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This paper investigates the information content of the limit order book on future volatility in the crude oil futures market. We propose a time-weighted limit order book slope that incorporates the duration of each bid and ask update. When volatility is expected to increase around weekly announcements on physical crude oil inventory, we observe that the limit order book slope decreases significantly. We also show that the time-weighted limit order book slope is informative about price volatility one day ahead. Overall, our findings illustrate the importance of the limit order book as a conduit for volatility information.

This study considers the evolution of price discovery in the S&P 500 E-mini futures and the corresponding exchange traded fund (SPY ETF) over the period January 2002 through December 2013. The study reports evidence that the E-mini futures dominate price discovery at the beginning of the sample period. However, from 2007 onward both the SPY ETF and E-mini futures contribute similar portions to the price discovery process. The level of price discovery is significantly influenced by volume measures and relative levels of transaction costs for both securities. Refereed/Peer-reviewed

We consider Theory of Mind, the ability to correctly predict the intentions of others. The skill requires abstraction from one’s own particular circumstances. Here, we posit that such abstraction can be transferred successfully to other, non-social contexts. We consider the disposition effect, which is a pervasive cognitive bias whereby investors, including professionals, improperly take their personal trading history into account when deciding on investments. We design an intervention policy whereby we attempt to transfer Theory of Mind skills, subconsciously, to personal investment decisions. In a within-subject repeated-intervention laboratory experiment, we record how the disposition effect is reduced by a very significant 85%, but only for those with high Theory of Mind skills. No such transfer is observed in subjects who score well only on the emotional dimension of interpersonal skills. Our findings open up a promising way to exploit cognitive talents in one domain in order to alleviate cognitive deficiencies elsewhere.

We exploit the exogenously instituted minimum tick size change to examine the dynamic relationship between the bid-ask spread in the lit market and dark trading activity in the exchange operated dark pool in Japan. Using a difference – in – differences methodology, we document a significant treatment effect where stocks that are affected by the minimum tick size change have a lower share of trading in the exchange operated dark pool. Overall, our empirical findings provide first-hand evidence that a significant amount of dark trading is liquidity seeking. Reducing minimum tick size can help lit venues regain market shares over dark venues.

The Asia-Pacific securities markets are among the fastest growing markets in the world and account for more than one third of the global market capitalization. Drawing from the literature and recent technological developments worldwide, we discuss the current state and the future developments of computerized trading in a set of the largest Asia-Pacific economies, which constitute approximately 85% of the region's securities market. We first identify the drivers and deterrents of computerized trading based on the academic literature and regulatory investigations. We then assess the current viability and the future growth of computerized trading in the Asia-Pacific economies. Finally, we survey the empirical findings on algorithmic and high frequency trading in the Asia-Pacific region in comparison with the global empirical and theoretical literature. Refereed/Peer-reviewed

We develop an intertemporal asset pricing model where cash-flow news, discount-rate news, and their second moments are priced by the market. This model generalizes the market-return decomposition framework, showing that intertemporal considerations imply a decomposition of squared market returns (coskewness risk). Our model accounts for 68% of the return variation across portfolios sorted by size, book-to-market ratio, momentum, investment, and profitability for a modern U.S. sample period. Further, our findings highlight the importance of covariation risk, that is, the risk of simultaneous unfavorable shocks to cash flows and discount rates, in understanding equity risk premia.

We use full order book data from the Australian Securities Exchange to investigate how noise trading affects informational efficiency of securities prices. In aggregate, noise trading harms price efficiency. However, this is driven mainly by higher levels of noise trading, indicating a non-linear effect. Further, behind the aggregate effects lies rich heterogeneity in how noise trading affects informational efficiency cross-sectionally. Noise trading harms informational efficiency of large and liquid stocks but can be beneficial in small and illiquid stocks, indicating that noise trading affects different stocks differently.

