Dr. Eleanor Strauss
Volatility Forecasting
Dr. Eleanor Strauss is recognized for her research on volatility forecasting and technical publications on model validation. Her best-known book examines the pitfalls of machine learning in applied finance and the necessity of robust peer review.
Dr. Strauss has spent over a decade at the intersection of machine learning and financial risk modelling, publishing technical papers on volatility estimation and model governance. Her most cited work addresses the role of peer review in mitigating overfitting and bias in algorithmic forecasting. She is known for her ability to translate complex methods into transparent, actionable insights for practitioners.
Dr. Strauss regularly leads workshops on data-driven critique, fostering open debate and skepticism in both classroom and industry settings. Her teaching philosophy emphasizes evidence over intuition and the importance of exposing the limits of predictive models.