Saturday, May 23, 2015

No Hesitations is Not a Phishing Site!

Google's "automatic system" a few days ago "determined" that No Hesitations ( was a phishing site. (Phishing sites attempt to scam users into revealing credit card numbers, etc. No Hesitations is not a phishing site! Indeed it's obviously impossible, as readers are never asked for any information of any kind.) So Google shut it down, with only a terse and uninformative machine-generated "no-reply" email to me. Literally, No Hesitations just vanished! I then found a way to request a human review, which Google did. They immediately agreed that they were mistaken, and they restored the site. HOWEVER, they neglected to remove No Hesitations from Google's "Safe Browsing" blacklist, so that a warning may appear when you attempt to access the site, depending on your browser and its settings. Obviously I have notified Google of this remaining problem, which they'll hopefully fix soon (although it's not obvious, as all the automated Google stuff is very much a black box). Meanwhile, if you get the bogus warning, just click on "details" and then "visit this infected site," and you'll be in. (Regarding "this infected site," thanks a lot, Google. Totally insulting, and surely harmful to the site's traffic. Isn't your motto "Don't be evil"?

Wednesday, May 20, 2015

Bond Yields, Macro Fundamentals, and Policy

Greetings my friends from Eurovision in Vienna. Yes, OK, that's not exactly the real reason I'm here, but still...

As I said in an earlier post that stressed DNS/AFNS yield-curve modeling with the zero lower bound imposed, "although Nelson-Siegel is almost thirty years old, and DNS/AFNS is almost a teenager, interesting and useful new variations keep coming." Another intriguing DNS/AFNS literature strand concerns the interaction of bond yields and macro fundamentals. That's hardly a new area, but recent work has some interesting twists.

Mesters, Schwaab and Koopman (2015) (MSK) focus on the effects of central bank policy on bond yields. There's lots of interesting new tech (stochastic volatility in measurement errors, interactions with non-Gaussian variables, a novel importance sampler for likelihood evaluation, ...). But most interestingly, MSK explore not only conventional policy tools like the overnight lending rate, but also direct measures of bond purchases.

MSK build on Diebold, Rudebusch and Aruoba (2006) (DRA), but the DRA emphasis is different. DRA were interested in whether and how the yield curve is linked to "standard" macro fundamentals. So DRA emphasized inflation, with an eye toward the yield curve level, and real activity, with an eye toward the yield curve slope. DRA also included an overnight lending rate, but certainly no measures of bond purchases.

Lots of interesting MSK-style work remains to be done. For example, someone needs to do an MSK-style analysis in a shadow-rate model that respects the zero lower bound and imposes no-arb. Also, someone needs to explore both causal directions more thoroughly. (Of course central bank bond purchases might influence the yield curve, but so too does the yield curve influence central bank bond purchases.)

Thursday, May 14, 2015

Interesting New Work on Yield Curve Modeling

Loved last week's PIER lectures at Penn. Good people, good times, good spring weather.  (Please join us next year in May 2016! More information in due course.) On Thursday we did yield curves, which had me thinking about what's new that I like in that area. Not surprisingly, I'm a fan of dynamic Nelson-Siegel (DNS), arbitrage-Free Nelson-Siegel (AFNS), and the many variations.  (See the Diebold-Rudebusch 2013 book.) What's more surprising is that although Nelson-Siegel is almost thirty years old, and DNS/AFNS is almost a teenager, interesting and useful new variations keep coming along.

The most important new work concerns imposition of the zero lower bound (ZLB). Fischer Black's "shadow rate" approach has influenced me most. Recently it's been taken to new heights by Glenn Rudebusch and coauthors at the Federal Reserve Bank of San Francisco (e.g., Christensen and Rudebusch 2015 -- just published in Journal of Financial Econometrics), and Leo Krippner at the Reserve Bank of New Zealand (see his wonderful 2015 book). The amazing thing is that one can stay in the DNS/AFNS framework -- the key tractable subclass of Gaussian affine models -- and still respect the ZLB by appropriately truncating simple simulations. The figure below, assembled from some of Krippner's, says it all. Also see these slides.   

I'm also partial to shadow-rate ZLB work by Cynthia Wu and coauthors at Chicago and San Diego (e.g. Wu and Xia, 2014). (Thanks to Jim Hamilton, her Ph.D. advisor, for reminding me!) See the monthly Wu-Xia shadow short rate series, produced and published to the web by FRB Atlanta.

Last and not at all least is the recent "ARG0" work of Monfort et al., which imposes the ZLB in a very different and elegant way. Again see these slides.   

Another interesting strand of recent DNS/AFNS progress concerns modeling the interaction of bond yield factors, macro fundamentals, and central bank policy.  More on that sometime soon.

Sunday, May 10, 2015

JPMorgan, Data-Rich Analyses, and the Public Good

I recently received an invitation to the JPMorgan Chase event below.

Reaction 1: JPMC should stick to its business, which is business, working to maximize the shareholder wealth with which it is entrusted, leaving to others (like me) the "provision of data-rich analyses and expert insights for promotion of the public good."

Reaction 2: JPMC is sticking to business, maximizing shareholder wealth, but not in appropriate ways.  Seriously, is it just me, or does this absolutely reek of Wall Street financiers working to capture Pennsylvania Avenue regulators? (I love that the event is actually on Pennsylvania Avenue.) By the way, I was wondering what Tony Blair knows about "provision of data-rich analyses." I still have no idea, but a quick Googling of "Tony Blair JPMorgan Chase" reveals that he's now very prominently on the JPMC payroll.

