Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading

By Joel Hasbrouck. 2007

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Universal features of price formation in financial markets: perspectives from deep learning (2018, methodology): “Linear state space models, such as Vector Autoregressive (VAR) models, have been widely used in the modeling of high-frequency data and in empirical market microstructure research (Hasbrouck 2007) and provide a natural benchmark for evaluating the performance of a forecast.”
How Markets Slowly Digest Changes in Supply and Demand (2008, unknown): “For example, if we define a jump as a one minute return exceeding three standard deviations, there are the order of ten such jumps per day, reflecting the very heavy tailed distribution of high frequency returns (Joulin et al. [2008]).”
The price impact of order book events: market orders, limit orders and cancellations (2009, background): “An important aspect of these VAR models is that once we have an estimate for their kernels, they can be used to forecast the future price changes caused by each component of the event flow based on the events that occurred in the recent past (Hasbrouck 2007).”
Statistical Properties of Microstructure Noise (2013, unknown): “See, for example, the seminal paper of Black (1986) and comprehensive reviews of Madhavan (2000), O’Hara (2003), Stoll (2003) and Hasbrouck (2007), among others.”
High Frequency Trading and Price Discovery (2014, unknown): “See Chapters 8 and 9 of Hasbrouck (2007) for a detailed discussion.”
A ReMeDI for Microstructure Noise (2019, background): “One may also allow for temporary misspricing (French and Roll (1986)) or fads effects (Lehmann (1990)); see also O’Hara (1995), Hasbrouck (2007) and Foucault et al. (2013) for insightful reviews.”
On the Volatility and Comovement of U.S. Financial Markets Around Macroeconomic News Announcements (2009, background): “2 See, for example, the discussion in Hasbrouck (2006). 3 The main properties of these data sets and references to their use in the literature are given in Section II.”
Measuring Closing Price Manipulation (2011, unknown): “Although the NYSE and AMEX closing procedures are sometimes described as auctions, they bear little resemblance to any other auction procedure (Hasbrouck, 2007), particularly automated closing call auctions, such as the ones currently used at Euronext Paris and the London Stock Exchange, for example”
Econophysics review: II. Agent-based models (2011, unknown): “Instead of reviewing the huge microstructure literature, we refer the reader to the well-known books of O’Hara (1995) and Hasbrouck (2007), for example, for a panoramic view of ySecurity Exchange Commission. this branch of finance.”
Modelling high-frequency limit order book dynamics with support vector machines (2015, background): “…other hand, machine learning methods, owing to their Data-driven characteristics and light-weight computation, have been applied to a variety of ﬁnancial markets such as liquidity and volatility in bonds and index trading (Lo et al. 1997, Crammer and Singer 2001, Tino et al. 2005, Hasbrouck 2006).”
Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution (2016, methodology): “The implicit assumption of the independent VaR violations in Kupiec (1995)’s LR test and the restrictive first order Markov alternative in the independence and conditional coverage tests are not usually satisfied in practice.”