Cyclicality of stock market volatility

By utilizing the significance and stochastic dominance tests, this paper formally tests the relationship between stock market volatility and the business cycle. Results show that, for most matured markets, stock market volatility is countercyclical, while for emerging markets, the volatility can be procyclical.     

An empirical analysis of the US stock market and output growth volatility spillover effects on three Anglo-Saxon countries

This paper examines the dynamic and switching effects of volatility spillovers arising from US stock market returns and GDP growth on those of Australia, Canada and the UK. For this purpose, we use quarterly data (1961q1–2013q1) and a constant probability Markov regime switching model. We found that the US stock market volatility significantly affects the stock market volatility of all three countries at least in one of the two specified regimes over time. However, the stock market volatilities in none of the three countries are contemporaneously influenced by the US output volatility even after allowing for two distinct regimes. On the other hand, the US stock market volatility exerts significant influences on the output volatilities of both Australia and the UK. Compared with Australia and the UK, Canada and the US show substantial output volatility co-movements, thereby confirming the close association between the two neighbouring economies through the NAFTA (North American Free Trade Agreement). We conclude that shocks emanating from the US stock market have unequivocal flow-on effects on the output and return volatilities of the other economies.     

Economic policy uncertainty and the Chinese stock market volatility: new evidence

This study investigates the impacts of the economic policy uncertainty (EPU) indexes of China and the G7 countries on Chinese stock market volatility and further constructs a new diffusion index based on these indexes using principal component analysis (PCA) to achieve enhanced predictive ability. The in-sample results indicate that the EPU indexes of China and some of the G7 countries show a significantly negative impact on future volatility. Moreover, our constructed diffusion index also has a significantly negative impact. Furthermore, the out-of-sample results show that this diffusion index exhibits a significantly higher forecast accuracy than the EPU itself and combination forecasts. Finally, various robustness checks are consistent with our main conclusions. Overall, we construct a new and useful indicator that can substantially increase forecast accuracy with respect to the Chinese stock market.     

Financial market segmentation,stock market volatility and the role of monetary policy

We study a segmented financial markets model where only the agents who trade stocks encounter financial income risk. In such an economy, the welfare-maximizing monetary policy attains the novel role of redistributing the traders' financial market risk among all agents in the economy. In order to do that, optimal monetary policy reacts to financial market movements; it is expansionary in bad times for the financial markets and contractionary in good ones. In our quantitative exercise, a dividend shock generates different policy responses and consumption paths among the optimal and the 2% inflation targeting policy. The latter implies large distributional welfare losses and risk sharing losses of similar magnitude with those generated by business cycle fluctuations. In addition, the optimal monetary policy does not minimize stock price volatility and implies lower inflation volatility than other commonly used policies.     

Investment horizons,cash flow news,and the profitability of momentum and reversal strategies in the Chinese stock market

This study investigates the profitability of momentum and reversal strategies of different investment horizons in the Chinese stock market. The findings indicate that momentum strategies are profitable for investment horizons less than one week. For longer investment horizons, reversal strategies are profitable. This result is very different from the US market, where profitable momentum strategies yield to much longer investment horizons. We show that this is because investors in Chinese stock market generally overreact to the company cash flow news while investors in US market underreact to cash flow news.     

股票市场系统动力学分析：以上海股票市场为例

本文突破了传统经济理论研究的线性框架,视股票为一非线性系统,运用分形、混沌等复杂性理论对上海股票市场的系统动力学特征进行实证研究,得出了上海股票市场系统的分形特征、复杂性程度、系统演化类型及稳定性,最后,探讨了这些结论对股票市场的理论与实践意义。     

A closer look at the determinants of international migration: decomposing cultural distance

Using a modified gravity model and three measures of cultural distance, we employ the zero-inflated negative binomial estimation technique to examine the impact of cultural distance on international migration flows. We confirm the finding of prior studies that there exists a negative relationship between composite measures of cultural distance and immigrant flows. Extending the literature, we decompose our composite cultural distance measures into their component dimensions to examine potential variability in the influences of individual dimensions on international migration. We find the cultural dimensions that reflect individualism, uncertainty avoidance, and perceived gender roles are typically more influential in determining immigrant flows than are other cultural dimensions.     

Crude oil and BRICS stock markets under extreme shocks: New evidence

In this paper, we propose an extreme Granger causality analysis model to uncover the causal links between crude oil and BRICS stock markets. Instead of analyzing the average causal relationship, as is usually done, we first decompose the data into three cumulative components and investigate the causality between different combinations of extreme positive, extreme negative and normal shocks. These types of combinations can describe all facets of the interactions between crude oil and BRICS stock markets, especially under extreme shocks. In contrast to the results obtained by the traditional Granger causality test, our empirical findings demonstrate that the effect of oil price changes on the stock markets is stronger under extreme circumstances than under normal circumstances. Furthermore, large upward or downward oil price changes have an asymmetric impact on extreme upward or downward stock price changes. Finally, robustness checks verify the rationality and validity of the extreme Granger causality analysis.     

Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash

Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.     

The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach

Abstract This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe‐Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show significant asymmetric static and dynamic tail dependence between the real stock returns and the real exchange rate returns, such that the two returns are more dependent in the left than in the right tail of their joint distribution. We explain this asymmetric dependence in terms of an asymmetric interest rate policy by Canadian monetary authorities in response to changes in the real exchange rate during sub‐periods of falling and rising commodity prices.     

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.     

