Startseite AllgemeinCollaborationsEventsPapersProjects
rikl

Innosuisse Innovation project on Reinforcement Learning in Finance successfully concluded

“The major winners will be financial services companies that embrace technology.” Alexander Peh, PayPal and Braintree Over the last few years, Reinforcement Learning (RL) has gained significant attention as a framework for learning optimal decisions even in complex environments. Moreover, RL is currently considered one of the most promising research areas in machine learning and […]

Innosuisse Innovation project on Towards Explainable Artificial Intelligence and Machine Learning in Credit Risk Management

For Switzerland, the reputation of stable long-standing financial institutions has always represented a crucial advantage for the acquisition and retention of customers. However, as the financial service industry becomes more global, clients expect personalized offerings and inclusiveness of service which in turn requires lenders to rely extensively on alternative data and advanced modelling techniques. Swiss […]

rikl
Kategorie: Projects

Innosuisse Innovation project on Deep Learning & Neural Networks: Autonomous AI agents for the development of novel trading strategies in asset management based on self-play

Private Alpha Switzerland is a leading developer of investment strategies for asset management in Switzerland in the field of algorithm-based and AI-assisted investing. As an investment advisor, you are responsible for two fund products in this area. This opens up this highly sophisticated investment approach to a broad investor base.

rikl
Kategorie: Projects

Innosuisse Innovation project on Deep Learning & Neural Networks: Autonomous AI agents for the development of novel trading strategies in asset management based on self-play

Private Alpha Switzerland is a leading developer of investment strategies for asset management in Switzerland in the field of algorithm-based and AI-assisted investing. As an investment advisor, you are responsible for two fund products in this area. This opens up this highly sophisticated investment approach to a broad investor base.

rikl
Kategorie: Projects

Interpretable machine learning for diversified portfolio construction

In this article, the authors construct a pipeline to benchmark hierarchical risk parity (HRP) relative to equal risk contribution (ERC) as examples of diversification strategies allocating to liquid multi-asset futures markets with dynamic leverage (volatility target). The authors use interpretable machine learning concepts (explainable AI) to compare the robustness of the strategies and to back […]

rikl
Kategorie: Papers