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Foreign investors’ information disadvantage is often viewed as a key impediment to their investment. This study questions whether foreign investors’ home media mitigates this information barrier by investigating the relation between U.S. mutual fund ownership and U.S. media coverage of local stocks in their host countries. Using a large sample of 38 host countries, we document a positive association between U.S. mutual fund ownership in a local stock and the coverage of U.S. major news providers on that stock. We find that home media-covered stocks incur lower information acquisition costs and gain greater investor awareness from U.S. investors. The home media effect is most salient in host countries with low quality information environments, supporting a novel home media effect that foreign investors tend to rely on their home market media coverage as an information source. The home media effect helps explain the prominent international finance anomaly regarding the dependence of firm returns on home and foreign market factors.

We show that contracts for difference (CFDs) may be viable substitutes for forward contracts and may have some features that are preferable to futures contracts. We develop parity relations between CFDs, forwards, and futures contracts using simple cost-of-carry arguments. We use these parity relations to consider whether exchange listed stock index CFDs might be viable substitutes for exchange listed futures contracts. Using the S&P/ASX 200 stock index we find that listed CFDs (ignoring an open interest charge) generate cash flows similar to listed futures contracts. Our analysis considers stochastic interest rates and uncertain dividend payments by the shares in the index.

This study models and tests empirically the role of public news arrivals in the quote matching across single-stock futures and underlying stock markets—a trading strategy often adopted by algorithmic traders. Our model suggests that quote return correlation across these two markets breaks down when the news uncertainty is sufficiently large and futures market makers switch from automating the quote matching process to manually analyze, monitor, and update quotes. We show empirically that the breakdown is more prominent for large stocks, and this effect of firm size falls during periods of high-market volatility. Our empirical results are robust to the effect of distraction due to extraneous news events.

We examine the nature of state blockholding across publicly listed firms in East Asia by assembling a unique dataset spanning 16 years and 9 economies. Our newly compiled data identifies ultimate owners for each firm annually between 1997 and 2012, totaling 2984 firm-year observations. Three findings stand out. First, large changes (>5%) to state blockholdings – both investments and divestments – are quite prevalent. Second, the identity of the largest shareholder frequently changes over time between state, family, and widely-held entities. Third, sovereign wealth funds are far more likely to acquire rather than sell large stakes in publicly traded firms.

This study examines dynamic order placement strategies in a low-latency environment together with limit orders' aggressiveness by a new approach which utilises survival analysis with a multiple-spell duration model. Two samples are considered, including the period immediately followed Australian Securities Exchange (ASX)’s migration to Integrated Trading System (ITS) and the period subsequent to the launch of ASX Trade. We find the evidence supporting both the ‘cost of immediacy hypothesis' and the ‘chasing hypothesis' as in Hasbrouck and Saar (2009). Furthermore, several distinctions in the results are found between the samples of ITS period and ASX Trade period as well as between the samples of small-cap stocks and large-cap stocks. The findings of this study are beneficial not only for high-frequency traders in forming dynamic order placement strategies in a low-latency stock market environment, but also for market regulators in helping their attempt to improve regulations for stock exchanges.

This paper analyzes the effects of news and its sentiment on the idiosyncratic volatility ( IVOL ) — expected return relation. We postulate that the perceived negative IVOL -expected return relation could be the artifact of the confounding effect of public news arrivals. Using the stock return data from the Center for Research in Security Prices (CRSP) database and the news database from the RavenPack News Analytics over the period from 2000 to 2011, we show that the strength of the positive relation is reduced systematically by 50% after accounting for the arrivals of good and bad news releases, which are defined by their sentiment scores. This finding is robust to numerous model specifications, and the inclusion of firm-level characteristics, liquidity risk and information risk. When we restrict the firm-specific news to value-relevant news, the positive relation disappears. We conclude that that the public arrivals of firm-specific news play a significant role in explaining the IVOL puzzle.

Using computational linguistic analysis of intraday firm-level news releases, this study models the relation between public information flows and stock volatility under different regimes. We analyze how the hourly return volatility of S&P100 stocks from 2000 to 2010 are linked to the various linguistics-based sentiment scores of the news releases, which are obtained from the RavenPack News Analytics Database. Results from the Markov Regime-Switching GARCH (MRS-GARCH) model indicate that firm-specific news sentiment is more significant in quantifying intraday volatility persistence in the calm (low-volatility) state than the turbulent (high-volatility) state. Furthermore, the impact of news sentiment differs across industries and firm size.

We exploit exogenous variation in the scheduling of gubernatorial elections to study the timing of bank failure in the US. Using hazard analysis, we show that bank failure is about 45% less likely in the year leading up to an election. Political control (i.e., lack of competition) can explain all of this average election year fall in the hazard rate. In particular, we show that the reduction in hazard rate doubles in magnitude for banks operating in states where the governor has simultaneous control of the upper and lower houses of the state legislature (i.e., complete control) heading into an election.

We use high-frequency data to better characterize price dynamics in global crude oil markets. Initially, we provide much-needed quantitative evidence on interactions between physical and financial layers of the Brent market, highlighting the ICE Brent futures contract as the overwhelming source of price discovery in this market. Thereafter, we quantify the impact of oil supply constraints at Cushing, showing they are a significant determinant of ever decreasing levels of cointegration between Brent and WTI markets. Finally, against this backdrop we show that, on days where ICE Brent and CME WTI futures remain cointegrated, the latter still dominate price discovery. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 35:148–162, 2015

This paper presents a formal analysis of the relation between monitoring and limit order submission risk. With heterogeneous information, limit order traders face two types of risk. First, they may be “picked off” when prices change unexpectedly after the limit order is entered (known as free trading option risk). Second, they face the possibility that their limit order will not result in a trade. To mitigate these risks, traders can monitor information and prices and cancel or revise their orders as needed. But such monitoring is costly, resulting in a trade-off between the cost of monitoring and the risks of limit order submission. The model predicts that if the stock is actively traded, limit order submission risks and order cancellations/revisions are positively related. Further, shares with a wide bid-ask spread will tend to have a lower rate of order cancellations and revisions than shares with small bid-ask spreads. Finally, the model suggests that if larger capitalization stocks have lower costs of gathering information (and hence more intense monitoring of limit orders), there will be more cancellations and revisions in limit orders. A sample of 23 liquid stocks provides evidence that is consistent with these three main hypotheses.

This study represents an empirical analysis of free trading options (FTOs), options that arise due to the arrival of adverse information. The analysis purports to measure three characteristics of these options: (i) the probability of the option ending in-the-money as a consequence of adverse information arrival, (ii) the value of the free trading option and (iii) the time taken for the free trading option to become in the money (its duration). The empirical methodology was applied to 163 earnings announcements on the Australian Stock Exchange (ASX) and a number of limit order strategies investigated. The results show that such free trading options do exist, and have value dependent particularly on trading volume, firm size and pre-announcement bid–ask spread.

This study employs firm-specific announcements as a proxy for information flows and investigates the information–volatility relation using high-frequency data from the Australian Stock Exchange. Our analysis reveals a positive and significant impact of the arrival rate of the selected news variable on the conditional variance of stock returns, even after controlling for the potential effects of trading volume and high opening volatility. Furthermore, the inclusion of the news variable in the conditional variance equation of the generalized autoregressive conditional heteroscedastic model also reduces volatility persistence, especially with intraday data. Combined with the evidence that news arrivals display a very strong pattern of autocorrelation, our results are consistent with the Mixture of Distribution Hypothesis, which attributes conditional heteroscedasticity of stock returns to time-dependence in the news arrival process.