Applications of Statistical Engineering Tools in Financial Time Series

Statistical engineering has capabilities. In this note, we (Reza Habibi) survey the application of statistical engineering in financial time series. The first chapter considers the filtering of a diffusion process. The second chapter is designed to study the adaptive filter and its applications. The third chapter studies the Wiener system structure. State space models and system stability are considered in chapters 4 and 5. Re-sampling methods are applied in change point detection in a financial time series in chapter 6. Genetic algorithms, Kalman filter and Neural networks are studied in the remaining chapters.

Autorentext

Reza Habibi is a free researcher in Central Bank of Iran. He has a PhD from Shiraz University. He has worked many different fields such as change point analysis, computational finance, data mining, converegnce in stochastic processes. He has published many different papers about above mentioned topics.