Dynamic modeling of mean-reverting spreads for statistical arbitrage

dc.creatorTriantafyllopoulos, Kostas
dc.creatorMontana, Giovanni
dc.date2008-08-12
dc.date2009-05-19
dc.date.accessioned2026-07-07T13:15:45Z
dc.date.available2026-07-07T13:15:45Z
dc.descriptionStatistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean-reverting spreads enjoying a certain degree of predictability. Gaussian linear state-space processes have recently been proposed as a model for such spreads under the assumption that the observed process is a noisy realization of some hidden states. Real-time estimation of the unobserved spread process can reveal temporary market inefficiencies which can then be exploited to generate excess returns. Building on previous work, we embrace the state-space framework for modeling spread processes and extend this methodology along three different directions. First, we introduce time-dependency in the model parameters, which allows for quick adaptation to changes in the data generating process. Second, we provide an on-line estimation algorithm that can be constantly run in real-time. Being computationally fast, the algorithm is particularly suitable for building aggressive trading strategies based on high-frequency data and may be used as a monitoring device for mean-reversion. Finally, our framework naturally provides informative uncertainty measures of all the estimated parameters. Experimental results based on Monte Carlo simulations and historical equity data are discussed, including a co-integration relationship involving two exchange-traded funds.
dc.description34 pages, 6 figures. Submitted
dc.identifierhttps://arxiv.org/abs/0808.1710
dc.identifierhttp://arxiv.org/abs/0808.1710
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/230569
dc.subjectStatistical Finance
dc.subjectPortfolio Management
dc.subjectApplications
dc.subjectMethodology
dc.titleDynamic modeling of mean-reverting spreads for statistical arbitrage
dc.typetext

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