Overnight Index Swap Research Articles

The network structure of overnight index swap rates

Graph theoretical techniques are utilized to examine the centrality structure of overnight index swap (OIS) networks. Correlation based graphs are constructed to encode pairwise relationships between distinct OIS rates. Multiple notions of graph centrality are considered, and the time evolution of these measures is studied. A principal component analysis based centrality measure is constructed to examine comovements between full OIS curves. Numerical examples demonstrating these ideas are provided.

Treasury inconvenience yields during the COVID-19 crisis

In sharp contrast to most previous crisis episodes, the Treasury market experienced severe stress and illiquidity during the COVID-19 crisis, raising concerns that the safe-haven status of US Treasuries may be eroding. We document large shifts in Treasury ownership and temporary accumulation of Treasury and reverse repo positions on dealer balance sheets during this period. We build a dynamic equilibrium asset pricing model in which dealers subject to regulatory balance sheet constraints intermediate demand/supply shocks from habitat agents and provide repo financing to levered investors. The model predicts that Treasury inconvenience yields, measured as the spread between Treasuries and overnight-index swap rates (OIS), as well as spreads between dealers’ reverse repo and repo rates, should be highly positive during the COVID-19 crisis, as is confirmed in the data. The same model framework, adapted to the institutional setting in 2007–2009, can also explain the negative Treasury-OIS spread observed during the Great Recession.

The Network Structure of Overnight Index Swap Rates

Graph theoretical techniques are utilized to examine the network centrality structure of overnight index swap (OIS) networks. Correlation based graphs are constructed to encode pairwise relationships between distinct OIS rates. Multiple notions of graph centrality are considered, and the time evolution of these measures is studied. A principal component analysis based centrality measure is constructed to examine comovements between full OIS curves. Numerical examples demonstrating these ideas are provided.

Japan’s impactful augmentation of quantitative easing sovereign-bond purchases

This article examines how and to what extent large-scale government bond purchases in the Bank of Japan’s monetary policy affected two components of long-term interest rates over the period 2009–2015. The article divides market yields on popular 5 and 10-year government bonds into future policy-rate expectations with uncertainty and a specific type of term premia required by investors for the bonds’ demand/supply imbalances, by using overnight index swap rates as a proxy for the former. The Bank of Japan augmented the purchases substantially by starting Quantitative and Qualitative Monetary Easing (QQME) in 2013. The QQME became impactful in the sense that it encouraged investors to improve the first component whilst reducing the second component. These appeared mainly as persisting announcement-effects – upward level shifts of the expectations and downward ones of the term premia. The reduction of term premia was much greater for the 10-year maturity than for 5-year one and strengthened after an additional expansion of the QQME in 2014. The QQME is estimated to have enhanced 5-year sovereign bond yields by 11.9 basis points (bps) a month on average whilst reducing 10-year ones by 8.3 bps. The impact on the 5-year yields turned to be negative after the QQME expansion.

Treasury Inconvenience Yields During the Covid-19 Crisis

In sharp contrast to most previous crisis episodes, the Treasury market experienced severe stress and illiquidity during the COVID-19 crisis, raising concerns that the safe-haven status of U.S. Treasuries may be eroding. We document large shifts in Treasury ownership during this period and the accumulation of Treasury and reverse repo positions on dealer balance sheets. To understand the pricing consequences, we build a model in which balance sheet constraints of dealers and demand/supply shocks from habitat agents determine the term structure of Treasury yields. A novel element of our model is the inclusion of levered investors’ repo financing as part of dealers’ intermediation activities. Both direct holdings of Treasuries and reverse repo positions of dealers are subject to a regulatory balance sheet constraint. According to the model, Treasury inconvenience yields, measured as the spread between Treasuries and overnight-index swap (OIS) rates, as well as spreads between dealers’ reverse repo and repo rates, should be increasing in dealers’ balance sheet costs. Consistent with model predictions, we find that both spreads are large and positive during the COVID-19 crisis. We further show that the same model, adapted to the institutional setting in 2007-2009, also helps explain the opposite signs of repo spreads and Treasury convenience yields during the financial crisis.

