We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that...

Financial econometrics has developed into a very fruitful and vibrant research area in the last two decades. The availability of good data promotes research in this area, specially aided by online data and high-frequency data. These two characteristics of financial data also create challenges...

Neural networks, grid computing, parallelization, high-dimensional optimization, quantitative investment, decision support. - Neuronale Netze, Parallelisierung, hoch-dimensionale Optimierung, quantitatives Investment, Entscheidungsunterstützung

This paper examines the main drawbacks of technical analysis. Although this is widely used by practitioners, from an academic perspective it can only be seen as a form of "voodoo finance". In particular, it runs into the following pitfalls: Subjectivity; Doubtful assumptions; Unjustified...

The determination of trends and prediction of stock prices is one of the main tasks of the MACD (Moving Average Convergence Divergence) and the RVI (Relative Volatility Index) indicators of the technical analysis. The research covers the sample representing stocks which are continually traded on...