Perspective on Risk - Oct. 20, 2024

Send me my Nobel Prize; Ex-Post Review of 2023 Liquidity Risk; Nerdy Phillips Curve Stuff; Financial Conditions Index; 2024 IgNoble Prize; More

A 2024 Nobel Lauriat Weighs In (On The Big Picture)

Daron Acemoglu, who was awarded the 2024 Nobel prize in economics, writes America Is Sleepwalking Into an Economic Storm (NYT). He literally starts with the same three factor methodology I have used¹ for the last two years, with a focus on the US:

Barreling toward us are three epochal changes poised to reshape the U.S. economy in coming years: an aging population, the rise of artificial intelligence and the rewiring of the global economy.

Together, if handled correctly, these challenges could remake work and deliver much higher productivity, wages and opportunities — something the computer revolution promised and never fulfilled. If we mismanage the moment, they could make good, well-paying jobs scarcer and the economy less dynamic.

Demographics

The U.S. work force has never aged like this. … Because these changes are driven mostly by a decline in fertility, the U.S. work force will also soon begin to grow more slowly. If immigration into the United States is reduced, as seems likely no matter who wins the election, this will only contribute to the aging problem.

Over the past three decades, Japan, Germany and South Korea have aged almost twice as rapidly as the United States is aging right now, which means we have models to follow. The good news is their economies have not grown more slowly than those of other industrialized nations, and several of their labor-dependent sectors, including cars, machine tools and chemicals, haven’t suffered.

Technology

The reason is simple: They introduced new machinery, including industrial robots and other automation technologies, to take over the tasks younger employees would have performed. … Scarcity of labor can drive wages up, especially if combined with the right investments in both equipment and people.

Alas, this isn’t what is happening in the United States. Investment in robots has increased rapidly, but it hasn’t been accompanied by adequate investments in people. The work force remains unready for taking on new tasks, including technical and advanced precision work.

There are similar opportunities, also likely to be wasted, when it comes to artificial intelligence. … Yet when you strip away the hype surrounding super-intelligent algorithms, the A.I. challenge is remarkably similar to that of adapting to aging. … Yet, even more than with aging, it looks like we’re going to mismanage this wave.

Globalization

Globalization may appear like a different kettle of fish, but there are major parallels. The era of rapid and largely unfettered globalization that followed the collapse of the Soviet Union is over.

What will replace globalization is less clear. It could be a fragmented system, in which countries trade with allies and friends, with broadly similar flows to what we are seeing today (say, less of China and more of Vietnam). It could be one with high tariffs and much less trade. It could also be a combination of trade restrictions and industrial policies …

The good news here is that we have time, and if we grab the opportunities presented by aging, A.I. and the new globalization, they can all serve to improve one another. … The bad news is that these issues are not getting the attention they deserve, even though they are much more important for our future than debates about price gouging, taxes on tips or whether inflation is one point higher or one point lower. Unless we focus on them and act decisively, they will not just be mismanaged but also may spell a more dire future of work.

Ex-Post Review of 2023 Liquidity Risk

The BIS has issued The 2023 banking turmoil and liquidity risk: a progress report (BIS). Thought I’d share a few of the highlights I saw:

Did the Liquidity Coverage Ratio (LCR), Net Stable Funding Ratio (NSFR) and liquidity supervisory review processes provides the relevant information, in a timely manner

[The] experience with CS at an entity level raises doubts about the operationalisation of the high-quality liquid assets (HQLA) buffer needed to meet LCR requirements.

In the case of CS, during a severe stress event, a large part of its Pillar 1 LCR requirement was needed to cover daily operational/intraday liquidity needs – which are not covered by the LCR – instead of potential outflows over the envisaged 30-day horizon, which raises questions about the design of the LCR, including the scope of risks captured.

Supervisory and market scrutiny were considered by CS as an impediment to the use of its LCR buffer. CS was of the view that “breaches” of Pillar 1 or Pillar 2 liquidity requirements needed to be communicated to comply with ad hoc disclosure requirements, which in turn may have affected its willingness to draw down the LCR buffer in a manner as envisaged in the LCR standard.

[The] NSFR for CS increased from 126% in the third quarter of 2021 to 136% a year later … CS never reported an NSFR below 100% during this period. As the NSFR was designed as a structural measure, the “available stable funding” factors of deposits were calibrated at levels that do not correspond with the outflow rates faced by CS.

Aside from risks covered by the LCR, additional liquidity needs materialised in the case of CS during the March 2023 turmoil. A large portion of the liquidity buffer was used to meet these additional needs and accordingly was not available to cover the outflows assumed in the LCR.

• Increased prepositioning requirements were imposed by payment agents (mainly banks), central counterparties and clearing institutions to facilitate settlements.

• Some counterparties also increased collateral quality requirements. In addition, regulatory and supervisory HQLA requirements and expectations in other jurisdictions as well as CS’s own liquidity management requirements at the entity level to ensure payment needs all added to the level of liquid assets that had to be held at the entity level.

• The increase of intraday requirements was another significant driver of CS’ liquidity needs. During the stress period, incoming payments were delayed due to changes in the payment behaviour of counterparties. CS, however, wanted to maintain normal outgoing payments to avoid negative signalling to counterparties. The total increased liquidity needs which arose from these risk factors is estimated to account for almost 100% of the LCR net outflows for the operating parent bank, CS AG, during March 2023

The experience of the US banks during the March 2023 turmoil highlighted, however, that private repo markets may become a less reliable option for monetising securities held at [amortized cost] for distressed banks during idiosyncratic liquidity stress scenarios

Secured funding raised using liquidity buffer assets, could have a significantly higher funding rate (cost) than the prevailing rates on HQLA securities purchased in prior years. This “negative carry” is transparent to market participants through public financial disclosures, which could trigger additional liquidity stress. In the case of First Republic Bank (FRC), it undermined confidence in the ability of the bank to restructure its balance sheet and precipitated additional outflows.

