Modeling asset prices for algorithmic and high frequency trading

Cartea, Álvaro; Jaimungal, Sebastian

Publication:
Modeling asset prices for algorithmic and high frequency trading

dc.affiliation.dpto	UC3M. Departamento de Economía de la Empresa	es
dc.contributor.author	Cartea, Álvaro
dc.contributor.author	Jaimungal, Sebastian
dc.date.accessioned	2011-09-21T17:22:36Z
dc.date.available	2011-09-21T17:22:36Z
dc.date.issued	2011-04-26
dc.description.abstract	Algorithmic Trading (AT) and High Frequency (HF) trading, which are responsible for over 70% of US stocks trading volume, have greatly changed the microstructure dynamics of tick-by-tick stock data. In this paper we employ a hidden Markov model to examine how the intra-day dynamics of the stock market have changed, and how to use this information to develop trading strategies at ultra-high frequencies. In particular, we show how to employ our model to submit limit-orders to profit from the bid-ask spread and we also provide evidence of how HF traders may profit from liquidity incentives (liquidity rebates). We use data from February 2001 and February 2008 to show that while in 2001 the intra-day states with shortest average durations were also the ones with very few trades, in 2008 the vast majority of trades took place in the states with shortest average durations. Moreover, in 2008 the fastest states have the smallest price impact as measured by the volatility of price innovations
dc.format.mimetype	application/pdf
dc.identifier.uri	https://hdl.handle.net/10016/12142
dc.language.iso	eng
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRights	open access
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.eciencia	Empresa
dc.subject.jel	G10
dc.subject.jel	G11
dc.subject.jel	G14
dc.subject.jel	C41
dc.subject.other	High frequency traders
dc.subject.other	Algorithmic trading
dc.subject.other	Durations
dc.subject.other	Hidden Markov model
dc.title	Modeling asset prices for algorithmic and high frequency trading
dc.type	working paper	*
dc.type.hasVersion	SMUR	*
dspace.entity.type	Publication