Hedging Interest Rate Risk Research Articles

Time-variation in bank income and expense betas

PurposeTo determine whether banks are able to hedge interest rate risk by matching interest income and expense betas each year, or only on average over longer time periods.Design/methodology/approachWe use state-space methods to estimate time-varying income and expense betas at the yearly frequency.FindingsWe find evidence that banks do match interest income to expense betas at the annual frequency, and the largest banks do the best job of matching interest income to expense sensitivities over time. Conversely, the smallest banks have the largest lag in matching interest income betas to changes in expense betas and have the largest net interest margins (NIM) sensitivity to the short-term rates.Originality/valuePrevious research was limited to constant deposit betas.

The collapse of Silicon Valley Bank and hedging strategies for interest rate risk

Research methodology This case was developed from published sources. Three types of data were used to develop this case. The accounting data were compiled by the case researcher from bank financial statements such as Form 10-K, Form 8-K and quarterly Financial Highlights issued by the bank. Market data were compiled from data providers such as FactSet, Yahoo! Finance, Pitchbook and the Federal Reserve System. Reports on market developments were gathered from major news outlets such as CNBC, The Wall Street Journal, Fortune and S&P Global. Case overview/synopsis Interest rate risk played a big role in the banking crisis of 2023. For Silicon Valley Bank (SVB), which specialized in providing banking services to venture-backed startups in the technology and life sciences sectors, its exposure to interest rate risk and the lack of hedging against interest rate risk had played a crucial role both directly and indirectly in the bank’s failure. This case study discussed the various channels that interest rate risk played in SVB’s failure as well as other risk factors that include an unusually high percentage of uninsured deposits and a high securities-to-asset ratio compared to its industry peers. In the low interest rate years of 2020 and 2021, startups were able to fundraise a record amount of funding from venture capital (VC) investors. As many startups deposited their funds at SVB, they became an important and concentrated depositor base for the bank and held large deposit accounts that easily exceeded the $250,000 limit insurable by the Federal Deposit Insurance Corporation. SVB benefited from the large deposit inflows in 2020 and 2021. The bank used some of the deposits to fund its loan portfolio, but most of the deposits were used to purchase debt securities such as US Treasuries and agency-used mortgage-backed securities. In fact, SVB’s investments in securities as a percentage of total assets were more than double its peers in the large banking organization (LBO) group, while the amount of loans funded as a percentage of total assets was almost half of its LBO peers. As interest rates increased rapidly throughout 2022, bond prices fell. SVB experienced unrealized losses of $15.2bn in its held-to-maturity securities portfolio, which was almost equivalent to its equity of $16bn at the time. However, SVB implemented little or no hedging against the risk of rising interest rates. At the same time, fundraising activities slowed in the VC sector amid high interest rates and, thus, SVB’s startups clients had to draw on past deposits to continue to fund their operations. This resulted in SVB experiencing significant deposit outflows throughout 2022. On March 8, 2023, SVB announced that it had sold all $21bn of its available-for-sale securities portfolio and suffered an $1.8bn in realized losses, which was greater than its entire last year’s net income. Markets jittered following the news. Over the next two days, depositors rushed to withdraw $142bn of deposits that represented 82% of its last year’s total deposits. Unable to withstand the crippling weight of deposit withdrawal, on March 10 the parent company of SVB filed for bankruptcy. Complexity and academic level Given the multiplexity of the banking crisis of 2023, this case study specifically discussed the collapse of SVB, which was the second largest bank failure at the time of its collapse. This case would be valuable for finance and economics students to learn how various risk factors interact that precipitated SVB’s failure. While there were many risk factors at play, this case study homes in on how SVB’s exposure to interest rate risk and the lack of hedging contributed to its downfall. For purpose of pedagogy, this case also explains how a bank could use on-balance-sheet as well as off-balance-sheet methods to hedge interest rate risk. This case is appropriate for courses in Risk Management, Derivatives as well as Financial Markets and Institutions with a focus on interest rate risk and its corresponding hedging methods. A course in Money and Banking may also find this case relevant. Before starting, it is assumed that students have already taken foundational finance and macroeconomics courses, have a basic understanding of financial statement analysis and its interpretations, derivative instruments such as futures and swaps, as well as have prior experience with basic duration calculations.

Deep treasury management for banks.

Retail banks use Asset Liability Management (ALM) to hedge interest rate risk associated with differences in maturity and predictability of their loan and deposit portfolios. The opposing goals of profiting from maturity transformation and hedging interest rate risk while adhering to numerous regulatory constraints make ALM a challenging problem. We formulate ALM as a high-dimensional stochastic control problem in which monthly investment and financing decisions drive the evolution of the bank's balance sheet. To find strategies that maximize long-term utility in the presence of constraints and stochastic interest rates, we train neural networks that parametrize the decision process. Our experiments provide practical insights and demonstrate that the approach of Deep ALM deduces dynamic strategies that outperform static benchmarks.

