Darya Yuferova

Assistant Professor of Finance
Norwegian School of Economics (NHH)
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Job Market Paper
Intraday Return Predictability, Informed Limit Orders, and Algorithmic Trading
(single authored)
 
I study the strategic choice of informed traders for market vs. limit orders by analyzing the informational content of the limit order book. In particular, I examine intraday return predictability from market and limit orders for all NYSE stocks over 2002-2010, distinguishing between two sources of predictability: inventory management and information. In contrast to the traditional view in the literature, I find that informed limit (not market) orders are the dominant source of intraday return predictability. The findings further indicate that the advent of algorithmic trading is associated with more informed trading, especially through market orders. Overall, my evidence emphasizes the role of limit orders in informed trading, which has implications for theory, investors, and widely used measures of informed trading.
Working Papers
The Propagation of Shocks Across International Equity Markets: A Microstructure Perspective
(with Dion Bongaerts, Richard Roll, Dominik Rösch, and Mathijs van Dijk)
 
We study the high-frequency propagation of shocks across international equity markets. We identify intraday shocks to stock prices, liquidity, and trading activity for 12 equity markets around the world based on non-parametric jump statistics at the 5-minute frequency from 1996 to 2011. Shocks to prices are prevalent and large, with regular spillovers across markets – even within the same 5-minute interval. We find that price shocks are predominantly driven by information rather than liquidity. Consistent with the information channel, price shocks do not revert and often occur around macroeconomic news announcements. Liquidity shocks tend to be isolated events that are neither associated with price shocks nor with liquidity shocks on other markets. Our results challenge the widespread view that liquidity plays an important role in the origination and propagation of financial market shocks.
Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods
(with Mario Bellia, Loriana Pelizzon, Marti Subrahmanyam, and Jun Uno)
 
We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to price discovery and liquidity provision in the subsequent opening call auction. We empirically investigate these questions using a unique dataset based on server IDs provided by the Tokyo Stock Exchange (TSE), one of the largest stock markets in the world. Our data allow us to develop a more comprehensive classification of traders than in the prior literature, and to investigate the behavior of the different categories of traders, based on their speed of trading and inventory holdings. We find that HFTs dynamically alter their presence in different stocks and on different days; therefore, we focus on HFT activity only when traders utilize their low-latency capacity. We find that, in spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to price discovery. They also contribute to liquidity provision in the opening call auction. In line with the previous literature, we also document that HFTs contribute to price discovery and are liquidity consumers during the continuous period. However, this result is driven by the three quarters of HFTs that were inactive in the pre-opening period. In contrast, those that were active in the pre-opening period contribute to liquidity provision in the subsequent continuous session. This indicates that, while HFTs contribute to both price discovery and liquidity provision, there is considerable heterogeneity in their contributions to both.

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