Trading Activity and Financial Market Integration

We investigate the effect of trading activity in the Asian emerging markets on the market integration across Asian emerging and major developed markets over the sample period of 1997 to 2009. The empirical evidence confirms that higher trading activity in Asian emerging markets can induce these markets and developed markets to become more integrated. Furthermore, we identify the mediation effect of market volatility on Asian emerging markets. This effect demonstrates that trading activity in Asian emerging markets not only directly enhances market integration, but also intensifies market volatility, indirectly increasing market integration.     

The intraday behaviors and relationships with its underlying assets: evidence on option market in Taiwan

In this paper, we use daily data to investigate the information asymmetric effects and the relationships between the trading volume of options and their underlying spot trading volume. Our results reveal that options with higher liquidity are near-the-money and expiration periods with 2 to 4 weeks have higher trading activity. We classify them into two parts with the ARIMA model: the expected trading activity impact and the unexpected trading activity impact. Using the bivariate generalized autoregressive conditional heteroscedasticity (GARCH) model, we investigate the trading activity effect and information asymmetric effect. In conclusion, the trading volume volatility of the spot and options markets move together, and a greater expected and unexpected trading volume volatility of the spot (options) market is associated with greater volatility in the options (spot) market. However, both markets generate higher trading volume volatility when people expect such an impact rather than when they do not. We also find that there are feedback effects within these two markets. Furthermore, when the spot (options) market has negative innovations, it generates a greater impact on the options (spot) market than do positive innovations. Finally, the conditional correlation coefficient between the spot and the option markets changes over time based on the bivariate GARCH model.     

Two shades of opacity: Hidden orders and dark trading

Regulators are concerned that large volumes of trading outside lit venues (i.e., dark trading) harms the functioning of financial markets. In contrast, regulators are neutral about hidden-order trading as these occur on lit venues and are associated with positive effects on market quality. An unanswered economic question concerns the interrelation between these two types of opaque trading, i.e., hidden orders and dark trading. Employing two different empirical methodologies we find that dark and hidden-order trading are substitutes. We also show that both types of opaque trading increase when markets are volatile and fewer algorithmic trading occurs. Smart order routing increases dark trading but reduces hidden-order activity.     

How effective are trading pauses?

Exploiting Nasdaq order book data and difference-in-differences methodology, we identify the distinct effects of trading pause mechanisms introduced on US stock exchanges after May 2010. We show that the mere existence of such a regulation makes market participants behave differently in anticipation of a pause. Pauses enhance price discovery during the break but have adverse effects on price stability and liquidity after the pause. We find that pauses ultimately do not “cool off” markets but cause extra volatility. This implies a regulatory trade-off between the protective role of trading pauses and their adverse effects on market quality.     

Why do traders choose dark markets?

We examine U.S. equity trader use of dark and lit markets. Marketable orders executed in the dark have lower information content and smaller fill rates. Dark orders take longer to execute, but they execute at more favorable prices. Traders are more likely to go dark when the bid-ask spread is wider and those with higher dark participation are more sophisticated. Although market regulators have expressed concern over the rise in dark trading, our results indicate that dark markets provide important benefits to traders that lit markets do not.     

Exchange trading rules and stock market liquidity

We examine stock exchange trading rules for market manipulation, insider trading, and broker–agency conflict, across countries and over time, in 42 stock exchanges around the world. Some stock exchanges have extremely detailed rules that explicitly prohibit specific manipulative practices, but others use less precise and broadly framed rules. We create new indices for market manipulation, insider trading, and broker–agency conflict based on the specific provisions in the trading rules of each stock exchange. We show that differences in exchange trading rules, over time and across markets, significantly affect liquidity.     

Stock repurchases and treasury share sales: Do they stabilize price and enhance liquidity?

Can companies reduce the volatility and increase the liquidity of their stocks by trading them? In the context of the Italian stock market, where companies have far more leeway to sell as well as buy their own stocks than in the U.S., the answer is yes. We examine the effects of trading (open-market share repurchases and treasury shares sales) on liquidity (bid-ask spread) and volatility (return variance). Further, we examine the impact of shareholder approvals of repurchase programs on liquidity and volatility. We find clear evidence that trading increases liquidity and reduces volatility. These results are consistent with our analysis of the motives Italian companies give for making share repurchases.     

On the Role of Futures Trading in Spot Market Fluctuations: Perpetrator of Volatility or Victim of Regret?

