Floating-rate Loans Research Articles

Deposit market power, funding stability and long-term credit

By increasing funding stability, deposit market power reduces banks’ funding risk over the cycle and provides the flexibility to originate long-term loans. Banks with deposit HHI one standard deviation above average extend loans with about 20% longer maturity than those one standard deviation below average. Deposit market power also allows banks to charge lower maturity premiums. The effects persist in the sample of zero-duration, floating rate loans. This has real effects: access to banks raising funds in less competitive markets improves growth in bank-dependent borrowers needing long-term finance. Deposit market power, by stabilizing bank funding costs, helps alleviate credit cycles.

The financing structures of social housing corporations: an examination of disclosure quality in the annual reports

This study examines the financing structures and the accompanying disclosures of social housing corporations. We found that in the period 2018–2021, the loans issued by the social housing corporations increased, while the overall interest costs decreased, leading to a lower cost of funding. In addition, we found that the social housing corporations favour fixed rate loans and the use of floating rate loans decreased. Most of these floating rate loans were hedged with derivatives, but the use of derivatives in general decreased with a significant amount. The disclosures related to the financing structures vary significantly in quality. The disclosures which can be improved relate to embedded derivatives, collateral requirements for derivatives, interest rate risk sensitivity analyses and the assumptions used for the fair value calculation.

Calculating lifetime expected loss for IFRS 9: which formula is measuring what?

PurposeThe purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This is done both for fixed-rate and floating rate loans under different assumptions on LGD modeling, prepayment, and discount rates.Design/methodology/approachThis study provides exact formulas for lifetime expected credit loss derived analytically together with the mathematical proofs of each expression.FindingsThis articles shows that the formula most commonly applied in the literature for calculating lifetime expected credit loss is inconsistent with measuring expected loss based on expected discounted cash flows. Formulas based on discounted cash flows always lead to more conservative numbers.Practical implicationsFor banks reporting under IFRS 9, the implication of this research is a better understanding of the different approaches used for computing lifetime expected loss, how they are connected, and what assumptions are underlying each approach. This may lead to corrections in existing frameworks to make applications of risk management systems more consistent.Originality/valueWhile there is a lot of literature explaining IFRS 9 and evaluating its impact, none of the existing research has systematically analyzed the calculation of lifetime expected credit loss for this purpose and how the formula changes under different modeling assumptions. This gap is filled by this study.

Interest Rate Swaps: A Comparison of Compounded Daily Versus Discrete Reference Rates

This paper studies the hedging effectiveness of interest rate swaps using different reference rates for eliminating interest rate risk from floating rate loans. Two different reference rates are studied. The first is a reference rate whose maturity, ∆, matches the payment interval of the floating rate loan. The second is a reference rate whose maturity is ∆/N. The prime examples are LIBOR and SOFR, respectively. We show that the ∆-based interest rate swap provides a good static hedge, but the ∆/N-based swap does not. Although dynamic hedging with the ∆-based interest rate swap is possible under some conditions, it both introduces model risk and increases transaction costs, making it a less practical alternative.

LIBOR Reform: Option Pricing for Compounded Rates

I present analytical pricing formulae for derivatives of compounded rates. Since the announced replacement of LIBOR, the compounded overnight rate has become the new market standard for floating-rate loans and notes. Many contracts contain a zero-based floor. The compounded rate is a time average of a series of benchmark rates. Floors and caps on compounded rates are thus Asian types of options. I prove that even if the rate process is non-Gaussian, the Gaussian process is asymptotically the correct model for pricing derivatives due to the central limit theorem. The approximation's maximum mispricing is bounded by the Berry-Esseen inequality.

Why do bank-dependent firms bear interest-rate risk?

Abstract I document that floating-rate loans from banks, particularly important for bank-dependent firms, drive most variation in firms’ exposure to interest rates. I argue that banks prefer to supply floating-rate loans, due to their finite ability to transform short-duration deposit liabilities into long duration assets. Three key findings support this argument: banks with more floating-rate liabilities make more floating-rate loans, hold more floating-rate securities, and quote lower prices for floating-rate loans. Intermediary funding structures therefore help determine what types of contracts non-financial firms use. Banks transmit rising policy rates to firms by contractually raising interest rates on existing loans, not just by reducing the supply of new loans.

The student loan consolidation option

The federal government makes credit for higher education widely available at subsidized prices through its student loan programs. A loan provision that at times has significantly increased the size and volatility of the subsidies is the consolidation option, which allows borrowers to convert floating rate loans to fixed rate loans, often on very favorable terms. The option provides a novel setting in which to study how unsophisticated borrowers respond to financial incentives. We develop a model to evaluate the option's cost to the government, and find that the ex-ante cost of the option ranged from 0.8% to 6.4% of loan principal between 1998 and 2005. Using a sample of 700,000 student loan records, we find that borrowers responded to the time-varying incentives to consolidate although some left sizeable amounts of money on the table; that more indebted borrowers were more likely to optimize; and that there is some evidence of learning over time.

