Search Results - subject:"algorithmic trading"

Machine learning, market manipulation and collusion on capital markets : Why the “Black Box” matters

Azzutti, Alessio; Ringe, Wolf-Georg; Stiehl, Hans Siegfried - 2021

the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and … and enforcement mechanisms, as well as current legal rules on the governance of algorithmic trading, to cope with … increasingly autonomous and ubiquitous algorithmic trading systems. It shows how the “black box” nature of specific ML …

Persistent link: https://www.econbiz.de/10012587161

Algorithms put to test: Control of algorithms in securities trading through mandatory market simulations?

Raschner, Patrick - 2021

Persistent link: https://www.econbiz.de/10012587378

Uncertain execution in order-driven markets

Sánchez-Betancourt, Leandro - 2021

Persistent link: https://www.econbiz.de/10012939003

On the benefits of robo-advice in financial markets

Lambrecht, Marco; Oechssler, Joerg; Weidenholzer, Simon - 2023

Robo-advisors are novel tools in financial markets that provide investors with low-cost financial advice, usually based on individual characteristics like risk attitudes. In a portfolio choice experiment running over 10 weeks, we study how much investors benefit from robo advice. We also study...

Persistent link: https://www.econbiz.de/10014476191

Stabilizing asset prices through transition from continuous trading to electronic auctions

Schulmeister, Stephan - 2023

"algorithmic" trading strategies in exploiting short-term asset price trends and strengthening them at the same time. Fourth, it is …

Persistent link: https://www.econbiz.de/10014374712

Optimal execution with stochastic delay

Cartea, Álvaro; Sánchez-Betancourt, Leandro - In: Finance and stochastics 27 (2023) 1, pp. 1-47

Persistent link: https://www.econbiz.de/10013489491

Deep Unsupervised Anomaly Detection in High-Frequency Markets

Poutré, Cédric; Chételat, Didier; Morales, Manuel - 2023

Inspired by recent advances in the deep learning literature, this article introduces a novel hybrid anomaly detection framework specifically designed for limit order book (LOB) data. A modified Transformer autoencoder architecture is proposed to learn rich temporal LOB subsequence...

Persistent link: https://www.econbiz.de/10014353405

Bandits for Algorithmic Trading with Signals

Cartea, Álvaro; Drissi, Fayçal; Osselin, Pierre - 2023

We propose a class of execution algorithms that consists of a strategic layer and a speculative layer. The strategic layer is an optimal trading schedule that encodes the trader's objective, her tolerance to risk, and the impact of her own trades in the market. The schedule of the strategic...

Persistent link: https://www.econbiz.de/10014353755

Short-Run Price Efficiency and Discovery of Algorithmic Traders : A Machine Learning Approach

Curran, Edward; Hunt, Jack; Mollica, Vito - 2023

This paper examines the short-run weak-form efficiency of equities, using a proprietary data set permitting analysis of orderbook characteristics to measure short-term price predictability. The results show that high levels of algorithmic trader activity in a stock lowers the level of short-run...

Persistent link: https://www.econbiz.de/10014353854

Optimal Inference for Spot Regressions

Bollerslev, Tim; Li, Jia; Ren, Yuexuan - 2023

Betas from return regressions are commonly used to measure systematic financial market risks. "Good" beta measurements are essential for a range of empirical inquiries in finance and macroeconomics. We introduce a novel econometric framework for the nonparametric estimation of time-varying betas...

Persistent link: https://www.econbiz.de/10014354368