About
BIO
Artur Sepp is Director of Research at Quantica Capital AG in Zurich focusing on systematic data-driven trading strategies. Prior, Artur worked at Julius Baer in Zurich as Senior Quant Strategist developing algorithmic solutions and strategies for the trading and portfolio advisory. Before, Artur has worked in leading roles as a Front Office Quant Strategist for equity and credit derivatives trading at Bank of America Merrill Lynch in London and Merrill Lynch in New York since 2006. Artur holds a PhD in Mathematical Statistics from University of Tartu, an MSc in Industrial Engineering and Management Sciences from Northwestern University, and a BA in Mathematical Economics with distinction from Tallinn University of Technology. Artur’s research and expertise are on econometric data analysis, statistical machine learning and computational methods along with corresponding technology and applications for quantitative trading, wealth management, and asset allocation. He is the author and co-author of several research articles on quantitative finance published in key journals and he is known for his contributions to stochastic volatility and credit risk modelling. He is a member of the editorial board of the Journal of Computational Finance.
Recent Posts
- Tail risk of systematic investment strategies and risk-premia alpha
- Trend-Following CTAs vs Alternative Risk-Premia (ARP) products: crisis beta vs risk-premia alpha
- My talk on Machine Learning in Finance: why Alternative Risk Premia (ARP) products failed
- Why Python for quantitative trading?
- Machine Learning for Volatility Trading
- Trend-following strategies for tail-risk hedging and alpha generation
- Lessons from the crash of short volatility ETPs
- Diversifying Cyclicality Risk of Quantitative Investment Strategies: presentation slides and webinar Q&A
- Volatility Modelling and Trading: Workshop presentation
- Allocation to systematic volatility strategies using VIX futures, S&P 500 index puts, and delta-hedged long-short strategies
- Why the volatility is log-normal and how to apply the log-normal stochastic volatility model in practice
- Volatility Modeling and Trading: Q&A with Euan Sinclair
- Quantitative Approaches to Wealth Management: An Interview for Instututional Investor Journals
- How to optimize volatility trading and delta-hedging strategies under the discrete hedging with transaction costs