A macro–financial analysis of the corporate bond market

We assess the contribution of economic and financial factors in the determination of euro area corporate bond spreads over the period 2001–2015. The proposed multi-market, no-arbitrage affine term structure model is based on the methodology proposed by Dewachter et al. (J Bank Finance 50:308–325, 2015). We model jointly the ‘risk-free curve’, measured by overnight index swap (OIS) rates, and the corporate yield curves for two rating classes (A and BBB). The model includes four spanned and six unspanned factors. We find that, in general, both economic (real activity and inflation) and financial factors (proxying risk aversion, flight to liquidity and general financial market stress) play a significant role in the determination of the spanned factors and hence in the dynamics of the risk-free yield curve and corporate bond spreads. Across the risk-free OIS curve, macroeconomic and financial factors are each responsible on average for explaining 30 and 65% of yield variation, respectively. For A- and BBB-rated corporate debt, the selected financial variables explain on average 50% of the variation in corporate spreads during the last decade.

Yield curve fitting with artificial intelligence: a comparison of standard fitting methods with artificial intelligence algorithms

The yield curve is a fundamental input parameter of valuation theories in capital markets. Information about yields can be observed in a discrete form, either directly through traded yield instruments (eg, interest rate swaps) or indirectly through the prices of bonds (eg, government bonds). Capital markets usually create benchmark yield curves for specific and very liquid market instruments, or for issuers where many different quotes of individual yield information for specific maturities are observable. The standard methods to construct a continuous yield curve from discrete observable yield data quotes are the fit of a mathematical model function, interpolation or regression algorithms. This paper expands these standard methods to include artificial intelligence algorithms, which have the advantage of avoiding any assumptions with regard to the mathematical model functions of the yield curve, and which can conceptually adapt easily to any market changes. Nowadays, the most widely used risk-free yield curve in capital markets is the overnight index swap (OIS) curve, which is derived from observable OISs and is used in this paper as the benchmark curve to derive and compare different yield curve fits.

A Resolution to Valuation Conflicts of Swaptions/Caps and OIS/LIBOR

In this article, the authors provide a unified valuation framework under which a multicurve economy can be established and caps/floors and swaptions can be consistently priced. Furthermore, if a lognormal distribution is employed for the forward price (or 1 plus forward rate), then a “model-free” volatility calibration can be achieved, and all swaptions and caps/floors are perfectly repriced. This article leverages earlier work by Chen, Hsieh, and Huang (2017) who fix a crucial drift-adjustment problem of the traditional LIBOR market model (LMM) where the LIBOR rates follow a lognormal distribution. By assuming 1 + LIBOR to be lognormal (hence LIBOR is shifted lognormal), Chen, Hsieh, and Huang achieve an exact and deterministic drift-adjustment term. In this article, they extend the model to provide a perfect calibration to both swaptions and caps/floors (which is not doable under the traditional LMM), and by using a foreign currency analogy, they show that the model supports multiple curves, which is a key element to overnight index swap (OIS) discounting.

Sparse-Group Independent Component Analysis with application to yield curves prediction

We propose a Sparse-Group Independent Component Analysis (SG-ICA) method to extract independent factors from high dimensional multivariate data. The method provides a unified and flexible framework that automatically identifies the number of factors and simultaneously estimates a sparse loading matrix, enables us to discover important features and offers improved interpretability of the estimators. We establish the consistency and asymptotic normality of the loading matrix estimator, demonstrate its finite sample performance with simulation studies, and illustrate its application using the daily US Overnight Index Swap rates from Oct 2011 to Mar 2015 with 15 maturities ranging from 1 week to 30 years. With higher efficiency of extracting factors, the forecasting performance of the SG-ICA is remarkably better than the popular parametric DNS model in an era of quantitative easing with short-term interest rate being close to zero.

Overnight Index Swap Market-Based Measures of Monetary Policy Expectations

I assess the use of overnight indexed swap (OIS) rates as measures of monetary policy expectations. I find that one to twelve-month US OIS rates provide measures of investors’ interest rate expectations that are comparable to those from corresponding-horizon federal funds futures rates, which have regularly been used as financial market-based measures of US interest rate expectations. More generally, I find that one to 24-month US, euro-zone and Japanese OIS rates and one to 18-month UK OIS rates tend to accurately measure expectations of future short-term interest rates. Motivated by these results, researchers can look to OIS rates as globally comparable measures of monetary policy expectations.

