John C Williams: "Elementary, Dear Data"
Remarks by Mr John C Williams, President and Chief Executive Officer of the Federal
Reserve Bank of New York, at the 2023 US Treasury Market Conference, Federal
Reserve Bank of New York, New York City, 16 November 2023.
* * *
As prepared for delivery
Introduction
This is the ninth year that our joint member agencies have come together for this
conference. It's been a wonderful five-way partnership. But the honorific of "greatest
crossover of all time" must be awarded to the theme and corresponding title of my
remarks today.
For those who know of my proclivity to lace my speeches with music references, no, I
am not referring to the crossover of Taylor Swift and Travis Kelce. Instead, I'm referring
of course-to the epic 29th episode of Star Trek: The Next Generation , titled
"Elementary, Dear Data," in which 221B Baker Street meets Enterprise-D in a brilliant
Sherlock Holmes-style mystery. It's a perennial fan favorite for Trekkies and
Sherlockians alike. But the reason I mention it today is that I'd like to speak about how
data-transactions-based, transparent, and well documented-is elementary to our
collective understanding and decision-making at the Federal Reserve and beyond.
Before I get in any deeper, and rest assured I will, I need to give the standard Fed
disclaimer that the views I express today are mine alone and do not necessarily reflect
those of the Federal Open Market Committee (FOMC) or others in the Federal Reserve
System.
Data Dashboard
Sherlock Holmes stressed the importance of "data, data, data." I, too, have been often
1
quoted emphasizing the need to be "data dependent." In Sherlock's world, data means
fingerprints, footprints, handwriting, and ciphers. In our world, data means economic
indicators like gross domestic product, the Consumer Price Index, and the
unemployment rate. These numbers make up the dashboard of what's happening in the
economy.
These are numbers we can trust. Government agencies in the U.S. and abroad put an
enormous amount of effort into developing the methodology, implementation, and
design of these official statistics. While no specific data series is without its limitations,
we have an excellent understanding of how these numbers come together and behave
over time.
Financial markets have their own data dashboards too. Equity indexes, bond yields,
and the value of the dollar are just a few aspects of understanding what's going on in
markets.
And policymakers like me aren't the only ones who are data dependent. Businesses,
households, journalists, and so many others rely on data to support their understanding
of the world around them.
Capital Mistake
To be clear, having access to an abundance of data is a wonderful problem to have.
Think about the plethora of data you can pull from a terminal and the endless ways to
use it. Many of us have spent more hours than we'd like to admit analyzing, plotting,
and running regressions on data. And while we assume that most data are "good,"
there are, unfortunately, "bad" data, too. The very same terminal that gives you access
to numbers that are supported by millions of transactions could also give you access to
numbers that have not seen a transaction in quite some time, if ever. And it can be very
hard-too hard, in fact-to spot the difference.
This is dangerous. I will echo the warning of our detective friend Sherlock Holmes: "It is
a capital mistake to theorize before one has data." I'll go a step further and say that it is
a capital mistake to theorize before one fully understands the origins of the data one
has downloaded.
LIBOR No More (But Still Important)
Of course, the prime example of a capital mistake of this nature is LIBOR. Which, by
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the way, officially ended 139 days ago, not that I'm still counting. Good riddance! OK,
I had to slip in one music reference, but that's all.
The lesson of LIBOR is that there are times when what we think of as strong financial
market data is only a mirage. LIBOR was one of the most widely used benchmarks in
the world, underpinning hundreds of trillions of dollars - that's trillions, with a "T"-of
financial instruments and contracts. We all know how that ended: LIBOR was inherently
fragile and subject to manipulation. It is astonishing to think about the entire global
financial system relying on the small set of transactions underlying LIBOR. In fact,
during periods of financial market stress, LIBOR was based on no transactions, which is
what opened the door to the fraud and bad behavior we now associate with it.
LIBOR was a wake-up call. It led to the collective realization that things we think of as
data may be merely smoke and mirrors. That's why the Federal Reserve, the Financial
Stability Board, and many others invested heavily in the transition off of LIBOR and on
to robust reference rates-like the Secured Overnight Financing Rate (SOFR)-that are
accurate, carefully constructed, and transparent.
Good Data
As we move forward in the post-LIBOR era, it's important that we continue to prioritize
transparency and clarity in data, especially financial market data. This is particularly
true in the age of AI, when the sources of data are harder to trace.
So, in addition to SOFR, what do "good data" look like? How can we, as Captain Picard
would say, "Make it so"?
