RISK–RETURN TRADE‐OFF AND BEHAVIOUR OF VOLATILITY ON THE SOUTH AFRICAN STOCK MARKET: EVIDENCE FROM BOTH AGGREGATE AND DISAGGREGATE DATA

The study analyses the nature and behaviour of volatility, the risk–return relationship and the long‐term trend of volatility on the South African equity markets using aggregate level, industrial level and sectoral level daily data for the period 1995‐2009. By employing dummy variables for the Asian and the sub‐prime financial crises and the 11 September political shock, the study further examines whether the long‐term trend of volatility structurally breaks during financial crises and major political shocks. Three time‐varying generalised autoregressive conditional heteroskedasticity models were employed: one of them symmetric, and the other two asymmetric. Each of these models was estimated based on three error distributional assumptions. The findings of the study are as follows: First, volatility is largely persistent and asymmetric. Second, risk at both aggregate and disaggregate level is generally not a priced factor on the South Africa (SA) stock market. Third, the threshold autoregressive conditional heteroscedasticity (TARCH) model under the generalised error distribution is the most appropriate model for conditional volatility of the SA stock market. Fourth, volatility generally increases over time, and its trend structurally breaks during financial crises and major global shocks. The policy and investment implications of the findings are outlined.     

宏观经济因素对我国股票市场波动影响的实证分析

股票市场的发展与一国的宏观经济因素存在密切的联系,本文选取工业增加值增长率,居民消费价格指数、利率、汇率、货币供应量、上证综合指数这6个变量建立VAR模型,并进行脉冲响应分析,对宏观经济因素对我国股票市场价格变动的影响进行定量分析。分析得出宏观经济因素与股票价格波之间存在长期稳定的均衡关系,并且货币政策只有很微弱的影响作用。     

Global commodity prices and global stock market volatility shocks: Effects across countries

We investigate the time-varying dynamics of global stock market volatility, commodity prices, domestic output and consumer prices. We find (i) stock market volatility and commodity price shocks impact each other and the economy in a gradual and endogenous adjustment process, (ii) impact of commodity price shock on global stock market volatility is significant during global financial crises, (iii) effects of global stock market volatility on the US output are amplified by endogenous commodity price responses, (iv) effects of global stock market volatility shocks on the economy are heterogeneous across nations and relatively larger in twelve developed countries, (v) four developing/small economies are more vulnerable to commodity price shocks.     

The Effects of Central Banks’ Rate Change Patterns on Financial Market Variables

This study examines whether different patterns of change to the benchmark interest rates of central banks are associated with their contributions to variances in the forecast errors of three financial market variables: the long-term interest rate, the foreign exchange rate, and the stock market index. On average, the central bank’s interest rate accounts for approximately 20% of the variance in each variable. We find that the total range of changes is more important than the frequency of changes. The panel regression shows that the range and frequency of policy rate changes is positively associated with the volatility of long-term interest rates but no association with the volatility of stock prices and exchange rates. These results suggest that small and frequent adjustments of policy rates are desirable for reducing the volatility of interest rates. The panel VAR represents interest rate channel is a more important than exchange rate and stock price channel.     

基于GARCH模型的上证指数与GDP波动性研究

中国的证券市场与宏观经济关系已进入弱相关阶段,本文通过使用ADF检验、ARCH效应检验、GARCH模型分析以及Granger检验对两者的波动性进行分析和研究。实证结果发现,中国的证券市场与宏观经济都具有非正态分布的特性。其次,证券市场不存在自回归条件异方差效应波动,宏观经济存在自回归条件异方差效应波动,并且GARCH(1,1)最适合描述宏观经济的自回归条件异方差效应波动,上证指数的预测与宏观经济的预测两者之间具有互相印证的关系。     

房地产上市公司股价影响因素实证分析

近年来,在持续的房地产调控政策影响下,我国商品房市场开始出现成交量大幅下滑,房价逐步松动下滑的现象。但在此期间,房地产上市公司股票价格不仅强于大盘走势,而且其波动幅度也高于房地产销售价格指数。为此,本文选择房地产上市公司股票价格指数为因变量,选择上证综指、发电量增长率、CPI、人民币贷款利率、房地产价格指数五个因素指标为自变量进行多元回归统计建模,模型检验结果表明,房地产上市公司股价波动除具有一般金融资产价格波动的系统性、集聚性等特点外,还具有与人民币贷款利率和房屋销售价格指数负相关的特点。受宏观调控政策的持续影响,中国当前房地产市场出现一定程度的扭曲,实体经济增长对房地产上市公司股价的影响不显著。     

