Welcome
to the future of financial forecasting
“Truth - more precisely, an accurate understanding of reality - is the essential foundation for producing good outcomes.”
About Us.
About Us
Convinced that artificial intelligence will profoundly change the world of finance, Rubinstein & Schmiedel pushes the boundaries of AI in the field of financial market forecasting. We develop and operate fully automated, high-precision trading systems capable of creating systematic and sustainable returns - so far unmatched by professional traders and rule-based algorithms.
Rubinstein & Schmiedel was founded in 2019 after more than six years of fundamental research and development. The result: a novel AI which extracts information and learns complex strategies without human input solely based on data. We are 14+ experts in Switzerland and Germany with research backgrounds in AI, Software Engineering, Data Science, Big Data, and High-Performance Computing.
We have created an end-to-end, fully automated software solution covering data acquisition, signal generation, back-testing, trade execution, portfolio and risk management. In 2019, we launched our first 24/7 actively managed investment solution for an exclusive group of professional investors. Focusing on the emerging class of digital assets, we have been providing our partners with impressive returns while minimizing downside risk – in an investment universe known for its high volatility and difficult market conditions.
We are looking to extend our range of solutions, targeting new clients, and connecting traditional asset classes to our unique AI framework.
NO HUMAN-IN-THE-LOOP
Our AI models are not limited by human experience. They rely solely on available market data and on individual investment goals to determine a “super-human” optimal trading strategy.
AI Trading 2.0
For our forecasting systems, we go beyond traditional optimization, machine learning approaches, and develop all algorithms from scratch, including hand-crafted compute-kernels for utmost performance.
Market Decomposition
Price charts are a superposition of many independent signals. Our AI system enables us to decompose market data into its underlying components (specific news, market makers, crowd behavior, etc.) to make much more precise predictions.
OPTIMIZATION FRAMEWORKS
Our next-gen deep networks require a different way of training compared to traditional approaches (e.g. SGD). Inspired by aerospace research, we have developed novel optimization frameworks for this purpose.
Deep Learning
(Deep) Neural Networks were not designed for market data initially. We have developed a novel deep network architecture with specialized neurons that are highly optimized for financial applications, handle the noise component well and don’t require labelled data.
GPU Computing
Different parts of our machine learning, analytics, and trading pipeline have been designed to run on GPU hardware for maximum performance. Custom CUDA kernels were developed to improve AI training speed and model response times.
BACK-TESTING
Large amounts of market data and news along with algorithmically enriched meta-information are collected to get a complete snapshot of the financial world at any point in time to ensure maximum reliability and a predictable live performance of all developed trading systems.
Secure Infrastructure
All storage and software services are deployed on geographically redundant premises and are configured for high availability. NIST-compliant encryption is used for all communication channels. Our custom-built hardware is locked and biometrically secured inside specialized data centers.
BOARD
DR Michael
VÖLTER
Michael has a PhD in law. He started his career at the auditing firm Arthur Andersen. He later worked at SV SparkassenVersicherung in various departments, being nearly 10 years member of the management board as CIO and CFO, before serving as Group CEO of Stuttgart Stock Exchange until end of 2021.
DANIEL
REBHORN
Daniel is an expert in the field of digital transformation and publishes as an author on the subject.
matthias
hüberli
Matthias has expertise in areas such as international business law, financial markets, IT, and stock corporation law.
management
KIRILL
RUBINSTEIN
Kirill holds a MSc degree in Financial Mathematics.
THOMAS
SCHMIEDEL
Thomas holds a MSc degree in Computer Science and has profound knowledge in areas such as big data, machine learning, neural networks and distributed ledger technology.
ADVISORY BOARD
Andreas
Schwend
Since he left the company, he has been working as an investor, supporting a few selected start-ups and helping them to grow and scale their business.
dr Michael
Kopp
Patrick
Ghali
In addition, he is a member of the Board of Vedra Partners Ltd, a UK FCA-regulated multi-family office.
Dr Heinrich
Zetlmayer
Before, he was Vice President of IBM and Co-CEO and Advisory Board Member of ESL, the world's leading e-sports platform.
Elisabeth
Roegele
Until 2021, Elisabeth served as a Board Member of the European Securities and Markets Authority (ESMA) and the International Organization of Securities Commissions (IOSCO).
Prof. Dr Christian
Bachmeir
Christian also has great expertise in the field of consulting and sales, having worked as director and scientific advisor for IBM and Mercer.
STEFAN
SCHINDLER
interested in joining the team?
Sihleggstrasse 23
8832 Wollerau
Hauptstrasse 151
10827 Berlin
Machtlfinger Straße 7
81379 Munich
Bangarten 26
9490 Vaduz
The products, services, information and/or materials contained within these web pages may not be available for residents of certain jurisdictions. Please consult the restrictions relating to the products or services in question for further information. Find our data privacy notice.here.