This study investigates individual and institutional trading activities around earnings announcements. We find evidence of individual and institutional informed trading in competing firms before earnings announcements. We also observe that institutional trading exhibits quicker incorporation of new information, which suggests that institutional investors are more likely to use private information in trading in competing firms. The individual net order flow transmits information cross-stock when a competitor is a small firm, while institutional net order flow conveys information cross-stock irrespective of firm size. Finally, we find that institutional trading in competing firms exhibits cross-stock price impact before earnings announcements. Refereed/Peer-reviewed

This study investigates the role of algorithmic trading in the price discovery process. We estimate a state space framework which decomposes stock prices into permanent price series and transient pricing errors. Algorithmic traders contribute more to the permanent price processes and less to the transient pricing errors compared to other traders overall, during periods of high individual stock volatility, and on market-wide stress days.Algorithmic order flows are more associated with future stock returns compared to non-algorithmic order flows.Our results suggest that algorithmic traders incorporate price-relevant information and mitigate transitory price pressures. Refereed/Peer-reviewed

This paper examines the impact of release time of earnings and take over announcements on motives of trade initiation. We find that investors’ initiate buy and sell (buy or sell) trades immediately before (after) earnings and takeover announcements ‘day’ announcements. High volatility and more prominent effective spread before overnight announcements indicate active informed trading, showing evidence of potential information leakage. Similarly, high volatility and less prominent effective spread before day announcements exhibit more active uninformed trading. Overall, private information (Differential information) is the likely motive for trade initiation before overnight announcements (day announcements). We suggest that day announcements are more effective than overnight announcements in controlling information leakage. Our results complement prior literature on effectiveness of continuous disclosure on the ASX.

We investigate the impact of short selling activity on trading activity and price volatility in the U.S corporate bond market. Consistent with prior literature, we find that investors use short selling as a platform to express their difference of opinions. In addition, we find that the positive relation between short selling activity and price volatility becomes weaker during period when investors’ expectations tend to be more homogenous such as the Global Financial Crisis (GFC). More importantly, we show that short selling in the corporate bond market is not simply a substitute to equity short selling and option trading for investors to trade negative news and information against the underlying company. On the contrary, it is an independent conduit for investors to express difference of opinions specific to bond.

We study the volume–volatility relation by splitting volume into the number of trades and the average trade size at individual and institutional level, and realized volatility into its continuous and jump components. We find that the number of trades is the most important variable driving realized volatility. The number of trades by the individual investors carries more explanatory power in explaining volatility compared to the number of trades by institutional investors. The average trade size cannot be entirely disregarded, though; its importance compared to the number of trades is limited. Order imbalance plays a minimal role in driving volatility. Refereed/Peer-reviewed

We investigate the effect of the removal of broker identities on institutional and individual order submissions on the Australian Stock Exchange (ASX). We document declines in order aggressiveness and effective spreads for both institutional and individual investors after the switch to the anonymous trading system. Institutions are more willing to improve the best quotes than individuals, especially in the anonymous market. Anonymity also reduces the "picked off" risk for individual limit orders. Overall, our findings highlight the benefits of withholding brokers' IDs in the form of lower transaction costs and higher liquidity supply and thus support the ASX's decision to stop disclosing broker identity information. Refereed/Peer-reviewed

The study examines the possibility of arbitrage profits among 40 cross-listed Asia-Pacific stocks traded both on their home exchanges and the New York Stock Exchange in the form of American Depositary Receipts without overlapping trading hours. We propose a statistical method categorizing the examined companies into three groups based on the regression analysis of the spreads between log prices adjusted for exchange rates. Our results indicate that deviations fromthe long-run mean can generate economically significant profits at relatively low levels of risk from trading cross-listed securities across moderately efficient markets such as Hong Kong, New Zealand, Indonesia Refereed/Peer-reviewed

This study investigates the relationship between underpricing, ownership structure and post-listing liquidity of initial public offerings (IPOs). It is argued that higher underpricing induces both broader investor participation and creates a more diffuse ownership structure. These two factors are in turn positively associated with the level of post-listing trading, and therefore offer an explanation of how underpricing can influence liquidity. Using a sample of Australian IPOs, we provide evidence of statistically significant relationship between underpricing and various proxies for shareholding distribution and liquidity. This result remains robust after controlling for a number of potential underlying factors that may drive both underpricing and ownership allocation decisions. Overall, our analysis suggests that liquidity is a partial but important benefit of underpricing an IPO.

