Size and Style Variability of Stability Filtrations: A Country and Regional Stock Market Study

In finance stability indicators are designed to measure and predict the dynamical behaviour of financial time series. This allows a better description and understanding of vulnerabilities, of instabilities and stress resistivity of financial investments and trading decisions. Recently Setz and W¨urtz [2014] have developed a new Bayesian filtration algorithm which can be used for wealth protection of investments leading to a more steady performance and less risk with higher returns and lower drawdowns with shorter recovery times.

The investigation discusses how to calculate and how to use the BCP filtrations over time to achieve investment goals with higher performance and lower risk. In Chapter 1 we define Bayesian filtrations and show how compute them and how to extract signals. In Chapter 2 we calculate for the selected markets the stabilized wealth index, its drawdowns and recovery times, and the signal strengths ans size and style confidence. Chapter 3 discusses the results. A brief summary chapter put the results together.