投资者结构与股价波动：基于过度自信和注意力分配的理论分析

本文假定市场上仅存在散户和机构,且他们之间存在过度自信的差异和对多期私有信息注意力分配方式的差异,在此基础上对投资者结构和股价波动的关系进行了理论分析,并进一步研究了投资者结构的长期均衡问题。研究表明,当两种差异同时存在时,第一,市场上现有的投资者结构决定了散户或机构比例的上升是否增加股价波动。如果市场是散户主导的,那么散户比例的上升将加剧股价波动;如果市场是机构主导的,那么在特定情形下,机构比例的上升将加剧股价波动。第二,散户在长期均衡时不仅不会彻底消失,甚至会在特定情形下完全占据市场。     

Global Financial Crises and Time‐Varying Volatility Comovement in World Equity Markets

This paper studies volatility comovement in world equity markets between 1994 and 2008. Global volatility factors are extracted from a panel of monthly volatility proxies relating to 25 developed and 20 emerging stock markets. A dynamic factor model (FM) is estimated using two‐year rolling‐window regressions. The FM's time‐varying variance shares of global factors map variations in volatility comovement over time and across countries. The results indicate that global volatility linkages are significantly stronger during financial crisis periods in Asia (1997‐1998), Brazil (1999), Russia (1998) and the United States (2000, 2007‐2008). Emerging markets are weakly synchronised with world volatility in comparison with developed markets. In particular, emerging market comovement is significantly lower than developed market comovement during the Asian and US sub‐prime crises. This suggests a degree of decoupling of emerging markets from the global drivers of volatility during these periods.     

Inflation and Market Uncertainty in South Africa

Comparison of the movements in the VIX index, the rand – dollar exchange rate and South African CPI inflation reveals a striking resemblance between them, raising the question as to whether or not there is an empirical relationship among them. The aim of this paper is to determine whether or not changes in market uncertainty, as reflected in the VIX index, influence South African inflation. Given that the VIX index reflects market uncertainty, its impact on the inflation rate may differ between times of heightened uncertainty and normality, thus suggesting the presence of multiple regimes. To cater for this possibility, the analysis first uses the general‐to‐specific procedure (including squared and cubed values of dependent and independent variables) with impulse indicator saturation dummies to look for non‐linear behaviour in the form of statistically significant squared and cubed variables and clustered periods of outlier dummies that might reflect an alternative regime. Finding such periods, the analysis next uses a Markov‐switching model to model this non‐linear behaviour explicitly. The results show that market volatility as measured by the VIX indeed explains South African inflation. Moreover, as shown by the second regime of the Markov‐switching model, when market volatility is elevated, its influence on inflation also increases.     

International spillovers of U.S. monetary uncertainty and equity market volatility to China’s stock markets

Due to the global economy that is currently being increasingly integrated and liberalized, the cross-country transmission of U.S. monetary policy surprises has become a critical issue attracting scholarly attention. This research thus extends the existing literature by assessing the causal linkages among U.S. monetary policy uncertainty (USMPU), equity market volatility, and China’s stock price index over the period from January 1994 to August 2021. We apply Granger causality in quantile analysis to explore the relationships in each quantile of the distribution in a comprehensible manner. The results indicate that equity market volatility and China’s stock price dynamics play little role in affecting USMPU. We also find that only greater changes in both positive monetary policy uncertainty and stock prices lead to changes in equity market volatility. Furthermore, fluctuations in monetary policy uncertainty and equity market volatility in the United States Granger-cause China’s stock prices. Knowing such causality results could prevent market participants from adopting a one-size-fits-all strategy.     

The Fed’s reaction to the stock market during the great depression: Fact or artefact?

A notable feature of the 1920s and 1930s is the volatility in several key macroeconomic aggregates, and this feature used to econometrically identify the reaction of the Fed to stock market developments. The volatility of economic activity may have contributed to deepening the divisions among policy-makers about how the Fed ought to respond to stock price developments. Relying on the technique of [Rigobon, R. 2003. Identification through heteroskedasticity. Review of Economics and Statistics 85, 777–792], volatility is used as an instrument to estimate the Fed’s response to the stock market. Other identification assumptions based on structural VARs produce compatible results. Fed behavior appeared to have changed following the stock market crash of 1929. Consistent with the Riefler-Burgess doctrine, interest rates and stock returns are negatively related. I conclude that, prior to the stock market crash of 1929, a form of benign neglect explains Fed behavior. Thereafter, the Fed reacts only slightly more aggressively to stock market developments.     

