We present a toolbox to compute and extract information from inhomogeneous (i. e. unequally spaced) time series.The toolbox contains a large set of operators, mapping from the space of inhomogeneous time series to itself. These operators are computationally efficient (time and memory-wise) and...

We present a toolbox to compute and extract information from inhomogeneous (i.e. unequally spaced) time series. The toolbox contains a large set of operators, mapping from the space of inhomogeneous time series to itself. These operators are computationally efficient (time and memory-wise) and...

Most financial markets produce inhomogeneous (i.e. unequally spaced) tick-by-tick data at high frequency. Recently developed time series operators can be used to directly compute statistical variables such as volatility from inhomogeneous data. This is not possible with traditional time series...

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and...