High frequency trading and the new market makers
TLDR
In this paper, the authors characterize the trading strategy of a large high frequency trader (HFT) and show that performance is very sensitive to cost of capital assumptions, and employ a cross-market strategy as half of its trades materialize on the incumbent market and the other half on a small, high-growth entrant market.About:
This article is published in Journal of Financial Markets.The article was published on 2013-11-01 and is currently open access. It has received 548 citations till now. The article focuses on the topics: High-frequency trading & Trading strategy.read more
Citations
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High-Frequency Trading and Price Discovery
TL;DR: In this paper, the role of high-frequency traders (HFTs) in price discovery and price efficiency is examined, and it is shown that HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors.
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Low-latency trading $
Joel Hasbrouck,Gideon Saar +1 more
TL;DR: In this paper, the authors define low-latency activity as strategies that respond to market events in the millisecond environment, the hallmark of proprietary trading by highfrequency traders though it could include other algorithmic activity as well.
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High frequency market microstructure.
TL;DR: In this article, the authors investigate the implications of technology and high frequency trading for high frequency market microstructure (HFT), with a particular focus on how HFT affects the strategies of traders and markets.
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The Flash Crash: High‐Frequency Trading in an Electronic Market
TL;DR: In this paper, the authors study intraday market intermediation in an electronic market before and during a period of large and temporary selling pressure, and they find that the trading pattern of the most active non-designated high frequency traders did not change when prices fell during the Flash Crash.
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The diversity of high-frequency traders ☆
Björn Hagströmer,Lars L. Norden +1 more
TL;DR: In this article, the authors compare market-making HFT strategies to opportunistic HFTs and find that market makers constitute the lion's share of HFT trading volume and limit order traffic.
References
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Bid, ask and transaction prices in a specialist market with heterogeneously informed traders
TL;DR: The presence of traders with superior information leads to a positive bid-ask spread even when the specialist is risk-neutral and makes zero expected profits as discussed by the authors, and the expectation of the average spread squared times volume is bounded by a number that is independent of insider activity.
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Market Liquidity and Funding Liquidity
TL;DR: In this article, the authors provide a model that links a security's market liquidity and traders' funding liquidity, i.e., their availability of funds, to explain the empirically documented features that market liquidity can suddenly dry up (i) is fragile), (ii) has commonality across securities, (iii) is related to volatility, and (iv) experiences “flight to liquidity” events.
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On estimating the expected return on the market: An exploratory investigation
TL;DR: In this article, three models of equilibrium expected market returns which reflect the dependence of the market return on the interest rate were analyzed and the non-negativity restriction of the expected excess return was explicity included as part of the specification.
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Optimal dealer pricing under transactions and return uncertainty
Thomas S. Y. Ho,Hans R. Stoll +1 more
TL;DR: In this paper, the optimal behavior of a single dealer who is faced with a stochastic demand to trade (modeled by a continuous time Poisson jump process) and facing return risk on his stock and on the rest of his portfolio was examined.
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An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse
TL;DR: In this article, the authors studied the Paris Bourse's limit order market and the interaction between the order book and order flow, showing that order flow is concentrated near the quote, while the depth of the book is somewhat larger at nearby valuations.