A Macro-financial Analysis of the Corporate Bond Market

We assess the contribution of economic and financial factors in the determination of euro area corporate bond spreads over the period 2001-2015. The proposed multi-market, no-arbitrage affine term structure model is based on the methodology proposed by Dewachter, Iania, Lyrio, and Perea (2015). We model jointly the ‘risk-free curve’, measured by overnight index swap (OIS) rates, and the corporate yield curves for two rating classes (A and BBB). The model includes four spanned and six unspanned factors. We find that, in general, both economic (real activity and inflation) and financial factors (proxying risk aversion, flight to liquidity and general financial market stress) play a significant role in the determination of the spanned factors and hence in the dynamics of the risk-free yield curve and corporate bond spreads. Across the risk-free OIS curve, macroeconomic and financial factors are each responsible on average for explaining 30 and 65 percent of yield variation, respectively. For A-and BBB-rated corporate debt, the selected financial variables explain on average 50 percent of the variation in corporate spreads during the last decade.

Overnight Index Swap Market-Based Measures of Monetary Policy Expectations

Overnight Index Swap Market-Based Measures of Monetary Policy Expectations

Yield Curve Fitting with Artificial Intelligence: A Comparison of Standard Fitting Methods with AI Algorithms

The yield curve is one of the fundamental input parameters of pricing theories in capital markets. Information about yields can be observed in a discrete form either directly through traded yield instruments (e.g. Interest Rate SWAP's) or indirectly through prices of bonds (e.g. Government Bonds). Capital markets usually create benchmark yield curves for specific and very liquid market instruments or issuers where many different quotes of individual yield information for specific maturities are observable. The standard methods to construct a continuous yield curve from the discrete observable yield data quotes are either a fit of a mathematical model function or a splines interpolation. This article expands the standard methods to Artificial Intelligence algorithms, which have the advantage to avoid any assumptions for the mathematical model functions of the yield curve and can conceptually adapt easily to any market changes. Nowadays the most widely used risk free yield curve in capital markets is the OIS curve, which is derived from observable Overnight Index SWAP's and is used in this article as the benchmark curve to derive and compare the different yield curve fits.

Revisiting Interest Rate Swap Valuation with Counterparty Risk, Wrong-Way Risk, and OIS Discounting

This article extends extant valuation models of interest rate swaps with counterparty credit risk by accounting for wrong-way risk and overnight index swap (OIS) discounting. The proposed model extends the models of previous researchers by capturing wrong-way risk in the credit value adjustment (CVA) calculation by way of the correlation between the intensity of default of the counterparty and the market interest rate. Under the proposed no-arbitrage pricing model, cash flows are discounted using OIS rates (mostly used by market practitioners following the 2007–2009 credit crisis), a proxy for risk-free rates. The authors thus propose a unified framework that captures under one umbrella: CVA, wrong-way risk, and OIS discounting. The model parameters are estimated using real market data. Their findings indicate that it is important to account for both counterparty and wrong-way risk in interest rate swap valuation since the two phenomena have nonnegligible impacts on CVA value. Additionally, using OIS rates as risk-free discount rates, the model yields adjustment values higher than those obtained with traditional LIBOR discount rates.

Volatility in the federal funds market and money market spreads during the financial crisis

We analyze the role of federal funds rate volatility in affecting risk premium as measured by various money market spreads during the 2007–2009 financial crisis. We find that volatility in the federal funds market contributed to elevated Overnight Index Swap (OIS) spreads of unsecured bank funding rates during the crisis. Using OIS as a proxy for market expectations, we also decompose London Inter-Bank Offered Rate (Libor) into its permanent and transitory components in a dynamic factor framework and show that increased volatility in the federal funds market contributed to substantial transitory movements of Libor away from its long-run trend during the financial crisis.

Unconventional Monetary Policy in the Eurozone: A Lack of Forward Guidance?