Shadow banking activities of non-financial companies and the information content of stock prices

In recent years, corporate investment rate has been declining, and they have been allocating financial capital to the shadow credit market, which lead to accumulation of financial risks. Based on the annual data of non-financial listed companies from 2007 to 2019, this paper explores the impact of non-financial companies’ shadow banking on the information content of stock prices. Results show that shadow banking of non-financial enterprises reduce the information content of stock price, and the above effects are more significant in regions with lower social trust and higher policy uncertainty, private enterprises, and enterprises without political connection. Enterprises engage in shadow banking can impact idiosyncratic information content of stock price through channels of earning management, irrational investor behavior, creditor risk concerns and informed trading; Analysts over-optimism and insider trading can also have an impact on the relationship between shadow banking activities and synchronization of stock price. This paper analyzes economic consequences of non-financial enterprises’ shadow banking activities, thus providing important theoretical support and policy guidance for enhancing signal mechanism of securities market, improving capital market efficiency of resource allocation, deepening financial market-oriented reforms.     

MODELLING SOUTH AFRICAN CURRENCY CRISES AS STRUCTURAL CHANGES IN THE VOLATILITY OF THE RAND

This study tests the theory that currency crises are associated with sudden large changes in the structure of foreign exchange market volatility. Due to increases in market uncertainty, crisis periods exhibit abnormally high levels of volatility. By studying short-term changes in volatility dynamics, it is possible to identify the start and end dates of crisis periods with a high degree of precision. We use the iterative cumulative sum of squares algorithm to detect multiple shifts in the volatility of rand returns between January 1994 and March 2009. Dummy variables controlling for the detected shifts in variance are incorporated in a generalised autoregressive conditional heteroscedasticity modelling framework. The analysis indicates that previously identified crisis periods in the rand coincide with significant structural changes in market volatility.     

Financial Reporting Opacity and Expected Crash Risk: Evidence from Implied Volatility Smirks

The recent financial crisis has stimulated a renewed interest in understanding the determinants of stock price crash risk (i.e., left tail risk). Recent research shows that opaque financial reports enable managers to hide and accumulate bad news for extended periods. When the accumulated bad news reaches a certain tipping point, it will be suddenly released to the market at once, resulting in an abrupt decline in stock price (i.e., a crash). This study extends this line of research by examining the impact of financial reporting opacity on perceived or expected crash risk. Prominent economists, such as Olivier Blanchard, argue that removing the perception of tail risks (in addition to realized tail risks) is crucial in restoring investor confidence and stabilizing the stock market. Using the steepness of option implied volatility skew as a proxy for perceived crash risk, we find that accrual management, the presence of financial statement restatements, and auditor‐attested internal control weakness are all positively and significantly associated with the level of perceived crash risk. Our results suggest that improving financial reporting transparency is an important mechanism for firms and policymakers to reduce the perception of tail risks and stabilize the stock market.     

投资者结构与股价波动关系——基于理论的思考

长期以来，人们认为机构投资者可以稳定股市。本文从更广的视角研究了投资者结构与股价波动的关系。本文结论如下：（1）在市场产品机构、交易制度和规则体系等要素给定的情况下，股价波动是投资者结构参数的函数。（2）机构投资者与稳定股市没有必然的联系。即使在市场的产品结构和交易制度等要素给定的情况下．不同的投资者结构中机构投资者比例的增加既可以增加股价波动，也可以减少股价波动。（3）在一些投资者结构中，股价波动反而随着理性机构投资者比例的增加而增加。即使在投资者结构中其他参数相同的情况下，理，比机构投资者的比例过多或过少均有可能增加波动。（4）即使在上市公司不分红且没有重大利好消息支持股价的情况下，在一定的投资者结构中，机构投资者仍能通过买入来制造股价波动。并从中获利。但这种策略能够成功依赖于市场中其他类型投资者的结构。（5）适度的羊群行为会使股价波动最小，而过强或者过弱的羊群行为都使股价波动增加。     

