A good concise introduction into the time series analysis is given by
Franses [1]. The comprehensive presentation of the subject can be
found in monographs by Hamilton [2] and Green [6]. Important
specifics of time series analysis in finance, particularly for analysis
and forecasting of volatility, are discussed by Alexander in [3]. In this
chapter, only time series on homogenous grids were considered. Spe-
cifics of analysis of tick-by-tick data on non-homogenous grids are
discussed in [7]. It should be noted that the exercises with the econo-
metric software packages are very helpful for learning the subject.
Besides the generic scientific software such as SAS, Splus, and Matlab
that have modules for the time series analysis, several econometric
software packages are available: PCGive, RATS, Shazam, and TSP.
While these packages may have the trial and student versions, Easy-
Reg offered by H. J. Bierens
has sufficient capability for an intro-
ductory course and is free of charge.
1. Verify equations (5.1.25)–(5.1.27).
2. Verify if the process y(t) ¼ 1:2y(t 1) 0:32y(t 2) þ e (t)
(where e(t) is IID) is covariance-stationary.
3. Estimate the linear dividend growth rate from the dividends
paid in the last years (verify these data on the AMEX website:
http://www.amex.com): 2000 $1.51, 2001 $1.42, 2002 $1.50,
and 2003 $1.63.
4. Verify equation (5.4.6) for the processes (5.4.4).
Time Series Analysis 57
This Page Intentionally Left Blank

Get Quantitative Finance for Physicists now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.