The effect of the liberalization of the Chinese stock market on returns

We examine the short-term effects of the liberalization of the Chinese stock market on returns. We find a positive and significant abnormal return associated with the announcement of the liberalization of the Shanghai Stock Exchange. Exploiting features of the reform, we are able to compare stocks directly and indirectly affected by the liberalization. We find that all stock prices reflect this announcement premium equally, suggesting that the premium does not reflect an increase in expected liquidity. We further find that observed liquidity, as measured by volume and price impact, did not increase following the liberalization. We conclude that the observed premium reflects a diversification benefit for Chinese investors.     

Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market

This paper focuses on investigating financial asset returns' extreme risks, which are defined as the negative log-returns over a certain threshold. A simple agent-based model is constructed to explain the behavior of the market traders when extreme risks occur. We consider both the volatility clustering and the heavy tail characteristics when constructing the model. Empirical study uses the China securities index 300 daily level data and applies the method of simulated moments to estimate the model parameters. The stationarity and ergodicity tests provide evidence that the proposed model is good for estimation and prediction. The goodness-of-fit measures show that our proposed model fits the empirical data well. Our estimated model performs well in out-of-sample Value-at-Risk prediction, which contributes to the risk management.     

China's liberalizing stock market,crude oil,and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.     

South African stock return predictability in the context data mining: The role of financial variables and international stock returns

In this paper, we examine the predictive ability, both in-sample and the out-of-sample, for South African stock returns using a number of financial variables, based on monthly data with an in-sample period covering 1990:01 to 1996:12 and the out-of-sample period of 1997:01 to 2010:04. We use the t-statistic corresponding to the slope coefficient in a predictive regression model for in-sample predictions, while for the out-of-sample, the MSE-F and the ENC-NEW tests statistics with good power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the critical values of both the in-sample and out-of-sample test statistics. Furthermore, we use a procedure that combines in-sample general-to-specific model selection with out-of-sample tests of predictive ability to further analyse the predictive power of each financial variable. Our results show that, for the in-sample test statistic, only the stock returns for our major trading partners have predictive power at certain short and long run horizons. For the out-of-sample tests, the Treasury bill rate and the term spread together with the stock returns for our major trading partners show predictive power both at short and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data mining. The general-to-specific model shows that valuation ratios contain very useful information that explains the behaviour of stock returns, despite their inability to predict stock return at any horizon. The model also highlights the role of multiple variables in predicting stock returns at medium- to long run horizons.     

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.     

中国推出股指期货的可行性分析

中国股票市场正在经历前所未有的变革，推出股指期货就是其中之一。推出股指期货可以完善证券市场的功能体系。有利于培育投资者的成熟度，进而促进股市与经济运行的关联程度，发挥股市经济“晴雨表”的功能。同时，中国已有17年股票市场和商品期货市场的管理经验，具备了发展股指期货的条件，只要能充分控制其潜在的风险，推出股指期货对整个股票市场是有利的。     

The dynamic impact of bilateral trade linkages on stock market correlations of Australia and China

This article aims to examine the long-run equilibrium relationship between bilateral trade linkages and stock market correlations of Australia and China using quarterly data from 1993 to 2015. Further, this study explores the impact of trade intensity on stock market correlations using OLS, Dynamic OLS (DOLS) and Fully Modified OLS (FMOLS) models. The empirical results confirm that there is a significant long-run relationship among the variables. In addition, our results, based on OLS, DOLS and FMOLS, show that increasing trade intensity between Australia and China has a significant and positive impact on their stock market correlations. The Global Financial Crisis also contributed for their stock market interdependence. Our results therefore suggest that the bilateral trade relations between Australia and China have brought their stock markets together over time. The findings of this study offer significant policy and practical implications. The policymakers need to be aware of the economic changes in those countries as they will immediately reflect on their stock market performance and relationship. Similarly, the global investors need to be aware of the fact that the diversification opportunities between Australia and China have considerably declined over time as their markets became more interdependent in the recent past.     

Modelling the volatility of the tanker freight market based on improved empirical mode decomposition

In this article, a method based on empirical mode decomposition (EMD) and BEKK–Multivariate GARCH (MVGARCH) is developed to analyse the volatility of the tanker freight market. First, the initial time series of tanker freight rates is decomposed into several independent intrinsic mode functions (IMFs). Next, the IMFs are composed as three components by an improved EMD: the long-term trend time series that represents the benchmark freight rates of the tanker freight market, the high-frequency time series that reflects the short-term supply–demand relation and the low-frequency time series caused by extreme events. Based on the results of EMD, the volatility spillover effects between the freight rates of Aframax, Suezmax and Very Large Crude Carrier (VLCC) markets are tested by the BEKK–MVGARCH model. The results indicate that there are volatility spillover effects between the reconstructed components, although the volatility spillover effects between the original freight series are not significant. The improved EMD method contributes to the retention of the economic characteristics of the original time series, thereby providing a vital approach for tanker freight market analysis. Furthermore, the potential volatility spillover among different sub-markets can be investigated through the integration of EMD and the BEKK–MVGARCH.     

On the dynamic effects of global commodities on stock market blocks in Africa

This article explores the commodity–equity links in the Africa markets by distinguishing between short- to long-run co-movements driven by market shocks. Using the value-weighted average method, available Africa’s stock markets are aggregated into four market blocks. Global oil and gold returns are used as proxies for commodities. Coherency between pairs of markets is examined with the use of continuous Morlet wavelet transform. Results reveal abstemiously high degree of co-movements between the commodity–equity markets in the short- to medium-term frequencies with nonhomogenous lead–lag nexuses, signifying greater benefits of diversification in the long-term. These findings provide investors with relevant strategies for hedging.