Monitoring Banks’ Publicity to Nonbanks: The Community of Interconnections Issues


The first submit on this collection mentioned the potential publicity of banks to the open-end funds sector, by advantage of commonalities in asset holdings that expose banks to steadiness sheet losses within the occasion of an asset fireplace sale by these funds. On this submit, we summarize the findings reported in a current paper of ours, during which we broaden the evaluation to think about a broad cross part of non-bank monetary establishment (NBFI) segments. We unveil an modern monitoring perception: the community of interconnections throughout NBFI segments and banks issues. For instance, sure nonbank establishments could not have a significant asset overlap with banks, however their fireplace gross sales may however signify a vulnerability for banks as a result of their property overlap carefully with different NBFIs that banks are considerably uncovered to.

Community Externalities in Hearth-Sale Shocks

We broaden the evaluation partially one in all this collection to think about concurrently twelve distinct nonbank establishment varieties. Increasing the cross part of NBFI varieties permits us to think about the complexity of interconnections within the monetary ecosystem, the place banks and nonbanks function in a number of markets. In flip, this consideration permits us to unveil the existence of vital community externalities within the transmission of fire-sale shocks.

For instance of community results, suppose we’re inquisitive about monitoring financial institution vulnerabilities with respect to a given NBFI sector S. Along with monitoring the similarity in asset holdings between banks and entities in S, it might even be vital to understand how central such entities may be—by way of asset holding interconnections—throughout the numerous community of all of the NBFI varieties. It’s because entities in S could carry a well-diversified portfolio of property, implying a big asset overlap with many different NBFI market segments. This broad asset overlap implies the next chance of experiencing misery if any of the opposite NBFI segments provoke fireplace gross sales, which in flip means the next chance that entities in S transmit shocks to banks. Furthermore, if central within the NBFI community, fireplace gross sales from entities in S may themselves impose misery on a broad set of different NBFIs. In sum, sector S might be a probably vital supply of financial institution vulnerabilities because of its centrality within the NBFI community, even when on a stand-alone foundation, their fireplace sale influence on banks have been restricted.

Evaluation of NBFI Networks

We accumulate data on the asset composition of NBFI segments utilizing the quarterly Monetary Accounts of the US (Z.1) issued by the Federal Reserve Board, generally referred to as the Move of Funds. As Move of Funds knowledge is reported solely as an combination for a given sector kind, we commerce off knowledge granularity with breadth of protection when inspecting the community. With combination knowledge, whereas we lose finer element, we acquire the flexibility to uncover (complicated) mechanisms of transmission and amplifications and generate modern monitoring insights. The desk under reveals the cross-holding matrix by establishment kind and asset from the 2021: This autumn Move of Funds.

Cross-Holding Matrix From the 2021:This autumn Move of Funds

Quantities in Billions of U.S. {Dollars} Fairness Company MBS Financial institution Mortgage Open Market Paper Corp Bond Gov’t Bond Muni Bond Money Whole
Banks 54 3,883 12,631 0 888 1,641 643 4,221 23,962
P&C insurers 643 136 28 4 702 188 289 142 2,133
Life insurers 133 231 808 23 3,266 175 222 141 4,998
Cash market funds 0 410 0 226 7 1,815 111 2,640 5,208
Mutual funds (fairness) 14,270 0 0 26 0 0 0 190 14,486
Mutual funds (bonds) 0 492 131 10 2,485 1,447 900 73 5,537
Mutual funds (hybrid) 1,264 49 13 3 250 145 90 24 1,840
Trade-traded funds 5,804 0 0 0 800 331 83 39 7,057
Mortgage REITs 0 168 0 0 12 0 0 17 197
Dealer-dealers 234 54 0 16 15 99 13 1,396 1,827
Finance firms 0 0 1,026 0 99 0 0 57 1,182
Hedge funds 1,140 8 181 0 474 165 15 227 2,210
Pension funds 4,932 321 23 44 1,312 695 0 666 7,993
Whole 28,475 5,753 14,840 354 10,308 6,701 2,367 9,832
Supply: Monetary Accounts of the US.
Be aware: Knowledge adjusted to interrupt Mutual Funds down into three subtypes.

The information reveals appreciable variation by way of relative dimension and portfolio of asset holdings within the cross part of establishment varieties, suggesting heterogeneity by way of each first-round fire-sale results, but in addition hard-to-guess, second-round losses following on from the first-round losses.

We apply the identical methodology used within the companion submit, and in earlier Liberty Avenue Economics posts right here and right here, based mostly on work by Greenwood, Landier, and Thesmar (2015). The desk under reveals the influence on banks from hypothetical first-round and second-round fireplace gross sales following from assumed losses for every establishment kind. The third via fifth columns show the first-round results expressed as, respectively, the greenback loss on the combination steadiness sheet of banks, the loss as a proportion of banks’ combination fairness capital, and the rank order of every NBFI establishment kind by way of banks’ losses. Finance firms and life insurance coverage firms create essentially the most first-round financial institution losses, adopted by mutual funds (bonds), hedge funds, and pension funds. As in Greenwood, Landier, and Thesmar (2015), an establishment’s significance to banks (their “systemicness”) depends upon a number of components: dimension (what number of {dollars} of property it sells), interconnectedness (whether or not it holds asset courses that banks additionally maintain), and the liquidity of holdings (for a given sale quantity, extra illiquid property may have a larger worth influence, leading to larger losses for holders of these property).

