Yield Curve Level Research Articles

Why Does the Cieslak–Povala Model Predict Treasury Returns? A Reinterpretation

This article presents a simple reformulation of the restricted Cieslak and Povala return-predicting factor, which retains by construction exactly the same (impressive) explanatory power as the original but affords an alternative and attractive interpretation. What determines the future returns, the new formulation shows, is a function of the distance of the yield-curve level and the slope not from a fixed reference level, but from a <i>conditional</i> one, determined by a function of the long-term inflation. The decomposition also allows a clear attribution of the predictive power of the Cieslak and Povala factor between the conditional level and slope deviations. The authors present new empirical evidence to show that, consistent with the interpretation they present, inflation surprises are powerful out-of-sample predictors of Treasury excess returns.

The maturity of sovereign debt issuance in the euro area.

We use information on new sovereign debt issues in the euro area to explore the drivers behind the debt maturity decisions of governments. We set up a theoretical model for the maturity structure that trades off the preference for liquidity services provided by short-term debt, roll-over risk and price risk. The average debt maturity is negatively related to both the level and the slope of the yield curve. A panel VAR analysis shows that positive shocks to risk aversion, the probability of non-repayment and the demand for the liquidity services of short-term debt all have a positive effect on the yield curve level and slope, and a negative effect on the average maturity of new debt issues. These results are partially in line with our theoretical framework. A forecast error variance decomposition suggests that changes in the probability of non-repayment as captured by the expected default frequency extracted from credit default spreads are the most important source of shocks.

The Maturity of Sovereign Debt Issuance in the Euro Area

We use information on new sovereign debt issues in the euro area to explore the drivers behind the debt maturity decisions of governments. We set up a theoretical model for the maturity structure that trades off the preference for liquidity services provided by short-term debt, roll-over risk and price risk. The average debt maturity is negatively related to both the level and the slope of the yield curve. A panel VAR analysis shows that positive shocks to risk aversion, the probability of non-repayment and the demand for the liquidity services of short-term debt all have a positive effect on the yield curve level and slope, and a negative effect on the average maturity of new debt issues. These results are partially in line with our theory. A forecast error variance decomposition suggests that changes in the probability of non-repayment as captured by the expected default frequency extracted from credit default spreads are the most important source of shocks.

Price and Size Discovery in Financial Markets: Evidence from the U.S. Treasury Securities Market

Abstract We study the workup protocol, an important size discovery mechanism in the U.S. Treasury market. We find that workup order flow shocks explain 6%–8% of the variation of returns on benchmark notes and, across maturities, 10% of the variation of the yield curve level factor. Information related to proprietary client order flow is more likely to show up in workup trades, whereas information derived from public announcements tends to come through preworkup trades. Our findings highlight how the nature of information affects the trade-off between speed and execution price when informed traders choose between the lit and workup channels. Received May 3, 2017; Editorial decision August 1, 2018 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online. Internet Appendix tables are numbered with “IA” prefix.

An Interpretation of the Cieslak-Povala Return-Predicting Factor

This paper presents a simple reformulation of the restricted Cieslak and Povala (2010) return-predicting factor which retains by construction exactly the same (impressive) explanatory power as the original one, but affords an alternative and attractive interpretation. What determines the future returns, the new factor shows, is a function of the distance of the yield-curve level and the slope not from a fixed reference level, but from a conditional one, determined by a function of the long-term inflation.The decomposition also allows a clear attribution of the predictive power of the Cieslak and Povala factor between the conditional level and slope deviations.Finally, the new reformulation shows that once the conditionality is taken into account, level deviations are important predictors of excess returns. (Hardly any predictability was found in earlier studies for the unconditional level.)

Dynamics of the term structure of interest rates and monetary policy: is monetary policy effective during zero interest rate policy?

The monetary policy targets the short rates; however, during zero interest rate policy (ZIRP), the short end of the yield curve cannot serve as a policy instrument. Relying on the joint yields-macro latent factors model, this study empirically examines the effect of monetary policy stances on term structure and the possible feedback effect on the real sector using the Japanese experience of ZIRP. The analysis indicates that it is the entire term structure that transmits the policy shocks to the real economy rather than the yield spread only. The monetary policy signals pass through the yield curve level and slope factors to stimulate the economic activity. The curvature factor, besides reflecting the cyclical fluctuations of the economy, acts as a leading indicator for future inflation. In addition, policy influence tends to be low as the short end becomes segmented toward medium/long-term of the yield curve. Furthermore, volatility in bond markets is found to be asymmetrically affected by positive and negative shocks and long end tends to be less sensitive to stochastic shocks than the short maturities. The expectation hypothesis of the term structure does not hold during the ZIRP period.

