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    Home»Investing»Bank Runs and Liquidity Crises: Insights from the Diamond-Dybvig Model
    Investing

    Bank Runs and Liquidity Crises: Insights from the Diamond-Dybvig Model

    IDKWYDBy IDKWYDFebruary 24, 2025No Comments7 Mins Read
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    Financial institution runs are among the many most destabilizing occasions in monetary markets, able to turning liquidity fears into full-blown crises. On the coronary heart of this phenomenon is the Diamond-Dybvig Mannequin, a foundational framework that explains how banks’ function in reworking illiquid belongings into liquid liabilities makes them inherently susceptible. Whereas this function offers vital financial worth, it additionally depends closely on depositor confidence.

    If expectations shift — whether or not attributable to actual or perceived dangers — a self-fulfilling crisis can emerge. This weblog explores the mechanics of financial institution runs — why they occur even within the absence of elementary monetary misery, and the way central banks can intervene to stabilize the system.

    start line is to look to the analysis of Douglas Diamond, the Merton H. Miller Distinguished Service Professor of Finance on the College of Chicago, who was awarded the Nobel Prize in Financial Sciences in 2022.[1]  Diamond is primarily identified for his analysis into monetary intermediaries, monetary crises, and liquidity, and his analysis agenda has been devoted to explaining what banks do, why they do it, and the results of those preparations. 

    He’s maybe finest identified for the Diamond-Dybvig Model[2], which exactly explains how the function of banks in creating liquid liabilities (deposits) to fund illiquid belongings (similar to enterprise loans) makes them essentially unstable and provides rise to financial institution runs.

    It additionally exhibits why banks may have a authorities security web greater than they want different debtors. Diamond-Dybvig Mannequin is elegant in its simplicity and intuitiveness; it exactly describes how financial institution failures like Silicon Valley Financial institution (SVB) in 2023 can occur and, certainly, even the higher liquidity disaster and financial institution failures that occurred through the Nice Monetary Disaster. Furthermore, the mannequin prescribes how such occasions might be averted.

    Easy Diamond-Dybvig Mannequin

    One of many key capabilities of banks within the economic system is the transformation of illiquid asset into liquid legal responsibility. This good feat of monetary engineering provides numerous worth to the economic system however exposes banks to liquidity threat of their very own and makes them inherently unstable.

    Assume that there exists an illiquid asset that an investor can maintain immediately. You may make investments on this asset at t=0 for $1.00. It may both be liquidated at t=1 for $1.00 or held till t=2 for a $2.00 payoff.

    Every investor on this economic system faces unsure future liquidity wants. Every is aware of that she or he will want money both at t=1 (Kind 1) or at t=2 (Kind 2), however with out certainty when at t=0. To be extra exact, we will assume that every particular person investor has a 25% chance of money want at t=1 and a 75% chance of money want at t=2.  

    Every investor has a easy risk-averse consumption utility operate U(C)=110-(100/C). The Kind 1 investor consumes $1.00 at t=1 and the Kind 2 investor consumes $2.00 at t=2.  Every investor’s anticipated utility at t=0 is 0.25*U(1) + 0.75*U(2)=47.50.

    What if a extra liquid asset is on the market on this economic system? As a substitute of $1.00 at t=1 and $2.00 at t=2, the extra liquid asset pays off $1.28 at t=1 and $1.81 at t=2.  Then the investor’s anticipated utility at t=0 can be 0.25*U(1.28) + 0.75*U(1.81)=49.11.

    This second, extra liquid asset doesn’t but exist. However can a financial institution create one?  Suppose a financial institution collects $1.00 from 100 traders and invests within the first illiquid asset and guarantees to pay $1.28 at t=1 for many who withdraw at t=1 and $1.81 to those that withdraw at t=2. 

    At t=1, the financial institution’s portfolio is barely price $100. If 25 traders withdraw as anticipated, then 32% of the portfolio have to be liquidated to pay the traders (25*($1.28) = $32). The remaining 68% of portfolio worth is price $68. At t=2, the remaining 75% of the traders can now obtain $1.81 ($68*$2.00)/75. 

    If fraction c receives a at t=1, then every of the remaining can obtain (1-c*a)*$2.00/(1-c). That is the optimum contract a financial institution can write given the payoff construction of the illiquid asset, the investor’s utility operate, and the proportion of investor varieties.

    This threat pooling and sharing and liquidity transformation is without doubt one of the most necessary capabilities a financial institution can carry out. It’s a powerful feat of monetary engineering that provides numerous worth to the economic system.

    Unstable Equilibrium

    However this monetary alchemy just isn’t with out its prices. Within the above instance, 25 of the 100 traders withdraw at t=1 and 75 withdraw at t=2. That is the equilibrium given everybody’s expectation at t=0. 

    However this isn’t the one attainable equilibrium. What if a future Kind 2 investor didn’t know what number of traders have been Kind 1 at t=0 and expects a better proportion of withdrawals at t=1? If, for instance, 79 of the 100 traders withdraw at t=1, the financial institution’s portfolio is price at most $100. If 79 of the traders obtain 1.28%, then the financial institution is anticipated to fail (79*$1.28=$101.12 > $100).

    Given this new expectation, a rational response can be for the Kind 2 investor to withdraw at t=1 to get one thing versus nothing. In different phrases, an expectation of 100% at t=1 is as self-fulfilling as an expectation of 25% at t=1 and 75% at t=2. The underside line is that the anticipation of liquidity issues (actual or perceived) result in present actual liquidity issues, and traders’ expectations can change primarily based on no elementary adjustments within the stability sheet. 

    Functions

    The Diamond-Dybvig Mannequin of liquidity is strong sufficient for analyzing all forms of “runs” {that a} advanced seller financial institution can face — flight of short-term financing, flight of prime brokerage purchasers, flight of spinoff counterparties, lack of money settlement privileges, amongst others.

    It additionally serves as a helpful framework for analyzing the financial penalties of a liquidity disaster and coverage responses. Panicked traders in search of liquidity on the identical time impose critical harm to the economic system as a result of they drive liquidation of productive longer-term investments and interrupt financing of the present productive tasks. 

    Financing by central banks as lender of final resort is perhaps wanted on this case. To drive the optimum resolution because the dominant technique, you want some type of insurance coverage from a reputable supplier (deposit insurance coverage, Fed line of credit score, or different third-party ensures), and if the clamor for liquidity is systemic, solely the central financial institution can credibly provide assurances. 

    The Diamond-Dybvig Mannequin illustrates a elementary reality about fashionable banking: confidence is the glue that holds the system collectively. When depositors, counterparties, or traders concern a liquidity crunch, their rush to withdraw funds can create the very disaster they concern; that’s, forcing untimely liquidation of long-term belongings and disrupting financial stability.

    Efficient coverage responses, similar to deposit insurance coverage and central financial institution intervention, are important to breaking the cycle of self-fulfilling expectations. Whether or not analyzing basic financial institution runs or fashionable monetary contagion, the teachings of liquidity administration stay clear: in occasions of uncertainty, notion can form actuality, and stabilizing expectations is simply as necessary as stabilizing stability sheets.


    [1] This writer was a graduate scholar on the College Chicago Sales space College within the late 90’s and was one in all his college students.

    [2] Douglas Diamond, Phillip Dybvig, “Financial institution Runs, Deposit Insurance coverage, and Liquidity,” Journal of Political Financial system, June 1983.



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