To start, I'd point to the Principles for Financial Benchmarks set forth by the
International Organization of Securities Commissions (IOSCO), which established a
very stringent and specific model for reference rates. As an administrator and producer
of reference rates, the New York Fed is committed to producing rates aligned with this
gold standard.4
5 6
Other examples include our regular market surveys. Questions for both the Survey
of Primary Dealers and the Survey of Market Participants are readily available on our
website, as are the respondents and aggregated responses. Our Survey of Consumer
7
Expectations follows a similarly demanding standard. If data are worth using, it's
absolutely worth the effort to make sure people know what they are getting.
We have also increased transparency with Trade Reporting and Compliance Engine
(TRACE) data. This initiative, which was started in 2017 to fill in the gaps on Treasury
transaction data, is a significant component of a broader interagency effort to enhance
understanding and transparency of the Treasury securities market. This has proven
valuable as it has allowed the official sector to closely track developments in the cash
Treasury market. Also currently underway are efforts to further increase the
transparency of this data to the public, including plans to share transaction data for
8 9
onthe-run nominal coupon securities. Can't Make Bricks Without Clay
Efforts like these are important because increased transparency and clarity around data
leads to better decision-making. "I can't make bricks without clay," Holmes said in The
Adventure of the Copper Beeches. He understood that he first needed to compile the
facts before building out the case. I argued a similar point in 2021 about LIBOR. If you
try to build on a foundation that is not absolutely sound, you are risking trouble at some
point in the future.10
Unfortunately, this issue is frequently underappreciated by users of financial market
data, as transparency and information on the sources of data are often scant.
I will use my favorite example of inflation options to illustrate the broader point. During
the recent bout of high inflation, some journalists, researchers, and analysts have
trumpeted the "market's estimate" of the probability of certain high inflation outcomes
using "data" on the prices of inflation options. These so-called "prices" are easily
downloaded from data platforms.
But here's the catch: based on our market contacts and public reporting of derivatives
transactions, these aren't data at all. There have been no trades reported in the U.S.
inflation options market since early 2021. The so-called data that people are citing are
generated by a model, not from investors putting real money on the line as is frequently
claimed. The situation is similar in Europe. Although there are scattered trades in euro
area and UK inflation options, market contacts tell us that liquidity in that market is
extraordinarily thin, and most of what little activity there is in this market is related to
complex financial products and the risk of deflation and not hedging higher inflation.
More broadly, there is an opportunity for central banks, governments, and the private
sector to come together to improve data transparency and accuracy. It takes a global
village-regulatory groups, industry groups, and global standard setters like IOSCO all
have a role to play. We must use forums and collaborations like these to think through
the opportunities to further develop data transparency and make improvements. One
benefit of this conference is the partnerships it has fostered. Participants have
accomplished so much by working together. And given our collective reliance on data,
this must continue to be a priority moving forward.
It's important to acknowledge that increasing transparency in some cases may face
challenges. But that is not a reason to hinder our work in this space. Past experiences
have proven that there are solutions that allow for greater transparency and confidence
in data, without distorting or undermining the markets themselves.
Closing
I hope that you took two things away from my remarks today. The first is that you've
been inspired to go home and dust off your Star Trek DVDs. The second is to heed my
call to action. We must continue to work together to increase data transparency and
understanding, so that we can have greater market confidence and make better
decisions.
It is elementary, my dear colleagues.
1
John C. Williams, Monetary Policy: A 'Data Dependent' Approach , remarks at the New
Jersey Bankers Association's Economic Leadership Forum, Somerset, New Jersey,
January 18, 2019.
2
Alternative Reference Rates Committee, AARC Statement on the Last 30 Days before
U.S. Dollar LIBOR Panels End , May 31, 2023.
3
John C. Williams, 901 Days , remarks at Securities Industry and Financial Markets
Association (SIFMA), New York City, July 15, 2019.
4
International Organization of Securities Commissions, Statement of Compliance with
the IOSCO Principles for Financial Benchmarks , July 28, 2023.
5
Federal Reserve Bank of New York, Survey of Primary Dealers .
6
Federal Reserve Bank of New York, Survey of Market Participants .
7
Federal Reserve Bank of New York, Center for Microeconomic Data, Survey of
Consumer Expectations .
8
Inter-Agency Working Group for Treasury Market Surveillance, Recent Disruptions
and Potential Reforms in the U.S. Treasury Market: A Staff Progress Report, November
8, 2021.
9
U.S. Department of the Treasury, Remarks by Under Secretary for Domestic Finance
Nellie Liang at the 2022 Treasury Market Conference, November 16, 2022.
John C. Williams, Measure Twice, Cut Once , remarks at SOFR Symposium: The
Final Year (Part II)-delivered via videoconference, May 11, 2021.