Recursive Estimation And Time Series Analysis

Providing a comprehensive overview of event study methodology in the field of corporate finance, this book discusses how traditional methods verify the significance and insignificance of events in statistical sampling, and emphasize possible deviation from the statistics of interest.

In 1960, R. E. Kalman published his celebrated paper on recursive min­ imum variance estimation in dynamical systems [14]. This paper, which introduced an algorithm that has since been known as the discrete Kalman filter, produced a virtual revolution in the field of systems engineering. Today, Kalman filters are used in such diverse areas as navigation, guid­ ance, oil drilling, water and air quality, and geodetic surveys.