This study provides new evidence on efficacy of daily price limit rules. We propose use of propensity score matching techniques to reduce sample selection bias in widely used Kim and Rhee (1997). Using data from the Tokyo Stock Exchange over a period of 5. years from January 2001 to December 2005, this study shows that price limit rules work quite efficiently for lower limit hits as there is no evidence of volatility spill-over. We also find that daily price limits have differential effects on permanent and transitory components of daily volatility. Our study reports evidence of spill-over of permanent volatility. However, we find price limit successfully curbs the transitory volatility on the post limit hit days. Refereed/Peer-reviewed

This paper investigates trade initiation activities ‘immediately’ before and after earnings and takeover ‘day’ announcements. We find that investors’ initiate buy and sell (buy or sell) trades immediately before (after) earnings and takeover day announcements. High volatility and more prominent effective spread before ‘overnight’ announcements indicate active informed trading, showing evidence of information leakage. Similarly, high volatility and less prominent effective spread before day announcements exhibit more active uninformed trading. Overall, private information (Differential information) is the likely motive for trade initiation before overnight announcements (day announcements). We suggest that day announcements are more effective than overnight announcements in controlling information leakage. Our results complement prior literature on effectiveness of continuous disclosure on the ASX.

This article investigates whether the divergence of opinion among investors affects the implicit trading costs in a limit order book market. The authors propose a new unbiased measure of divergence of opinion among investors. Examining order submissions and transaction data from the Australian Stock Exchange (ASX), they document that divergence of opinion has negative impacts on implicit trading costs. The intensity of this relationship depends on the level of short-selling constraints in each stock. The authors find that divergence of opinion has a smaller impact on implicit costs when short-selling constraints are the smallest.

This paper investigates informed traders' order-splitting strategies on different days of the week and times of the day for a sample of stocks traded on the Australian Stock Exchange. Based on cumulative price changes, we document that informed traders tend to use medium size trades. We find that informed investors concentrate their strategic trading on Mondays and particularly during the first trading hour. In addition, informed investors also use large size trades around market opening and closing, as well as on days other than Mondays and Fridays. These results are more pronounced for the large market capitalization stocks.

Given a background of relatively weak findings documented in previous Australian work, the current study aims to provide new robust evidence of commonality in liquidity (CL) in this pure order driven market and some rationales regarding unexplained empirical findings. We also extend the methodology employed by previous studies in several ways. In so doing, we employ an enhanced research design, new liquidity proxies and an extended sample period. Apart from conventional measures of systematic liquidity, we also investigate potential non-linearities employing a simple 'up' and 'down' market setup, as well as a quadratic CL specification. Generally, we document a richer set of positive findings regarding the existence of CL in this order driven market setting.

Analyzing equity market co-movements is important for risk diversification of an international portfolio. Copulas have several advantages compared to the linear correlation measure in modeling co-movement. This paper introduces a copula ARMA-GARCH model for analyzing the co-movement of international equity markets. The model is implemented with an ARMA-GARCH model for the marginal distributions and a copula for the joint distribution. After goodness of fit testing, we find that the Student’s t copula ARMA(1,1)-GARCH(1,1) model with fractional Gaussian noise is superior to alternative models investigated in our study where we model the simultaneous co-movement of nine international equity market indexes. This model is also suitable for capturing the long-range dependence and tail dependence observed in international equity markets.

This study investigates individual and institutional trading in competing firms around earnings announcements. We find individual and institutional informed trading in competing firms, which is dominant prior to earnings announcements. Magnitude of institutional (individual) net order flow coefficient decreases (increases) with lag length, suggesting that institutional trading captures information faster than individual trading. Individual net order flow transmit information cross-stock when competitor is a small firm while institutional net order flow conveys information cross-stock irrespective of firm size. Our results are informative for regulators regarding insider trading laws and provide insights for market participants in understanding individual and institutional trading impact on cross-stock price discovery process.

