is to build robust tools that keep up with the sea of noise in social data. From my experience, it is not the most popular and promising model that contributes to our understanding of financial data science, neither for publication success nor for finding outperforming solutions. Instead, it takes a deep understanding of the underlying riddles and a lot of creativity and wit to solve them. Data science is still in an early stage, so the journey has just started. This website offers updates on my research projects and information on events I attend or find interesting.
Data science, the science and art of bringing the data to “speak”. Data science can be seen as an envelope covering any activity of interest. It can provide consultation, can shape best practice by analytics and brings an eminently strong toolbox for prediction tasks. Major struggles in financial data science arise from low signal-to-noise environments in the financial domain.
Financial services allow the efficient allocation of resources within economies and provide liquidity to the markets. Getting an edge finance is hard, but frequently facilitated with the power of computers. My research interests in finance include equities, risk factors, portfolio management, sustainability, quantitative finance, and noise in financial markets.
Economics shapes the theoretical playground for financial data science and offers theoretical guidance in small data cases. My major interests in economics are international macro finance, macroeconomic risk factors and microeconomic multi-agent simulation frameworks.
We overcome the low performance of standard portfolio optimization by modeling portfolio weights as functions of stock characteristics. Instead of predicting asset returns in a first step and subsequently modeling portfolio weights in a second step, we…
Continue readingMarkowitz Portfolio Optimization is haunted by estimation errors in mean and covariance estimates. Instead of optimizing the Sharpe ratio out-of-sample, the optimizers tend to maximize the estimation Error (Michaud 1989). The estimation error maximization property…
Continue readingFactor momentum is persistent and observable in global equity markets (Gupta & Kelly (2019)). We take the perspective of a value investor that faces disappointing returns in domestic markets and attempts to chase positive value returns over the world. A strategy that buys winning international…
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