In the Spring of 2007, we will use the book Time Series Analysis and Its Applications (with R Examples) by Schumway and Stoffer. We will go through much of the book quickly, but some parts we will examing very carefully. The use of this text should give us a very efficient path through the basics of time series analysis. We'll need to go quickly so that we can spend a substantial amount of time on more specialized issues of modeling finacial time series.
I have tried to avoid giving a dry list of books that one can find in any relevant bibliography. To be sure, I include a few of the "usual suspects," but as the list grows I hope to give increasing attention to resources that offer more novel perspectives.
Chris Chatfield, The Analysis of Time Series: An Introduction (6th Edition), Chapman and Hall, New York, 2004.
This is perhaps the most widely required texts for time series courses at the level of our course. It does not focus specifically on financial series, but it provides one will a good general basis. It strikes a sensible balance between theory and practice.
N. H. Chan, Time Series: Applications to Finance, John Wiley and Sons, New York, 2004.
A straightforward text that develops the theory of time series a the level of our course. It is less encyclopedic than Zivot and Wang, and this makes it easier to read. This text is useful even though it does not fully engage the struggle required by an honest attempt to understand real-world financial time series.
James D. Hamilton, Time Series Analysis, Princeton University Press, Princeton New Jersey, 1994.
For many, the "big green book" is their main resource. Weighing in at just under 800 pages, it is arguably the most complete treatment of the theory of time series as it is currently applied in economics and finance. It is more mathematical than our course, but for students who expect to make time series a serious part of their professional tool kit, it is worth the investment.
Terence C. Mills, The Econometrics of Financial Time Series (second edition), Cambridge University Press, Cambridge UK, 1999.
This book is close to the level of our course, and it provides good supplementary reading. Chapter 5, Modelling Return Distributions is particularly relevant. Whereas Zivot and Whang devote their energy to reporting on models that are off current interest, Mills takes a more editorial point of view. This is also one of our aims.
C.W.J. Granger (editor), Modelling Economic Series: Readings in Econometric Methodology, Clarendon Press, Oxford, 1990.
This is a collection of essays by leading econometrician's. The book now shows signs of age, but some bits are timeless, such as Leamer's "Let's Take the Con out of Econometrics." If I had picked the subtitle, I might have chosen "Modelling is not (or should not be) for Sissies."
J. Durbin and S. J. Koopman, Time Series Analysis by State Space Models, Oxford University Press, 2000.
This is book is at the level of our class and it provides as smooth an introduction to state space models as you are likely to find. The basic theory is developed without going overboard.
A. C. Harvey, Forecasting, Structural Time Models and the Kalman filter, Cambridge University Press, 1989.
This text is also at the level of our course, and it is also well worth your time. When I first looked at it I thought it was "too hard" for our class, but now I don't see what I thought was the problem.
M. West and J. Harrison, Bayesian Forecasting and Dynamic Models (2nd Ed.), Springer-Verlag, 1999.
This book is often referenced, perhaps more often than it is read. Its 680 pages make it a book that many need to reference but few need to digest. Once you have some experience with state space models, it becomes a useful resource which (ironically!) turns out to be less encyclopedic than one might hope.
David F. Hendry, Econometrics: Alchemy or Science (New Edition), Oxford University Press, Oxford, 2000.
This bravely titled collection of essays is well-worth dipping into, though I doubt that few readers will plow through all of the individual works. Certainly one of the attractive features of the book is its willingness to tackle some hard issues head-on. De minimus, it gives us a list of the problems that you will face.
Authors of academic papers often relegate their acknowledgment of the shortcomings of their work to their closing paragraphs, and, just as often, they suggest that the present defects will be remedied at a later date. The authors and the readers quietly conspire in their knowledge that no remedy is unlikely to be forthcoming.
Robert E. Rubin and Jacob Weisberg, In an Uncertain World: Tough Choices from Wall Street to Washington, Random House, New York, 2003.
Rubin's premise is that to think wisely about the world, one must think probabilistically. He does not suggest that explicit models must be used at every turn, but he does argue that leaders are nuts unless they explicitly consider multiple circumstances that have widely differing likelihood of coming to pass. The work is autobiographical, and it comes from a certain political perspective. Nevertheless, Rubin is about as nonpartisan as a person can be who has had access to the top levels of financial decision making. This is a nontechnical book, but reading it will enrich almost anyone's understanding of the potential and the limitation of probabilistic models.
Andrei Shleifer, Inefficient Markets: An Introduction to Behavioral Finance, Oxford University Press, Oxford, 2000.
This brief, efficient survey puts on the table all of the most important examples of situations where the Efficient Market Hypothesis is known to break. It sets forth many of the basic arguments both for and against the EMH in all its many flavors.
Textbooks provide an efficient way to get a quick view of the "playing field," but, if you really want to play, then eventually you must engage the original resources. A person who tries to do original research without reading original research is like a person who tries to dance without listening to music. It can be done, but something vital is missing.
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