Term Structure

Purpose -The purpose of this paper is to investigate the performance of the arbitrage pricing theory (APT) in the Istanbul Stock Exchange (ISE) on a monthly basis, for the period January 2001 to September 2005. Design/methodology/approach -This study examines six pre-specified macroeconomic variables which are: the term structure of interest rate, unanticipated inflation, risk premium, exchange rate and money supply. All these are the same as those used by Chen, Roll and Roll for the US market. In this study, the authors develop one more variable namely unemployment rate, which has a relation with the stock return. Findings -Using the OLS technique, the authors observed that there are some differences among the market portfolios. Before starting to comment on the result of OLS, the serial correlation problem was discussed by using Durbin-Watson statistics. In this study, the critical values were ranged from between 1.33 and 1.81 (T ¼ 57, K ¼ 6). Our test results confirmed that in ten out of the 13 there were no serial correlations. Our results show that there are big differences among market portfolios against macroeconomic variables through the variation of R 2 . In the remaining portfolios; there was no evidence to suggest.

| Acute kidney injury (AKI) as a consequence of ischemia is a common clinical event leading to unacceptably high morbidity and mortality, development of chronic kidney disease (CKD), and transition from pre-existing CKD to end-stage renal disease. Data indicate a close interaction between the many cell types involved in the pathophysiology of ischemic AKI, which has critical implications for the treatment of this condition. Inflammation seems to be the common factor that links the various cell types involved in this process. In this Review, we describe the interactions between these cells and their response to injury following ischemia. We relate these events to patients who are at high risk of AKI, and highlight the characteristics that might predispose these patients to injury. We also discuss how therapy targeting specific cell types can minimize the initial and subsequent injury following ischemia, thereby limiting the extent of acute changes and, hopefully, long-term structural and functional alterations to the kidney.

Résumé : Dans un environnement économique incertain, les taux d’intérêt longs se trouvent très volatiles et leur sensibilité par rapport aux taux courts apparait encore mitigée. Le but de notre travail de recherche est d’analyser cette relation et d’évaluer l’impact de la politique monétaire sur les taux longs tout en envisageant le Maroc comme cas d’application. Pour ce faire, on a utilisé un New Keynesian Model (NKM) augmenté de la structure par terme des taux d’intérêt estimé par la méthode bayésienne sur les données trimestrielles de la période 2004-2015. Le résultat obtenu montre que le taux long augmente suite à une augmentation du taux court ce qui nous permet ainsi de conclure que la politique monétaire au Maroc arrive à influencer les taux d’intérêt à long terme.

Mots clés : Modèle NKM, Politique monétaire, Taux long, Structure par terme
Classification JEL : E12, E52, E43, E30.

Abstract: In an uncertain economic environment, long-term interest rates appear to be highly volatile and their sensitivity towards short-term interest rates appears to be still ambiguous. The aim of this work is to analyze this relationship, and to evaluate the impact of short-term interest rate on long-term interest rate in Morocco. We used a New Keynesian Model augmented with the term structure of interest rates, estimated with Bayesian methods on quarterly data for the period 2004-2015. The result shows that long-term interest rate increases in response to an increase in short term interest rate, which signifies that monetary policy in Morocco has the ability to influence long-term interest rates.

Key words: NKM Model, Monetary Policy, long-term interest rates, term structure
JEL Classification: E12, E52, E43, E30.

We study the implications of imperfect information for term structures of credit spreads on corporate bonds. We suppose that bond investors cannot observe the issuer's assets directly, and receive instead only periodic and imperfect accounting reports. For a setting in which the assets of the firm are a geometric Brownian motion until informed equityholders optimally liquidate, we derive the conditional distribution of the assets, given accounting data and survivorship. Contrary to the perfect-information case, there exists a default-arrival intensity process. That intensity is calculated in terms of the conditional distribution of assets. Credit yield spreads are characterized in terms of accounting information. Generalizations are provided.

The amount of information in the yield curve for forecasting future changes in short rates varies with the maturity of the rates involved. Indeed, spreads between certain long and short rates appear unrelated to future changes in the short rate contrary to the rational expectations hypothesis of the term structure. This paper estimates a daily model of Federal Reserve interest rate targeting behavior, which, accompanied by the maintained hypothesis of rational expectations, explains the varying predictive ability of the yield curve and elucidates the link between Fed policy and the term structure.