We examine the role of index futures trading in spot market volatility. We use the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) approach to measure volatility, analyze causality and feedback relations between volatilities in the spot and futures markets, and test various hypotheses in the context of a multivariate model that incorporates other macrostate variables. Our empirical results suggest index futures trading may not be blamed for the observed volatility in the spot market. Rather, we find stronger and more consistent support for the alternative posture that volatility in the futures market is an outgrowth of a turbulent cash market. We use the regret (cognitive dissonance) theory to explain our results.     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

The day of the week effect on stock market volatility and volume: International evidence

This study investigates the day of the week effect on the volatility of major stock market indexes for the period of 1988 through 2002. Using a conditional variance framework, we find that the day of the week effect is present in both return and volatility equations. The highest volatility occurs on Mondays for Germany and Japan, on Fridays for Canada and the United States, and on Thursdays for the United Kingdom. For most of the markets, the days with the highest volatility also coincide with that market's lowest trading volume. Thus, this paper supports the argument made by Foster and Viswanathan [Rev. Financ. Stud. 3 (1990) 593] that high volatility would be accompanied by low trading volume because of the unwillingness of liquidity traders to trade in periods of high stock market volatility.     

The dynamics of quote adjustments

Liquidity providers on the NYSE make faster quote adjustments towards equilibrium spreads and depths than they do on NASDAQ. Liquidity providers in both markets make faster spread and depth adjustments for stocks with more frequent trading, greater return volatility, higher prices, smaller market capitalizations, and smaller trade sizes. We find that stocks with greater information-based trading and in more competitive trading environments exhibit faster quote adjustments. The speed of quote adjustment is faster after decimalization in both markets. These results are robust and not driven by differences in stock attributes between the two markets or time periods. Overall, our results indicate that stock attributes, market structure, and tick size exert a significant impact on the speed of quote adjustment.     

The Intraday Relation between NYSE and CBOE Prices

I extend the literature regarding price discovery across stock and option markets through an empirical model that allows information to flow through an error‐correction term and volatility. NYSE prices tend to lead CBOE prices by at least thirty minutes over the entire six‐year sample period. In addition, informed trading in the options market is revealed more strongly through persistence in volatility and the spillover of volatility to the stock market than it is through returns.     

Effects of Price Regulations and Dark Pools on Financial Market Stability: An Investigation by Multiagent Simulations

We built an artificial market model and investigated the impact of large erroneous orders on financial market price formations. Comparing the case of consented large erroneous orders in the short term with that of continuous small erroneous orders in the long term, if amounts of orders are the same, we found that the orders induced almost the same price fall range. We also analysed effects of price variation limits for erroneous orders and found that price variation limits that employ a limitation term shorter than the time erroneous orders exist effectively prevent large price fluctuations. We also investigated effects of up-tick rules, adopting the trigger method that the Japan Financial Services Agency adopted in November 2013. We also investigated whether dark pools that never provide any order books stabilize markets or not using the model including one lit market, which provides all order books to investors, and one dark pool. We found that markets become more stable as the dark pool is increasingly used. We also found that using the dark pool more reduces the market impacts. However, if other investors’ usage rates of dark pools become too large, investors must use the dark pool more than other investors to avoid market impacts. When a tick size of a lit market is larger, dark pools are more useful to avoid market impacts. These results suggest that dark pools stabilize markets when the usage rate is under some threshold and negatively affect the market when the usage rate is over that threshold. Our simulation results suggest the threshold might be much larger than the usage rate in present real financial markets. This study is the first to discuss whether or not several concrete and actually adoptable regulations, including those that have never been employed (e.g. price variation limits with various parameters), could prevent large fluctuations of market prices, including those beyond our experience, using artificial market simulations, and to discuss quantitatively how spreading of dark pools beyond our experience could affect market price formations using the artificial market simulations. In short, this study is the first study to comprehensively discuss how regulations and financial systems beyond our experience could affect price formations using the artificial market simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

THE CHOICE OF TRADING VENUE AND RELATIVE PRICE IMPACT OF INSTITUTIONAL TRADING: ADRs VERSUS THE UNDERLYING SECURITIES IN THEIR LOCAL MARKETS

We address two important themes associated with institutions’ trading in foreign markets: (1) the choice of trading venues (between a company's listing in its home market and that in the United States as an American Depositary Receipt [ADR]) and (2) the comparison of trading costs across the two venues. We identify institutional trading in both venues using proprietary institutional trading data. Overall, our research underscores the intuition that the choice of institutional trading in a stock's local market or as an ADR is a complex process that embodies variables that measure the relative adverse selection and liquidity at order, stock, and country levels. Institutions route a higher percentage of trades to more liquid markets, and these trades are associated with higher cumulative abnormal returns. We also find that institutional trading costs are generally lower for trading cross‐listed stocks on home exchanges even after controlling for selection bias.     