Reducing transaction costs for interest rate risk hedging with stochastic programming

Traditional methods for hedging interest rate risk do not take transaction costs into account as they aim to eliminate all risk. We propose a two-stage stochastic programming model for hedging interest rate risk where transaction costs are weighed against portfolio variance. High-quality measurements of term structures enable us to extract the systematic risk factors and make precise estimates of the perceived transaction costs. The hedging cost is weighed against the reduction in portfolio variance by using an adjustable hedging parameter. The hedging procedure is simulated on a daily basis in a realistic setting over an out-of-sample period from 2002 to 2018, and the results are compared to traditional hedging methods through detailed performance attribution. Using second-order stochastic dominance, we show that the proposed method is preferred by all risk-averse investors.

Governed by the cycle: interest rate sensitivity of emerging market corporate debt

This study addresses interest rate sensitivity of emerging market corporate debt. Previous research suggests that interest rate sensitivity of corporate bonds depends on residual maturity of issues, creditworthiness of issuers, embedded options and other idiosyncratic factors. However, the dependence of interest rate sensitivity on phases of the business cycle has not received an appropriate academic attention. This paper provides empirical evidence and theoretical interpretation of a dichotomy of interest rate sensitivity across the phases of the cycle, and sheds light on how credit spreads respond to interest rates. The historical span of the research covers the period of 2004–2016. The findings imply that hedging interest rate risk ought to be a dynamic process and take into consideration where the economy is positioned in the current business cycle. This research provides important insights on the nature of interest rate sensitivity, capable of enhancing financial stability and improving efficiency of financial system.

Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis

Using multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods, this paper investigates the hedging effectiveness of Chinese Treasury bond futures. We utilize MF-DFA approach and show that Treasury bond spot and futures markets are multifractal. Moreover, results based on MF-DCCA suggest persistent cross-correlation between 10-year Treasury bond spot and futures, but no significant cross-correlation between 5-year Treasury bond spot and futures. Interestingly, there also exists persistent cross-correlation between 10-year Treasury bond futures and other Treasury bonds (5-year and long-term). Results based on MF-CCA verify the persistent cross-correlations above. Our findings imply that 10-year Treasury bond futures contracts can serve as better tools to hedge interest rate risk.

Enterprise Risk Management in Walmart and Target

The purpose of this paper is to analyse and discuss the main differences between the Enterprise Risk Management systems of two of the most important retailers in the United States, namely Target Corporation and Walmart Inc. Firstly, the authors will briefly introduce the two companies, focusing on the different types of business strategies implemented and their history, considering then the main risk factors that characterize each company such as competitive and reputational, operational and investment, security and data privacy, supply chain and finally a short introduction about financial risks that will be the subject of deeper analysis afterwards. Likewise, the authors will evaluate the distinctive features of the financial structures and the strategic and tactical risk management processes of both companies, starting from the top level of the strategic planning to get to selected tools by the firms in order to face both financial and business risks that affect their activities. After that, it will be provided a deep analysis about the risk factors faced by Target and Walmart during their activities, with a main focus on financial risks that emerge from their financial structures, also considering derivative contracts to address the interest rate risk and the performance and cost of hedging interest rate risk. Moreover, the authors will underline differences and similarities among the two retailers in order to facilitate the comparison and the evaluation of the two ERM systems, but even further considerations highlighted in the paper.

Bank Interest Rate Risk Management

Empirically, bank equity value is decreasing in the interest rate. Yet (i) many banks do not hedge interest rate risk, and (ii) more than 50% of hedging banks use derivatives to increase exposure. I model a bank’s capital structure and show that these facts are consistent with optimal hedging under financial frictions. Novel predictions on the characteristics of banks taking long or short interest rate derivative positions are tested and supported by the data. Therefore, banks’ derivatives exposures are not necessarily evidence of excessive risk taking. More broadly, the results challenge the view that “hedging” and “speculative” positions can be identified from a positive comovement between derivatives payoffs and equity value. This paper was accepted by Gustavo Manso, finance.

The Three-Factor Hedging Strategy for Mortgage Pass-Through Securities: Empirical Evidence

The mortgage pass-through securities sector of the investment-grade bond market is attractive to institutional investors seeking to outperform a bond index without taking a view on credit risk. Market participants view this sector as being less price efficient than the other investment-grade bonds sectors, offering opportunities within the sector to take contrary positions relative to prevailing prices, particularly with respect to future prepayments. In executing a relative value strategy to enhance returns in this sector, portfolio managers must be able to remove interest rate risk. Unlike hedging interest rate risk in the other sectors of the investment-grade bond market, the cash flow structure of mortgage pass-throughs is such that there is interest rate exposure, via prepayment rates, due to a change in the term structure of interest rate. Both academics and practitioners have proposed several strategies for hedging interest rate risk. In this article, the authors evaluate a three-factor hedging strategy for agency pass-throughs, comparing the performance of this strategy to both the single-factor and two-factor hedging strategies. Their analysis finds that under certain conditions the three-factor hedging strategy outperforms both the one- or two-factor hedging strategy.

