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.     

Cross‐Asset Speculation in Stock Markets

In practice, heterogeneously informed speculators combine private information about multiple stocks with information in prices, taking into account how their trades influence the inferences of other speculators via prices. We show how this speculation causes prices to be more correlated than asset fundamentals, raising price volatility. The covariance structure of asset fundamentals drives that of prices, while the covariance structure of liquidity trade drives that of order flows. We characterize how speculator profits vary with the distributions of information and liquidity trade across assets and speculators, and relate the cross‐asset factor structure of order flows to that of returns.     

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.     

Impacts of trades in an error-correction model of quote prices

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the characteristics of the trades occurring between quote observations, if any. From this model we are also able to extract the implied model for the spread and the mid-quote. We find that short duration and medium volume trades have the largest impacts on quote prices for all one hundred stocks. Further, we find that buys have a greater impact on the ask price than on the bid price, while sells have a greater impact on the bid price than on the ask price. Both buys and sells increase spreads in the short run, but in the absence of further trades, the spreads mean revert. Trades have a greater impact on quotes for the infrequently traded stocks than for the more actively traded stocks.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

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.     

Prices, liquidity, and the information content of trades

We investigate the effect of asymmetric information on pricesand liquidity by analyzing trades, quotes, spreads, and depths.Information content should increase with trade size and theinformation asymmetry of the trading period. Results show thatprice and liquidity effects are significantly associated withinformation content as measured by both trade size and timingrelative to information events. Results are stronger for purchasesthan sales. Quoted prices are better measures of informationeffects than transaction prices, because they control for bid-askbounce. Finally, trades that a priori contain no informationhave no impact on prices and liquidity, despite their largesize.     

Random walks,liquidity molasses and critical response in financial markets

Stock prices are observed to be random walks in time despite a strong, long-term memory in the signs of trades (buys or sells). Lillo and Farmer have recently suggested that these correlations are compensated by opposite long-ranged fluctuations in liquidity, with an otherwise permanent market impact, challenging the scenario proposed in Quantitative Finance, 2004, 4, 176, where the impact is instead transient, with a power-law decay in time. The exponent of this decay is precisely tuned to a critical value, ensuring simultaneously that prices are diffusive on long time scales and that the impact function is nearly lag independent. We provide new analysis of empirical data that confirm and make more precise our previous claims. We show that the power-law decay of the bare impact function comes both from an excess flow of limit order opposite to the market order flow, and to a systematic anti-correlation of the bid–ask motion between trades, two effects that create a ‘liquidity molasses’ which dampens market volatility.     

Quote-based competition and trade execution costs in NYSE-listed stocks

This study examines quotations, order routing, and trade execution costs for seven markets that compete for orders in large-capitalization NYSE-listed stocks. The competitiveness of quote updates from each market varies with measures of the profitability of attracting additional order and with volatility and inventory measures. The probability of a trade executing on each market increases when the market posts competitive quotes. Execution costs for non-NYSE trades when the local market posts competitive (non-competitive) quotes are virtually the same (substantially exceed) costs for matched NYSE trades. Collectively, these results imply a significant degree of quote-based competition for order flow and are consistent with off-NYSE liquidity providers using competitive quotations to signal when they are prepared to give better-than-normal trade executions.     

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book (LOB) markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in LOBs based on a recent sample of 30 German Deutscher Aktienindex (DAX) stocks. We find that Hasbrouck's (1991) measure of trade informativeness Granger causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news-induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis, we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity.     

Trading and Liquidity on the Tokyo Stock Exchange: A Bird's Eye View

The trading mechanism for equities on the Tokyo Stock Exchange (TSE) stands in sharp contrast to the primary mechanisms used to trade stocks in the United States. In the United States, exchange-designated specialists have affirmative obligations to provide continuous liquidity to the market. Specialists offer simultaneous and tight quotes to both buy and sell and supply sufficient liquidity to limit the magnitude of price changes between consecutive transactions. In contradistinction, the TSE has no exchange-designated liquidity suppliers. Instead, liquidity is provided through a public limit order book, and liquidity is organized through restrictions on maximum price changes between trades that serve to slow down trading. In this article, we examine the efficacy of the TSE's trading mechanisms at providing liquidity. Our analysis is based on a complete record of transactions and best-bid and best-offer quotes for most stocks in the First Section of the TSE over a period of 26 months. We study the size of the bid-ask spread and its cross-sectional and intertemporal stability; intertemporal patterns in returns, volatility, volume, trade size, and the frequency of trades; and market depth based on the response of quotes to trades and the frequency of trading halts and warning quotes.     

A functional approach to the price impact of stock trades and the implied true price

We propose a functional approach to estimate the instantaneous price impact of a trade and to infer an implied true price. Our model expresses price impact as an S-shaped function of signed volume. It has two parameters, one for price impact and one for liquidity depth. The latter measures the differential impact of small and large trades. The price impact is instantaneous, that is, it occurs at the instant of trade execution. Our specification also permits the price impact of buys and sells to be asymmetric. We compute an implied true price from our model, and we find that it is closer than the quote midpoint to the unobservable true price. Our empirical analysis also shows that the effective spread, which is computed using the midpoint, has an upward bias, and that the implicit transaction costs may be lower than previous estimates.     

