Public Information Arrivals, Limit Order Book, and Stock Price Changes

2011 ◽  
Author(s):  
Huong Giang (Lily) Nguyen ◽  
Fariborz Moshirian ◽  
Peter K. Pham
2017 ◽  
Vol 20 (03) ◽  
pp. 1750019 ◽  
Author(s):  
ANATOLIY SWISHCHUK ◽  
TYLER HOFMEISTER ◽  
KATHARINA CERA ◽  
JULIA SCHMIDT

The paper considers a general semi-Markov model for limit order books with two states that incorporates price changes that are not fixed to one tick. Furthermore, we introduce an even more general case of the semi-Markov model for limit order books that incorporates an arbitrary number of states for the price changes. For both cases, the justifications, diffusion limits, implementations and numerical results are presented for different limit order book data: Apple, Amazon, Google, Microsoft, Intel on 21 June 2012 and Cisco, Facebook, Intel, Liberty Global, Liberty Interactive, Microsoft, Vodafone from 3 November 2014 to 7 November 2014.


2009 ◽  
Vol 71 (4) ◽  
pp. 499-510 ◽  
Author(s):  
B. Tóth ◽  
J. Kertész ◽  
J. D. Farmer

Author(s):  
Ravi Jagannathan

Abstract I show that frequent batch auctions for stocks have the potential to reduce the severity of stock price crashes when they occur. For a given sequence of orders from a continuous electronic limit order book market, matching orders using one-second apart batch auctions results in nearly the same trades and prices. Increasing the time interval between auctions to one minute significantly reduces the severity stock price crashes. In spite of this and other advantages pointed out in the literature, frequent batch auctions have not caught on. There is a need for carefully designed market experiments to understand why and what aspect of reality academic research may be missing.


2005 ◽  
Vol 05 (02) ◽  
pp. L209-L216 ◽  
Author(s):  
FABRIZIO LILLO ◽  
J. DOYNE FARMER

Recent empirical analyses have shown that liquidity fluctuations are important for understanding large price changes of financial assets. These liquidity fluctuations are quantified by gaps in the order book, corresponding to blocks of adjacent price levels containing no quotes. Here we study the statistical properties of the state of the limit order book for 16 stocks traded at the London Stock Exchange (LSE). We show that the time series of the first three gaps are characterized by fat tails in the probability distribution and are described by long memory processes.


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