Stock markets fragmentation,volatility and final investors

The 2000s in equity markets are marked by two major regulatory shocks: RegNMS in the United States, and MiFID in the European Union. Simultaneously, there is a massive increase in the proportion of high-frequency trading, and market orders volume. However, trading volumes do not significantly increase. We propose a theoretical model describing the effects of stock markets fragmentation on two types of investors optimization problems: “intermediary” high-frequency and “final” investors. Volatility has a permanent and a transitory component, whose weights depend on market fragmentation via the share of non-marketable orders of intermediary investors. The trading volume of final investors depends on market fragmentation both directly via transaction costs, and indirectly via total volatility. Finally a shock in fragmentation may lead to a decrease in trading volume, enhanced in the case of an equity markets crisis by a rise in the components of volatility.     

Using implied volatility on options to measure the relation between asset returns and variability

Prior research has documented that volatility in financial asset markets is most directly related to trading rather than calendar days, and that there is an inverse asymmetric relation between volatility and returns in both stocks and long-term bonds. We examine these relations in 37 futures options markets representing a wide variety of asset types. Using futures prices and implied volatilities from this extensive array of markets, we confirm that in all of them, save one, market volatility is more directly related to trading days. However, the nature of the association between implied volatility and underlying asset returns varies greatly across asset categories and across exchanges. Thus, we show that findings from equity markets apparently are not generalizable to other asset classes.     

Circuit Breakers,Trading Collars,and Volatility Transmission Across Markets: Evidence from NYSE Rule 80A

The NYSE's Rule 80A attempted to delink the futures and equity markets by limiting index arbitrage trades in the same direction as the last trade to reduce stock market volatility. Rule 80A leads to a small but statistically significant decline in intraday U.S. equity market volatility. In addition, the results are asymmetric: volatility is dampened more in a rising market than in a declining one. These results suggest that, to a limited extent, rule restrictions on trading can sufficiently delink the futures and equity markets enough to reduce the transmission of volatility.     

Disagreement and asset prices

How do differences of opinion affect asset prices? Do investors earn a risk premium when disagreement arises in the market? Despite their fundamental importance, these questions are among the most controversial issues in finance. In this paper, we use a novel data set that allows us to directly measure the level of disagreement among Wall Street mortgage dealers about prepayment speeds. We examine how disagreement evolves over time and study its effects on expected returns, return volatility, and trading volume in the mortgage-backed security market. We find that increased disagreement is associated with higher expected returns, higher return volatility, and larger trading volume. These results imply that there is a positive risk premium for disagreement in asset prices. We also show that volatility in and of itself does not lead to higher trading volume. Instead, only when disagreement arises in the market is higher uncertainty associated with more trading. Finally, we are able to distinguish empirically between two competing hypotheses regarding how information in markets gets incorporated into asset prices. We find that sophisticated investors appear to update their beliefs through a rational expectations mechanism when disagreement arises.     

High‐Frequency Trading and the New Stock Market: Sense And Nonsense

The stock market has been transformed during the last 25 years. Human suppliers of liquidity like the NASDAQ dealers and NYSE specialists have been replaced by algorithmic market making; stocks that once traded on a single venue now trade across twelve exchanges and a multitude of alternative trading systems. New venues like dark pools, and new participants like high‐frequency traders, have emerged to take on prominent roles. This new market has had more than its share of controversy and regulatory scrutiny, particularly in the wake of Michael Lewis’s bestseller Flash Boys. In this article, the authors analyze five of the most controversial new market practices, including various high‐frequency trading strategies and dark pool activities. They set out a simple conceptual framework based on adverse selection and agency problems, and apply that framework to assess the welfare effects of each of the five practices. While much that is criticized is indeed objectionable, other controversial practices are much more complex than popularly imagined and may in fact be socially desirable. They conclude by evaluating a range of potential reforms to equity market structure.     

SHORT SELLING AND PRICE DISCOVERY: EVIDENCE FROM AMERICAN DEPOSITARY RECEIPTS

The underlying shares of some American Depositary Receipts (ADRs) can be short sold in their home markets, and others cannot. This institutional feature offers a unique opportunity to investigate the relation between short selling and price discovery. We hypothesize and confirm that ADR short selling on a U.S. exchange is more informative when the ADRs’ underlying shares cannot be short sold in the home market. These and related results suggest that short sellers make a significant contribution to price discovery. Short sellers’ trading activity, representing more than 20% of total ADR share volume, increases the benefits of cross‐listing on U.S. exchanges.