Interaction of investor trades and market volatility: Evidence from the Tokyo Stock Exchange

This paper examines the relation between market volatility and investor trades by identifying who supplies and demands market liquidity on the Tokyo Stock Exchange. Because the different trading patterns of various investor types such as individual investors, institutional investors, and foreign investors affect market liquidity differently, we find that market volatility fluctuates significantly depending on which investor types participate in trade. We show that market volatility increases by more than 50% from the average level when there are greater buy trades by momentum investors that demand liquidity and there are less sell trades by contrarian (or profit-taking) investors that supply liquidity. On the other hand, volatility dampens by more than 57% when there are greater sell trades by profit-taking investors, mostly by domestic investors, while there are less momentum buy trades.     

Liquidity, analysts, and institutional ownership

In this paper, we investigate the empirical relationship between institutional ownership, number of analysts following and stock market liquidity. We find that firms with larger number of financial analysts following have wider spreads, lower market quality index, and larger price impact of trades. However, we find that firms with higher institutional ownership have narrower spreads, higher market quality index, and smaller price impact of trades. In addition, we show that changes in our liquidity measures are significantly related to changes in institutional ownership over time. These results suggest that firms may alleviate information asymmetry and improve stock market liquidity by increasing institutional ownership. Our results are remarkably robust to different measures of liquidity and measures of information asymmetry.     

Stealth trading: The case of the Tokyo Stock Exchange

The stealth trading hypothesis asserts that informed traders trade strategically by breaking up their orders so as to more easily hide among the liquidity traders. Using data for the Tokyo Stock Exchange (TSE), a pure order-driven market, we find evidence that price changes are driven by small- and medium-size trades, with small trades making the greatest contribution to price change relative to their contribution to trading volume. We also find that large trades explain a greater portion of the cumulative price change on high volatility days. Hence, our results support the stealth trading hypothesis for the TSE.     

The difference a day makes: Timely disclosure and trading efficiency in the muni market

The Real-Time Transaction Reporting System (RTRS) reduced the delay in reporting municipal bond trades from one-day to 15 min. We find a significant reduction in secondary market trading costs after the introduction of the RTRS. Our estimates imply that retail investors benefited primarily from reduced dealer intermediation costs, while large trades benefited from reductions in bargaining costs. Bonds experienced increases in trading volume across the liquidity spectrum. We find higher dealer capital commitment, longer intermediation chains, and fewer pre-arranged trades, all suggesting increased market-making incentives for dealers. These results are largely consistent with predictions from search-based models.     

Determinants of Trading Profits: The Liquidity Provision Decision

Theories show that liquidity provision implies negative contemporaneous correlation between trades and returns. Dealers on the Taiwan Stock Exchange are granted typical dealer trading advantages without obligations to provide liquidity and, thus, are ideal to test whether these advantages lead to voluntary liquidity provision (earning bid-ask spreads) or information trading (trading in the direction of the market). We find a strong positive correlation in aggregate, implying that these unrestricted dealers prefer information trading. We also find that smaller dealers are more likely to provide liquidity and that small-cap stocks (with larger bid-ask spreads) are more profitable for liquidity provision.     

Trading and Pricing in Upstairs and Downstairs Stock Markets

We provide empirical evidence on the economic benefits of negotiatingtrades in the upstairs trading room of brokerage firms relativeto the downstairs market. Using Helsinki Stock Exchange data,we find that upstairs trades tend to have lower informationcontent and lower price impacts than downstairs trades. Thisis consistent with the hypotheses that the upstairs market isbetter at pricing uninformed liquidity trades and that upstairsbrokers can give better prices to their customers if they knowthe unexpressed demands of other customers. We find that theseeconomic benefits depend on price discovery occurring in thedownstairs market.     

IPO Trading without Market Makers or Underwriter Price Support

We investigate the trading behavior and liquidity supply of Chinese initial public offerings (IPOs) that trade in an order‐driven market system with pure limit order books where no market makers or price support is allowed. We find large trades and quoted depths dominate the first day of trading, but this pattern quickly reverses as small trades and quoted depths are more prevalent on subsequent trading days. Quoted depths are positively related to the number of shares offered in the IPO and trade size, but are negatively related to underpricing. Trade size and transaction immediacy are positively related, and large and positive (negative) order imbalance is associated with more aggressive buys (sells). Finally, long‐run performance is not related to initial order imbalance. Overall, our results suggest that despite underwriters not participating in the IPO aftermarket, liquidity provision evolves very quickly and price discovery is immediately reflected in prices.     