The silver lining:  After this blog, I doubt I'll ever again be invited.

Jamie Dimon
Chairman and CEO of JPMorgan Chase & Co.


Diana Farrell
Founding President and CEO of the JPMorgan Chase Institute 

Invite you to the launch of the JPMorgan Chase Institute –
a global think tank dedicated to delivering data-rich analyses and expert insights for the public good.

A preview of the JPMorgan Chase Institute's consumer data asset and groundbreaking first research report on individual income and consumption volatility
Jamie Dimon, Chairman and CEO of JPMorgan Chase & Co.
Diana Farrell, Founding President and CEO of the JPMorgan Chase Institute
Tony Blair, Quartet Representative and Former Prime Minister of Great Britain and Northern Ireland
David Wessel, Senior Fellow at the Brookings Institution, Former Economics Editor at The Wall Street Journal
Zoƫ Baird, CEO and President of the Markle Foundation
Heather Boushey, Executive Director of Washington Center for Equitable Growth
Robert Groves, Provost of Georgetown University, Former Director of US Census Bureau
The Newseum
Knight Conference Center
555 Pennsylvania Ave NW
Washington, DC 20001

This invitation is non-transferrable.
JPMorgan Chase seeks to comply with applicable rules concerning meals, gifts and entertainment offered to public officials and employees, including related disclosure requirements. We estimate the cost of hospitality to be provided at JPMorgan Chase & Co. Institute Launch to be $27.00 per person. To the extent you wish to pay the cost of , or to decline, the hospitality to be provided at this event please contact Kathryn Kulp at to make the necessary arrangements.
©JPMorgan Chase & Co. All Rights Reserved. JPMorgan Chase Bank, N.A. Member FDIC. All services are subject to applicable laws and regulations and service terms. Not all products and services are available in all geographic areas. Eligibility for particular products and services is subject to final determination by J.P. Morgan and/or its affiliates/subsidiaries.
Please note that you may not be able to complete this registration on your mobile device or tablet. For best results, please use a laptop or desktop computer.

Monday, May 4, 2015

Measuring Predictability

A friend writes the following.  (I have edited very slightly for clarity.)
Based on forecasts you've seen, what would you say is a "reasonable" ratio of the standard deviation of the forecast error to the standard deviation of a covariance-stationary series being forecast? ... It would be great if you can tell me "I'd consider x reasonable and y too high." 
The problem is that the premise underlying the question (namely, that there is such a "reasonable" value of the ratio \(r\) of innovation variance to unconditional  variance) is false.  That is, there's no small value \(c\) of \(r\) such that \(r<c\) means that we've done a good forecasting job.  Equivalently, there's no large value \(c'\) of the predictive \( R^2~ (R^2 = 1 - r^2) \) such that \(R^2 > c'\) means that we've done a good forecasting job.  Instead, "good" \(c\) or \(c'\) values depend critically on the dynamic nature of the series being forecast.  Consider, for example, a covariance-stationary AR(1) process, \(y_t = \phi y_{t-1} + \varepsilon_t\), where \(\varepsilon_t \sim iid (0, \sigma^2)\). The innovation variance is \(\sigma^2\) and the unconditional variance is \(\sigma^2 / (1 - \phi^2)\), so the lower bound on  \(r\) (and hence the upper bound on  \(R^2\)) depends entirely on \(\phi\) and can be anywhere in the unit interval! This is an important lesson: "predictability" can (and does) differ greatly across economic series. For more than you ever wanted to know, see Diebold and Kilian (2001), "Measuring Predictability: Theory and Macroeconomic Applications".

Wednesday, April 29, 2015

Volatility Institute 2015

I'm baaaaaack...

Speaking of being back, I'm just back from the Rob Engle / NYU Volatility Institute Annual Conference.  (Well, more or less just back.) Great people, great science, tightly-focused on a fascinating and timely area, the bond market and yield-curve modeling.  Program and links to papers here.  I think they'll post slides soon as well.  Mine are here.  Shortly I'll blog separately on what I see as the two key econometric approaches to arbitrage-free yield-curve modeling in zero-lower-bound environments:  The ARG0 approach of Monfort et al. (the new paper I discussed) and the shadow-rate approach of Krippner et al. (going way back to Fischer Black.)

Monday, April 6, 2015

Monday, March 23, 2015

Run Over by a Bus

Thanks for your concerned emails.  No, I have not been run over by a bus, just crazy busy with no time for new posts in the past few weeks.  We'll see how the next few go.  Meanwhile, here's the latest tennis graphic.  It's now dynamic; when it stops playing, just click on it to blow it up and re-play.

This graphic is for yesterday's Indian Wells Championship.  To really feel the drama, you'll want the slower animation.  I'll post on my web page one of these days.  In the future we'll shade tiebreakers, such as the second-set tiebreaker in the Djokovic-Federer match above. What else should we do?

Monday, February 23, 2015

Tennis Graphic Version 2

The tennis graphic is coming along; here's version 2 static. Thanks for the earlier comments on version 1 (more emailed than posted, you technophobes). Same Federer-Monfils example below. We now simply show points-from-set, set-by-set. (Sorry I had to shrink it to fit the blog format; you can blow it up using Ctrl+ in your browser.) I am exceptionally grateful to our talented "tennis team," especially Bas Bergmans, Modibo Camara, Joonyup Park, and Ken Teoh.

(Compare Version 1, here, which instead tracked points-from-match, set-by-set, with shading to convey intra-set developments.)