Empirical Identification of Non-Informational Trades Using Trading Volume Data

This paper empirically identifies non-informational and informational trades using stock returns and trading volume data of the U.S., Japanese, and U.K. stock markets and five individual firms. We achieve the identification by imposing a restriction from theoretical considerations. Our results show that trading volume is mainly driven by non-informational trades, while stock price movements are primarily driven by informational trades. We also find that, around the 1987 stock market crash, trading volumes due to non-informational trades increased dramatically, while the decline in stock market prices was due mainly to informational trades. Increases in volatilities both in returns and in trading volumes during and after the crash are mainly due to non-informational trades. Regarding the trading volume-serial correlation in the stock returns relationship, we find evidence that is consistent with theoretical predictions that non-informational components can account for high trading volume accompanied by a low serial correlation of stock returns.     

Crash-neutral currency carry trades

Currency carry trades exploiting violations of uncovered interest rate parity in G10 currencies deliver significant excess returns with annualized Sharpe ratios equal to or greater than those of equity market factors (1990–2012). Using data on out-of-the-money foreign exchange options, I compute returns to crash-hedged portfolios and demonstrate that the high returns to carry trades are not due to peso problems. A comparison of the returns to hedged and unhedged trades indicates crash risk premia account for at most one-third of the excess return to currency carry trades.     

Ripples through markets: Inter-market impacts generated by large trades

This paper uses a sample of large trades executed on the London Stock Exchange's SEAQ-I market for European cross-traded firms to investigate their impact on home market prices when parallel markets suffer from information frictions. I find that (a) large London trades produce price impacts in home markets even though no timely information is published, (b) market makers appear to pre- and post-position their inventories by splitting orders across markets, and (c) the price discovery process across markets changes significantly around large trades with the foreign market making a significantly bigger contribution to price discovery at this time, even though information opaqueness exists.     

Competition For Order Flow, Market Quality, And Price Discovery In The Nasdaq 100 Index Tracking Stock

We investigate competition for order flow, market quality, and price discovery in the Nasdaq 100 Index Tracking Stock (QQQ). The QQQ, an AMEX‐listed, exchange‐traded fund, is the most actively traded security in the U.S. equities market. On July 31, 2001, the NYSE began trading the QQQ, marking the first time it traded securities of companies it does not list. The greatest volume of trading takes place on electronic communication networks (ECNs), following by trading on the AMEX and the NYSE. Most of the block trades are executed on the AMEX, where the bid‐ask spreads are narrower. We find that ECNs contribute the most to the price‐discovery process. The spreads on all trading platforms have decreased and market quality and price discovery have improved since QQQ shares have traded on the NYSE.     

UNLISTED TRADING PRIVILEGES,LIQUIDITY, AND STOCK RETURNS

In this study we examine the effect of dual trading through unlisted trading privileges (UTPs) on liquidity and stock returns. Stocks with UTPs trade in a different market structure than stocks listed and traded only on the AMEX and NYSE. Differences in market structure may affect stock returns through liquidity services provided by the competing markets. The sample comprises 852 AMEX and NYSE firms that began unlisted trading on the Philadelphia, Pacific, Midwest, or Cincinnati exchanges between 1984 and 1988. The results show significantly positive abnormal returns around the SEC's announcement of a regional exchange's filing for UTPs. The results also suggest that increased competition improves trading liquidity. Only stocks with low liquidity before UTPs announcements experience significantly improved liquidity and positive stock returns.     

Index-option pricing with stochastic volatility and the value of accurate variance forecasts

In pricing primary-market options and in making secondary markets, financial intermediaries depend on the quality of forecasts of the variance of the underlying assets. Hence, pricing of options provides the appropriate test of forecasts of asset volatility. NYSE index returns over the period of 1968–1991 suggest that pricing index options of up to 90-days maturity would be more accurate when: (1) using ARCH specifications in place of a moving average of squared returns; (2) using Hull and White's (1987) adjustment for stochastic variance in the Black and Scholes formula; (3) accounting explicitly for weekends and the slowdown of variance whenever the market is closed. (JEL C22, C53, C10, G11, G12)     

Microstructural dynamics in a foreign exchange electronic broking system

This paper explores the relationships between quotations, spreads and transactions in the Foreign Exchange market. Such interactions have been the subject of much work in markets such as the NYSE, but until now have gone unexamined in the FX market owing to a lack of data. Using a 7 hour, transactions-based data set we examine the determinants of both quote revisions and spreads. The results indicate that trades are a major factor in spread determination and quote revisions. Furthermore, there is evidence that the widely documented negative auto-correlation in quote returns is at least partially caused by the ‘thinness’ of this particular segment of the FX market.     

