In this bibliometric study, the significant transformations in the financial sector brought about
by automation and technological advancements from 1984 to 2022 are explored. A total of …

The design of trading algorithms requires sophisticated mathematical models backed up by
reliable data. In this textbook, the authors develop models for algorithmic trading in contexts …

Metahuman systems are new, emergent, sociotechnical systems where machines that learn
join human learning and create original systemic capabilities. Metahuman systems will …

Separate from just attacking some of the standard problems in reinforcement learning as
they are found in many books as an example, it's good to look at fields where the answers …

We develop a high frequency (HF) trading strategy where the HF trader uses her superior
speed to process information and to post limit sell and buy orders. By introducing a …

We provide an explicit closed-form strategy for an investor who executes a large order when
market order-flow from all agents, including the investor's own trades, has a permanent price …

We develop an optimal execution policy for an investor seeking to execute a large order
using limit and market orders. The investor solves the optimal policy considering different …

Algorithmic traders acknowledge that their models are incorrectly specified, thus we allow for
ambiguity in their choices to make their models robust to misspecification in (i) the arrival …

Nowadays, investors seek more sophisticated decision-making tools that maximize their
profit from investing in the financial markets by suitably determining the optimal position …

We provide two explicit closed-form optimal execution strategies to target volume weighted
average price (VWAP). We do this under very general assumptions about the stochastic …