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Forecasting the future movement of yield curves contains valuable information for both academic and practical issues such as bonding pricing, portfolio management, and government policies. The purpose of this paper is to develop a dynamic factor approach that can provide more precise and consistent forecasting results under various yield curve dynamics.

The paper develops a unified dynamic factor model based on Diebold and Li (2006) and Nelson and Siegel (1987) three-factor model to forecast the future movement yield curves. The authors apply the state-space model and the Kalman filter to estimate parameters and extract factors from the US yield curve data.

The authors compare both in-sample and out-of-sample performance of the dynamic approach with various existing models in the literature, and find that the dynamic factor model produces the best in-sample fit, and it dominates existing models in medium- and long-horizon yield curve forecasting performance.

The authors find that the dynamic factor model and the Kalman filter technique should be used with caution when forecasting short maturity yields on a short time horizon, in which the Kalman filter is prone to trade off out-of-sample robustness to maintain its in-sample efficiency.

Bond analysts and portfolio managers can use the dynamic approach to do a more accurate forecast of yield curve movements.

The enhanced forecasting approach also equips the government with a valuable tool in setting macroeconomic policies.

The dynamic factor approach is original in capturing the level, slope, and curvature of yield curves in that the decay rate is set as a free parameter to be estimated from yield curve data, instead of setting it to be a fixed rate as in the existing literature. The difference range of estimated decay rate provides richer yield curve dynamics and is the key to stronger forecasting performance.

This study investigates the relation between two kinds of par yield curves estimated in Korean bond market: benchmark par yield curve and company par yield curve. The former is published as a benchmark for corporate bonds with a given credit rating and the latter is utilized for valuing a specific corporate bond. Spot rate curves are extracted from the par yield curves by applying bootstrapping method. The spreads between the two spot rate curves are analyzed for 7 years (2005~2012) of corporate bond transaction data. Six results are obtained from various sub-samples classified by credit rating and maturity. 1) Most of the sample means of the spreads are above zero. 2) Negative average spreads are found mainly from the sample of BBB rated bonds. 3) Average spreads from the sample with credit greater than or equal to A tend to positively related with credit risk. 4) Absolute value of the average spreads are positively related with credit risk. 5) The average spreads are increased rapidly after the year of 2009. 6) The proportion of sub-samples having negative average spreads are decreased as the average maturity of the sample is shortened.

The purpose of this paper is to forecast future inflation using a joint model of the nominal and real yield curves estimated with survey data. The model is arbitrage free and embodies incompleteness between the nominal and real bond markets.

The methodology is based on the affine class of term structure of interest rate. The model is estimated using the Kalman filter technique.

The authors show that the inclusion of survey data in the estimation procedure improves significantly the inflation forecasting. Moreover, the authors find that the monetary policy has significant effects on the inflation expectation and risk premium.

This paper is the first to estimate inflation using a joint model of nominal and real yield curves with Brazilian data. Moreover, the authors propose a simple arbitrage-free model that takes it account incompleteness between the nominal and real bond markets.

The purpose of this study is to examine the pertinence of combining the positioning along the US presidential election cycle and the inversions of the yield curve as a guide for a market timing strategy on the S&P 500. These variables provide warning signals for either an abnormally high probability of tighter future economic conditions or an abnormally high probability of more accommodative future economic conditions, not both. As such, they represent natural complement.

The combination of the two variables leads to four scenarios: inverted yield curve or not and first half or second half of the presidential cycle. Two timing strategies are proposed to act on these scenarios: the “type T” strategy for Traditional investors not allowed to sell short and focusing on active risk focus and the “type H” strategy for Hedge Fund‐like investors focusing on absolute risk.

Compared to a buy‐and‐hold investment in the S&P 500, the “type H” version increases the return per unit of risk from 0.81 to 1.10 and the “type T” delivers an annualized information ratio of 0.62. Robustness tests show that the strategy adds value under both specifications in the majority of 1‐, 3‐ and 10‐year sub‐periods. Application of the Henriksson‐Merton test confirms that the two strategies have a genuine market timing ability.

While the predictive variables have been investigated on a standalone basis, the idea of combining these two predictors is new. The idea of examining market timing from the perspective of both traditional investor and hedge fund like investor is also original.

This chapter examines the impact of price fluctuations in foreign stock markets on the stock prices of domestic banks in Korea, Malaysia, Singapore, and Thailand. Some studies have argued that the 2007–2009 global financial crisis (GFC) affected domestic banks less in East Asia, even though the supporting evidence is rather limited. Employing a multinomial logit model, we estimate how changes in the United States and Japanese stock markets affected the banking sectors in the sampled countries before the 1997 Asian financial crisis, and before and during the more recent GFC. We interpret the number of banks in a given country that experienced a large price shock on the same day (or “coexceedance”) as shocks to the domestic banking sector. The results suggest that fluctuations in foreign stock market indices exerted a larger impact on the prices of East Asian banking stocks during the 2000s than during the 1990s. In addition, although the shocks brought about by the deterioration of foreign stock markets were significant before the GFC, both increases and decreases in foreign stock prices significantly affected the banking sectors of the respective countries during the crisis. Lastly, we conclude that increasing foreign capital flows and foreign assets and liabilities greatly influenced domestic banking systems in East Asia during the 2000s.