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.     

Informed Trading Around Earnings Announcements: Another Look

This study is an empirical test of the Easley, O'Hara, and Srinivas (1998) multimarket sequential trade model of stock and option markets. We employ two approaches to determine the information content of signed stock and option trades executed around quarterly earnings announcements. The first approach expands the vector autoregression (VAR) technique of Hasbrouck (1991a) to include signed option trade volumes and inter‐trade durations. Estimates from the VAR models provide insight into whether both equity and option trades are viewed as informative by the equity specialist. The second approach focuses on the information content of the earnings releases to determine whether signed equity and option trades executed prior to the announcements are informed. Results indicate that although informed traders prefer to transact in both markets around earnings announcements, option market transactions contain no incremental information.     

Weather and intraday patterns in stock returns and trading activity

We examine the relation between weather in New York City and intraday returns and trading patterns of NYSE stocks. While stock returns are found to be generally lower on cloudier days, cloud cover has a significant influence on stock returns only at the market open. There are significantly more seller-initiated trades when there is more cloud cover at the market open, which is consistent with the return results. Cloudy skies are associated with higher volatility and less market depth over the entire trading day. Finally, cloud cover is not significantly correlated with spread measures and turnover ratios. The findings overall suggest that weather has a significant influence on investors’ intraday trading behavior.     

Trade size and components of the bid-ask spread

The relation between theorized components of the bid-ask spreadand trade size for a sample of NYSE firms is examined. We findthat the adverse selection component increases uniformly withtrade size. Conversely, order processing costs decrease withincreased in trade size for all but the largest trades. We findthat order persistence decreases with trade size. The adverseselection component is highest at the beginning of the day andlowest at the end of the day for all but the largest trades.Trades of NYSE firms executed on regional exchanges or NASDAQcontain a large order processing cost component but no significantadverse information effect.     

Returns transmission, value at risk, and diversification benefits in international REITs: evidence from the financial crisis

We examine daily cross-market return interactions and downside risk between a US REIT returns index and the return indexes of twelve international REIT markets. These relationships are investigated for a period of normal REIT market conditions as well as for periods of inflating and collapsing REIT prices. We find that US REIT returns are contemporaneously correlated with other REITs most strongly during the bubble and crash market conditions where the US REIT market is an almost unilateral transmitter of returns. We also find that the Value at Risk (VaR) of the least capitalized REIT markets is proportionally higher during base/normal market conditions but that the largest REIT markets have the highest VaR contribution during the crash (financial crisis) period. Overall, our evidence indicates that REIT market risk shifted to the largest REIT markets and that diversification benefits eroded considerably during turbulent market conditions.     

The Relation between Stock Market Movements and NYSE Seat Prices

Exchange seat prices are widely reported and followed as measures of market sentiment. This paper analyzes the information content of NYSE seat prices using: (1) annual seat prices from 1869 to 1998, and (2) the complete record of trades, bids and offers for the seat market from 1973 to 1994. Seat market volumes have predictive power regarding future stock market returns, consistent with a model where seat market activity is a proxy for unobserved factors affecting expected returns. We find abnormally large price movements in seats prior to October 1987, consistent with the hypothesis that seat prices capture market sentiment.     

Why effective spreads on NASDAQ were higher than on the New York stock exchange in the 1990s

Two hypotheses have been advanced to explain why spreads on NASDAQ were substantially higher than those on the NYSE in the 1990s: “collusion” and “preferencing and payment for order flow.” We present data on all actively traded stocks in these markets of relative effective spreads (RES), aggregated monthly over 1987–1999 and advance a third hypothesis: NASDAQ “SOES-day-trading.” We estimate NASDAQ and NYSE informed-trade losses and gains to market makers and other liquidity providers on six trade sizes, and find that losses on trades we ascribe to SOES day traders were substantially greater than those on other trades, offset somewhat by gains from small-trade-size investors. NASDAQ market makers' response to these losses and additional operations costs incurred to reduce the losses resulted in greater RES and increased trading within the best quotes, predominantly on larger trade sizes. The data are consistent with the “SOES-day-trading” hypotheses, but not with the other two. Furthermore, the mandatory SOES “experiment” provides insights into the negative effects of automated trading systems (such as ECNs, which now dominate NASDAQ) when their design does not adequately consider opportunistic traders.     

