Thought Leadership
Rothko has been a thought leader in the field of artificial intelligence and technology driven investing, with major publications and conference attendances in the top Finance and Technology venues. There has been a direct link between the research excellence of our research team and partner institutions and the generation of our strategies’ performance characteristics.
Part of our story is our collaboration with academia. Rothko is a partner of the City, London University Data Science Institute (DSI) and a participant in the Gillmore Centre for Financial Technology at the University of Warwick.
Featured publications
Interpretable, Transparent, and Auditable Machine Learning: An Alternative to Factor Investing
By Dan Philps, PhD, CFA, David Tilles, and Timothy Law
Interpretability, transparency, and auditability of machine learning (ML)-driven investment has become a key issue for investment managers as many look to enhance or replace traditional factor-based investing.
Machine Learning: Explain It of Bust
By Dan Philps, PhD, CFA
“If you can’t explain it simply, you don’t understand it.” And so it is with complex machine learning (ML). ML now measures environmental, social, and governance (ESG) risk, executes trades, and can drive stock selection and portfolio construction, yet the most powerful models remain black boxes. ML’s accelerating expansion across the investment industry creates completely novel concerns about reduced …
ChatGPT and Large Language Models:
Six Evolutionary Steps
By Dan Philps, PhD, CFA and Tillman Weyde, PhD
The evolution of language models is nothing less than a super-charged industrial revolution. Google lit the spark in 2017 with the development of transformer models, which enable language models to focus on, or attend to, key elements in a passage of text. The next breakthrough — language model pre-training, or self-supervised learning …
By Dan Philps, PhD, CFA and Tillman Weyde, PhD
ChatGPT and other large language models (LLMs) may someday automate many investment management and finance industry tasks. While that day is not here yet, LLMs are still useful additions to the analyst’s toolkit. So, based on what we have learned about the new, dark art of prompt engineering, how can quant and fundamental analysts apply LLMs like ChatGPT?
By Dan Philps, PhD, CFA and Tillman Weyde, PhD
With the emergence of ChatGPT, large language models (LLMs) have captured the zeitgeist, and the future opportunities and pitfalls they imply for finance and investment management are enormous. For a small elite of high-tech investment managers, LLMs provide another systematic tile in an ever-expanding mosaic.