LIBOR Floors in Leveraged Loans

I examine the use of LIBOR floors in U.S. leveraged (syndicated) loans. These options, rare prior to 2008, provide a minimum interest rate on these otherwise floating rate loans. This contract design is consistent with theory suggesting lenders prefer more fixed rate assets while interest rates are low in order to cover their fixed costs. Two main findings support this rationale. First, borrowers seeking to extend loans between 2009 and 2016 were able to attract 34% more principal from lenders if a floor was added, suggesting demand for floors originated from the supply of credit. Second, banks that participated in floor-adjusted credit lines had significantly higher fixed costs than did banks in purely floating rate facilities. Floors are concentrated in institutional facilities, in particular those that are most likely to trade in the secondary market. This is consistent with cost savings associated with embedded floors over those obtained through third-parties when expected trading volume is high. Consistent with their theoretically higher interest rate sensitivity, loans that embed floors are more likely to include call protection, in the form of cancellation and upfront fees. Floors represent a significant component of loan pricing, contributing three to five times as much as upfront fees to total lender compensation.

Effects of Negative Interest Rates on Floating Rate Loans and Bonds. Analysis of Legal and Financial Profiles

Effects of Negative Interest Rates on Floating Rate Loans and Bonds. Analysis of Legal and Financial Profiles

Why Do Bank-Dependent Firms Bear Interest-Rate Risk?

I document that floating-rate loans from banks (particularly important for bank-dependent firms) drive most variation in firms' exposure to interest rates. I argue that banks lend to firms at floating rates because they themselves have floating-rate liabilities, supporting this with three key findings. Banks with more floating-rate liabilities, first, make more floating-rate loans, second, hold more floating-rate securities, and third, quote lower prices for floating-rate loans. My results establish an important link between intermediaries' funding structure and the types of contracts used by non-financial firms. They also highlight a role for banks in the balance-sheet channel of monetary policy.

Why Do Bank-Dependent Firms Bear Interest-Rate Risk?

I document that floating-rate loans from banks (particularly important for bank-dependent firms) drive most variation in firms' exposure to interest rates. I argue that banks lend to firms at floating rates because they themselves have floating-rate liabilities, supporting this with three key findings. Banks with more floating-rate liabilities, first, make more floating-rate loans, second, hold more floating-rate securities, and third, quote lower prices for floating-rate loans. My results establish an important link between intermediaries' funding structure and the types of contracts used by non-financial firms. They also highlight a role for banks in the balance-sheet channel of monetary policy.

What Are Reference Rates For?

What is the precise role of reference rates? Why does it matter if LIBOR was manipulated? To address these questions, I analyze the use of reference rates in floating-rate loans and interest rate derivatives in the context of lending relationships. I develop a simple framework combining maturity transformation with three key frictions which generate meaningful funding risk and a rationale for risk management. Reference rates like LIBOR mitigate contractual incompleteness, facilitating management of funding risk. As bank funding costs move with bank credit risk, it makes sense for the reference rate to have a bank credit risk component. Manipulation can add noise, reducing the usefulness of reference rates for this purpose.

What Are Reference Rates For?

What is the precise role of reference rates? Why does it matter if LIBOR was manipulated? To address these questions, I analyze the use of reference rates in floating-rate loans and interestrate derivatives in the context of lending relationships. I develop a simple framework combining maturity transformation with three key frictions which generate meaningful funding risk and a rationale for risk management. Reference rates like LIBOR mitigate contractual incompleteness, facilitating management of funding risk. As bank funding costs move with bank credit risk, it makes sense for the reference rate to have a bank credit risk component. Manipulation can add noise, reducing the usefulness of reference rates for this purpose.

Loans and Negative Interest Rates

Payments of interest amounts in floating rate loans are generally linked to specific reference parameters, such as EURIBOR. Given the decrease of such parameters to reference values around zero, what would happen if such a fall continued below this value (so that lenders have to pay interest amounts to borrowers)? General principles of interpretation of contracts, good faith and equity, jointly with an analysis of nature / characteristics of loan contracts could help to find a solution being the most transnational possible. In particular, reference could be made to: (i) an interpretation of the loan contract by which such contract cannot betray its nature (and interest payments are necessary in non-gratuitous loans); (ii) the equity principle, under which contracts have to be reasonable / fair (and lenders should receive back by borrowers at least the capital amount); (iii) the nature of loans as contracts necessarily requiring interest payments by borrowers.

