The intraday relation between return volatility, transactions, and volume

In this article, we examine the relation between return volatility, average trade size, and the frequency of transactions using transaction data. Consistent with Jones, Kaul, and Lipson (1994)(. Review of Financial Studies, 7, 631–651), our results show that the frequency of trades has a high explanatory power for return volatility. However, contrary to their finding, we find that average trade size contains nontrivial information for return volatility. The positive relation between return volatility and average trade size is more significant for actively traded stocks. Furthermore, return volatility exhibits significant intraday variations. It is found that the effect of trade frequency on return volatility is much stronger in the opening trading period.     

Price and tick size preferences in trading activity changes around stock split executions

We investigate the low prices preferences and the optimal relative tick size hypotheses, as possible explanations of the stock split execution effects in a pure order-driven and multi-tick market. Using intraday data for the Spanish Stock Exchange during 1997-2001, we find that stock splits do not improve liquidity but do change trading composition. Following splits, small trades from retail investors increase significantly, especially in the larger stock splits. However, we find that this effect seems to disappear with the new tick-size rules adopted by Spanish market in 1999. We extend the optimal relative tick size hypothesis for a multi-tick market by considering the effects of stock splits on the absolute tick size. We observe that the increase in small trades occurs only in those splits that increase the relative tick and decrease the tick-size simultaneously. Our findings suggest that small investors are attracted by stock splits that cause an absolute tick-size reduction, which are those with relatively lower transaction costs.JEL Classification: G19, G32, G35We thank two anonymous referees and the editor, J.M. Campa, for their comments and for providing us very helpful guidance on how to improve the paper. The authors gratefully acknowledge financial support from the Dirección General de Investigación del Ministerio de Ciencia y Tecnología, grant BEC2002-03797. A first version of this study has been published in the working paper series of the Instituto Valenciano de Investigaciones Económicas, IVIE. Any remaining errors are the authors responsibility.     

The heterogeneous volume-volatility relations in the exchange-traded fund market: Evidence from China

We decompose the trading volume of exchange-traded funds (ETFs) into specific components according to different triggers of trades: (i) private information, (ii) disagreement among investors due to their different opinions on public information or having different information, and (iii) investor impatience. Then we examine the particular impact of each type of ETF trade on the market volatility of the tracked index. Focusing on the three ETFs tracking the CSI 300, we show that ETF trades stemming from investor disagreement are a key determinant of CSI 300 volatility, dominating other factors considered. Liquidity ETF trades can partially explain CSI 300 volatility. However, little evidence supports a significant correlation between privately informed trades of ETFs and CSI 300 volatility.     

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.     

The relationship between the Vietnam stock market and its major trading partners – TECM with bivariate asymmetric GARCH model

This study employs threshold error-correction model with bivariate Glosten–Jagannathan–Runkle-generalized autoregressive conditional heteroscedasticity model to examine the relationship between the Vietnam stock market and its major trading partners, the United States, Japan, Singapore and China. The results indicate that the Vietnam stock market and return risks are influenced by Japan and Singapore stock markets. We also find that the volatility of stock market in Vietnam and its trading countries have an asymmetrical effect. These findings could be valuable to individual investors and financial institutions holding long-run investment portfolios in the Vietnam stock market.     

Daily happiness and stock returns: The case of Chinese company listed in the United States

Existing literature exclusively focuses on the association between local investor sentiment and local stock market performance. In this paper, we investigate the contemporaneous and the lead-lag relationship between local daily happiness sentiment extracted from Twitter and stock returns of cross-listed companies, i.e., the Chinese companies listed in the United States. The empirical results show that: 1) by respectively controlling for the firm capitalization, liquidity and volatility, there exists the largest skewness on the Most-happiness subgroup. (2) There exist bi-directional relationships between daily happiness sentiment and market variables, i.e., the stock return, range-based volatility and excess trading volume. (3) There are significantly positive stock returns, higher excess trading volume and higher range-based volatility around the daily happiness sentiment spike days. These findings not only suggest that there exists significant interdependence between online activities and stock market dynamics, but also provide evidence for the existence of “home bias”.     

A three-objective social welfare function for cost–benefit analysis

This article applies quantile regression to assess the factors that influence the risk of incurring high trading costs. Using data on the equity trades of the world's second largest pension fund in the first quarter of 2002, we show that trade timing, momentum, volatility and the type of broker intermediation are the major determinants of the risk of incurring high trading costs. Such risk is increased substantially by either high or low momentum and by strong volatility. Moreover, agency trades are substantially more risky in terms of trading costs than similar principal trades. Finally, we show that the quantile regression model succeeds well in forecasting future trading costs.     

