes

Information theory is used to examine the dynamic relationships between stock returns, volatility and trading volumes for S&P500 stocks. This provides an alternative approach to traditional Granger causality tests when dealing with nonlinear relationships. The article highlights the dominant role played by trading volumes in all of these relationships – even in the return–volatility relation – and finds evidence of a market level feedback effect from index returns to the return–volatility relation at the stock level. The article also produces a number of stylized facts from an information theoretic perspective.     

Exchange Rate Exposure of Sectoral Returns and Volatilities: Further Evidence From Japanese Industrial Sectors

In this paper we argue that the commonly employed exposure coefficient/beta is inadequate for capturing the entire impact of exchange rate changes on firms' future operating cash flows. Instead, we employ the bivariate Glosten–Jagannathan–Runkle generalized autoregressive conditional heteroskedasticity mean model to investigate four aspects of exchange rate exposure, including sensitivity of stock returns to exchange rate changes, sensitivity of stock returns to the volatility of exchange rate changes, sensitivity of conditional variance of returns to exchange rate volatility, and the dynamic conditional correlation between returns and exchange rate changes, respectively, using data from 10 industrial sectors in Japan. We find significant evidence of such exchange rate exposure which is not captured by the conventional measure. The diagnostic statistics confirm the adequacy of our model, and, hence, the robustness of the results.     

The Effect of Annual Earnings Announcements on the Chinese Stock Markets

This paper examines the annual earnings announcement effect of the stock markets in China. The investigation is based on events analysis and carried out by modeling the daily changes of stock returns using the M-EGARCH approach, by testing the news effects of annual earnings announcement on the conditional mean of abnormal return and the variance of the returns. It is found that a higher than expected earnings announcement leads to a rise in the conditional mean of stock returns on days before the news announcement and a fall afterwards. The conditional volatility of the changes are significantly reduced by bigger absolute values of reported earnings before the news announcement and increased afterwards, supporting the rejection of semi-strong-form efficiency.     

The impact of 11/13 Paris terrorist attacks on stock prices: evidence from the international defence industry

This study explores the effect of the Paris terrorist attacks on the stock returns and the volatility for the most important companies in the global defence industry. To this end, it employs the General Autoregressive Conditional Heteroscedasticity methodology. The findings clearly indicate that this terrorist event has a positive impact on both the returns and the volatility of these stocks.     

DYNAMIC CORRELATION BETWEEN STOCK RETURNS AND EXCHANGE RATE AND ITS DEPENDENCE ON THE CONDITIONAL VOLATILITIES – THE CASE OF SEVERAL EASTERN EUROPEAN COUNTRIES

The objective of the paper is to determine whether the linkage between stock returns and exchange rates in several Eastern European countries was in accordance with the flow oriented model or the portfolio‐balance approach. The dynamic interdependence between exchange rate and stock returns is determined using the Dynamic Conditional Correlation (DCC) framework. The results pointed to a negative dynamic correlation which is in line with portfolio‐balance approach. Rolling regression revealed that conditional correlation was affected primarily by conditional volatility of currency, while the impact of stock returns volatility was negligible.     

Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach

This article adopts a nonparametric quantile causality approach to examine the causal effects of the U.S. and Japan stock markets on the stock markets of the Pacific-Rim region. This approach allows us to detect not only nonlinear causalities in conditional return (mean) and conditional volatility (variance) but also the asymmetries of causalities under extreme market conditions (bullish vs. bearish states). Our results provide significant evidence of causality in return and volatility at different points of the conditional distributions of returns, with the greater effects from the U.S. than from Japan. Asymmetric quantile causality patterns are particularly pronounced in the case of Japan.     

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.     

Volatility Spillovers and Contagion from Mature to Emerging Stock Markets

This paper models volatility spillovers from mature to emerging stock markets, tests for changes in the transmission mechanism during turbulences in mature markets, and examines the implications for conditional correlations between mature and emerging market returns. Tri‐variate GARCH–BEKK models of returns in mature, regional emerging, and local emerging markets are estimated for 41 emerging market economies (EMEs). Wald tests suggest that mature market volatility affects conditional variances in many emerging markets. Moreover, spillover parameters change during turbulent episodes. In the majority of the sample EMEs, conditional correlations between local and mature markets increase during these episodes. While conditional variances in local markets rise as well, volatility in mature markets rises more, and this shift is the main factor behind the increase in conditional correlations. With few exceptions, conditional beta coefficients between mature and emerging markets tend to be unchanged or lower during turbulences.     

房地产市场对银行收益的系统性影响研究——以美国、中国香港、中国大陆市场为例

文章研究了三地上市银行和房地产公司股票之间的收益关系,发现三个市场的银行股票收益都显著地受到房地产股票波动的影响,并且利用三地数据的结构性差异点,确定了次贷危机发生作用的时点.对比次贷危机前后的三个市场银行股和房地产股票收益的关系后发现,代表银行股收益对房地产股波动敏感性的回归系数在次贷危机后均有所增大,显示美国和中国的银行业所面临的房地产风险已经由非系统性风险转变为系统性风险,其风险敞口在加大.