Merger Announcements and Trading

We test whether an increase either in informed trades or in large liquidity trades leads to greater correlation of trading volume across markets. We confirm that both trading volume and positive returns of target companies are abnormally high before merger announcements. We find a statistically significant increase in the correlation between New York Stock Exchange and Nasdaq/regional trading volume before merger announcements. Furthermore, after merger announcements, we find evidence of both large liquidity trading and a statistically significant increase in the correlation of trading volume across markets.     

Upstairs Market for Principal and Agency Trades: Analysis of Adverse Information and Price Effects

This paper directly tests the hypothesis that upstairs intermediation lowers adverse selection cost. We find upstairs market makers effectively screen out information-motivated orders and execute large liquidity-motivated orders at a lower cost than the downstairs market. Upstairs markets do not cannibalize or free ride off the downstairs market. In one-quarter of the trades, the upstairs market offers price improvement over the limit orders available in the consolidated limit order book. Trades are more likely to be executed upstairs at times when liquidity is lower in the downstairs market.     

THE DYNAMICS OF QUOTED LIQUIDITY AROUND LARGE TRADES ON THE NYSE

Large trades have potentially disruptive effects on the continuation of subsequent trade. If the large trade executes against volume from limit orders or specialist quotations, continued trade may be unavailable until new liquidity enters the market. Evidence presented in this paper indicates that large trades on the NYSE are followed by decreases in quoted liquidity, which last for an average of fifteen minutes. Both the decreases in quoted liquidity and the time to its subsequent return are related to trade-specific factors. This evidence suggests that not all large trades have the same effect on the continuation of trade.     

LIQUIDITY COMMONALITY BEYOND BEST PRICES

Previous market microstructure research focuses on commonality in liquidity at the inside spread. However, liquidity at the inside spread only determines the systematic liquidity risk of small and medium trades. We study commonality in displayed liquidity beyond best prices, which determines the systematic liquidity risk of large trades. We show that it is much larger than commonality at the inside spread. The deeper we look into the order book, the higher is the level of commonality. In addition, it rises in the morning and when markets fall.     

Large option trades, market makers, and limit orders

This article focuses on the difference between market makersand limit orders in their role as suppliers of liquidity. Forboth sources of liquidity I analyze the price behavior of stocksand options around large option trades and I estimate the premiumpaid by the initiator of the large trade. My findings suggestthat limit orders for options are 'picked off' after adversechanges in the underlying stock price. Furthermore, I find thatfor these transactions there is a permanent change in quotationsin the direction of the transaction. After transactions wheremarket makers supply liquidity, quotes tend to return to theirpretrade level.     

Time-Varying Arrival Rates of Informed and Uninformed Trades

We propose a dynamic econometric microstructure model of trading,and we investigate how the dynamics of trades and trade compositioninteract with the evolution of market liquidity, market depth,and order flow. We estimate a bivariate generalized autoregressiveintensity process for the arrival rates of informed and uninformedtrades for 16 actively traded stocks over 15 years of transactiondata. Our results show that both informed and uninformed tradesare highly persistent, but that the uninformed arrival forecastsrespond negatively to past forecasts of the informed intensity.Our estimation generates daily conditional arrival rates ofinformed and uninformed trades, which we use to construct forecastsof the probability of information-based trade (PIN). These forecastsare used in turn to forecast market liquidity as measured bybid-ask spreads and the price impact of orders. We observe thatPINs vary across assets and over time, and most importantlythat they are correlated across assets. Our analysis shows thatone principal component explains much of the daily variationin PINs and that this systemic liquidity factor may be importantfor asset pricing. We also find that PINs tend to rise beforeearnings announcement days and decline afterwards.     

Liquidity in the Foreign Exchange Market: Measurement,Commonality, and Risk Premiums

We provide the first systematic study of liquidity in the foreign exchange market. We find significant variation in liquidity across exchange rates, substantial illiquidity costs, and strong commonality in liquidity across currencies and with equity and bond markets. Analyzing the impact of liquidity risk on carry trades, we show that funding (investment) currencies offer insurance against (exposure to) liquidity risk. A liquidity risk factor has a strong impact on carry trade returns from 2007 to 2009, suggesting that liquidity risk is priced. We present evidence that liquidity spirals may trigger these findings.     

Optimal trading strategy and supply/demand dynamics

In this paper, we study how the intertemporal supply/demand of a security affects trading strategy. We develop a general framework for a limit order book market to capture the dynamics of supply/demand. We show that the optimal strategy to execute an order does not depend on the static properties of supply/demand such as bid–ask spread and market depth, it depends on their dynamic properties such as resilience: the speed at which supply/demand recovers to its steady state after a trade. In general, the optimal strategy is quite complex, mixing large and small trades, and can substantially lower execution cost. Large trades remove the existing liquidity to attract new liquidity, while small trades allow the trader to further absorb any incoming liquidity flow.     

Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures

The increasing volume of messages sent to the exchange by algorithmic traders stimulates a fierce debate among academics and practitioners on the impacts of high-frequency trading (HFT) on capital markets. By comparing a variety of regression models that associate various measures of market liquidity with measures of high-frequency activity on the same dataset, we find that for some models the increase in high-frequency activity improves market liquidity, but for others, we get the opposite effect. We indicate that this ambiguity does not depend only on the stock market or the data period, but also on the used HFT measure: the increase of high-frequency orders leads to lower market liquidity whereas the increase in high-frequency trades improves liquidity. We hypothesize that the observed decrease in market liquidity associated with an increasing level of high-frequency orders is caused by a rise in quote volatility.     

Liquidity Dynamics Around Jumps: The Evidence from the Warsaw Stock Exchange

The aim of our study is to examine the dynamics of trading volume and the number of trades around jumps detected in intraday stock returns. We detect jumps in equally spaced 10-minute returns for most liquid stocks quoted on the Warsaw Stock Exchange within one-year sample period. We match jumps with macroeconomic and firm specific news. We find that only the minority of jumps is associated with public information releases, whereas the majority of them is motivated by liquidity shocks observed in the spreads, volume, and the number of trades. Our findings show that jumps are related to the inability of the market to absorb new and big orders. Liquidity shocks in volatility, volume, and quoted spread are the key drivers accompanying the occurrence of the jumps. Finally, the introduction of a faster and more efficient trading system improves the liquidity by increasing the depth of the market.     

Bid ask spread in a competitive market with institutions and order size

Large orders, particularly from institutions, are quite common these days and hence there is interest to know if institutional trading has any bearing on the price effect associated with large trades. Recent empirical studies contradict earlier evidence of negative price effect on selling large blocks and find no price effect associated with large trades. Existing theoretical framework suggests a monotonic and increasing adverse price effect for large trades, where the motivation for a large trade is private information. We model a trading system where pure information, information-liquidity, and pure liquidity traders trade small and large sizes. The pure information traders strategically choose an order size. Institutions trade only large sizes because of their low execution costs for large trades; they are information-liquidity traders whose ability to use an information signal to determine their trades is subject to a binding liquidity constraint. We show that in such a market a separating equilibrium where trade size is informative does not exist and hence there is no price effect for large trades. Trade size may be revealing only if there is a buy sell asymmetry (large buy size is not equal to large sell size) or the corresponding price effect is asymmetric (price effect due to a large buy is not equal to that of a large sell). Further for a pooling equilibrium to exist, where trade size is not informative, the width of the market denoted by the ratio of order size (large size/small size) needs to be small, while the shallowness (inverse depth) of the market denoted by the ratio between pure information and institutional trades and the information signal needs to be stronger (higher). Our results on bid and ask prices and spread confirm recent empirical evidence on price effect of large and institutional trades found in the literature.

Information Disclosure and Stock Liquidity: Evidence from Borsa Italiana

This article examines the effect of increased corporate information disclosure on stock liquidity. Using the adoption of International Financial Reporting Standards (IFRS) in Italy as a natural experiment we extend previous work examining the effect on one measure of liquidity—bid‐ask spreads—to others, specifically depth and the price impact of transactions (or effective bid‐ask spreads). Consistent with previous research we find that bid‐ask spreads of stocks decline following the introduction of IFRS, which implies that stock liquidity increases for small traders. However, we also provide evidence that depth at the best quotes declines, which challenges the proposition that liquidity increases for large trades following an increase in disclosure. In additional tests, we find that effective bid‐ask spreads of block trades also decline following the introduction of IFRS. Overall, this evidence confirms that stock liquidity for both small and large trades increases following an increase in corporate information disclosure.     

Dealer Markets Under Stress: The Performance of NASDAQ Market Makers During the November 15, 1991, Market Break

The liquidity of the NASDAQ market was seriously undermined during the crash on October 19, 1987, when bid-ask spreads widened dramatically and dealers reputedly withdrew from market making. This paper studies the liquidity of 36 NASDAQ issues on November 15, 1991, when average prices fell over 4%, representing the first major correction in the post-crash era. We find that bid-ask spreads, the percentage of dealers posting inside quotes, and trading volume remained virtually unaffected. Effective spreads were also largely unaffected, except for trades in excess of 1,000 shares among issues whose market makers avoided odd-eighth quotes. Our evidence implies that, unlike October 1987, the liquidity of the NASDAQ market did not deteriorate appreciably during this episode of unusual market stress.