融资、融券交易及其波动对股价稳定性的影响一致吗*

本文区分并讨论了融资交易、融券交易及二者的波动对标的股价稳定性影响的不一致性。研究表明,融资交易提高了标的股价的整体稳定性却加剧了股价异常下跌频率,而融券交易对股价整体稳定性及异常下跌频率并不存在显著影响。更重要的是,融资交易的异常波动加剧了股价的不稳定,而融券交易的异常波动则有助于提高股价稳定性。本文的政策启示在于,应采取比较“温和”的方式调控融资交易以避免融资交易的过度波动加剧标的股价的不稳定。     

Has the Asian crisis changed the role of foreign investors in emerging equity markets: Taiwan's experience

This paper examines whether the 1997 Asian crisis changed the trading behaviors of foreign investors and of local institutional investors in Taiwan's stock market. There is little evidence that the Asian crisis changed the relationship between equity flows and market returns in Taiwan's stock market but there is evidence that volatility effects and volatility spillover were strengthened after the crisis. The general findings are (i) feedback trading arguments are much stronger than information arguments; (ii) relationships between returns and sale changes are the weakest but volatility effects using sale measures are the strongest; (iii) strong volatility effects and volatility spillover are found after the crisis; and (iv) the results for domestic institutional investors are slightly stronger than those for foreign investors.     

Firm return volatility and economic gains: The role of oil prices

In this paper we investigate whether the oil price contributes to stock return volatility for 560 firms listed on the NYSE. Using daily data, we find that the oil price is a significant determinant and predictor of firm return variance. We devise trading strategies based on forecasts of firm return variance using the oil prices and historical averages. We find that investors can make substantial gains in returns by using the oil price in forecasting firm return variances.     

中国股市上交易活动与股票预期收益关系的实证研究

用交易金额和换手率来度量股票的交易活动,并用它们的标准差、变异系数反映交易活动的变化,本文通过构造投资组合与进行Fama-Macbeth多元回归等方法对中国股市所有A股股票的预期月收益率与交易活动及其波动性之间的关系进行实证研究.研究结果表明,无论控制影响股票收益率的其它因子与否,A股股票交易活动的水平与波动性均与股票的预期收益负相关.     

中国封闭式基金价格报酬过度波动的经验分析

本文研究了中国封闭式基金价格报酬与净资产报酬的数据特征及其影响关系 ,主要的结果是 :( 1 )中国封闭式基金的价格报酬相对于基金的净资产报酬一方面存在过度波动 ,另一方面又存在反映不足 ;( 2 )通过检验表明 ,投资者情绪风险对价格报酬过度波动具有显著的影响 ,而Fama的三因素风险因子对价格报酬的过度波动几乎没有解释力 ;( 3 )封闭基金价格报酬的过度波动表明 :由于投资者行为使基金股票价格相对于基金净值存在额外的系统风险 ,封闭式基金折价正是对这种系统风险的一种补偿。     

Liquidity commonality in order-driven trading: evidence from the Athens Stock Exchange

We examine the presence of liquidity commonality in the order-driven Athens Stock Exchange (ASE). Unlike the majority of liquidity commonality studies that focus on the bid–ask spread, our analysis extends deeper in the Limit Order Book, providing insight on the price impact of both small and large trades. We utilize a 6-month FTSE/ATHEX-20 intraday data set to estimate the liquidity factor model of Chordia et al. (2000). To this end, we conduct single-equation analysis as well as panel data analysis with the use of two-way clustered errors, correcting for simultaneous firm and time correlations. Moreover, we apply standard principal component analysis on stock liquidities to extract the marketwide liquidity component. We find that liquidity commonality is low at the bid–ask spread, whereas it increases deeper in the book; consequently, large traders face liquidity risks associated with both individual stock and marketwide illiquidity. Moreover, our empirical evidence hints that liquidity commonality is asynchronous, suggesting that the ASE trading process includes various levels of information speed. Our analysis contributes to the understanding of liquidity commonality in order-driven trading, especially in emerging markets like the ASE where trading activity is limited and information speed is low.     

Oil Price Shocks and Volatility in Australian Stock Returns

This paper examines the effect of oil shocks on return and volatility in the sectors of Australian stock market and finds significant effects for most sectors. For the overall market index, an increase in oil price return significantly reduces return, and an increase in oil price return volatility significantly reduces volatility. An advantage of looking at sector returns rather than a general index of stock returns is that sectors may well differ markedly in how they respond to oil price shocks. The energy and material sectors (as expected) and the financial sector (surprisingly) are out of step (in different ways) with results for the other sectors and for the overall index. A rise in oil price increases returns in the energy and material sectors and an increase in oil price return volatility increases stock return volatility in the financial sector. Explanation for the negative (positive) association between oil return (oil return volatility) and returns (volatility of returns) in the financial sector must be based on the association via lending to and/or holdings of corporate bonds issued by firms with significant exposure to oil price fluctuations and their speculative positions in oil‐related instruments.     