Quantitative easing, credibility and the time-varying dynamics of the term structure of interest rate in Japan

A key issue in current research about quantitative easing monetary policy (QEMP) is the ability of this strategy to impact the term structure of interest rates. Using a dynamic model for the yield curve with time-varying-parameters to the Japanese data, we provide three insights. First, the expectations hypothesis of the term structure of interest rates is generally supported even during the QEMP period. Second, the estimation results reveal that the contribution of macroeconomic variables on the variation of the yield curve is relatively small, especially during the QEMP period. As for the feed-back effect, the yield curve factors contribute only marginally to inflation variation. However, they account for more relevant part of output gap dynamics. Third, the monetary policy shock has a significant effect on yield curve level factor only during the high interest rate periods. However, the decline in the level factor during the QEMP period, while insignificant, indicates a strengthening credibility of the Bank of Japan and thus the effectiveness of its policy.

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Yield Curve Factors, Factor Volatilities, and the Predictability of Bond Excess Returns

We introduce a Nelson-Siegel type interest rate term structure model with the underlying yield factors following autoregressive processes revealing time-varying stochastic volatility. The factor volatilities capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve's level, slope and curvature. Estimating the model based on U.S. government bond yields applying Markov chain Monte Carlo techniques we find that the yield factors and factor volatilities follow highly persistent processes. Using the extracted factors to explain one-year-ahead bond excess returns we observe that the slope and curvature yield factors contain the same explanatory power as the return-forecasting factor recently proposed by Cochrane and Piazzesi (2005). Moreover, we identify slope and curvature risk as important additional determinants of future excess returns. Finally, we illustrate that the yield and volatility factors are closely connected to variables reflecting macroeconomic activity, inflation, monetary policy and employment growth. It is shown that the extracted yield curve components have long-term prediction power for macroeconomic fundamentals.

A Multi-Factor Model for the Valuation and Risk Managment of Demand Deposits

How should we value and manage deposit accounts where deposits have a zero contractual maturity, but which, in practice, remain stable through time and are remunerated below market rates? Does the economic value of the deposit account differ from the face value and can we reliably measure it? To what extent is the economic value sensitive to yield curve changes? In this paper, we try to answer the above questions. The valuation is performed on yield curve, deposit rate and deposit balance data between December 1994 and June 2005 for a sample of Belgian bank retail savings deposits accounts. We find that the deposits premium component of Belgian savings deposits is economically and statistically significant, though sensitive to assumptions about servicing costs and outstanding balances average decay rates. We also find that deposit liability values depreciate significantly when market rates increase, thereby offsetting some of the value losses on the asset side. The hedging characteristics of deposit accounts depend primarily on the nature of the underlying interest rate shock (yield curve level versus slope shock) and on the average decay rate. We assess the reliability of the reported point estimates and also report corresponding duration estimates that results from a dynamic replicating portfolio model approach more commonly used by large international banks.

A new measure of cross-sectional risk and its empirical implications for portfolio risk management

Litterman et al. [Litterman, R., Scheinkman, J., Weiss, L., 1991. Volatility and the yield curve. Journal of Fixed Income 1 (June), 49–53] and Engle and Ng [Engle, R.F., Ng, V.K., 1993. Time-varying volatility and the dynamic behavior of the term structure. Journal of Money, Credit and Banking 25(3), 336–349] provide empirical evidence of a relation between yield curve shape and volatility. This study offers theoretical support for that finding in the general context of cross-sectional time series. We introduce a new risk measure quantifying the link between cross-sectional shape and market risk. A simple econometric procedure allows us to represent the risk experienced by cross-sections over a time period in terms of independent factors reproducing possible cross-sectional deformations. We compare our risk measure to the traditional cross-yield covariance according to their relative performance. Empirical investigation in the US interest rate market shows that (1) cross-shape risk factors outperform cross-yield risk factors (i.e., yield curve level, slope, and convexity) in explaining the market risk of yield curve dynamics; (2) hedging multiple liabilities against cross-shape risk delivers superior trading strategies compared to those stemming from cross-yield risk management.

A New Measure of Cross-Sectional Risk and its Empirical Implications for Portfolio Risk Management

Litterman, Scheinkman, and Weiss (1991) and Engle and Ng (1993) provide empirical evidence of a relation between yield curve shape and volatility. This study offers theoretical support for that finding in the general context of cross-sectional time series. We introduce a new risk measure quantifying the link between cross-sectional shape and market risk. A simple econometric procedure allows us to represent the risk experienced by cross-sections over a time period in terms of independent factors reproducing possible cross-sectional deformations. We compare our risk measure to the traditional cross-yield covariance according to their relative performance. Empirical investigation in the US interest rate market shows that 1) cross-shape risk factors outperform cross-yield risk factors (i.e., yield curve level, slope, and convexity) in explaining the market risk of yield curve dynamics; 2) hedging multiple liabilities against cross-shape risk delivers superior trading strategies compared to those stemming from cross-yield risk management.