Research & Publications
Our work bridges the gap between technological possibility and business value. We apply data-driven technologies – especially blockchain and machine learning – to solve concrete problems in real economic sectors, with a strong focus on finance, regulated supply chains, and sustainability.
Research Focus Areas
Pillar 1: Blockchain & Distributed Ledger Technology (DLT)
We focus on "Real-Economy Applications" of blockchain technology, examining pragmatic business value in highly regulated markets.
Pillar 2: Crypto-Assets, Digital Money & Macroeconomics
We analyze the profound economic and political implications of digital currencies, including the introduction of private global currencies and their threat to European monetary sovereignty.
Pillar 3: Data Science, ML and ESG/Sustainability
We demonstrate how quantitative methods can be used to evaluate sustainability factors, including machine learning models to predict ESG ETF performance based on external factors.
Current Research Projects
MoltShell – Quantum-Safe Blockchain Infrastructure
Status: Active Development | Type: Flagship Project
MoltShell is our current research and development project at the intersection of Post-Quantum Cryptography and Distributed Ledger Technology – built for autonomous machines and AI agents. The platform offers quantum-safe encryption combined with high-performance blockchain technology. As a side effect, it exceeds the stringent requirements of European central banks and financial institutions for security and compliance.
Research Focus: Post-Quantum Cryptography (PQC), Lattice-based Cryptography, CBDC Architecture, Regulatory Compliance, High-Performance DLT
Selected Publications
• How I used Machine Learning to predict ESG Fund performance (2021)
Read on Medium
• Crypto money and cryptocurrency competition (2020)
Holste & Mayer | Routledge
• Can the German Cannabis Supply Chain Benefit from Blockchain Technology? (2020)
Springer
• Real-Economy Applications of Blockchain Technology (2018)
Holste & Schöber | SSRN