We train a machine learning method on a class of informed trades to develop a new
measure of informed trading, informed trading intensity (ITI). ITI increases before earnings …

The continuous limit order book is a prominent design feature of modern securities markets.
Theoretical literature suggests that this feature has an undesirable side effect; it enables …

We examine the effect of high frequency trading on market quality from the perspective of a
limit order trader. By competing with slower limit order traders, high frequency traders (HFT) …

We examine the effect of high-frequency trading on market quality from the perspective of a
limit order trader. By competing with slower limit order traders, high-frequency traders …

We design and train machine learning models to capture the nonlinear interactions between
financial market dynamics and high-frequency trading (HFT) activity. In doing so, we …

We analyse the price discovery process in bitcoin-dollar trading on Coinbase, the most
established cryptocurrency spot exchange. Using a modified reinforcement learning …

Cryptocurrency markets are highly fragmented and exhibit a regulatory blend of a single fully-
regulated derivatives platform, a handful of semi-regulated spot venues, and numerous self …

This study proposes and evaluates a new methodology to study indirect market impact of
limit order book (LOB) messages using state-of-the-art machine learning models and early …

We examine which components of message traffic in a high-speed equity market, including
orders from traders with varying technological capabilities, signal short-term illiquidity. Our …

Liquidity costs and the flow of information into prices exhibit persistent yet distinct seasonal
patterns. Using a multi-year sample of high-frequency US data, we show that liquidity costs …