Mortgage Rate Intelligence & Market Updates

Stablecoins are digital assets whose value is pegged to that of a fiat currency, typically the U.S. dollar at a peg of $1.00 per token.  In a previous blog post, we described the rapid growth of stablecoins through early 2025, highlighted changes in stablecoins’ reserve-asset composition, and examined their reactions to Bitcoin price shocks. In this post, we document the growth of stablecoins since our last post. Then, we examine how shocks from outside the crypto industry can impact the composition of stablecoins’ reserve assets. For our case study, we use the 2023 failure of Silicon Valley Bank (SVB) and its impact on USD Coin (USDC, issued by Circle), the second-largest stablecoin by market capitalization.

This post concludes a three-part series on how bank regulation interacts with the organizational structure of banking firms. The first post documented the equity-rich nonbank subsidiaries inside bank holding companies (BHCs); the second post showed that BHCs met Basel III by reallocating capital internally, moving equity from nonbank affiliates to bank subsidiaries rather than raising new external capital. Here we ask what that reallocation meant for financial stability. The series draws on the authors’ recent Staff Report, “Regulatory Arbitrage Within the Firm.”

This post is the second in a three-part series on how bank regulation interacts with the organizational structure of banking firms. The first post documented that nonbank subsidiaries inside bank holding companies (BHCs) are large, equity-rich “reservoirs,” and that bank-level capital diverged sharply from consolidated capital after Basel III took effect in 2015. This post asks why, and traces the answer through the internal plumbing of the holding company. The series draws on the authors’ recent Staff Report, “Regulatory Arbitrage Within the Firm.”

This post is the first in a three-part series on how bank regulation interacts with the organizational structure of banking firms. The series draws on the authors’ recent Staff Report, “Regulatory Arbitrage Within the Firm.”

How has the recent implementation of tariffs affected small businesses? Due to lack of data, little is known about this issue. In this Liberty Street Economics post, we use data from the 2025 edition of the Small Business Credit Survey (SBCS) to explore this question for businesses nationally and in the Second District (defined, for the purpose of this study, as New York, New Jersey, and Connecticut). We find that the majority of national firms in the goods and retail sectors reported experiencing financial challenges due to tariffs in 2025, with even larger shares of regional firms doing so. In response, about 80 percent of national and regional firms passed on at least some of the higher costs of imported inputs to customers, while about 60 percent absorbed some of the costs, as many firms did some of both. Firms that faced greater tariff challenges in 2025 were more pessimistic about employment and revenues in 2026.

The past year brought dramatic changes to U.S. trade policy, including sweeping new tariffs, as well as a Supreme Court decision that further reshaped the tariff landscape. Many businesses saw their costs increase significantly and faced complex decisions about whether to absorb the tariffs through lower profit margins, raise their prices to recover the higher costs, or some combination of the two. Last year, we found that most businesses had passed on at least some of these higher costs to their customers through higher prices. Now, over a year later, have businesses finished adjusting prices, or do further tariff-induced price increases lie ahead? Our latest regional business surveys reveal that nearly half of firms that have paid tariffs still plan additional price increases to offset these costs, with some expecting to raise prices six months or more in the future.

Runs on financial institutions are one of the salient markers of financial crises. But the role of runs in crises is a topic of longstanding debate. Runs can be seen as the key turning point, whereby even small shocks can generate severe crises with widespread bank failures. Another view is that runs are mainly a symptom of deeper rot in the financial system, exacerbating crises rather than being their primary cause. Understanding this debate has first order implications for how to think about financial crises and the appropriate policy responses. In this post, we use a new database of more than 3,000 bank runs (introduced in our companion post) to show that poor fundamentals are central to explaining both when runs occur and when they have severe economic effects. We argue that this evidence tempers the view that small shocks can have outsized real effects through self-fulfilling run dynamics.

Banking crises are commonly associated with bank runs and banking panics, yet our empirical understanding of bank runs is constrained by a lack of bank-level data. In a new paper, we use large language models (LLMs) to extract information on bank runs from millions of digitized historical newspaper pages, creating the most comprehensive database of bank runs in U.S. history. Every bank run episode that we identify is documented on a companion website where users can browse and examine individual episodes, and read the original newspaper articles. In this post, we describe how we built this dataset and discuss what its basic features reveal.

In a 2021 Liberty Street Economics post, we documented the “overnight drift”—a large, persistent return to holding U.S. equity futures in the narrow window between 2:00 and 3:00 a.m. Eastern time, when European equity markets open. Five additional years of data later, that pattern appears to have faded: the 2:00–3:00 window that previously generated roughly 3.7 percent per annum has averaged close to zero since 2021. In this post, we revisit the overnight drift in light of the post-publication sample and use our inventory-risk framework to ask which of three observable channels—the dispersion of closing order imbalances, the level of return variance, or the risk-bearing capacity of liquidity providers—accounts for the change.