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1Leibniz Universität Hannover, Germany; 2Macquarie University Sydney, Australia
Discussant: Samia Badidi (Tilburg University)
In this paper, we study the emergence and elimination of arbitrage opportunities in computerized limit order markets. We measure price changes, buy/sell market/limit order submissions/cancellations at message frequency during arbitrage opportunities in NYMEX WTI futures and their options and find that market makers update quotes before trades become profitable so that actual arbitrage trades hardly ever occur. In the more liquid futures market, executed trades eliminate arbitrage, whereas in the options markets, liquidity providers are the ones who correct arbitrage opportunities. These results highlight the critical role of market makers in maintaining price efficiency.
9:30am - 10:00am
Inferring the trade direction in option auctions
Leander Gayda
Universität Münster, Germany
Discussant: Tobias Lauter (Leibniz Universität Hannover)
This study introduces a new approach for inferring the trade direction in option auctions by incorporating minimum price improvement requirements. Using a matched dataset of intraday transactions, this study shows that trades executed at a one-cent quoted spread involving fewer than 50 contracts, which are subject to a minimum price improvement of one cent, systematically buy at the bid and sell at the ask. The commonly applied quote rule misclassifies 95% of these trades. Accounting for this pattern increases the overall classification accuracy from 62% to 76%, and for options with less than one week to expiration from 56% to 81%.
10:00am - 10:30am
Forecast dispersion and the price impact of macroeconomic news
Samia Badidi
Tilburg University, Netherlands, The
Discussant: Leander Gayda (Universität Münster)
Using data on 25 major U.S. macroeconomic announcements, I study how forecast dispersion affects market reactions to news. I find that the price impact of announcement surprises is negatively related to forecast dispersion, challenging the conventional view of dispersion as a good proxy for uncertainty. Instead, dispersion also reflects forecaster-specific noise. To rationalize these findings, I extend the endogenous information acquisition model of Benamar, Foucault and Vega (2021) to incorporate noisy forecasts. The model predicts that higher noise-driven dispersion incentivizes investors to acquire more pre-announcement information, increasing price informativeness ahead of the release and reducing the announcement’s price impact. My findings reveal an important channel through which forecaster heterogeneity shapes market reactions to macroeconomic news.
