This literature can be broadly categorized into two groups. The first group uses network theory to evaluate how an illiquidity shock to one firm propagates to others. The second group identifies liability connectedness through reliance on a “common liquidity pool.”
A.2.1 Liability Connectedness through the Lens of Network Theory
One body of literature uses the tools of network theory to examine how a funding shock to one firm spreads to other firms through the interbank lending market. These papers attempt to characterize how the structure of linkages between individual institutions affects the likelihood and severity of a systemwide funding dry up. According to this literature, the complexity of direct and indirect linkages between institutions within a financial network is a critical component of a network’s resilience. Many studies have analyzed how direct funding linkages, while introducing the possibility of systemic
failure, can also prevent such failure where banks engaging in cross-holdings of deposits effectively insure each individual bank against an idiosyncratic liquidity shock. For
example, if Bank A and Bank B each hold one another’s deposits, a liquidity shock to Bank A can be met simply by liquidating its holdings in Bank B.13 Such a network works well
when there is sufficient aggregate liquidity in the system to meet demand, but in the case where demand exceeds supply even a small, localized liquidity shock to one bank can spread rapidly through the entire financial network through direct interbank lending arrangements. When an initial shock causes a bank to fail, this failure reduces the overall pool of common liquidity available for the remaining solvent banks in the network. A negative feedback cycle can afflict the system whereby insolvency reduces liquidity, which then causes further insolvency, and so on. The end result can be complete systemic
collapse. To a degree, the numerous interconnections between banks within a network serve as a “shock absorber,” diffusing the shock throughout the vastness of the financial system, much as does asset connectedness as discussed above. The network provides mutual insurance to each institution, and negative shocks dissipate with no systemic consequences. However, the range of absorbable shocks is bounded by a “tipping point.”
Beyond this point, interconnections no longer dampen the shock to the system but rather serve to amplify and propagate the damage; this is the same analysis as discussed above for asset connectedness. “The system acts not as a mutual insurance device but as a mutual incendiary device.”14 While the precise threshold of absorbable shocks can be difficult to specify, the existence of such “tipping points” in a connected network can be shown.15
The concentration of institutions within a financial network also plays an important role in the propagation of a shock through the system. A more concentrated (“fat-tailed”) network is one with a small number of highly connected key players, where
connectedness refers to both the number of interbank relationships and the total value of those relationships.16 A concentrated network is more robust to random shocks than less concentrated networks, provided the shocks are within a given range.17 However, for shocks outside that range, “higher concentration in the network makes the system more susceptible to a systemic liquidity crisis.”18 Furthermore, since concentrated networks are vulnerable to shocks targeting the key players, when the initial shock hits the most
connected interbank lender, the likelihood of systemic failure increases.19 However, it may require an exceptionally large liquidity shock to destabilize the system. For example, in Gai, Haldane, and Kapadia (2011) instability is triggered by a sudden doubling of repo haircuts.20 The only plausible explanation for such a tremendous liquidity shock is run- like behavior (i.e., contagion), so connectedness absent contagion would not be a serious problem.
Over the decade preceding the 2008 financial crisis, US financial networks increased in complexity, concentration, connectedness, and homogeneity. From a network theory perspective, such a combination leads to fragility.21 Securitization and derivatives have lengthened the network chains, while also multiplying the number of links between institutions. Over the past two decades, nodes in the financial network have increased fourteen-fold and “links have become fatter and more frequent, increasing roughly 6- fold.”22 As firms diversified and engaged in risk management strategies with common characteristics, the diversification of individual firms created less diversity in the
aggregate system. The network became more homogeneous. Finally, the international
finance network has increasingly displayed the characteristics of a fat-tailed network, comprising a relatively small number of highly connected financial institutions.23
These features have resulted in a “robust-yet-fragile” system, well equipped to absorb adverse shocks within a given range but vulnerable to failure in the case of shocks outside that range. In addition to the relative magnitude of the shock, the location of a shock in the network (i.e., hitting a so-called super-spreader) can have catastrophic consequences for systemic stability.24 The basic fragility of the US financial network is best illustrated by the fact that, while the system demonstrated resilience to “fairly large shocks prior to 2007 (e.g., 9/11, the Dotcom crash and the collapse of Amaranth to name a few),”25 the past fifteen years were in fact a “lengthy period of seeming robustness (the Golden Decade from 1997 to 2007) ... punctuated by an acute period of financial fragility.”26
Importantly, in most theoretical network models of liability connectedness, the
destabilizing mechanism is not a cessation of lending due to default of a lender. Instead, the financial system is disrupted by contagious waves of liquidity hoarding. The structure of the network determines how an initial shock is transmitted throughout the system, but the fundamental destabilizing force is an abrupt onset of liquidity hoarding behavior, often without regard the credit quality of a bank’s counterparties. Hence liability connectedness itself is less problematic than contagious run-like behavior.
A.2.2 Liability Connectedness through Reliance on a Common Pool of Liquidity A second body of literature examines how banks are exposed to funding shocks through reliance on a common pool of liquidity. Empirical studies have documented that market liquidity (the ease with which an asset is traded) co-varies with market prices and
volatility,27 and that an asset’s sensitivity to market liquidity is priced (e.g., the less liquid, the lower price).28 The value of liquidity provides some explanation for the “flight to
quality” or “liquidity hoarding” that takes place during crises. Archarya and Pedersen
(2005) set forth an equilibrium model that explains these phenomena. Brunnermeier and Pedersen (2009) propose a model that further explains these phenomena and includes a feedback mechanism that illustrates how this need for liquidity can create financial fragility. In their framework, an “asset’s market liquidity is linked with investors’
“funding liquidity (i.e., the ease with which a firm or more generally an investor can obtain funding).” When market liquidity decreases, and the value of assets decrease as a result, margin requirements will increase. But, if funding liquidity also decreases, it will be difficult to obtain such margin. Thus a small shock to market liquidity can produce outsize effects on market prices through “margin spirals” and “loss spirals.” In a loss spiral, firms are forced by a drop in market prices to liquidate assets, which further
impairs market liquidity and also asset prices. As a result firms are faced with ever more increased demands for collateral. In a margin spiral, increased demands for collateral prompt firms to sell into an illiquid market, feeding back into the loss spiral. This
mechanism creates multiple equilibria in which “a small change in fundamentals can lead to a large jump in illiquidity” and a corresponding decline in asset prices. These spirals may be transmitted between markets and institutions. According to Kodres and Pritsker
(2002), “the correlated liquidity shock channel posits that when some market participants need to liquidate some of their assets to obtain cash, perhaps due to a call for collateral, they chose to liquidate assets in a number of markets, effectively transmitting the shock.”
This illustrates how contagion can spread throughout the financial sector via fire sales, even absent direct balance sheet links between institutions. A similar point is made in Liu (2015), that “indirect interconnectedness” can occur though fire sales and mark-to-
market accounting practices.29 However, these are really consequences of contagion and not the chain reaction of failures that is the key feature of interconnectedness. While Liu (2015) also posits that correlation of CDS spreads is evidence of interconnectedness, that is more indicative of correlation, discussed below.