Interest rate risk in long‐dated commodity options positions: To hedge or not to hedge?

AbstractWe empirically assess hedging interest rate risk beyond the conventional delta, gamma, and vega hedges in long‐dated crude oil options positions. Using factor hedging in a model featuring stochastic interest rates and stochastic volatility, interest rate hedges consistently provide an improvement beyond delta, gamma, and vega hedges. Under high interest rate volatility and/or when a rolling hedge is used, combining interest rate and delta hedging improves performance by up to four percentage points over the common hedges of gamma and/or vega. Thus, contrary to common practice, hedging interest rate risk should have priority over these “second‐order” hedges.

The Bond Coupon’s Impact on Liquidity

Corporate bond investors are compensated for liquidity and counterparty risk in the yield received in excess of the credit premium and risk-free rate. This article shows that the liquidity premium as a hedge against uncertain future states is determined by the ratio of excess coupon payments after paying for credit protection to the capital gain realized after hedging interest rate risk. The liquidity premium increases with the time that investors must wait for compensation. The results suggest that the way in which investors receive compensation for liquidity risk is a more significant determinant of the liquidity premium than turnover.

Supplier-Customer Relationships and Corporate Hedging Policy

We investigate the relation between a firm’s hedging policy and its major customer relationships. We find that the likelihood of a supplier using derivatives to hedge interest rate risk is higher when a major customer has high leverage. This result is increasing in the supplier’s dependence on a major customer, such as when the customer represents a large share of its sales, when the supplier operates in a durable goods industry, or when the supplier makes high relationship-specific investments. We also find that hedging helps the supplier maintain durable relationships with customers, especially highly leveraged customers. Further, we find that announcements of customers’ bond offers and credit rating downgrades have more negative effects on the market value of non-hedging suppliers than that of hedging suppliers. These results suggest that a major customer’s financial health is an important determinant of a supplier’s hedging policy, and that supplier hedging helps increase the perceived viability of the future customer relationship and alleviate potential negative spillover effects along the supply chain.

Structural Recovery of Face Value at Default

A Recovery of Face Value at Default (RFV) means receiving the same fractional recovery of par at default for bonds of the same issuer and seniority, regardless of remaining maturity. We find that RFV in a parsimonious structural credit risk model has a profound impact on hedging interest rate risk as it strongly affects model sensitivities to interest rates. In particular, RFV explains and quantifies two important stylized facts: i) the low empirical duration of high-yield bonds and ii) the decreasing sensitivity of credit spreads to interest rates as credit quality declines. The recovery form used in empirical studies influences their interpretation as the default-free term structure (level and slope) interacts with the recovery form in determining model credit spreads.

Mitigating Interest Rate Risk in Variable Annuities: An Analysis of Hedging Effectiveness under Model Risk

ABSTRACTVariable annuities are investment vehicles offered by insurance companies that combine a life insurance policy with long-term financial guarantees. These guarantees expose the insurer to market risks, such as volatility and interest rate risks, which can be managed only with a hedging strategy. The objective of this article is to study the effectiveness of dynamic delta-rho hedging strategies for mitigating interest rate risk in variable annuities with either a guaranteed minimum death benefit or guaranteed minimum withdrawal benefit rider. Our analysis centers on three important practical issues: (1) the robustness of delta-rho hedging strategies to model uncertainty, (2) the impact of guarantee features (maturity versus withdrawal benefits) on the performance of the hedging strategy, and (3) the importance of hedging interest rate risk in either a low and stable or rising interest rate environment. Overall, we find that the impact of interest rate risk is equally felt for the two types of products considered, and that interest rate hedges do lead to a significant risk reduction for the insurer, even when the ongoing low interest rate environment is factored in.

