-
作者：Huang, Weibing; Lehalle, Charles-Albert; Rosenbaum, Mathieu
作者单位：Sorbonne Universite
摘要：Through the analysis of a dataset of ultra high frequency order book updates, we introduce a model which accommodates the empirical properties of the full order book together with the stylized facts of lower frequency financial data. To do so, we split the time interval of interest into periods in which a well chosen reference price, typically the midprice, remains constant. Within these periods, we view the limit order book as a Markov queuing system. Indeed, we assume that the intensities of...
-
作者：Peterson, Christine; Stingo, Francesco C.; Vannucci, Marina
作者单位：Stanford University; Rice University; University of Texas System; UTMD Anderson Cancer Center
摘要：In this article, we propose a Bayesian approach to inference on multiple Gaussian graphical models. Specifically, we address the problem of inferring multiple undirected networks in situations where some of the networks may be unrelated, while others share common features. We link the estimation of the graph structures via a Markov random field (MRF) prior, which encourages common edges. We learn which sample groups have a shared graph structure by placing a spike-and-slab prior on the paramet...
-
作者：Zhou, Zhengyi; Matteson, David S.; Woodard, Dawn B.; Henderson, Shane G.; Micheas, Athanasios C.
作者单位：Cornell University; Cornell University; Cornell University; University of Missouri System; University of Missouri Columbia
摘要：Ambulance demand estimation at fine time and location scales is critical for fleet management and dynamic deployment. We are motivated by the problem of estimating the spatial distribution of ambulance demand in Toronto, Canada, as it changes over discrete 2 hr intervals. This large-scale dataset is sparse at the desired temporal resolutions and exhibits location-specific serial dependence, daily, and weekly seasonality. We address these challenges by introducing a novel characterization of ti...
