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.     

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.     

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.     

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.     

Habit Formation and Macroeconomic Models of the Term Structure of Interest Rates

This paper introduces a new class of nonaffine models of the term structure of interest rates that is supported by an economy with habit formation. Distinguishing features of the model are that the interest rate dynamics are nonlinear, interest rates depend on lagged monetary and consumption shocks, and the price of risk is not a constant multiple of interest rate volatility. We find that habit persistence can help reproduce the nonlinearity of the spot rate process, the documented deviations from the expectations hypothesis, the persistence of the conditional volatility of interest rates, and the lead‐lag relationship between interest rates and monetary aggregates.     

Do regulatory policies affect the flow of information in emerging markets?

In a previous paper we established that volatility is best explained by contemporaneous rather than lagged trading volume in the Egyptian stock exchange (EGX). The main objective of this paper is to investigate the effects of regulatory policies - namely the switch from price limit to circuit breaker - on the dynamic relationship between trading volume and stock returns volatility in the EGX. Using daily returns data for 20 actively traded companies as well as the EGX30 market index, the Generalised Method of Moments (GMM), results show that the volume-volatility relationship is not only endogenous but is also structurally altered by the switch.     

Economy-wide bond default rates: A maximum expected utility approach

We consider the 12-month moving average aggregate default rate of S&P-rated US-bonds. We estimate the conditional probability distribution of this default rate as a function of a weighted average bond rating, a lagged default rate and a preliminary predictor that is based on lagged new issuance. Our modeling approach is asymptotically optimal for an expected utility maximizing investor. The resulting conditional probability density is consistent with our intuition. We measure the model’s performance by the out-of-sample expected utility. According to this measure, our model clearly outperforms a simple regression model, a regression model with ARMA error terms and a Poisson model.     

Samuelson Hypothesis & Indian Commodity Derivatives Market

Samuelson (1965) devised that futures price volatility increases as the futures contract approaches its expiration. The relation amid the volatility and time to maturity has significant inference for hedging strategies. Interestingly, so far the empirical evidence in favor of the Samuelson Hypothesis (maturity effect) is mixed in various markets. Considering no significant work to examine the relationship is so far carried out in commodity derivative markets of India, this paper ordeal the Samuelson Hypothesis on 8 commodities traded on Multi-Commodity Exchange (MCX), India. We have examined the issue by applying different regression techniques to test the hypothesis for 8 commodities (Aluminium, Nickel, Copper, Gold, Silver, Natural Gas, Crude Oil and Wheat) using inter-day data on MCX India. In order to test the Samuelson’s hypothesis, tests have been conducted using a series of GARCH, EGARCH and TGARCH models by including trading volume, open interest and time-to-maturity in the conditional variance equation. From our results, it is concluded that Samuelson’s hypothesis does not hold true for majority of commodity contracts considered. Our results also find that volatility series depend on the trading volume, compared to the time-to-maturity or open interest. As Samuelson hypothesis does not hold true for majority of commodity contracts, traders in Indian commodity derivative markets should not bias their decisions solely based on the time-to-maturity, but should also consider trading volume and open interest as they are an important determinant of price volatility. They should also consider the possibility of leverage effect while predicting future price volatilities, and the associated margin requirements.     

Volatility in stocks subject to takeover bids: Australian evidence using daily data

Using daily price and volume data on 112 of the largest takeover targets in Australia during the period from 1985 to 1993, we find that conditional price volatility declines after the takeover announcement. This decline is greatest for targets of cash bids and smallest for targets of share-exchange bids. We argue that the phenomenon is due to convergence of trader opinion regarding the value of the target stock, and reflects a change in the price formation process that has not hitherto been recognised. Our findings have implications for event studies of takeovers that inappropriately assume a time-invariant risk-return relation, and also for regulatory policies in the market for corporate control.     

From pit to electronic trading: Impact on price volatility of U.S. Treasury futures

This paper investigates the dynamics of price volatility and trading volume of 10-year U.S. Treasury note futures within the context of transition from pit to electronic trading. The analysis is conducted over four discernible phases of futures trading evolution: the pit-only phase, the leap to electronic trading, and the electronic trading dominant phase, which is divided further into two periods, the before and after the financial crisis of 2007/2009. Generalized autoregressive conditional heteroskedasticity with in-mean conditional variance and generalized error distribution parameterization (GARCH-M-GED) tests are conducted to examine the conditional volatility of total returns index as a function of trading volume. The empirical results show a consistently negative relationship between the trading volume and price volatility for all four analyzed phases. They also show decreasing leptokurtosis (except for the direct effects of the recent crisis), continuously high persistency in volatility, as well as a weakening impact of unexpected ARCH-type shocks during the most recent analyzed period. Overall, the shift to electronic trading entails a substantial increase in trading volume, but not in price volatility of Treasury futures.     

Accounting Ratios and the Cross‐section of Expected Stock Returns

Under clean‐surplus accounting, the log return on a stock can be decomposed into a linear function of the contemporaneous log return on equity, the contemporaneous log dividend–price ratio (if the stock pays a dividend), and both the contemporaneous and lagged values of the log book‐to‐market equity ratio. This paper studies the implications of this decomposition for the cross‐section of conditional expected stock returns. The empirical analysis reveals that the log accounting ratios capture cross‐sectional variation in both the conditional mean and conditional variance of log stock returns, which is consistent with the decomposition. It also brings fresh insights to the relation between firm size (market equity) and conditional expected stock returns. The evidence indicates that the conditional median return increases with firm size, while the conditional return skewness decreases with firm size. Empirically, the skewness effect outweighs the median effect, leading to the well‐documented inverse relation between size and average returns. The results of out‐of‐sample tests suggest that investors could use the information provided by the observed values of the log accounting ratios to formulate more effective portfolio strategies.     

Race to the center: competition for the Nikkei 225 futures trade

This paper examines the impact of changes in margin requirements on returns, transaction volume, and price volatility of the Nikkei 225 futures traded on the Osaka Securities Exchange (OSE) and the Singapore International Monetary Exchange (SIMEX). An increase in margin requirement on one exchange reduces its trading volume and shifts trade to the competing exchange. Both conditional price volatility and returns are not systematically affected by changes in margin requirements. The loss of OSE's market share of the Nikkei futures trade from 1990 to 1993 is partly due to the increased transactions costs (relative to SIMEX), including the margin requirement.     

The Effects of Regulating Hidden Add‐On Costs

We examine the welfare effects of price and disclosure regulation in a model where firms can shroud add‐on costs, such as penalty fees for consumer financial products. Such regulation can increase or decrease welfare even when there are no direct costs. There are, however, strong complementarities between price controls and disclosure mandates: conditional on disclosure being mandated, price controls always (weakly) increase welfare, and conditional on prices being sufficiently constrained, disclosure mandates always (weakly) increase welfare.     

Volatility estimation on the basis of price intensities

This paper investigates the use of price intensities, i.e. the time between price changes of a given size, to estimate volatilities based on high-frequency data. We interpret the conditional probability for the occurrence of a price event within a certain time horizon as a risk measure which allows us to obtain an estimator of the conditional volatility per time. To consider censoring effects caused by nontrading periods, we use a proportional hazard model. Seasonalities are taken into account by including regressors based on a flexible Fourier form capturing intraday and time-to-maturity seasonalities. Testing for serial correlation and controlling for unobservable heterogeneity permits us to check for misspecification on different aggregation levels. Empirical results are based on intraday transaction data of Bund future trading at the LIFFE, London.