Dmitriy Muravyev

Order Flow and Expected Option Returns

I show that the inventory risk faced by market-makers has a first-order effect on option prices. I introduce a simple approach that decomposes the price impact of trades into inventory risk and asymmetric information components. While both components are large for option trades, the inventory risk component is larger. Using the full panel of daily option returns, I find that option order imbalances attributable to inventory risk have five times larger impact on option prices than previously thought. Finally, I find that past order imbalances have greater predictive power than any other commonly used predictor of option returns.

Option Trading Costs Are Lower than You Think

Conventional estimates of the costs of taking liquidity in equity options markets are large. This presents a puzzle, which we resolve by taking seriously the implication of models of dynamic limit order markets that the bid-ask midpoint can be a poor proxy for the true value of a security, conditional on the occurrence of a trade. Changes in option prices can be predicted using publically available information, and a large proportion of option trades exploit this high-frequency predictability to take liquidity at low cost, buying and selling immediately before option prices are expected to change. Conventional measures of effective spreads and price impact do not account for this execution timing but can be adjusted to do so. For the average trade, effective spreads that take account of trade timing are one-third smaller than the conventionally measured effective spreads; for trades that reflect execution timing, they are four times smaller. Conventional measures of price impact overstate it by a factor of more than two. These findings have striking implications for the profitability of options trading strategies that involve taking liquidity. Our main results are robust to recent changes in option market structure.

Does Trade Clustering Reduce Trading Costs? Evidence from Periodicity in Algorithmic Trading

We use quasi-exogenous variation in trading activity at the sub-second frequency to show that higher trade and quote intensities cause higher volatility but perhaps surprisingly have no significant effect on stock liquidity. This result has significant implications for the theories of strategic trading. We use the fact that many more trades and quote updates arrive within the first 100 milliseconds than during the rest of a second. These periodicities originate from algorithms that trade predictably by repeating instructions in loops with round start times and time increments. This seemingly irrational behavior serves as a synchronization mechanism for other investors. We also show that HFTs are much less prone to this bias.

The Informational Role of Index Option Trading

Do order flows in index derivatives capture informed trading? We show that net buying pressure in index put options traded on the International Securities Exchange (ISE) positively and robustly predicts SP specifically in index futures and the ETF on the index, as well as order flow in the underlying index. The contrarian nature of return prediction from option order flow (net put buying predicts a higher index return) suggests that market makers who take the other side of the option orders have private information, and set quotes to attract orders from outside customers and brokers. Supporting the notion that market makers lower spreads to attract trading when they have information, we find that the predictive ability of put order flow for index options is higher when puts are more liquid.

Informed Trading in the Stock Market and Option Price Discovery

Using a comprehensive sample of trades from Schedule 13D filings by activist investors, we show that both directional and volatility information is reflected in stock and option prices. Option prices reflect the adverse selection risk associated with the volatility component of private information rather than the directional component. We then study the role of informed trading in price discovery and find that activists choose to trade stocks and to not trade derivatives in about 98% of cases. When they use derivatives, they typically seek to increase their overall economic exposure to the stock. We find that on days when activists accumulate shares, option implied volatility decreases and volatility skew increases. We conclude that informed trading in the stock market contributes to the flow of volatility information into option prices.

Why Do Option Returns Change Sign from Day to Night

Returns for S&P 500 index options are negative and large: -0.7% per day. Strikingly, when we decompose these delta-hedged option returns into intraday (open-to-close) and overnight (close-to-open) components, we find that average overnight returns are -1% while intraday returns are actually positive, 0.3% per day. A similar return pattern holds for all maturity and moneyness categories, equity and ETF options, and VIX futures. Rational theories struggle to explain positive intraday returns. We show that returns change sign and become positive because option prices fail to account for the well-known fact that stock volatility is substantially higher intraday than overnight. Thus, option market-makers, some of the most sophisticated investors, appear to completely ignore one of the strongest volatility seasonalities, which can be easily added to option pricing models. Finally, other option investors also appear unaware of this anomaly, which may explain its persistence.