About
Welcome to my personal website covering my research and blog posts
I am the Global Head of Investment Solutions Quant Group at LGT Bank in Zurich, where I lead a quant team and build the quantitative investment platform for systematic asset allocation and portfolio strategies. I am committed to advancing applied finance through research, technology, and team development to deliver data-driven investment solutions that reflect LGT’s long-term perspective and pursuit of excellence for clients. Named Risk Magazine’s Quant of the Year 2024, I bring over 20 years of experience spanning both the buy-side and sell-side. I hold a PhD in Mathematical Statistics from the University of Tartu. My research spans systematic strategies, portfolio optimization, stochastic volatility modeling, machine learning, and blockchain/DeFi, with over 1,200 citations and H-index of 18. I am co-originator of the ROSAA (Robust Optimization of Strategic and Active Asset Allocation) framework and the log-normal beta stochastic volatility model. I actively contribute to the quant community through my editorial board role at The Journal of Computational Finance and by developing open-source Python libraries for quantitative finance. Outside of finance, I am a dedicated Brazilian Jiu-Jitsu practitioner, holding a purple belt.
My profile for Quant of the Year – Risk Awards 2024: https://www.risk.net/awards/7958305/quant-of-the-year-artur-sepp
You can follow me and my research on public profiles:
You can contact me at artursepp@gmail.com
Recent Posts
- The Science and Practice of Trend-following Systems: paper and presentation
- Lognormal Stochastic Volatility – Youtube Seminar and Slides
- Optimal allocation to cryptocurrencies in diversified portfolios – update on research paper
- Unified Approach for Hedging Impermanent Loss of Liquidity Provision – Research paper
- Log-normal stochastic volatility with quadratic drift – open access publication
- Stochastic Volatility for Factor Heath-Jarrow-Morton Framework – research paper
- AD Derivatives podcast on volatility modeling and DeFi
- What is a robust stochastic volatility model – research paper
- Robust Log-normal Stochastic Volatility for Interest Rate Dynamics – research paper
- Optimal Allocation to Cryptocurrencies in Diversified Portfolios – research paper
- Log-normal Stochastic Volatility Model for Assets with Positive Return-Volatility Correlation – research paper
- Developing systematic smart beta strategies for crypto assets – QuantMinds Presentation
- Toward an efficient hybrid method for pricing barrier options on assets with stochastic volatility – research paper
- Paper on Automated Market Making for DeFi: arbitrage-fee exchange between on-chain and traditional markets
- 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