Analysis of binarized high frequency financial data

Analysis of High Frequency Financial Data

Financial econometric analysis at ultra-high frequency: Data handling concerns

Data collection at ultra high-frequency on financial markets requires the manipulation of complex databases, and possibly the correction of errors present in the data. The New York Stock Exchange is chosen to provide evidence of problems affecting ultra high-frequency data sets. Standard filters can be applied to remove bad records from the trades and quotes data.A method for outlier detection ...

High-Frequency Financial Econometrics

This book is fundamentally about the estimation of risk. At an intuitive level, risk is easy to understand: given an asset with a current price of say $100, what is the likelihood that at some future time—the risk horizon—its price will be less than $90? Or more than $120? And how does the probability of observing a price below $90 change as a function of the risk horizon? Such heuristic notion...

Evaluating interval forecasts of high-frequency financial data

A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based t...

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