Liquidity of the CBOE Equity Options

We examine the CBOE option market depth and bid-ask spreads. Absence of price effects surrounding large option trades suggests excellent market depth. However, bid-ask spreads for the CBOE options and the NYSE stocks are nearly equal, even though an average option is equivalent to less than half a stock plus borrowing. We explain this tradeoff between market depth and bid-ask spreads on the CBOE and the NYSE by differences in market mechanisms. We also show that the adverse-selection component of the option spread, which measures the extent of information-related trading on the CBOE, is very small.     

An Investigation of Transactions Data for NYSE Stocks

Using transactions data, the behavior of returns and characteristics of trades at the micro level is examined. A minute-by-minute market return series is formed and tested for normality and autocorrelation. Evidence of differences in return distributions is found among overnight trades, trades during the first 30 minutes following the market opening, trades at the close, and trades during the remainder of the day. The latter distribution is found to be normal. Unusually high returns and standard deviations of returns are found at the beginning and the end of the trading day. When the beginning-and end-of-the-day effects are omitted, autocorrelation in the market return series is reduced substantially. A number of patterns in trading are reported.     

The role of trades in price convergence: A study of dual-listed Canadian stocks

We examine the role of trades in restoring price parity for equities trading in multiple markets. Using a sample of stocks trading on the Toronto Stock Exchange and on the NYSE, AMEX or NASDAQ, we contrast price convergence when market makers (a) observe only lagged quotes from both markets and (b) also observe local order flow. Traditional error correction model estimates show that prices in the two markets adjust towards parity in response to quoted price discrepancies, meaning that observation of the cross-market quote helps restore parity. Including order flow in an augmented error correction model, we find that incremental price convergence occurs when trades are routed to the market with the better price, and the importance of quotes in the price convergence process is reduced. Cross-sectional analysis reveals that the importance of order flow in each market is decreasing in firm size and increasing in measures of liquidity. Our findings point to an important, and hitherto unexamined, role for trades in promoting inter-market price convergence.     

One Market? Stocks,Futures, and Options During October 1987

We provide new evidence regarding the degree of integration among markets for stocks, futures and options prior to and during the October 1987 market crash. Where previous analyses have resulted in recommendations for the implementation of circuit breakers, the coordination of margin requirements across markets, and changes in regulatory jurisdiction, our analysis indicates that delinkage between markets during the crash was primarily caused by an antiquated mechanism for processing stock market orders. The results suggest that market integration may be better served by efficient order execution than by further restricting markets. To a large extent, the problems of mid-October can be traced to the failure of these market segments [stocks, stock index futures, and stock options] to act as one. (Report of the Presidential Task Force [Brady Report] (1988, Executive Summary, p. vi)).     

Cream-Skimming or Profit-Sharing? The Curious Role of Purchased Order Flow

Purchased order flow refers to the practice of dealers or trading locales paying brokers for retail order flow. It is alleged that such agreements are used to “cream skim” uninformed liquidity trades, leaving the information-based trades to established markets. We develop a test of this hypothesis, using a model of the stochastic process of trades. We then estimate the model for a sample of stocks known to be used in order purchase agreements that trade on the New York Stock Exchange (NYSE) and the Cincinnati Stock Exchange. Our main empirical result is that there is a significant difference in the information content of orders executed in New York and Cincinnati, and that this difference is consistant with cream-skimming.     

The trades of NYSE floor brokers

This paper studies the contribution of NYSE floor brokers to the Exchange's agency auction market. Floor brokers represent 44%, specialists 11%, and system orders 45% of the value of all executed orders in our sample. We analyze how the cross-sectional distribution of floor broker trading depends on liquidity, block volume, on- and off-exchange competition, volatility, and order flow internalization. Floor brokers participate in large trades, primarily in liquid stocks, and they trade more when volatility is high. They provide two-sided liquidity to the market and often provide liquidity that would otherwise have been supplied by NYSE specialists.