In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

We study the role of high-frequency trading in a dynamic limit order market. Being fast is valuable because it enables traders to revise outstanding limit orders upon news arrivals when interacting with slow market participants. On the one hand, the existence of fast traders can help to reduce...

We propose a new model of trading in OTC markets. Dealers accumulate inventories by trading with end-investors and trade among each other to reduce their inventory holding costs. Core dealers use a more efficient trading technology than peripheral dealers, who are heterogeneously connected to...

We study the role of high-frequency trading in a dynamic limit order market. Being fast is valuable because it enables traders to revise outstanding limit orders upon news arrivals when interacting with slow market participants. On the one hand, the existence of fast traders can help to reduce...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

We propose a new model of trading in OTC markets. Dealers accumulate inventories by trading with end-investors and trade among each other to reduce their inventory holding costs. Core dealers use a more efficient trading technology than peripheral dealers, who are heterogeneously connected to...