Time-dependent scaling patterns in high frequency financial data

Time-dependent scaling patterns in high frequency financial data

We measure the influence of different time-scales on the intraday dynamics of financial markets. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures of complexity: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices ...

Estimation of Continuous–Time Financial Models Using High–Frequency Data

Analysis of High Frequency Financial Data

Intraday Patterns and Local Predictability of High Frequency Financial Time Series

The structure of high frequency time series of financial data taking the DAX future as an example is investigated with respect to the existence of local order on a time horizon of a few minutes. We will show that there might be special local situations where there exist local order, and where the predictability is considerably higher than in average. We discretize the time series and investigat...

High frequency data in financial markets: Issues and applications

The development of high frequency data bases allows for empirical investigations of a wide range of issues in the financial markets. In this paper, we set out some of the many important issues connected with the use, analysis, and application of high-frequency data sets. These include the effects of market structure on the availability and interpretation of the data, methodological issues such ...