International linkages and macroeconomic news effects on interest rate volatility — Australia and the US

We examine international linkages between daily time series of US and Australian 3-month treasury bills and 10-year government bonds from 1987–1995, paying particular attention to the effects of macroeconomic announcements in both countries. The two countries' interest rate data are modeled by a bivariate exponential generalized autoregressive conditional heteroscedasticity (EGARCH) formulation. The results suggest that market participants believed the Reserve Bank of Australia targeted the consumer price index (CPI), while the Federal Reserve targeted economic activity. Monetary policy announcements had significant effects on interest rates, as well as on their volatility in the short term. US macroeconomic activity announcements significantly moved Australian interest rates, particularly at the short end. Australian interest rates moved significantly in response to the previous day's US interest rate shocks. The conditional volatility of the Australian interest rate changes was also significantly influenced by lagged US interest rate shocks, as well as by surprises in US macroeconomic announcements. Some macroeconomic news announcements raised conditional volatilities, while others reduced them. Overall, there was a remarkable and complex array of linkages between the two countries.     

中国A股量价之间动态关系的实证研究

本文采用了VAR模型以及Granger因果检验的方法来考察量价之间的动态相关关系.我们选定1996年12月16日至2008年12月31日作为样本研究区间,实证发现滞后期的交易量和收益对当前期交易量与收益的解释力度存在下降趋势;同时,交易量同收益之间由收益对交易量的单向引导发展为双方互为Granger原因.本文得到的交易模式的动态演变轨迹反映了我国投资者式逐步趋于理性成熟.     

中国A股量价之间动态关系的实证研究

本文采用了VAR模型以及Granger因果检验的方法来考察量价之间的动态相关关系。我们选定1996年12月16日至2008年12月31日作为样本研究区间,实证发现滞后期的交易量和收益对当前期交易量与收益的解释力度存在下降趋势;同时,交易量同收益之间由收益对交易量的单向引导发展为双方互为Granger原因。本文得到的交易模式的动态演变轨迹反映了我国投资者式逐步趋于理性成熟。     

Does Bitcoin still own the dominant power? An intraday analysis

The study investigates the intraday dynamics and price patterns of the primary cryptocurrencies. The Granger Mackey-Glass (M-G) model is employed to examine the asymmetric and nonlinear dynamic interactions in the first moment using positive and negative returns. The bivariate BEKK-GARCH model is applied to identify cross-market volatility shocks and volatility transmissions in the cryptocurrency market. The intra-cryptocurrency market analysis reveals that Bitcoin contains predictive information that can nonlinearly forecast the performance of other digital currencies when cryptocurrency prices either are rising or declining. The dominant power of Bitcoin is not dismissed using the intraday data. Further, Bitcoin's intraday lagged shocks and volatility induces more rapid and destabilizing effects on the conditional volatility of other currencies than each of the other currencies does on BTC's conditional volatility. The virtual currency markets are dynamically correlated and integrated through first and second-moment spillovers.     

The Informational Role of Option Trading Volume in Equity Index Options Markets

This paper examines the dynamic relations between future price volatility of the S&P 500 index and trading volume of S&P 500 options to explore the informational role of option volume in predicting the price volatility. The future volatility of the index is approximated alternatively by implied volatility and by EGARCH volatility. Using a simultaneous equation model to capture the volume-volatility relations, the paper finds that strong contemporaneous feedbacks exist between the future price volatility and the trading volume of call and put options. Previous option volumes have a strong predictive ability with respect to the future price volatility. Similarly, lagged changes in volatility have a significant predictive power for option volume. Although the volume-volatility relations for individual volatility and volume terms are somewhat different under the two volatility measures, the results on the predictive ability of volume (volatility) for volatility (volume) are broadly similar between the implied and EGARCH volatilities. These findings support the hypothesis that both the information- and hedge-related trading explain most of the trading volume of equity index options.     

Transmission of shocks from cross-listed markets to the return and volatility of domestic stocks

This paper examines the transmission of information from German and the U.S. markets to domestic markets using daily price and volume data of 264 stocks from 26 countries that are traded in their home country and cross-listed outside their home market as depository receipts (DRs); in the German market as Global Depository Receipts (GDRs) and in the U.S. as American Depository Receipts (ADRs). We identify days with significant news arrivals in a market through minimum thresholds for both significant absolute price change and trading volume. DR returns and volatilities are affected by the shocks in the markets where they are cross-listed controlling for domestic shocks. Contemporaneous and/or lagged shocks to the cross-listed markets are transmitted to domestic stock returns and volatilities. South American DRs are affected mostly by U.S. shocks, while Eastern European DRs show greater reaction to the German shocks.     

TIME-VARYING FACTORS AND CROSS-AUTOCORRELATIONS IN SHORT-HORIZON STOCK RETURNS

In this paper I show that the lead-lag pattern between large and small market value portfolio returns is consistent with differential variations in their expected return components. I find that the larger predictability of returns on the portfolio of small stocks may be due to a higher exposure of these firms to persistent (time-varying) latent factors. Additional evidence suggests that the asymmetric predictability cannot be fully explained by lagged price adjustments to common factor shocks: (i) lagged returns on large stocks do not have a strong causal effect on returns on small stocks; (ii) trading volume is positively related to own- and cross-autocorrelations in weekly portfolio returns; and (iii) significant cross-autocorrelation exists between current returns on large stocks and lagged returns on small stocks when trading volume is high.     

The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility

We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from 1973 to 2000. The results show a positive correlation between trading volume and the absolute value of the stock price change. Granger causality tests demonstrate that for some countries, returns cause volume and volume causes returns. Our results indicate that trading volume contributes some information to the returns process. The results also show persistence in volatility even after we incorporate contemporaneous and lagged volume effects. The results are robust across the nine national markets.     

证券市场成交量对收益率波动性影响的实证分析

本文根据上海证券市场上证综合指数2005年1月1日到2006年1月1日的复合收益率和日成交量。用GARCC模型描述日成交量对复合收益率的波动性影响。在GARCH模型中加入当期交易量、滞后一期的交易量，结果表明当期交易量变化率能明显削弱收益率条件方差的波动性，而滞后一期的成交量只通过对当期的成交量间接的影响复合收益率。     

Surprise volume and heteroskedasticity in equity market returns

Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume—i.e. unexpected above-average trading activity—which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and Lastrapes () model by an asymmetric GARCH in-mean specification following Golsten et al. (). Model estimation for the US as well as six large equity markets shows that surprise volume provides superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surprise volume reveals a significant positive market risk premium, asymmetry and a surprise volume effect in conditional variance. The findings suggest that e.g. a surprise volume shock (breakdown)—i.e. large (small) contemporaneous and small (large) lagged surprise volume—relates to increased (decreased) conditional market variance and return.