Purpose – The purpose of this paper is to investigate the immediate impact of firm-specific announcements on the trading volume of individual and institutional investors on the Australian Securities Exchange (ASX), during a period when the market becomes fragmented. Design/methodology/approach – This study uses intraday trading volume data in five-minute intervals prior to and after firm-specific announcements to measure individual and institutional abnormal volume. There are 70 such intervals per trading day and 254 trading days in the sample period. The first 10 minutes of trading (from 10.00 to 10.10 a.m.) is excluded to avoid the effect of opening auction and to ensure consistency in the “starting time” for all stocks. The volume transacted during five-minute intervals is aggregated and attributed to individual or institutional investors using Broker IDs. Findings – Institutional investors exhibit abnormal trading volume before and after announcements. However, individual investors indicate abnormal trading volume only after announcements. Consistent with outcomes expected from a dividend washing strategy, abnormal trading volume around dividend announcements is statistically insignificant. Both individual and institutional investors’ buy volumes are higher than sell volumes before and after scheduled and unscheduled announcements. Research limitations/implications – The study is Australian focused, but the results are applicable to other limit order book markets of similar design. Practical implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Social implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Originality/value – These results will help regulators to design markets that are less predatory on individual investors.

In this paper we investigate short-term contrarian investment strategies in the Australian stock market using weekly data of those stocks comprising the All Ordinaries Index during the period 1994–2001. We find both the (Rev. Financ. Stud. 3 (1990) 175) equal-weighted strategy and a new value-weighted strategy yield statistically significant short-term contrarian profits. Importantly, these observed profits could not be fully explained by measurement errors such as bid–ask bounce or by risk, seasonality or volume. Profits are largely related to firm size with overreaction to firm specific information being the primary source of short-term contrarian profits in Australia. However, when a ‘practical’ short-term contrarian strategy including reasonable transaction costs is implemented, all profits vanish. Thus, while the contrarian approach is not viable as a stand-alone strategy, we argue that it may in fact be value-enhancing when employed as an overlay strategy, particularly in the context of managed funds.

This study examines the relation between individual investor trading and future stock returns in the Australian equity market. We find that the net trading of Australian individual investors is positively related to future returns. We show that this association is driven by individual investors who play the role as liquidity providers. We further document that the proliferation of algorithmic trading in recent years dampens the relation between individual trading and future returns. Finally, we present evidence that the net individual trading prior to earnings announcements predicts post-announcement returns. This prediction, however, is only observed for individual investors using full-service brokers Refereed/Peer-reviewed

Purpose – This paper aims to establish the relation between corporate governance – as represented by investor protection at both the legal and firm levels – and stock market liquidity. Design/methodology/approach – This paper avails of the unique features of Hong Kong- and China-based stocks that are traded on the Hong Kong Stock Exchange so as to test whether differences between “common law” and “civil law” legal environments contribute to differences in stock liquidity. In addition, by constructing an internal corporate governance index score for each firm based on board size, board independence and information on the audit and remuneration committee, we document whether firms with better corporate governance scores have narrower spreads, greater depth and higher trading volumes. Findings – Overall, results provide support for a linkage between corporate governance issues – as investor rights protection at both the environment and firm protection levels – and stock market liquidity. Research limitations/implications – This paper recognizes that investor protection constitutes a single component of the desirability of investing in a firm’s stock. Nevertheless, it does appear to constitute an important component of a stock’s attractiveness. Practical implications – The practical implications are clear, namely, that good corporate governance of firms leads to their attractiveness as investment vehicles (for both the shorter and the longer terms). Social implications – The paper has clear social implications. In particular, the paper serves to highlight that prospects for enduring wealth creation are contingent on the safeguards accorded to the equity ownership of a firm’s stock. Originality/value – The originality lies in taking advantage of the unique features of the Chinese and Hong Kong firms on the Hong Kong Exchange, so as to examine the contrasting influences of common law and civil law on stock liquidity. Thus, the authors allow for the effects of corporate governance across the two legal environments (China and Hong Kong) to be compared and contrasted while maintaining other influences unchanged across Chinese and Hong Kong shares.

