To Trade or Not to Trade: The Effect of Broker Search and Discretionary Trading on Securities Market Performance

In this article we examine the interaction of brokerage search with the Bayesian learning behavior of competitive dealers under asymmetric information. We particularly focus on the effects of price search and discretionary trading on the performance of a dealer market. A search process is incorporated into a model in which brokers determine their reservation price and whether to continue their trades. The model enables us to uncover the interrelationships among search cost, bid‐ask spread, and price volatility. We show that both spread revision and price volatility are dependent upon the optimal search process, inventory fluctuation, and search cost. Furthermore, our model predicts a negative relationship between price volatility and liquidity trading volume.     

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.     

INSIDER TRADING,REGULATION, AND THE COMPONENTS OF THE BID–ASK SPREAD

In this article we investigate the relation between insider trading regulations and the bid–ask spread. We decompose the spread into its components before and after the enactment of strict new insider trading rules in New Zealand. We find that the enactment led to a significant decrease in the information asymmetry component of the spread, which is observed mainly in illiquid and high prechange information asymmetry companies. These findings are robust to model specification. In addition, we find a decrease in the contribution of information asymmetry to price volatility.     

ARE PRICE LIMITS EFFECTIVE? EVIDENCE FROM THE ISTANBUL STOCK EXCHANGE

There is considerable discussion about controlling volatility by imposing price limits on asset prices. We examine the effects of price limits on a stock market by testing the volatility spillover, delayed price discovery, and trading interference hypotheses in a leading emerging market, the Istanbul Stock Exchange, which has a unique market microstructure as related to price limits. Our results support the volatility spillover, delayed price discovery, and trading interference hypotheses. We also show price locks at limits provide significantly stronger evidence regarding the effects of price limits than limit moves only. Finally, price limits have a significant effect on the stock market, casting doubt on their effectiveness.     

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.     

When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions

We examine high-frequency market reactions to an intraday stock-specific news flow. Using unique pre-processed data from an automated news analytics tool based on linguistic pattern recognition we exploit information on the indicated relevance, novelty and direction of company-specific news. Employing a high-frequency VAR model based on 20 s data of a cross-section of stocks traded at the London Stock Exchange we find distinct responses in returns, volatility, trading volumes and bid-ask spreads due to news arrivals. We show that a classification of news according to indicated relevance is crucial to filter out noise and to identify significant effects. Moreover, sentiment indicators have predictability for future price trends though the profitability of news-implied trading is deteriorated by increased bid-ask spreads.     

SWITCHING TO A TEMPORARY CALL AUCTION IN TIMES OF HIGH UNCERTAINTY

We evaluate a stock-specific circuit breaker implemented in several European stock exchanges, which consists of a short-lived call auction triggered by intraday stock-specific price limits. It differs from U.S. trading halts in that it is short-lived and nondiscretionary, and a trading mechanism (continuous or discrete) is always going. It differs from daily price limits in that trade prices are not restricted once the limit is hit. Intraday price ranges are smaller and adjusted to the recent volatility, so that limit hits are more frequent. We contribute to the debate about circuit breakers by enlarging the span of these mechanisms studied.     

Effects of Passive Intensity on Aggregate Price Dynamics

We find that passive intensity (PI), measured by the passive‐linked share of total stock market trading volume, is strongly related to the overall pattern of stock price movements. A one‐standard‐deviation increase in PI is associated with an 8% higher price synchronicity. We further investigate the channels through which this relation is established by separately analyzing its impact on aggregate systematic and idiosyncratic volatility of stock returns. PI has a positive effect on systematic volatility and a negative impact on firm‐specific volatility. Consistent with the effect of passive trading on price dynamics, we find evidence that PI is negatively associated with mutual funds alpha dissimilarity. After controlling for market and idiosyncratic volatility, a one‐standard‐deviation increase in PI corresponds to a 0.20% decrease in fund dissimilarity. Our findings are robust after controlling for various macro and corporate factors known to affect systematic or firm‐specific volatility.     

