Tilman Sayer is a Chief Information Officer in Advanced Logic Analytics. He worked in OptiRisk for two years as a visiting researcher working on the topic of financial analytics. He obtained his PhD in Financial Mathematics at the University of Kaiserslautern in Germany in 2012 with a thesis on the valuation of American-style derivatives within the stochastic volatility model of Heston.
Putting Big Data, Advanced Analytics and Break-Through Trading Strategies To Work in the Financial Markets
The classic Markowitz model considers the standard characteristics: return and volatility. Second order stochastic dominance (SSD) in contrast encompasses the whole distribution of asset returns.
The true magic of SSD lies in its choice of portfolio based on the minimisation of downside tail risk. Using this modelling paradigm we have developed an innovative and dynamic trading product for equities. News sentiment is integrated into the system to digest market moods and enhance prediction. Regime switching algorithms are used to detect market shifts. We provide insight into these novel techniques and supply performance results.