Price clustering on the Shanghai Stock Exchange

We investigate price clustering of intraday trades and negotiated block trades on the Shanghai Stock Exchange (SSE) from 2003 to 2009. Prices of traded assets tend to cluster on certain final digits, such as 0 and 5. In Chinese culture, 8 is associated with good luck and 4 with death so these numbers may be attractive or avoided. We find that price clustering on the final digit of 0 is significantly higher during the morning call auction and early in the trading day. We find no evidence of price clustering for the digit 8, but there is a significant dearth of prices ending in the inauspicious number 4. Price clustering is significantly higher for negotiated block trades, for which about 28% end with 0. Multivariate analysis shows that price clustering is lower for more liquid firms, but higher for firms with higher return volatility, a higher price level, or when the market is volatile. Our evidence supports the costly negotiation hypothesis. Our results also support the attraction hypothesis in that we document significant price clustering at round numbers and even numbers even after controlling for factors that are associated with price uncertainty.     

Investor attention and stock market activity: Evidence from France

The aim of this paper is to study the influence of investor attention on the French stock market activity and volatility. Following an original way, we construct a non-standard proxy of investor attention on the basis of investors' online search behavior exclusively provided by “Google insights for search”. We find that Google search volume is a reliable proxy of investor attention. Interestingly, we show that investor attention is strongly correlated to trading volume and is a significant determinant of the stock market illiquidity and volatility. Most importantly, this evidence is maintained even after controlling for the financial crisis effect.     

Extreme returns and the idiosyncratic volatility puzzle: African evidence

We examine the cross-sectional relationship between the expected stock return and both the maximum daily return (MAX) and the idiosyncratic volatility (IVOL) in the five largest emerging African stock markets over the period from 2001 to 2015. First, we find that there is a robust and significantly negative MAX effect in the pooled African stock markets. Second, though we initially document a negative IVOL effect, it disappears after controlling for MAX. Finally, the negative MAX effect is only significant in the small-SIZE, high-illiquidity and high-skewness portfolios. Our results suggest risk-seeking behaviour among African investors similar to that in other parts of the world.     

The determinants of exchange settlement practices and the implication of volatility smile: Evidence from the Taiwan Futures Exchange

This paper proposes that the Taiwan Futures Exchange (TAIFEX) adopts a linear extrapolation method to set the settlement price for the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) options with less liquidity and thin trading. The empirical results indicate that the settlement-price-determined implied volatility is a smile function, consistent with the pattern of the market-price-determined implied volatility. Moreover, we examine the influence of economic factors on the TAIFEX's decision regarding the parameters of implied volatility function. Compared with the economic determinants of market-force-driven volatility parameters, the TAIFEX inappropriately values the impacts of the parameters of prior days, current stock returns, distribution of stock returns, long-term measurement of the stock market trend, market transaction cost, and time to maturity.     

Return spillovers around the globe: A network approach

We study the connectedness of a sample of 40 stock markets across five continents using daily closing prices and return spillovers based on Granger causality. All possible 1560 return spillovers between 40 markets create a complex network of relationships between equity markets around the world. Apart from analyzing the topological and time-varying properties of the created networks, we also identify the determinants of the connectedness of equity markets over time. Adjusting for non-synchronous trading, our modelling approach leads to evidence that the probability of return spillover from a given stock market to other markets increases with market volatility and market size and decreases with higher foreign exchange volatility. We empirically show that the temporal proximity between closing hours is important for information propagation; therefore, choosing markets that trade during similar hours bears an additional risk to investors because the probability of return spillovers increases.     

Forecasting stock market volatility: The role of technical variables

Accurate volatility forecasts are required by both market participants and policy makers. In this paper, we forecast stock return volatility by using a wide range of technical indicators constructed based on the past behavior of stock price, volatility and trading volume. Our out-of-sample results indicate that the incorporation of technical variables in the autoregression benchmark can produce significantly more accurate volatility forecasts. The forecasting performance of the combination of technical indicators is further compared with that of the popular economic indicators. Technical variables perform better than economic variables when the economy is an expansion, while the economic variables generate more accurate forecasts when the economy belongs a recession. These two types of variables provide complementary information over the business cycle. We obtain more reliable forecasts by combining all economic and technical information together than by combining either type of information alone.