Preface
As many countries struggle to recover from the recent global financial crisis, one thing clear is that we do not want to suffer another crisis like this in the future. We must study the past in order to prevent future financial crisis. Financial data of the past few years thus become important in empirical study. The primary objective of the revision is to update the data used and to reanalyze the examples so that one can better understand the properties of asset returns. At the same time, we also witness many new developments in financial econometrics and financial software packages. In particular, the Rmetrics now has many packages for analyzing financial time series. The second goal of the revision is to include R commands and demonstrations, making it possible and easier for readers to reproduce the results shown in the book.
Collapses of big financial institutions during the crisis show that extreme events occur in clusters; they are not independent. To deal with dependence in extremes, I include the extremal index in Chapter 7 and discuss its impact on value at risk. I also rewrite Chapter 7 to make it easier to understand and more complete. It now contains the expected shortfall, or conditional value at risk, for measuring finanical risk.
Substantial efforts are made to draw a balance between the length and coverage of the book. I do not include credit risk or operational risk in this revision for three reasons. First, effective methods for assessing credit risk ...