This chapter investigates the influence of improved pre-trade transparency on the information content of the limit order book. Data from two natural experiments are examined: when the Sydney Futures Exchange increased the limit order book disclosure from the best bid and ask level to the best three price levels in 2001 and from the best three to the best five price levels in 2003. Evidence shows that the limit order book contains information on future return and volatility. The limit order book also becomes more informative following the two improvements in pre-trade transparency, with stronger result for the first event. The findings of this study highlight a diminishing benefit of additional limit order book disclosure.

We investigate the effect of broker anonymity on the information content of the limit order book on the Australian Stock Exchange. We argue that the move to anonymity has stronger impact on institutional than individual investors. We document that anonymity increases the informativeness of institutional limit orders about future volatility but has little effect on individual limit orders. Our findings imply that anonymity allows institutional investors to display informative orders in the limit order book. Prices, however, adjust less sufficiently to institutional investors' order flow. Overall, anonymity may improve liquidity but it comes at the cost of reduced price efficiency. Refereed/Peer-reviewed

This analysis presents an application of a recently developed approach by Matteson and James (2012) for the analysis of change points in time-series data; in this case financial market indices converted to financial return series. The method involves the nonparametric estimation of both the number of change points and the positions at which they occur without making assumptions about the nature of the distributions involved. The procedure is used to explore the timing and number of change points in the data sets corresponding to the effects of the GFC and subsequent European Debt Crisis and their impact on daily market index return series for the Japanese, Chinese, Malaysian, Singaporean, and Indonesian markets from 2003 to 2013.

The effect of stressors on financial market investment decisions is underexplored. We investigate the association of a common stressful life event, divorce, with the trading behavior of individual investors. In the critical three year period around their divorce, investors realize lower returns compared to a control sample, as well as compared to their own portfolios in other years. After controlling for a number of demographic variables, we document that men and women both underperform immediately around divorce. Two years after, the trading performance of women recovers to pre-divorce levels, while that of men continues to be significantly lower.

We investigate the volume-volatility relation and the effect of the number of trades and average trade size, institutional and individual trading, and order imbalance on price volatility. We document a positive relation between trading volume and volatility for stocks traded on the Australian Securities Exchange (ASX). We further show that the number of trades has a more significant effect on price volatility than average trade size. When the number of trades is decomposed into the number of trades of different sizes, the number of trades in the medium size category often has the most significant impact on volatility. The trading activity of both institutions and individuals are positively related to volatility, with individual trading has a more significant role in explaining price volatility than institutional trading. Finally, we document that on the ASX (a pure limit order book market) order imbalance-however it is important in explaining the volume-volatility dynamics-it is not the main factor driving this relation.

Volatility swaps and volatility options are financial products written on discretely sampled realized variance. Actively traded in over-the-counter markets, these products are often priced by continuously sampled approximations to simplify the computations. This paper presents an analytical approach to efficiently and accurately price discretely sampled volatility derivatives, under a general stochastic volatility model. We first obtain an accurate approximation for the characteristic function of the discretely sampled realized variance. This characteristic function is then applied to price discrete volatility derivatives through either semi-analytical pricing formulae (up to an inverse Fourier transform) or an efficient Fourier-cosine series method. Numerical experiments show that our approxima- tion is more accurate in comparison to the approximations in the literature. We remark that although discretely sampled variance swaps and options are usually more expensive than their continuously sampled counterparts, discretely sampled volatility swaps are more prone to be cheaper than the continuously sampled counterparts. An analysis is then provided to explain why this is the case in general for realistic contract specifications and reasonable model parameters. Refereed/Peer-reviewed

