We demonstrate that the lowest possible price change (tick-size) has a large impact on the structure of financial return distributions. It induces a microstructure as well as possibly altering the tail behavior. On small return intervals, the tick-size can distort the calculation of...

We present a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards...

We analyse the structure of the distribution of eigenvalues of the stock market correlation matrix with increasing length of the time series representing the price changes. We use 100 highly capitalized stocks from the American market and relate the result to the corresponding ensemble of...

Diese Dissertation untersucht die Messung finanzieller Risiken und besteht aus vier eigenständigen Forschungspapieren über die Analyse, Modellierung und Vorhersage solcher Risiken in verschiedenen wirtschaftlichen Szenarien. Die gegenwärtigen Risikomaße ignorieren größtenteils das...

Romanian insurance industry has a competitive market, having, however, a deep character of heterogeneity, which has had an impact on different financial ratios that define it. In an international framework, non-life insurance market in Romania was a different pattern as compared to similar...

We analyze the statistical dependence structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange’s TAQ database. Instead of using a given parametric copula with a predetermined shape, we study the empirical pairwise copula...

The Epps effect, the decrease of correlations between stock returns for short time windows, was traced back to the trading asynchronicity and to the occasional lead-lag relation between the prices. We study pairs of stocks where the latter is negligible and confirm the importance of...

The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility,...