First and Second Spherical Losses for Banks

First-Spherical Loss Second-Spherical Loss
Establishment Sort Measurement (Billions of U.S. {Dollars}) Billions of U.S. {Dollars} Financial institution Capital (%) Rank Billions of U.S. {Dollars} Financial institution Capital (%) Rank Second-Spherical Share (%)
Banks 23,962
P&C insurers 2,133 -2.2 -0.12 7 -18.6 -0.97 7 89
Life insurers 4,998 -21.3 -1.11 2 -45.9 -2.39 4 68
Cash market funds 5,208 -2.6 -0.14 6 -2.9 -0.15 10 53
Mutual funds (fairness) 14,486 -1.2 -0.06 9 -60.3 -3.15 2 98
Mutual funds (bonds) 5,537 -8.9 -0.46 3 -68.6 -3.58 1 89
Mutual funds (hybrid) 1,840 -1 -0.05 10 -12.3 -0.64 8 93
Trade-traded funds 7,057 -1.7 -0.09 8 -43.4 -2.27 5 96
Mortgage REITs 197 -0.3 -0.02 11 -0.4 -0.02 12 57
Dealer-dealers 1,827 -0.2 -0.01 12 -1.5 -0.08 11 86
Finance firms 1,182 -22.3 -1.16 1 -10.3 -0.54 9 32
Hedge funds 2,210 -4.6 -0.24 4 -23.6 -1.23 6 84
Pension funds 7,993 -3.3 -0.17 5 -52.8 -2.75 3 94
Sources: Authors’ calculations on knowledge from Monetary Accounts of the Unites States and the Funding Firm Institute.

For the primary spherical of fire-sale losses, what issues is whether or not an establishment holds asset courses that banks additionally maintain. If we embody different establishments’ reactions, it additionally issues whether or not an establishment holds asset courses held by establishments that maintain asset courses that banks additionally maintain. To look at these derived results, we simulate a second spherical of fireplace gross sales inside our framework, the place we now take into account the losses incurred by each establishment kind to every of the first-round fireplace gross sales, and the ensuing second-round fireplace gross sales. The second half of the above desk reveals the influence on banks from the aggregation of second-round fireplace gross sales. Mutual Funds (Bonds) are the very best ranked as vectors of shock amplification. Inside our framework, company bonds are essentially the most broadly held asset class and thus a firesale concentrated in bonds has a big second-round impact. The second to fourth rank are actually taken by mutual funds (fairness), pension funds, and as soon as once more life insurance coverage firms. Along with their dimension and the character of their holdings, life insurers’ diversification ends in excessive connectedness. Equally, due to an absence of connectedness, finance firms’ rank drops from first to ninth. Whereas their mortgage gross sales can damage banks instantly, because of their portfolio focus they’re much less prone to damage others, and thus the extra induced fireplace gross sales are comparatively much less extreme.

Lastly, the final column of the desk above reveals the “community multiplier,” outlined because the ratio of the second-round loss over the entire (first- plus second-round) loss. The ratio by building ranges between 0 and 100%. The pretty massive estimates within the cross part thus counsel that if we solely deal with the direct fire-sale impact of a given NBFI phase onto banks, we’re lacking an vital and probably dominant element of the entire impact.

Closing Phrases

We’ve got documented the potential vulnerabilities of banking establishments to fireside gross sales initiated within the NBFI sector when contemplating each direct spillovers (fireplace gross sales of property which are additionally held by banks) and oblique, “second-round” spillovers (fireplace gross sales that induce additional fireplace gross sales by different NBFIs that in flip damage banks). Our evaluation sheds gentle on the intricate community of spillover exposures within the U.S. monetary system and identifies a rank ordering of monitoring priorities throughout NBFI segments. Our framework thus helps the creation of novel monitoring instruments.

Photo: portrait of Nicola Cetorelli

Nicola Cetorelli is the pinnacle of Non-Financial institution Monetary Establishment Research within the Federal Reserve Financial institution of New York’s Analysis and Statistics Group. 

Mattia Landoni is a senior monetary economist on the Federal Reserve Financial institution of Boston.

Lina Lu is a senior monetary economist on the Federal Reserve Financial institution of Boston.

Methods to cite this submit:
Nicola Cetorelli, Mattia Landoni, and Lina Lu, “Monitoring Banks’ Publicity to Nonbanks: The Community of Interconnections Issues,” Federal Reserve Financial institution of New York Liberty Avenue Economics, April 18, 2023,

The views expressed on this submit are these of the writer(s) and don’t essentially mirror the place of the Federal Reserve Financial institution of New York or the Federal Reserve System. Any errors or omissions are the accountability of the writer(s).


Please enter your comment!
Please enter your name here