Monday, March 26, 2018

Classic Jacod (1994) Paper

J. Financial Econometrics will soon publish Jean Jacod's brilliant and beautiful 1994 paper, "Limit of Random Measures Associated with the Increments of a Brownian Semimartingale", which I just had the pleasure of reading for the first time. (Ungated version here.) Along with several others, I was asked to supply some comments for the issue's introduction. What follows is adapted from those comments, providing some historical background. (Except that it's not really historical background -- keep reading...)

Jacod's paper effectively lays the foundation for the vast subsequent econometric "realized volatility" (empirical quadratic variation) literature of the past twenty years.  Reading it leads me to recall my early realized volatility work with Torben Andersen and Tim Bollerslev in the late 1990's and early 2000's. It started in the mid-1990's at a meeting of the NBER Asset Pricing Program, where I was the discussant for a paper of theirs, eventually published as Andersen and Bollerslev (1998). They were using realized volatility as the "realization" in a study of GARCH volatility forecast accuracy, and my discussion was along the lines of, "That's interesting, but I think you've struck gold without realizing it -- why not skip the GARCH and instead simply characterize, model, and forecast realized volatility directly?".

So we decided to explore realized volatility directly. Things really took off with Andersen et al. (2001) and Andersen et al. (2003). The research program was primarily empirical, but of course we also wanted to advance the theoretical foundations. We knew some relevant stochastic integration theory, and we made progress culminating in Theorem 2 of Andersen et al. (2003). Around the same time, Ole Bardorff-Nielsen and Neil Shephard were also producing penetrating and closely-related results (most notably Barndorff-Nielsen and Shephard, 2002). Very exciting early times.

Now let's return to Jacod's 1994 paper, and consider it against the above historical background of early econometric realized volatility papers. Doing so reveals not only its elegance and generality, but also its prescience: It was written well before the "historical background"!! One wonders how it went unknown and unpublished for so long.


Andersen, T. G. and T. Bollerslev (1998), "Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts," International Economic Review, 39, 885-905.

Andersen, T.G., T. Bollerslev, F.X. Diebold, and P. Labys (2001), "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, 96, 42-55.

Andersen, T.G., T. Bollerslev, F.X. Diebold, and P. Labys (2003), "Modeling and Forecasting Realized Volatility," Econometrica, 71, 579-625.

Barndorff-Nielsen, O. and N. Shephard (2002), "Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models," Journal of the Royal Statistical Society, 64,

Jacod, J. (1994), "Limit of Random Measures Associated with the Increments of a Brownian Semimartingale," Manuscript, Institute de Mathematiques de Jussieu, Universite Pierre et Marie Curie, Paris.

Monday, March 19, 2018

Big Data and Economic Nowcasting

Check out this informative paper from the Federal Reserve Bank of New York: "Macroeconomic Nowcasting and Forecasting with Big Data", by Brandyn Bok, Daniele Caratelli, Domenico Giannone, Argia Sbordone, and Andrea Tambalotti.

Key methods for confronting big data include (1) imposition of restrictions (for example, (a) zero restrictions correspond to "sparsity", (b) reduced-rank restrictions correspond to factor structure, etc.), and (2) shrinkage (whether by formal Bayesian approaches or otherwise).

Bok et al. provide historical perspective on use of (1)(b) for macroeconomic nowcasting; that is, for real-time analysis and interpretation of hundreds of business-cycle indicators using dynamic factor models. They also provide a useful description of FRBNY's implementation and use of such models in policy deliberations.

It is important to note that the Bok et al. approach nowcasts current-quarter GDP, which is different from nowcasting "the business cycle" (as done using dynamic factor models at FRB Philadelphia, for example), because GDP alone is not the business cycle. Hence the two approaches are complements, not substitutes, and both are useful.

Monday, March 12, 2018

Sims on Bayes

Here's a complementary and little-known set of slide decks from Chris Sims, deeply insightful as always. Together they address some tensions associated with Bayesian analysis and sketch some resolutions. The titles are nice, and revealing. The first is "Why Econometrics Should Always and Everywhere Be Bayesian". The second is "Limits to Probability Modeling" (with Chris' suggested possible sub-title: "Why are There no Real Bayesians?").

Thursday, March 8, 2018

H-Index for Journals

In an earlier rant, I suggested that journals move from tracking inane citation "impact factors" to citation "H indexes" or similar, just as routinely done when evaluating individual authors. It turns out that RePEc already does it, here. There are literally many thousands of journals ranked. I show the top 25 below. Interestingly, four "field" journals actually make the top 10, effectively making them "super (uber?) field journals" (J. Finance, J. Financial Economics, J. Monetary Economics, and J. Econometrics). For example, J. Econometrics is basically indistinguishable from Review of Economic Studies. 

The rankings

1American Economic Review, American Economic Association2623897539641395549
2Journal of Political Economy, University of Chicago Press2352275342978229129
3Econometrica, Econometric Society (also covers Econometrica, Econometric Society )2332660313530267883
4The Quarterly Journal of Economics, Oxford University Press2312116382311212892
5Journal of Finance, American Finance Association2102130764558215655
6Journal of Financial Economics, Elsevier1651380732654149337
7Journal of Monetary Economics, Elsevier (also covers Carnegie-Rochester Conference Series on Public Policy, Elsevier )1581237053334128056
8Review of Economic Studies, Oxford University Press1571143592317115072
9Journal of Econometrics, Elsevier1491318234160141376
10Journal of Economic Literature, American Economic Association1457291689173201
11Journal of Economic Perspectives, American Economic Association14577073167377758
12The Review of Economics and Statistics, MIT Press1401093303953109953
13Economic Journal, Royal Economic Society (also covers Economic Journal, Royal Economic Society )1371037633663104399
14Journal of International Economics, Elsevier12276446298381228
15Review of Financial Studies, Society for Financial Studies11966261165767063
16Journal of Public Economics, Elsevier11790038372295659
17Journal of Development Economics, Elsevier11365314311168204
18European Economic Review, Elsevier11174123387075847
19Journal of Economic Theory, Elsevier10883540423890223
20Journal of Business & Economic Statistics, Taylor & Francis Journals (also covers Journal of Business & Economic Statistics, American Statistical Association )10544499172644729
21Journal of Money, Credit and Banking, Blackwell Publishing (also covers Journal of Money, Credit and Banking, Blackwell Publishing )10451991295552610
22Management Science, INFORMS9570575689176945
23Journal of Banking & Finance, Elsevier9361760482972982
24International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association (also covers International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association )9148542253748823
25Journal of Labor Economics, University of Chicago Press9137921108438993