Measuring the impact of option market activity on the stock market: Bivariate point process models of stock and option transactions

I apply the bivariate Autoregressive Conditional Duration model of Engle and Lunde [2003. Trade and quotes: a bivariate point process. Journal of Financial Econometrics 1, 159–188] to stock and option market transactions. The first model uses option trades and stock trades. Shocks to option trade/option trade durations have a significant impact on option trade/stock trade durations. Higher implied volatility, larger stock and option market order imbalances, larger stock trades, larger spreads, smaller depths in the stock market and faster trading in the stock and option markets are all associated with faster trading in both markets. In the second model, option trade/option trade timing leads option trade/stock quote timing and several information-related stock and option market covariates impact the expected inter-market event durations.     

Limit order revisions

This paper empirically examines limit order revisions and cancellations which contribute to a significant portion of the order activity in many order-driven markets. We document that limit orders are more likely to be revised or cancelled if they are large and near the bid-ask quote. We show that order revisions generate net economic benefits to traders. Our evidence shows strong links between these activities and limit order submission risk using bid-ask spread, volatility and post-event return as proxies. We also find that these activities are less intense when the opportunity cost to monitor a stock is high, such as during lunch hours or when stock volume relative to the entire market is low.     

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.     

Is there price discovery in equity options?

We use tick-by-tick quote data for 39 liquid US stocks and options on them, and we focus on events when the two markets disagree about the stock price in the sense that the option-implied stock price obtained from the put-call parity relation is inconsistent with the actual stock price. Option market quotes adjust to eliminate the disagreement, while the stock market quotes behave normally, as if there were no disagreement. The disagreement events are typically precipitated by stock price movements and display signed option volume in the direction that tends to eliminate the disagreements. These results show that option price quotes do not contain economically significant information about future stock prices beyond what is already reflected in current stock prices, i.e., no economically significant price discovery occurs in the option market. We also find no option market price discovery using a much larger sample of disagreement events based on a weaker definition of a disagreement, which verifies that the findings for the primary sample are not due to unusual or unrepresentative market behavior during the put-call parity violations.     

Making a Market with Spreads and Depths

Abstract:   In this paper we study the quote revision behavior of NASDAQ market makers by analyzing inter‐temporal changes in their spread and depth quotes. Using individual dealer quote and trade data for a sample of 2,319 stocks, we find that NASDAQ dealers make more frequent revisions in depths than in spreads and the extent of liquidity management is greater for stocks of smaller companies, lower‐priced stocks, and stocks with larger trade sizes and fewer number of transactions. We show that intraday variation in the number of quote revisions follows the U‐shaped pattern, indicating that the extent of liquidity management is greater during the early and late hours of trading than during midday.     

Option market making under inventory risk

We propose a mean-variance framework to analyze the optimal quoting policy of an option market maker. The market maker’s profits come from the bid-ask spreads received over the course of a trading day, while the risk comes from uncertainty in the value of his portfolio, or inventory. Within this framework, we study the impact of liquidity and market incompleteness on the optimal bid and ask prices of the option. First, we consider a market maker in a complete market, where continuous trading in a perfectly liquid underlying stock is allowed. In this setting, the market maker may remove all risk by Delta hedging, and the optimal quotes will depend on the option’s liquidity, but not on the inventory. Second, we model a market maker who may not trade continuously in the underlying stock, but rather sets bid and ask quotes in the option and this illiquid stock. We find that the optimal stock and option quotes depend on the relative liquidity of both instruments as well as on the net Delta of the inventory. Third, we consider an incomplete market with residual risks due to stochastic volatility and large overnight moves in the stock price. In this setting, the optimal quotes depend on the liquidity of the option and on the net Vega and Gamma of the inventory.      

Informed Trading in Stock and Option Markets

We investigate the contribution of option markets to price discovery, using a modification of Hasbrouck's (1995) "information share" approach. Based on five years of stock and options data for 60 firms, we estimate the option market's contribution to price discovery to be about 17% on average. Option market price discovery is related to trading volume and spreads in both markets, and stock volatility. Price discovery across option strike prices is related to leverage, trading volume, and spreads. Our results are consistent with theoretical arguments that informed investors trade in both stock and option markets, suggesting an important informational role for options.     