During the March 2023 stress, the lack of preparedness and operational capacity at some banks to quickly finance their securities via established access to secured financing channels or other types of contingent sources, such as central bank liquidity, impacted their ability to meet outflows

Nerdy Phillips Curve Stuff

I’m not an economist; I just played one at the Fed (and AIG).

Beveridge Curve Normalizes

The Beveridge Curve, which relates job openings to unemployment, seems to have normalized.

Phillips meets Beveridge

Phillips meets Beveridge (SF Fed)

Interesting paper. I can see a lot of DSGE models getting modified after this.

The Phillips curve plays a central role in the macroeconomics literature. However, there is little consensus on the forcing variable that drives inflation in the model, i.e., on the appropriate measure of “slack” in the economy. In this work, we systematically assess the ability of variables commonly used in the literature to (i) predict and (ii) explain inflation fluctuations over time and across U.S. metropolitan areas. In particular, we exploit a newly constructed panel dataset with job openings and vacancy filling cost proxies covering 1982–2022.

We find that the vacancy-unemployment (V/U) ratio and vacancy filling cost proxies outperform other slack measures, in particular the unemployment rate. Beveridge curve shifts—notably, movements in matching efficiency—are responsible for the superior performance of the V/U ratio over unemployment.

Smashing The Phillips Curve

How AI & Robots are Smashing Economics, and Why It Matters (Kedrosky)

The rise of artificial intelligence (AI) and robotics isn't just transforming industries and job markets—it is reshaping economic theory and policy. As machines increasingly replace human labor across sectors, from manufacturing to white-collar professions, they're dismantling long-held assumptions.

… AI and automation are flattening the Phillips curve …

We live in a machine age, where robots and AI, riding declining cost curves, and immune to wage negotiations and labor market pressures, are becoming the dominant workforce.

Financial Conditions Index

More nerdy central banker/bank supervisor stuff. The Global Financial Crisis of 2006/7 spurred the development of numerous Financial Conditions Indexes (FCIs). I read all three of these recent papers and thought that I would summarize them for you:

Targeted financial conditions indices and growth-at-risk (Bank of England)

• The Bank’s paper purports to develop a new and better index.

Assessing and Combining Financial Conditions Indexes∗

• The second paper finds that reliable predictability is generally only present when the sample includes the 2008 financial crisis. The authors suggest that some predictive power may be due to data mining and non-synchronous trading effects, and conclude that FCIs are better used as indicators of current financial conditions rather than as predictive tools.

Why your financial conditions index sucks (FT)

• The FT article suggests that FCIs are often not as informative as claimed and are frequently used to justify policy decisions or explain why economic predictions didn't come true. The author concludes that FCIs are essentially a sophisticated way of repackaging information already available in stock prices and bond spreads.

This last is part of the reason I like to use the Federal Reserve’s Senior Loan Officer Opinion Survey (SLOOS). It is less influenced by stock and bond prices, though it is arguably a function of credit spreads and balance sheet capacity.

More TD Bank

TD’s 2013 Consent Order with Fincen

OCC’s 2013 Consent Order For A Civil Money Penalty

1. Between April 2008 and September 2009, customer account activity repeatedly triggered alerts in the Bank’s anti-money laundering monitoring system. The Bank incorrectly determined that the activity giving rise to the alerts was not suspicious activity that would warrant the timely filing of SARs.

2. By reason of the foregoing failures to file SARs on a timely basis, as described in Paragraph (1) of this Article, the Bank violated 12 C.F.R. § 21.11(c) and (d) with respect to each of the alerts.

3. The Bank’s violations of 12 C.F.R. § 21.11 are part of a pattern of misconduct and caused more than a minimal loss to the Bank.

2024 IgNoble Prize

Coin flips are not fair. This paper was one of the winners of the 2024 Ig Noble Awards, but it has a legit finding.

Fair coins tend to land on the same side they started: Evidence from 350,757 flips

Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process.

In a preregistered study we collected 350,757 coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51%.

Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, Pr(same side)=0.508, 95% credible interval (CI) [0.506, 0.509], BFsame-side bias=2359. Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: Pr(heads)=0.500, 95% CI [0.498, 0.502], BFheads-tails bias=0.182. Furthermore, this lack of heads-tails bias does not appear to vary across coins.

Additional exploratory analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for the DHM physics model of coin tossing.

Click here to read about the other winners, including research that some animals can breathe through their anus (I’ve been accused of speaking out of that orifice).

More

Format for Incident Reporting Exchange (FIRE): Consultation report (FSB)

This consultation report sets out a common format that financial firms can use for the reporting of operational incidents, including cyber incidents.

OCC Solicits Research on Artificial Intelligence in Banking and Finance

The Office of the Comptroller of the Currency (OCC) is soliciting academic research papers on the use of artificial intelligence in banking and finance for submission by December 15, 2024.

Journal of Financial Crises: Volume 6, Issue 3 (2024)

• 23 case studies, 1 survey, 2 policy notes, and 2 "Lessons Learned" interviews with past crisis fighters

1. I’ve been talking about these three factors since this Substack began in 2020. We went deeper into deglobalization when commenting on the work of Zoltan Poszar. I first published the Venn diagram in Perspective on Risk - Sept. 16, 2022 (Demographics)