Using a rich data set of transaction-level buy and sell orders from the major digital currency
exchange Coinbase, we formulate a measure for investor sentiment and shed new evidence …

We study statistical aspects of state-dependent Hawkes processes, which are an extension
of Hawkes processes where a self-and cross-exciting counting process and a state process …

Machine learning is driving the evolution of algorithmic trading, but the demands for fast
execution speed remain. Although both aim to increase profitability, embedding more …

Thanks to advanced technologies, ultra-high-frequency limit order book (LOB) data are now
available to data analysts. An LOB contains comprehensive information on all transactions …

We analyze intraday liquidity for a range of cryptocurrencies across different exchanges.
Among the liquidity measures used, slippage is most interesting for crypto traders, as it …

We propose a framework to study the optimal liquidation strategy in a limit order book for
large-tick stocks, with the spread equal to one tick. All order book events (market orders, limit …

One of the most interesting and challenging issues in the field of finance at the moment is
high-frequency trading (HFT). This is because HFT is a relatively new issue for most of the …

A quasi-centralized limit order book (QCLOB) is a limit order book (LOB) in which financial
institutions can only access the trading opportunities offered by counterparties with whom …

With the proliferation of algorithmic high-frequency trading in financial markets, the Limit
Order Book has generated increased research interest. Research is still at an early stage …

High-frequency trading (HFT) employs cutting-edge hardware for rapid decision-making and
order execution but often relies on simpler algorithms that may miss deeper market trends …