Co-movements of index options and futures quotes

We report evidence that the co-movements of index options and index futures quotes differ sharply from perfect correlation in periods with option trades. In half-hour intervals with (without) option trades 25% (12%) of call option quote changes have either the opposite sign or are larger in magnitude than the corresponding index futures quote changes. We calibrate a stochastic volatility model that allows for trade and no-trade periods using real data and simulate the joint co-movements of index quotes and option quotes in this model. We show that for trade intervals the observed co-movements differ from the benchmark case established by our simulations approximately three times too often. We provide empirical evidence that market microstructure effects – specifically, stale quotes and aggressive quotes – explain the majority of the deviations from the benchmark. Our findings are relevant for techniques that use estimates of local co-movements as inputs to price or hedge options.     

Mutual Fund Stock‐Picking Skill: New Evidence from Valuation‐ versus Liquidity‐Motivated Trading

We propose a novel Trade Motivation Matrix that allows differentiating funds’ valuation‐motivated (VM) and liquidity‐motivated (LM) trades on single trade level. It thus enables analyses of stock‐picking skill on three levels: trade, stock, and fund. On trade level, we find significant outperformance of VM buys and significant underperformance of VM sells, indicating manager stock‐picking skills, especially during illiquid market periods. VM trades outperform LM trades, confirming negative performance effects due to flow risk, especially when market liquidity is low. On stock level, collective VM buying explains high future stock returns while collective VM selling is related to future losses, indicating wisdom of the crowd. On fund level, higher trading discretion, measured by a higher degree of VM trading, is observed for smaller, older funds holding higher cash buffers. Finally, higher trading discretion is related to higher future fund alpha, especially during illiquid times.     

交易所大宗交易流动性折价研究——来自沪深交易所的经验证据

随着证券市场规模的扩大及机构投资者规模的壮大，机构投资者对市场流动性的需求日益剧增，大宗交易制度是满足投资者流动性需求的制度性创新。由于大宗交易的数量较大，其交易价格有别于正常交易规模的价格。本文利用沪深交易所的大宗交易数据实证探讨大宗交易价格及其影响因素。研究结果表明，大部分大宗交易价格低于当日收盘价格，呈现流动性折价现象，折价率达到1．27％：研究还发现，折价水平还受交易数量、正常交易时间段股票流动性水平、市场流动性水平及股价波幅等因素影响。     

Order imbalance and liquidity supply: Evidence from the bubble burst of Nasdaq stocks

In this study we analyze the effect of order imbalance on the quotation behavior of Nasdaq market makers. We find that Nasdaq market makers use both price and quantity quotes when dealing with order imbalances. However, order imbalance affects only price movement, not spreads. We also find that Nasdaq market makers quote more shares and compete more intensively on bid-side (ask-side) when public sells (buys) exceed public buys (sells). These suggest that market makers increase liquidity supply when order imbalances exist. More interestingly, we show that both market conditions and price movements affect investors' trading behavior.     

How and when is dual trading irrelevant?

Within a general model of speculative trade, we derive the aggregate consequences of dual traders who process retail liquidity trades and trade on their own account. We prove that dual trading reduces total expected speculator profits unless speculators process all liquidity trade and trade with the same intensity on liquidity trade. In contrast, dual trading does not affect the information content of prices. We show how results generalize when we endogenize (a) speculator information via costly information acquisition about fundamentals or costly processing of liquidity trade, and (b) liquidity trader motives and welfare via endowment shocks.     

Evaluation of the biases in execution cost estimation using trade and quote data

We use order data to assess the accuracy of execution cost estimation with trade and quote data. For our sample, estimates of the effective spread overstate actual execution costs by up to 17%. The biases result from errors in the inference of the trade direction and errors in the assignment of the benchmark quote. We find the accuracy of two popular trade direction algorithms improve marginally when trades are not lagged 5 seconds. Evaluation of the biases in execution cost measurement reveal the Ellis et al. (Journal of Financial and Quantitative Analysis (2000) 529) trade direction algorithm, combined with assigning benchmark quotes contemporaneous with trades, provides the least amount of bias. In general, biases are lower for relative effective spread estimates than effective spread estimates.     

Liquidity determination in an order-driven market

We exploit full order level information from an electronic FX broking system to provide a comprehensive account of the determination of its liquidity. We not only look at bid-ask spreads and trading volumes, but also study the determination of order entry rates and depth measures derived from the entire limit order book. We find strong predictability in the arrival of liquidity supply/demand events. Further, in times of low (high) liquidity, liquidity supply (demand) events are more common. In times of high trading activity and volatility, the ratio of limit to market order arrivals is high but order book spreads and depth deteriorate. These results are consistent with market order traders having better information than limit order traders.