Research

Advancing the frontier of trading technology through rigorous research, academic partnerships, and open science. Bridging theory and practice in financial markets.

Active Research Areas

Our research spans multiple domains, from fundamental market theory to practical implementation challenges.

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Active

Market Microstructure Analysis

Deep analysis of market dynamics, order flow patterns, and microstructure effects on trading performance.

Publications

Partners

Key Partnerships:

University of ZurichSwiss Finance Institute

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Active

Algorithmic Trading Optimization

Research into execution algorithms, slippage reduction, and optimal order scheduling strategies.

Publications

Partners

Key Partnerships:

ETH ZurichEPFL

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Ongoing

Alternative Data Integration

Exploring novel data sources including satellite imagery, social sentiment, and IoT sensors for market prediction.

Publications

Partners

Key Partnerships:

University of St. Gallen

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Planning

Risk Management Innovation

Advanced risk models incorporating tail risk, regime changes, and behavioral factors.

Publications

Partners

Key Partnerships:

Swiss National Bank

Recent Publications

Contributing to the scientific community through peer-reviewed research and open access publications.

📄 Peer-Reviewed

202423 citations

High-Frequency Trading in Commodity Markets: A Microstructure Perspective

Authors: J. Mueller, A. Schmidt, et al.

Published in: Journal of Financial Markets

This paper examines the impact of high-frequency trading on commodity market microstructure...

📄 Conference

20248 citations

Machine Learning Applications in Cross-Market Arbitrage

Authors: J. Mueller, R. Weber

Published in: International Conference on AI in Finance

We present novel applications of deep learning techniques for identifying arbitrage opportunities...

📄 Peer-Reviewed

202335 citations

Behavioral Factors in Automated Trading Systems

Authors: J. Mueller, S. Chen, M. Johnson

Published in: Quantitative Finance

This study investigates how behavioral biases can be incorporated into algorithmic trading strategies...

Open Science & Collaboration

We believe in open science and collaborative research. Our work is transparent, reproducible, and contributes to the advancement of the entire financial technology community.

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Open Research

Datasets, methodologies, and code available to the community

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Academic Partnerships

Collaborative projects with leading universities and institutions

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Reproducible Results

All research includes complete methodology and replication instructions