Managing Real Estate Exposure: An Empirical Analysis on Interest Rate Risk

Real estate is an illiquid investment with cyclical returns, so risk management techniques should be used for sustainable returns. The risk management techniques include asset based, portfolio, insurance and derivatives solutions. Asset based solutions include the risk character of the real estate, based on where it’s located and how well it is developed. Some property such as foreclosure and those require maintenance is riskier than others. Portfolio solutions allow real estate companies to include real estate with different location and segments such as office and retail. Using this, the risk is limited to the systematic component, where asset based-idiosyncratic risk is tried to be reduced when included enough number of assets to the basket. The management should be capable of determining which risks taking and which to transfer. Some risks such as earthquake, fire, vehicle crush, terrorist activities are rare in nature but can cause severe damage when it takes place. The insurance policies can cover these events which most of the time are reinsured. In addition derivatives are available to hedge some of the risks. These can be traded on the market or over-the-counter. By using derivatives it is possible to hedge interest rate risk, inflation, currency risks, and property price changes. To hedge interest rate risk which is also studied in this paper, instruments such as cap, swap, and collar are available. The research is investigating the role of interest rate risk in the performance of real estate management companies. The variables used in this research are 30 years treasury yield, and exchange closing price for CBRE Group Inc., Colliers International Group, and Jones Lang LaSalle Incorporated. The data is daily for the period 16 June 2004 and 19 June 2015. The methods used are Johansen Cointegration and Granger Causality. The results of the study indicate there is a short-run and long-run relationship between interest rate and real estate management firm stock performance. In other words, interest rate fluctuation is a critical risk in performance of real estate management companies. In the paper, it is also discussed risk mitigation ideas for controlling this and other risks that real estate management industry is exposed.

Score-Driven Nelson Siegel: Hedging Long-Term Liabilities.

textabstractDue to its affine structure the Nelson-Siegel model for yield curves can be transformed to a factor model for excess bond returns. Hedging interest rate risk in this framework amounts to eliminating the factor exposure and minimizing the residual risk. Fitting the model directly on excess returns with constant factor loadings leads to large hedging errors caused by substantial and persistent time-variation in the shape parameter of the Nelson-Siegel factor loadings. To capture this variation we develop a Dynamic Conditional Score (DCS) model for the shape parameter. This dynamic model offers superior hedging performance and reduces the hedging error standard deviation by almost 50% during the financial crisis. Much of the improvement is due to the model for the shape parameter with some further reduction achieved by a GARCH model for the residual risk.

Hedging Interest Rate Risk Using a Structural Model of Credit Risk

Recent evidence has shown that structural models fail to capture interest rate sensitivities of corporate debt. We consider a structural model that incorporates a three-factor dynamic term structure model (DTSM) into the Merton (1974) model. We show that the proposed model largely captures the interest rate exposure of corporate bonds. We also find that for investment-grade bonds, hedging effectiveness substantially improves under the proposed model. Our results indicate that to better capture and hedge the interest rate exposure of corporate bonds, we need to incorporate a more realistic DTSM in the existing structural models.

The Bond Coupon's Impact on Liquidity

Corporate bond investors are compensated for liquidity and counter-party risk in the yield received in excess of the credit premium and risk-free rate. This paper shows that the liquidity premium as a hedge against uncertain future states is determined by the ratio of excess coupon payments after paying for credit protection to the capital gain realized after hedging interest rate risk. The liquidity premium increases with the time that investors must wait for compensation. The results suggest that the way in which investors receive compensation for liquidity risk is a more significant determinate of the liquidity premium than turnover.

A reduced-form contingent convertible bond model with deterministic conversion intensity

The purpose of this paper is to build a contingent convertible bond (CoCo) model with a minimal number of stochastic factors that includes all relevant sources of risk. The value of a CoCo stems from future coupon payments, the redemption of the principal in case the CoCo does not convert and a possible conversion into equity or cash. For calibration and hedging we propose to use the issuing firm's stock, interest rate swaps and credit default swaps. We model the stock price as a geometric Brownian motion with a jump at conversion. Conversion and default are assumed to occur at the first two jump times of a time-changed Poisson process. The dynamics of interest rates does not have to be specified. For pricing and calibration it is not needed, and to hedge interest rate risk one can simply immunize against the most common movements of the yield curve. A CoCo's sensitivity to conversion is described by its jump-to-default and jump-to-conversion. As case studies we analyze CoCos issued by Lloyds Banking Group in December 2009 and Rabobank in March 2010.

A Reduced Form CoCo Model with Deterministic Conversion Intensity

The purpose of this paper is to build a CoCo model with a minimal number of stochastic factors that includes all relevant sources of risk. The value of a CoCo stems from future coupon payments, the redemption of the principal in case the CoCo does not convert and a possible conversion into equity or cash. For calibration and hedging we propose to use the issuing firm's stock, interest rate swaps and CDS's. We model the stock price as a geometric Brownian motion with a jump at conversion. Conversion and default are assumed to occur at the first two jump times of a time-changed Poisson process. The dynamics of interest rates does not have to be specified. For pricing and calibration it is not needed, and to hedge interest rate risk one can simply immunize against the most common movements of the yield curve. A CoCo's sensitivity to conversion is described by its jump-to-default and jump-to-conversion. As case studies we analyze CoCos issued by Lloyds Banking Group in December of 2009 and Rabobank in March of 2010.