TAILOR – A NETWORK OF RESEARCH EXCELLENCE CENTRES
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 … Weiterlesen
Fintech and Artifical Intelligence in Finance
Using Financial News Sentiment for Stock Price Direction Prediction
Using sentiment information in the analysis of financial markets has attracted much attention. Natural language processing methods can be used to extract market sentiment information from texts such as news articles. The objective of this paper is to extract financial market sentiment information from news articles and use the estimated sentiment scores to predict the … Weiterlesen
ESG 4.0 – Enabling Sustainable and Responsible Investment leveraging AI and Big Data, Digitalisierungsinitiative DIZH
Identifying optimal strategies for sustainable investing remains hampered by a plethora of technical and methodological challenges. We propose to leverage patent data and AI to take green finance to a new level of efficiency in mitigating global threats such as climate change and pollution.
Innosuisse Innovation project on Advanced/AI-supported Rating Models for P2P systems
Our innovative idea is to provide a Proof of Concept concerning a superior and adaptive rating system applicable to both SME and personal lending, able to cope with low-quality, sparse data that is commonplace in the context of P2P lenders. If successful, we will have both a new methodology (how to deal with low-quality, sparse … Weiterlesen
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 … Weiterlesen
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 … Weiterlesen
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 … Weiterlesen