A Structural Model of Credit Risk for Illiquid Debt

In this article, the authors develop a structural credit risk model that relies on cash flow data to derive credit risk metrics. The model is useful for illiquid assets for which a time series of prices is not observable. The methodology is designed to require a parsimonious dataset of observable inputs and provides a clear link between an asset’s fundamental characteristics and its risk profile. The model is flexible enough to value debt instruments with path-dependent cash flows, such as mortgages and floating rate loans and can incorporate various debt covenants, such as debt refinancing, and restructuring options, as well as cash sweeps, dividend lockups, and reserve accounts. The implementation of the model is illustrated with project finance debt, which is highly illiquid and suffers from a serious lack of price data. The authors show that the dynamic of the debt service cover ratio (DSCR) along with the debt repayment profile and the debt covenants are sufficient to implement our credit risk model. For reasonable parameter values of the DSCR dynamics, the model reproduces stylized empirical regularities regarding the probabilities of default for two generic types of infrastructure projects.

Leveraged Liquidity: Bear Raids and Junk Loans in the New Credit Market

As instability in the credit market has spread from sub-prime mortgages to commercial sectors, demand grows for a cogent account of current liquidity dynamics and their implications. To that end, I distinguish between market and funding liquidity and analyze how these distinct forms of liquidity contributed to financial instability in the corporate leverage market since July 2007. After introducing the major themes in terms accessible to a nonfinancial reader, I draw on economist Hyman Minsky's work on financial instability to analyze the liquidity dynamics of leverage cycles. In particular, I focus on four shifts in credit market structure that are vexing financial market regulators: the rise of nonbank lenders, the growth of floating-rate debt; the 'marketization' of corporate credit; and the attitude shifts that come with financial euphoria. I then zero in on the corporate version of sub-prime borrowing that many U.S. corporations used to finance the recent wave of mergers, acquisitions, and other types of shareholder-friendly transactions: leveraged loans. These are secured, sub-investment-grade, floating-rate loans priced off LIBOR, an asset class that corelates most closely with junk bonds. I conclude with recommendations for how regulatory and financial models can better reflect the new realities of the credit market.

The Determinants of Household Credit in Spain

This paper estimates a single-equation model to analyse the main explanatory factors behind changes in Spanish household credit, considering that the behaviour of its determinants is exogenous. According to the evidence reported, household borrowing is determined in the long run by real spending, gross wealth and the repayment term for outstanding credits, which have a positive influence, and by the cost of loans and the unemployment rate, the effect of which is of a negative sign. Developments in the short run are influenced by changes in long-term interest rates and in employment. The evidence offered suggests that, in general terms, the financing received by households over the period analysed is in line with what may be inferred from its determinants; however, the high volume of debt incurred entails greater exposure of the sector to unexpected changes in its income, in its wealth or in the cost of borrowing, especially in a setting in which floating-rate loans are increasingly significant.

The Use of Fixed-rate and Floating-rate Debt for Hotels

A time-series simulation that compares hotel-industry revenue per available room (RevPAR) with London Interbank Offer Rate (LIBOR) indicates that hotel investors would fare more favorably with floating-rate loans than with the commonly used fixed-rate financing. Using data from 1987 through 2004, the study determined that LIBOR and RevPAR changes are strongly correlated, indicating a relationship of RevPAR and floating interest rates. Moreover, a simulation found that hotels using variable-rate mortgages would have been more likely to cover debt service in good times and bad than would hotels financed with fixed-rate loans. The correlation was strongest for midscale, limited-service properties but also operated for budget and resort deals. The relationship of RevPAR with floating rates suggests a reduction in the costs to borrowers and lenders arising from distressed loans.

Corporate Use of Interest Rate Swaps: Theory and Evidence

We develop a simply theory on interest rate swaps based on the difference between bank loans and public debts. While restrictive covenants of bank loans help reduce agency costs, banks also have natural disadvantages in bearing interest rate risk due to their floating liabilities. A firm that wants a fixed-rate loan can borrow a floating-rate loan from a bank and enter an interest rate swap to hedge the interest rate risk. Consistent with our theory, we find empirically that fixed-rate swap payers generally have lower credit ratings, higher leverage ratios, higher percentages of long-term floating-rate loans, and are more likely to use bank loans than floating-rate swap payers.

Corporate use of interest rate swaps: Theory and evidence

We develop a simply theory on interest rate swaps based on the difference between bank loans and public debts. While restrictive covenants of bank loans help reduce agency costs, banks also have natural disadvantages in bearing interest rate risk due to their floating liabilities. A firm that wants a fixed-rate loan can borrow a floating-rate loan from a bank and enter an interest rate swap to hedge the interest rate risk. Consistent with our theory, we find empirically that fixed-rate swap payers generally have lower credit ratings, higher leverage ratios, higher percentages of long-term floating-rate loans, and are more likely to use bank loans than floating-rate swap payers.