Volatility swaps and variance options are financial products written on discretely sampled realized variance. Actively traded in over-the-counter markets, these products are priced often by a continuously sampled approximation to simplify the computations. This paper presents an analytical approach to efficiently and accurately price discretely sampled volatility derivatives, under the Heston stochastic volatility model. We first obtain an accurate approximation for the characteristic function of the discretely sampled realized variance. This characteristic function is then applied to derive semi-analytical (up to an inverse Laplace transform) pricing formulae for variance options, volatility swaps and volatility options. We examine with numerical examples the accuracies of the approach in pricing these volatility derivatives. We also test the effect of discrete sampling in pricing volatility derivatives. For realistic contract specifications and model parameters, we find that although continuously sampled variance swaps and options are cheaper than their discretely sampled counterparts, continuously sampled volatility swaps are, however, more expensive than their discretely sampled counterparts.

Daily price limits are criticized for their role in disrupting price adjustment process. We propose a flexible price limits mechanism as an alternative to daily price limit rules. First, we identify volatility spill-over and consecutive price limit hits as the source for disrupting informed trading. Later, we propose flexible price limits that can be implemented by using predicted probability of volatility spill-over and consecutive price limit hits. We provide empirical evidence in support of flexible price limits’ efficiency by using 5 years intra-day data of stocks listed on the Tokyo Stock Exchange. Refereed/Peer-reviewed

This study investigates the impact of timing of the release of firm-specific announcements on trading volume of individual and institutional investors. We use trading data in five-minute intervals to capture the immediate impact of announcements on the trading volume. We find that individual investors exhibit positive and significant abnormal volume prior to, issued capital announcements and after earnings announcements. However, institutions exhibit significant and positive abnormal volume prior to, and after earnings, periodic and issued capital announcements. Notably, both individual and institutional investors do not exhibit significant abnormal volume prior to, and after dividend announcements. Furthermore, individual (institutional) investors’ buy (sell) volume is significantly higher than sell (buy) volume prior to, and after scheduled and unscheduled announcements. Our results suggest that timing of the release of firm-specific announcements influences investor trading volume.

Algorithmic trading (AT) is widely adopted by equity investors. In the current paper we investigate whether AT increases stock price volatility in turbulent periods. By exclusively focusing on the volatile days on the Australian Securities Exchange during the period of 27 October 2008 till 23 October 2009, we find a significant negative association between the level of AT activities in a particular (individual) share and the price swing of that stock. We also provide evidence that the AT’s order imbalances have smaller impact on the abnormal returns of individual stocks compared to order imbalances based on non-algorithmic trading. Overall, our findings indicate that, in turbulent market conditions, the AT improves market quality by reducing volatility and minimizing price pressure.

This study investigates individual and institutional investors’ behaviour around firm specific news announcements. We find that individual investors and institutional investors have positive and significant abnormal volume on announcement days and significantly less abnormal volume on days without announcements. Both investor types show significant abnormal volume around progress reports, periodic reports, dividend and takeover announcements. Individual and institutional investors exhibit positive abnormal volume around scheduled and unscheduled firm specific announcements. Buy and sell abnormal volume around scheduled announcements are positive for the investor classes whereas institutional buy and individual sell abnormal volume are positive around unscheduled announcements, both at 1% significant level.

In this paper we introduce a consistent framework for pricing options written on the S&P500 stock index and volatility index (VIX). Gatheral (2007, 2008) proposes a three-factor stochastic volatility model to achieve this goal. However, the non-affine structure of the model leads to analytical intractability so closed-form pricing formulae may not exist either for S&P500 options, or for VIX options. The Monte Carlo simulation method adopted in Gatheral is rather inefficient in terms of calculation and model calibration. This study proposes two analytical asymptotic formulae to efficiently price S&P500 options and VIX options, respectively, based on Gatheral's three-factor stochastic volatility model. By applying singular perturbation techniques, our formulae are obtained by solving a set of partial differential equation systems. We then rigorously justify the convergence of the asymptotic formulae. In addition, we present some numerical examples to demonstrate that our asymptotic formulae can achieve high efficiency and accuracy for a large class of options with relative short tenor.