scholarly journals Price Discovery of a Speculative Asset: Evidence from a Bitcoin Exchange

2019 ◽  
Vol 12 (4) ◽  
pp. 164 ◽  
Author(s):  
Eric Ghysels ◽  
Giang Nguyen
Keyword(s):  
Price Discovery ◽  
Theoretical Models ◽  
Secondary Market ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order ◽  
Limit Order Markets ◽  
High Volatility ◽  
Speculative Trading ◽  
High Level

We examine price discovery and liquidity provision in the secondary market for bitcoin—an asset with a high level of speculative trading. Based on BTC-e’s full limit order book over the 2013–2014 period, we find that order informativeness increases with order aggressiveness within the first 10 tiers, but that this pattern reverses in outer tiers. In a high volatility environment, aggressive orders seem to be more attractive to informed agents, but market liquidity migrates outward in response to the information asymmetry. We also find support to the Markovian learning assumption often made in theoretical models of limit order markets.

scholarly journals Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers

2020 ◽  
Vol 2020 (095) ◽  
pp. 1-36
Author(s):  
James Collin Harkrader ◽  
◽  
Michael Puglia ◽  
Keyword(s):  
Theoretical Models ◽  
Limit Order Book ◽  
Price Impact ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order ◽  
Limit Orders ◽  
Cash Transaction ◽  
Informational Advantage

We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTF), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of liquidity provider. Conversely, we find that dealer trades have higher price impact when the dealer is the aggressive party, playing the role of liquidity taker. Trades in which multiple firms (whether dealers or PTFs) participate on one or both sides, however, have relatively low price impact. We interpret these results in light of theoretical models suggesting that traders with only a “small” informational advantage prefer to use (passive) limit orders, while traders with a comparatively large informational advantage prefer to use (aggressive) market orders. We also analyze the events that occurred in Treasury markets in March 2020, during the onset of the COVID-19 pandemic.

scholarly journals Trade informativeness and liquidity in Bitcoin markets

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255515
Author(s):  
J. Christopher Westland
Keyword(s):  
Trading Volume ◽  
Limit Order Book ◽  
Small Sample ◽  
Market Liquidity ◽  
Order Book ◽  
Information Asymmetries ◽  
Limit Order ◽  
Limit Orders ◽  
Market Orders ◽  
Book Markets

Liquid markets are driven by information asymmetries and the injection of new information in trades into market prices. Where market matching uses an electronic limit order book (LOB), limit orders traders may make suboptimal price and trade decisions based on new but incomplete information arriving with market orders. This paper measures the information asymmetries in Bitcoin trading limit order books on the Kraken platform, and compares these to prior studies on equities LOB markets. In limit order book markets, traders have the option of waiting to supply liquidity through limit orders, or immediately demanding liquidity through market orders or aggressively priced limit orders. In my multivariate analysis, I control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity. The current research offers the first empirical study of Glosten (1994) to yield a positive, and credibly large transaction cost parameter. Trade and LOB datasets in this study were several orders of magnitude larger than any of the prior studies. Given the poor small sample properties of GMM, it is likely that this substantial increase in size of datasets is essential for validating the model. The research strongly supports Glosten’s seminal theoretical model of limit order book markets, showing that these are valid models of Bitcoin markets. This research empirically tested and confirmed trade informativeness as a prime driver of market liquidity in the Bitcoin market.

Public information arrival: Price discovery and liquidity in electronic limit order markets

2013 ◽  
Vol 37 (4) ◽  
pp. 1148-1159 ◽  
Author(s):  
Ryan Riordan ◽  
Andreas Storkenmaier ◽  
Martin Wagener ◽  
S. Sarah Zhang
Keyword(s):  
Price Discovery ◽  
Public Information ◽  
Limit Order ◽  
Limit Order Markets

Public Information Arrival: Price Discovery and Liquidity in Electronic Limit Order Markets

2011 ◽  
Author(s):  
Ryan Riordan ◽  
Andreas Storkenmaier ◽  
Martin Wagener
Keyword(s):  
Price Discovery ◽  
Public Information ◽  
Limit Order ◽  
Limit Order Markets

Limit order book, anonymity and market liquidity: evidence from the Sydney Futures Exchange

2008 ◽  
pp. ???-??? ◽  
Author(s):  
Alex Frino ◽  
Dionigi Gerace ◽  
Andrew Lepone
Keyword(s):  
Limit Order Book ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order

Limit order book transparency, execution risk, and market liquidity: Evidence from the Sydney Futures Exchange

2006 ◽  
Vol 26 (12) ◽  
pp. 1147-1167 ◽  
Author(s):  
Luke Bortoli ◽  
Alex Frino ◽  
Elvis Jarnecic ◽  
David Johnstone
Keyword(s):  
Limit Order Book ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order

The Information Content of Open Limit order Book in Price Discovery of KOSPI200 index Futures Market

2010 ◽  
Vol 18 (1) ◽  
pp. 1-42
Author(s):  
Woo Baik Lee ◽  
Jong Oh Kim ◽  
Min Cheol Woo
Keyword(s):  
Price Discovery ◽  
Empirical Finding ◽  
Correction Method ◽  
Futures Market ◽  
Limit Order Book ◽  
Order Book ◽  
Information Share ◽  
Limit Order ◽  
Index Futures ◽  
Limit Orders

This paper assesses the informational contents of open electronic limit order book in KOSPI 200 index futures market spanning sample period from December 2004 to November 2005 with a particular focus on the incremental information contained in the limit orders behind the best bid and offer. Using Vector Error Correction Method to estimate ‘Information share’ of quotes as suggested by Hasbrouck (1995), we find that the order book is significantly informative–its contribution to price discovery is approximately above 70%, while remaining is from cash price. Furthermore, we find the limit orders from step 2 to 5 is more informative than the best bid and offer in price discovery process, based on the estimation of information share. This empirical finding sharply contradicts the evidence suggested by previous literature that the best quotes contribute the most to price discovery and the contribution of order book the beyond the best bid and offer is marginally additional in cash market. Summarizing overall empirical evidence, limit order book in KOSPI 200 index futures market plays a differential role in contrast with stock markets.

scholarly journals Price Dynamics in an Order-Driven Market with Bayesian Learning

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Jiahua Wang ◽  
Hongliang Zhu ◽  
Dongxin Li
Keyword(s):  
Financial Markets ◽  
Bayesian Learning ◽  
Limit Order Book ◽  
Order Book ◽  
Price Dynamics ◽  
Stylized Facts ◽  
Limit Order ◽  
Learning Mechanism ◽  
Limit Order Markets ◽  
Order Driven Market

In this paper, we have developed a model of limit order book with learning mechanism and investigated its price dynamics. In this model, continuous Bayesian learning is introduced to describe the dynamics of self-adjusting learning mechanism of agents, which can result in some important stylized facts of limit order markets. This study also provides some behavioral explanations for these well-known stylized facts that are commonly observed in the financial markets.

Limit Order Book, Anonymity and Market Liquidity: Evidence from the Sydney Futures Exchange

2007 ◽  
Author(s):  
Alex Frino ◽  
Andrew Lepone ◽  
Dionigi Gerace
Keyword(s):  
Limit Order Book ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order

Dark Pools and Price Discovery in Limit Order Markets

2021 ◽  
Author(s):  
Vladimir Levin
Keyword(s):  
Price Discovery ◽  
Limit Order ◽  
Limit Order Markets ◽  
Dark Pools
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