Recent U.S. Treasury yields have been constrained to some extent by the zero lower bound (ZLB) on nominal interest rates. Therefore, we compare the performance of a standard affine Gaussian dynamic term structure model (DTSM), which ignores the ZLB, to a shadow-rate DTSM, which respects the ZLB. Near the ZLB, we find notable declines in the forecast accuracy of the standard model, while the shadow-rate model forecasts well. However, 10-year yield term premiums are broadly similar across the two models. Finally, in applying the shadow-rate model, we find no gain from estimating a slightly positive lower bound on U.S. yields.

This paper aims to propose a scenario-based approach for measuring interest rate risks. Many regulatory capital standards in banking and insurance make use of similar approaches. The authors provide a theoretical justification and extensive backtesting of our approach.

The authors theoretically derive a scenario-based value-at-risk for interest rate risks based on a principal component analysis. The authors calibrate their approach based on the Nelson–Siegel model, which is modified to account for lower bounds for interest rates. The authors backtest the model outcomes against historical yield curve changes for a large number of generated asset–liability portfolios. In addition, the authors backtest the scenario-based value-at-risk against the stochastic model.

The backtesting results of the adjusted Nelson–Siegel model (accounting for a lower bound) are similar to those of the traditional Nelson–Siegel model. The suitability of the scenario-based value-at-risk can be substantially improved by allowing for correlation parameters in the aggregation of the scenario outcomes. Implementing those parameters is straightforward with the replacement of Pearson correlations by value-at-risk-implied tail correlations in situations where risk factors are not elliptically distributed.

The paper assumes deterministic cash flow patterns. The authors discuss the applicability of their approach, e.g. for insurance companies.

The authors’ approach can be used to better communicate interest rate risks using scenarios. Discussing risk measurement results with decision makers can help to backtest stochastic-term structure models.

The authors’ adjustment of the Nelson–Siegel model to account for lower bounds makes the model more useful in the current low-yield environment when unjustifiably high negative interest rates need to be avoided. The proposed scenario-based value-at-risk allows for a pragmatic measurement of interest rate risks, which nevertheless closely approximates the value-at-risk according to the stochastic model.

This paper provides an objective approach based on available market information capable of reducing subjectivity, inherently present in the process of expected loss provisioning under the IFRS 9.

This paper develops the two-step methodology. Calibrating the Credit Default Swap (CDS)-implied default probabilities to the through-the-cycle default frequencies provides average weights of default component in the spread for each forward term. Then, the impairment provisions are calculated for a sample of investment grade and high yield obligors by distilling their pure default-risk term-structures from the respective term-structures of spreads. This research demonstrates how to estimate credit impairment allowances compliant with IFRS 9 framework.

This study finds that for both investment grade and high yield exposures, the weights of default component in the credit spreads always remain inferior to 33%. The research's outcomes contrast with several previous results stating that the default risk premium accounts at least for 40% of CDS spreads. The proposed methodology is applied to calculate IFRS 9 compliant provisions for a sample of investment grade and high yield obligors.

Many issuers are not covered by individual Bloomberg valuation curves. However, the way to overcome this limitation is proposed.

The proposed approach offers a clue for a better alignment of accounting practices, financial regulation and credit risk management, using expected loss metrics across diverse silos inside organizations. It encourages adopting the proposed methodology, illustrating its application to a set of bond exposures.

No previous research addresses impairment provisioning employing Bloomberg valuation curves. The study fills this gap.

The purpose of this paper is to present several methods on how to deal with yield surface discontinuities. The explicit formulations, first presented by Koiter (1953), result in multisingular constitutive matrices which can cause numerical problems in elasto-plastic finite element calculations. These problems, however, are not documented in previous literature. In this paper an amendment to the Koiter formulation of the constitutive matrices for stress points located on discontinuities is proposed.

First, a review of existing methods of handling yield surface discontinuities is given. Examples of the numerical problems of the methods are presented. Next, an augmentation of the existing methods is proposed and its robustness is demonstrated through footing bearing capacity calculations that are usually considered “hard”.

Previous studies documented in the literature all present “easy” calculation examples, e.g. low friction angles and few elements. The amendments presented in this paper result in robust elasto-plastic computations, making the solution of “hard” problems possible without introducing approximations in the yield surfaces. Examples of “hard” problems are highly frictional soils and/or three-dimensional geometries.

The proposed method makes finite element calculations using yield criteria with corners and apices, e.g. Mohr-Coulomb and Hoek-Brown, much more robust and stable.