"Connecting financial applications with science and technology"
PhD in Statistics | Quantitative Researcher | Author
Global Head of Investment Services Quant Group @ LGT Private Banking
I'm a statistician and quant researcher passionate about connecting financial applications with science and technology. With 20+ years of experience in financial markets, my professional journey spans quantitative research, portfolio management, and trading of quantitative investment strategies across investment and private banks, hedge funds, and family offices.
- Quantitative investing and asset allocation
- Modeling of financial markets and instruments
- Statistical and Machine Learning methods
- Modern computational and programming tools
- Stochastic volatility models
Quant of the Year β Risk Awards 2024
Profile on Risk.net
For a complete list of publications and blog posts, visit artursepp.com
- π Website: artursepp.com
- π§ Email: artursepp@gmail.com
- π¦ Twitter: @artursepp
- πΌ LinkedIn: @artursepp
- π Google Scholar: Research Profile
- π SSRN: Author Page
QuantInvestStrats (qis
)
Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies.
Features:
- Financial data visualization
- Performance reporting and analytics
- Quantitative strategy analysis
- Portfolio construction tools
OptimalPortfolios (optimalportfolios
)
Implementation of optimization analytics for constructing and backtesting optimal portfolios in Python.
Features:
- Portfolio optimization algorithms
- Risk budgeting implementation
- Backtesting frameworks
- Performance attribution
StochVolModels (stochvolmodels
)
Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including Karasinski-Sepp log-normal stochastic volatility model and Heston volatility model.
Features:
- Karasinski-Sepp log-normal stochastic volatility model
- Heston model
- Monte Carlo simulations
- Analytical valuation of European call and put options
BloombergFetch (bbg-fetch
)
Python functionality for getting different data from Bloomberg: prices, implied vols, fundamentals.
Features:
- Bloomberg data fetching wrapper
- Price data retrieval
- Implied volatility data
- Fundamental data access
- Built on xbbg package integration
VanillaOptionPricers (vanilla-option-pricers
)
Python implementation of vectorised pricers for vanilla options
Features:
- Black-Scholes log-normal option pricing
- Bachelier normal option pricing
Package | GitHub Stars | GitHub Forks | Total Downloads | Monthly Downloads | Weekly Downloads |
---|---|---|---|---|---|
QuantInvestStrats (qis) | |||||
OptimalPortfolios (optimalportfolios) | |||||
StochVolModels (stochvolmodels) | |||||
BloombergFetch (bbg-fetch) | |||||
VanillaOptionPricers (vanilla-option-pricers) |