Information transmission in informationally linked markets: Evidence from US and Chinese commodity futures markets

This paper investigates information transmission and price discovery in informationally linked markets within the multivariate generalized autoregressive conditional heteroskedasticity and information share frameworks. Based on both synchronous and non-synchronous trading information from Chinese futures/spot markets, the New York Mercantile Exchange (NYMEX), Chicago Board of Trade (CBOT), and CME Globex futures markets for copper and soybeans, we show that there is a bidirectional relationship in terms of price and volatility spillovers between US and Chinese markets, with a stronger effect from US to Chinese markets than the other way around. Additionally, the NYMEX and CBOT play a more important role than the CME Globex in the flow of information from US to Chinese markets. Moreover, we find that Chinese copper market adjusts more quickly than the NYMEX copper market to correct the disparity between both markets. However, the converse is true in the case of soybeans. Finally, our results highlight the remarkable role of Chinese futures markets in the price formation process, though NYMEX and CBOT futures markets are the main driving force in price discovery.     

期货市场的交易量与价格波动

本文检验了美国期货市场WTI原油、S＆P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系,发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用,非预期的隔日交易量与期货价格波动之间有正相关关系,非预期的目内交易量对价格波动的影响不显著。从信息对称性的角度分析,预期的交易量中含有更多信息,能抑制期货价格的偏离;非预期的交易量主要由信息反馈者提供,他们往往对期货价格的变动做出过度反应,从而加剧价格波动。     

Long memory in volatility and trading volume

We use fractionally-integrated time-series models to investigate the joint dynamics of equity trading volume and volatility. Bollerslev and Jubinski (1999) show that volume and volatility have a similar degree of fractional integration, and they argue that this evidence supports a long-run view of the mixture-of-distributions hypothesis. We examine this issue using more precise volatility estimates obtained using high-frequency returns (i.e., realized volatilities). Our results indicate that volume and volatility both display long memory, but we can reject the hypothesis that the two series share a common order of fractional integration for a fifth of the firms in our sample. Moreover, we find a strong correlation between the innovations to volume and volatility, which suggests that trading volume can be used to obtain more precise estimates of daily volatility for cases in which high-frequency returns are unavailable.     

Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis

This paper models the relationship of European Union Allowance spot- and futures-prices within the second commitment period of the European Union emissions trading scheme. Based on high-frequency data, we analyze the transmission of information in first and second conditional moments. To reveal long-run price discovery, we compute common factor weights of Schwarz and Szakmary (1994) and information shares of Hasbrouck (1995) based on estimated coefficients of a VECM. To analyze the short-run dynamics, we perform Granger-causality tests. We identify the futures market to be the leader of the long-run price discovery process, whereas the informational role of the futures market increases over time. In addition, we employ a version of the UECCC-GARCH model as introduced by Conrad and Karanasos (2010) to analyze the volatility transmission structure. The volatility analysis indicates a close relationship between the volatility dynamics of both markets, whereas in particular we observe spillovers from the futures to the spot market. As a whole the investigation reveals that the futures market incorporates information first and then transfers the information to the spot market.     

Exploring the relationship between investor sentiment and price volatility

By performing Grey relation analysis, this study elucidates the relationship between investor sentiment and price volatility in the Taiwanese stock market. A sequential relationship is identified between investor sentiment and price volatility, and ranked according to order of importance. Analytical results show that short sales volumes may be an individual leading indicator useful in observing the effects of sentiment on price volatility, followed by open interest put/call ratios and trading volumes, and buy/sell orders. Institutional investors are related, to a lesser extent, to price volatility and sentiment. Qualified foreign institutional investors, or more rational investors, are the least influenced by price volatility, followed by securities investment trust companies and dealers. TAIEX options exert the strongest influence on sentiment during the study period, making them a valuable reference for gauging price volatility.     