On the Distribution of CBOE Option Trade Prices Occurring Between Consecutive Stock Trades

This paper examines the volume distribution of option trade prices that occurs when the underlying stock price remains constant. The width of these option trade price bands provides direct evidence on the law of one price and the redundancy of options assumed in many option models. We find that index option bands are narrower than equity option bands. Furthermore, for both equity and index options, puts have narrower bandwidths than calls. In general, option price bandwidth is narrow and can be explained by the minimum price movement allowed by the Chicago Board Options Exchanges (CBOE). This supports the single price law and the redundancy assumption. The existence of bid/ask quotes on the option does not materially affect the above results although it does alter the frequency of multiple option trade prices for a given underlying stock price. We note that over 53% of option trading volume occurs without bid/ask quotes on the CBOE compared to less than 15% a decade ago. Our results suggest that the effective bid/ask spread on options is probably no larger than the minimum price movements allowed by the CBOE. Furthermore, the need for the liquidity services of market makers may be declining if the decline in quoting activity stems from cross trading (i.e. trades not involving market makers).     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

Short sales and put options: Where is the bad news first traded?

Although the literature provides strong evidence supporting the presence of informed trading in both the option and the short equity markets, it is not clear which market attracts more informed trading. Using a unique dataset that covers intraday transaction data in the option and short equity markets, we investigate informed trading in a cross-market environment by explicitly studying the lead–lag relationship between the put net trade volume and short sales of the underlying stock. Our high frequency analysis shows that in general short sales contain more information. However, put options become more informative before the release of negative earnings announcements.     

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.     

Short sales and speed of price adjustment: Evidence from the Hong Kong stock market

We present empirical evidence that short sales contribute to market efficiency by increasing the speed of price adjustment to not only private/public firm-specific information but also market-wide information. Shortable stocks are characterized by weaker trade continuity and stronger quote reversals. They adjust faster to new information than non-shortable counterparts. These findings remain robust even in an “up” market condition in which short sales are not binding. The amount of information incorporated in each trade is also significantly higher for shortable than non-shortable stocks in both “up” and “down” market conditions. After controlling for firm size, trading volume, liquidity, price and option trading, short sales stand out as one of the significant factors that speed up the price adjustment.     

Market transparency: who wins and who loses?

This study uses laboratory experiments to determine the effectsof trade and quote disclosure on market efficiency, bid-askspreads, and trader welfare. We show that trade disclosure increasesthe informational efficiency of transaction prices, but alsoincreases opening bid-ask spreads, apparently by reducing market-makers'incentives to compete for order flow. As a result, trade disclosurebenefits market makers at the expense of liquidity traders andinformed traders. We find that quote disclosure has no discernibleeffects on market performance. Overall our results demonstratethat the degree of market transparency has important effectsof market equilibria and on trader and market-maker welfare.     

ANALYST REPUTATION,DEALER AFFILIATION,AND MARKET MAKING

We investigate the effects of analysts' affiliation and reputation on dealers' market making activities. We find that for a given stock, dealers who have affiliated analysts covering the stock quote and trade more aggressively than those who do not have any affiliated analysts. More important, the reputation of affiliated analysts plays an additional role in the affiliated dealer's quote and trade behavior. Dealers with affiliated star analysts post more aggressive quotes and have larger market shares than dealers with affiliated nonstar analysts. Although dealers who post more aggressive quotes also induce affiliated star analysts to cover the stocks, the positive effect of analyst reputation on the affiliated dealers' quote aggressiveness remains significant and robust after controlling for potential endogenous and simultaneous problems.     

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 informativeness of domestic and foreign investors’ stock trades: Evidence from the perfectly segmented Chinese market

This paper uses the perfect market segmentation setting in China's stock market to compare the information content of the stock trades of domestic and foreign investors. We study 76 firms that issue both A-shares (for domestic investors) and B-shares (for foreign investors) and compare the price discovery role of the two segmented markets in China. Before Feb 19, 2001, the A-share market led the B-share market in price discovery, as the signed volume and quote revision of the A-share market had strong predictive ability for B-share quote returns, but not vice versa. After Feb 19, 2001, because some domestic investors were allowed to invest in the B-share market, we find evidence for a reverse causality from the B-share to the A-share market. Nevertheless, the [Hasbrouck (1995). One security, many markets: determining the contributions to price discovery, Journal of Finance 50, 1175–1199.] information share analysis reveals that A-shares continue to dominate the price discovery process.     

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.     

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.     

Volatility Information Trading in the Option Market

This paper investigates informed trading on stock volatility in the option market. We construct non-market maker net demand for volatility from the trading volume of individual equity options and find that this demand is informative about the future realized volatility of underlying stocks. We also find that the impact of volatility demand on option prices is positive. More importantly, the price impact increases by 40% as informational asymmetry about stock volatility intensifies in the days leading up to earnings announcements and diminishes to its normal level soon after the volatility uncertainty is resolved.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.