ABSTRACTFrom July to December 2011, the three-month EURIBOR-OIS and EURIBOR-Repo spreads quadrupled and reached 100 basis points due to a stabilization of the EURIBOR and a decrease in the overnight index swap (OIS) and Repo. Using a specific monetary policy announcements and financial indicators database, we find that the European Central Bank’s (ECB’s) unconventional measures did not systematically have a calming effect: Asset buyout announcements decreased market strains, whereas interest rates and liquidity provision announcements did not. Moreover, liquidity provision seems to have a stressing effect. Our findings are consistent with the theoretical underpinnings according to which forward guidance crucially determines the effectiveness of unconventional monetary policies.

Unconventional Monetary Policy in the Euro Zone: A Lack of Forward Guidance?

ABSTRACTFrom July to December 2011, the three-month EURIBOR-OIS and EURIBOR-Repo spreads quadrupled and reached 100 basis points due to a stabilization of the EURIBOR and a decrease in the overnight index swap (OIS) and Repo. Using a specific monetary policy announcements and financial indicators database, we find that the European Central Bank’s (ECB’s) unconventional measures did not systematically have a calming effect: Asset buyout announcements decreased market strains, whereas interest rates and liquidity provision announcements did not. Moreover, liquidity provision seems to have a stressing effect. Our findings are consistent with the theoretical underpinnings according to which forward guidance crucially determines the effectiveness of unconventional monetary policies.

Modeling Money Market Spreads: What Do We Learn About Refinancing Risk?

We quantify the effect of refinancing risk on euro area money market spreads, a major factor driving spreads during the financing crisis. With the advent of the crisis, market participants' perception of their ability to refinance over a given period of time changed radically. As a result, borrowers preferred to obtain funding for longer tenors and lenders were willing to provide funding for shorter tenors. This discrepancy resulted in a need to refinance more frequently in order to borrow over a given horizon, thus increasing refinancing risk. We measure refinancing risk by quantifying the sensitivity of the spread to the refinancing frequency. In order to do so we introduce a model to price EURIBOR-based money market spreads vis-a-vis the overnight index swap. We adopt a methodology akin to a factor model in which the parameters determining the spreads are the intensity of the crisis, its expected half-life, and the sensitivity of spreads to the refinancing frequency. Results suggest that refinancing risk affects the spread significantly across time, albeit in a largely varying manner. Central bank interventions have reduced the spreads as well as the effect of refinancing risk on them.

Modeling Money Market Spreads: What do we Learn about Refinancing Risk?

We quantify the effect of refinancing risk on euro area money market spreads, a major factor driving spreads during the financing crisis. With the advent of the crisis, market participants' perception of their ability to refinance over a given period of time changed radically. As a result, borrowers preferred to obtain funding for longer tenors and lenders were willing to provide funding for shorter tenors. This discrepancy resulted in a need to refinance more frequently in order to borrow over a given horizon, thus increasing refinancing risk. We measure refinancing risk by quantifying the sensitivity of the spread to the refinancing frequency. In order to do so we introduce a model to price EURIBOR-based money market spreads vis-à-vis the overnight index swap. We adopt a methodology akin to a factor model in which the parameters determining the spreads are the intensity of the crisis, its expected half-life, and the sensitivity of spreads to the refinancing frequency. Results suggest that refinancing risk affects the spread significantly across time, albeit in a largely varying manner. Central bank interventions have reduced the spreads as well as the effect of refinancing risk on them.

Modeling Money Market Spreads: What Do We Learn About Refinancing Risk?

We quantify the effect of refinancing risk on euro area money market spreads, a major factor driving spreads during the financing crisis. With the advent of the crisis, market participants' perception of their ability to refinance over a given period of time changed radically. As a result, borrowers preferred to obtain funding for longer tenors and lenders were willing to provide funding for shorter tenors. This discrepancy resulted in a need to refinance more frequently in order to borrow over a given horizon, thus increasing refinancing risk. We measure refinancing risk by quantifying the sensitivity of the spread to the refinancing frequency. In order to do so we introduce a model to price EURIBOR-based money market spreads vis-a-vis the overnight index swap. We adopt a methodology akin to a factor model in which the parameters determining the spreads are the intensity of the crisis, its expected half-life, and the sensitivity of spreads to the refinancing frequency. Results suggest that refinancing risk affects the spread significantly across time, albeit in a largely varying manner. Central bank interventions have reduced the spreads as well as the effect of refinancing risk on them.