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AI managed Investment Fund

AXOVISION develops a model of interrelated artificial intelligences which analyzes the stock market. All relevant data for share prices, from financial ratios to sentiment analysis, are being utilized. The stock portfolio generated by our prototype shows a performance of 33% p.a. and thereby outperforms the broader stock market significantly. The portfolio will be put on the market as an investment fund.

No Human Factor

The advantage over a human is that the Machine Learning model can detect relevant and neglect irrelevant data. It is able to solve complex, interdependent coherences in short order without the interference and influence of emotions and biases. Additionally, the usage of one model is scalable at only minimal cost – unlike the services of fund managers.

Drift Handling

Modern day financial markets are fast-paced and dynamic. This requires flexible models that constantly detect changes and adapt accordingly. Our model incorporates strategies to handle concept drifts and adjust to shifts in market behavior and ensures suitability at all times.

Our USPs

Intelligent

The unique way of integrating different machine learning approaches into a higher-level ensemble enables more course-relevant information to be processed.

Dynamic

Concept Drift Handling enables a constant prediction quality over time and an automatic adaptation to the market and investor behaviour.

Comprehensive

Diverse data analysis on traditional and alternative data enables higher ROI opportunities by improving decision making in the investment process.

Market neutral

The implemented long/short trading strategy enables high return opportunities, unaffected by the general market performance or investor behaviour.

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Model Features

Our model features range over a vast variety of data. This includes:

Fundamental Indicators

Technical Indicators

Statistics

Sentiment Analysis

Alternative Data

Backtest Statistics

33%

Return p.a.

1.9 Sharpe Ratio

Positive Risk Compensation

0.04 Beta

Market Neutral

Our Team

Thomas Kutschera

B.A. in Economics
M.Sc. in Business Administration

Thomas gained international experience at universities in London and Chicago and established contacts in the international financial industry. The focus of his studies was on financial markets and finance. His bachelor and master theses deal with capital market anomalies and portfolio theory. He gained experience with portfolio and fund management at a regional asset management company and was able to expand this experience by working for HSBC, a major British bank. There he was involved in the trading, advisory, marketing and distribution of derivatives and structured products. Thomas is responsible for the business development, trading strategies and controlling.

Christoph Peter

B.A. in Economics
M.Sc. in Business Informatics

The focus of Christoph’s bachelor degree programme was on financial markets, in his master's he specialized in data science and business intelligence. He supplemented his theoretical knowledge with practical insights at a technology specialist, a tax firm and an asset manager. As a research assistant he worked together with an energy analytics provider, gaining valuable experience in data science and business intelligence. His network is rooted in the local financial industry and is regularly used to gather know-how. Christoph is responsible for business development, marketing and sales of the fund.

Jan Wessling

B.Sc. in Natural Language Processing
M.Sc. in Computational Linguistics

Jan´s specialty is speech recognition and he has proven this in practice: As part of the Daimler Mercedes-Benz User Experience (MBUX) Development Team, he was involved in designing an innovative, voice-controlled user interface using state-of-the-art technology. In the course of his work he was part of several scientific publications at renowned conferences. Jan constantly improves the predictive model. His core tasks are sentiment, language and text analysis.

Timo Mechsner

B.Sc. in Cognitive Informatics
Currently: M.Sc. Data Science

During his previous studies, Timo specialized in pattern recognition as well as machine and especially deep learning. In his bachelor thesis he investigated possibilities to recognize changes in market behavior (concept drift) and how to use them in automated stock trading. In addition to working with Predictive Maintenance for Industrial Machines and developing a Learning Interface for Smart Homes, he also worked several years as a freelance IT consultant and full-stack developer. He advised clients on various web and application development projects. His core tasks are Concept Drift Handling and Predictive Analysis.

Lukas Krabbe

B.Sc. in Computer Science and Software Engineering
Currently: M.Sc. in Computer Science

Lukas completed his bachelor's degree in Computer Science and Software Engineering and is currently studying for his master's degree in Computer Science at the Christian-Albrechts-Universität in Kiel. During his previous studies he focused on data-driven topics, in particular data management and the use of AI in Big Data. During his Bachelor studies, Lukas gained his first international project experience in a research project at the Moscow State University of Civil Engineering in Russia. He has been working for several years in the Business Intelligence department of the Otto Group. There he was able to contribute significantly to the success of various projects in the data engineering and data science area. As a sideline, he has been dealing with the use of AI in the financial market. His core tasks are data management and the technical infrastructure of the trading system.

Get In Touch

Just send us an email:

Email: info@axovision.com