The best textbook for Financial Economics or an Asset Pricing course at the Ph.D-level that there is. Highly recomended.
Reviewed in the United States on November 20, 2017
This is a welcome second edition following an excellent first edition.
But the most important question for Professors of Ph.D. in Finance or Applied Mathematical Finance and the students should ask is: Why Kerry E. Back’s Asset Pricing and Portfolio Choice Theory instead of Merton's Continues Time Finance, or Cochrane for Financial Economics. Or Shreve and George Pennachi’s Asset Pricing Theory?
Kerry Back's clarity is the main utility here. He does spend a *lot* of time on the binomial model (discrete time) (Chapters 1 through 11, and then 18 through 22 for Options, etc.) before extending it to Continuous Time, but this grounding helps in the intuition. Merton’s weakness is it leaps (too quickly) into (rigorous, mathematical) Continuous Time. To be clear, the discrete time explains optimization over a one-period framework, with one consumption good and a selection of risky investments, so at the end of the period there is only wealth maximization for consumption. In a continuous time model, at each moment consumption and investment are rebalancing, and wealth maximization (could, theoretically) continue to infinity.
New to this edition are extensive (hooray!) correction of the previous edition’s typos. To be fair, professor Back’s website always had a (regularly updated) errata sheet (www.kerryback.net/APErrata.pdf).
Also new to this edition are welcome extensions of both pricing and preferences under skewness and kurtosis (both of observed and expected return choice sets), Jensen’s alpha and performance evaluation, Campbell-Schiller linearization and log-linearization, outlier disasters (n=large moment outliers), long-run risks, jump processes (better than just hand-waving over Poisson distributions, I might add), the Lealand Captial Structure model, q theory, Filtering (i.e. “learning”), the Glosten-Milgrom model (I’d never heard of it), Glosten model of limit order markets, and auctions (see the Numberphile videos on YouTube for more fun on the maths of auctions).
But on the basics that it is imperative to be rock-ribbed and knowledgeable of, Back is excellent. For example, this is probably the best pedagogic layout of Ito's formula I have ever encountered, and this thoroughly covers Black Scholes, and asset pricing through Heleyete Geman's final extension.
Back's work benefits from all previous work in computational and continuous time finance in that more (not all) of the mathematical notation is standardized.
However, some of his choices for superscripts and subscripts strike you as odd, particularly if you've come from an MSF that emphasizes, say, John Hull's notation (most), or an MSFE (Carnegie Mellon) that emphasizes Merton's notation. Those coming to a PhD in Finance from Engineering or pure or applied Math will face a new, but slope familiar curve with comprehending the notation.
So the admonition in Financial Mathematics that you really have to pay attention to the author's sometimes idiosyncratic choices for mathematical notation remains, but Kerry Back has (to his credit) extensively used that which is agreed upon or in general consensus in this volume, so it is in fact easier to read (n relationship to other books) than say, Merton or Oksendal.
And so here a word on difficulty. This is not Oksendal. This is not Shreve and Karatzas. Those would be more appropriate for a PhD in Financial Mathematics, not a PhD in Finance.
So in short, this is a great, clear, readable, and understandable Finance PhD level treatment of asset pricing that is a good choice for a variety of courses on discrete and continuous time asset pricing and financial economics. Some may argue it is too light for a Financial Mathematics PhD, but a solid basic or supplemental text, but this edition strengthens from the first and it fast becoming the go-to text in the field.
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