Accounting Quality,Stock Price Delay,and Future Stock Returns*

In frictionless capital markets with complete information and rational investors, stock prices adjust to new information instantaneously and completely. However, a substantial body of research studies information imperfections such as asymmetric information and incomplete information. Information imperfections potentially hinder timely price discovery and are likely associated with delayed stock price adjustment to information. Our first research question therefore is whether the quality of accounting information (or “accounting quality”) is one such information imperfection that is associated with cross‐sectional variation in stock price delay. We define accounting quality as the precision with which financial reports convey information to equity investors about the firm’s expected cash flows. Poor accounting quality is likely associated with higher expected returns through uncertainty about stock valuation parameters and incomplete information. Our second research question therefore is whether the accounting quality component of price delay is associated with higher future stock returns. Consistent with our hypotheses, the results show that poor accounting quality is associated with delayed price adjustment and higher future stock returns. Thus, accounting quality plays a role in timely stock price discovery.     

Do global financial crises validate assertions of fractal market hypothesis?

The frequent occurrence of crises in recent decades has triggered a debate between the proponents of Efficient market hypothesis and Fractal market hypothesis. While, the proponents of Efficient market hypothesis view crises as non-existent and highly improbable, the advocates of Fractal market hypothesis view crises as the dominance of certain investment horizons. We test whether the assertion of Fractal Market hypothesis regarding the dominance of certain frequencies during financial crises hold for the global stock markets. Following Kristoufek (Sci Rep 3:2857, 2013) the wavelet power spectra based on continuous wavelet framework are used to test the said hypothesis. It is shown that stock markets around the globe indicate the dominance of higher frequencies during the crises periods, hence, validate the assertions of Fractal market hypothesis. The results drawn are robust to the use of different countries as well as different crises.     

Macroeconomic Variables and Stock Prices in Malaysia: An Empirical Analysis

The article investigates the dynamic interactions between seven macroeconomic variables and the stock prices for an emerging market, Malaysia, using cointegration and Granger causality tests. The results strongly suggest informational inefficiency in the Malaysian market. The bivariate analysis suggests cointegration between the stock prices and three macroeconomic variables – consumer prices, credit aggregates and official reserves. From bivariate error-correction models, we note the reactions of the stock prices to deviations from the long run equilibrium. These results are further strengthened when we extend the analysis to multivariate settings. We also note some evidence that the stock prices are Granger-caused by changes in the official reserves and exchange rates in the short run.     

基于神经网络模型的智能产业板块股价探究

针对金融波动性和市场风险,基于A股市场上70余只智能板块的股票近10年的四因子数据,从神经网络模型入手实证分析,利用随机梯度算法对收盘价预测,比较预测值与实际值的模型误差及损失函数,进行因子选取、算法改进及指标择优。结果表明,神经网络模型参数在批次为2、迭代次数为4 150时,MSE(均方误差)、MAPE(平均绝对百分比误差)、MAE(平均绝对误差)分别为60.191 1、30.732 6、4.803 2,收盘价的拟合效果最佳,该参数下的神经网络模型可用于探究股票市场价格趋势,为投资者、金融机构提供一定参考依据。     

Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy

In a similar way to the stock market, the housing market in China has often been portrayed as highly speculative, giving rise to “bubble” concerns. Over the last decade, residential prices increased every year on average by double digits in Beijing or Shanghai. However many observers and researchers argue that fundamentals of the housing sector, both sector-specific and macroeconomic, may have been the driving force behind housing price volatility. While existing empirical work exclusively relies on the government housing prices which may suffer from the well-documented downward bias, this paper uses original high frequency unit price as well as transaction series for the residential resale housing markets of Beijing and Shanghai between January 2005 and December 2010 to test alternative hypotheses about housing prices volatility.We propose a sequential strategy in five steps integrating several techniques previously developed in a piecemeal and scattered way. First, we construct daily hedonic prices. Second, in order to search for the possible presence of bubbles on such high-frequency data, we propose using recently developed tests of an explosive root as an alternative to the unit root hypothesis. The third step is generated by the necessity of handling microstructure noise present at a daily frequency, thus filtering the raw data to extract a random walk component. The fourth step extracts a slowly changing monthly volatility component from the filtered daily hedonic real estate data. Finally, in so far as the presence of bubbles does not seem to characterize the residential housing market in major Chinese cities, such as Beijing and Shanghai, in a fifth step we show that fundamentals are able to explain slowly changing volatility, as well as transaction volumes in these first‐tier cities.