PRICE AND QUANTITY QUOTES ON NASDAQ: A STUDY OF DEALER QUOTATION BEHAVIOR

We show that the majority of quotes posted by NASDAQ dealers are noncompetitive and only 19.5% (18.4%) of bid (ask) quotes are at the inside. The percentage of dealer quotes that are at the inside is higher for stocks with wider spreads, fewer market makers, and more frequent trading, and lower for stocks with larger trade sizes and higher return volatility. These results support our conjecture that dealers have greater incentives to be at the inside for stocks with larger market‐making revenues and smaller costs. Dealers post large depths when their quotes are at the inside and frequently quote the minimum required depth when they are not at the inside. The latter quotation behavior leads to the negative intertemporal correlation between dealer spread and depth.     

Consolidation, fragmentation, and the disclosure of trading information

It is commonly believed that fragmented security markets havea natural tendency to consolidate. This article examines thisbelief, focusing on the effect of disclosing trading informationto market participants. We show that large traders who placemultiple trades can benefit from the absence of trade disclosurein a fragmented market, as can dealers who face less price competitionthan in a unified market. Consequently, a fragmented marketneed not coalesce into a single market unless trade disclosureis mandatory. We also compare and contrast fragmented and consolidatedmarkets. Fragmentation results in higher price volatility andviolations of price efficiency.     

Semi‐transparency,dealership market,and foreign exchange market quality

This paper examines the effects of a semi-transparency event, the introduction of the electronic trading system (EBS), on the market quality of a typical dealership market – the FX market. We find that increasing transparency leads to smaller quote disagreement among dealers and higher trading volume, but the beneficial effects are bigger for uninformed dealers than informed dealers. We also find that information efficiency improves overall in the semi-transparent system; however, informed dealers are found to quote less aggressively in the more transparent market. We conclude that semi-transparency raises market quality in general, but that it is the uninformed dealers who benefit more from this increased quality.     

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.     

Investor Attention and Time‐varying Comovements

This paper analyses the effect of an increase in market‐wide uncertainty on information flow and asset price comovements. We use the daily realised volatility of the 30‐year treasury bond futures to assess macroeconomic shocks that affect market‐wide uncertainty. We use the ratio of a stock's idiosyncratic realised volatility with respect to the S&P500 futures relative to its total realised volatility to capture the asset price comovement with the market. We find that market volatility and the comovement of individual stocks with the market increase contemporaneously with the arrival of market‐wide macroeconomic shocks, but decrease significantly in the following five trading days. This pattern supports the hypothesis that investors shift their (limited) attention to processing market‐level information following an increase in market‐wide uncertainty and then subsequently divert their attention back to asset‐specific information.     

WHEN‐ISSUED SHARES,SMALL TRADES,AND THE VARIANCE OF RETURNS AROUND STOCK SPLITS

The increases in volatility after stock splits have long puzzled researchers. The usual suspects of discreteness and bid‐ask spread do not provide a complete explanation. We provide new clues to solve this mystery by examining the trading of when‐issued shares that are available before the split. When‐issued trading permits noise traders to compete with a more homogenous set of traders, decreasing the volatility of the stock before the split. Following the split, these noise traders reunite in one market and volatility increases. Thus, the higher volatility after the ex date of a stock split is a function of the introduction of when‐issued trading, the new lower price level after the split date, and the increased activity of small‐volume traders around a stock split.     

Investor structure and the informational efficiency of commodity futures prices

This article investigates the impact of the trading positions of hedgers (i.e., producers, merchants, processors, or users of a commodity), speculators (i.e., commodity pool operators, trading advisors, or hedge funds), and swap dealers on the price formation process in the agricultural, metal, and energy futures markets. The hedgers' relative positions exert negative impacts on price efficiency in commodity futures markets. Hedgers are less likely to be information motivated, so their trading delays the price formation process. However, speculators' positions have positive impacts on price efficiency because speculators correct pricing errors. This study also offers evidence that the role of swap dealers, similar to speculators in futures markets, is to provide liquidity and cross-market arbitrage. These findings highlight the role of producers, hedge funds, and swap dealers in price formation processes in commodity futures—information that is beneficial to academics, practitioners, and regulators.