This study examined interest rates and the profitability of commercial banks in Nigeria from 1980 – 2014. The objective was to investigate the extent to which various interest rate measures affect profitability performance of the quoted commercial banks. Time series data were sourced from annual financial reports of the commercial banks, and Central Bank of Nigeria (CBN) statistical bulletin various issues. Profitability measures such as Return on Investment (ROI), Return on Assets (ROA) and Return on Equity (ROE) were modeled as the function of Monetary Policy Rate (MPR), Prime Lending Rate (PLR), Short-term Savings Rate (STSR), Long-term Saving Rate (LTSR), Treasury Bill Rate (TBR) and Maximum Lending Rate (MLR). The Ordinary Least Square (OLS) method of Regression Analysis was used to estimate the relationship between the dependent and the independent variables. Augmented Dickey Fuller Test (ADF), Johansen Cointegration Test, Granger Causality Test and Vector Error Correction (VEC) Test were used to determine the dynamic relationship among the variables. Findings showed that the independent variables have greater impact on ROI and ROA than ROE. The Granger Causality proved no casual relationship between the variables. Therefore we recommend that interest rate policies should be integrated with profitability objectives of the commercial banks.

Recent advances in the field of behavioral finance have given a fillip to the use of behavioral factors in asset pricing models. This study adds to the understanding of the REIT return generating process by exploring the behavioral impact of investor sentiment on REIT returns. The results show that when investors are optimistic (pessimistic), REIT returns become higher (lower). These findings are robust when conventional control variables are considered. Empirical analysis indicates steady erosion in the importance of the default and term structure interest rate variables previously considered as important determinants of REIT returns. Previous noise trading papers that consider the impact of institutional traders conclude that institutional investors cannot arbitrage away noise trader risk. The results of this paper find an exception in the case of small REITs. Examination of REITs based on size reveals that the return generating process of small REITs differs from that of mid-size and large REITs. Analysis of the return generating process by performance shows high performance REITs are more sensitive to the independent variables in the model as compared to the low and mid performance REITs.

This paper investigates the informational content of the yield curve in the European market using data on the Italian term structures. According to the expectation hypothesis theory (EHT) the current forward rate equals the future short rate plus a constant risk premium that is time invariant but maturity dependent. This theory has been widely tested in the empirical literature providing various findings according to the country where it has been applied and to the segment of the yield curve examined or the period under study. The standard approach to test the EHT uses the regression techniques assuming data on spot rates and their first differences to be stationary. Recently an increasing number of studies evidenced the non stationarity of interest rates time series and some tests of the EHT are formulated using term spread and forward-spot spread which are stationary. A new strand of literature suggests to investigate the EHT using a restricted VAR framework. In this paper, following [Jondeau, E., Ricart, R., 1999. The expectations hypothesis of the term structure: tests on us, german, french and uk euro-rates. Journal of International Money and Finance 18, 725–750, Ghazali, N.A. Low, S.W., 2002. The expectations hypothesis in emerging financial markets: the case of malaysia. Applied Economics 34, 1147–1156 and Seo, B., 2003. Non linear mean reversion in the term structure of interest rates. Journal of Economic Dynamics and Control 27, 2243–2265], we test if the expectation hypothesis holds using cointegration and error correction analysis. For the period under study results suggest that the long and short term interest rates are cointegrated and therefore subject to a long equilibrium path, providing evidence that the EHT holds for the Italian and the European market.

In this work we analyze market payoffs of Credit Default Swaps (CDS) and we derive rigorous standard market formulas for pricing options on CDS. Formulas are based on modelling CDS spreads which are consistent with simple market payoffs, and we introduce a subfiltration structure allowing all measures to be equivalent to the risk neutral measure.

We review the theories on how liquidity affects the required returns of capital assets and the empirical studies that test these theories. The theory predicts that both the level of liquidity and liquidity risk are priced, and empirical studies find the effects of liquidity on asset prices to be statistically significant and economically important, controlling for traditional risk measures and asset characteristics. Liquidity-based asset pricing empirically helps explain (1) the cross-section of stock returns, (2) how a reduction in stock liquidity result in a reduction in stock prices and an increase in expected stock returns, (3) the yield differential between on-and off-the-run Treasuries, (4) the yield spreads on corporate bonds, (5) the returns on hedge funds, (6) the valuation of closed-end funds, and (7) the low price of certain hard-to-trade securities relative to more liquid counterparts with identical cash flows, such as restricted stocks or illiquid derivatives. Liquidity can thus play a role in resolving a number of asset pricing puzzles such as the small-firm effect, the equity premium puzzle, and the risk-free rate puzzle. * The authors thank Joel Hasbrouck for helpful comments.

The paper deals with the problem of predicting the time to default in credit behavioural scoring. This area opens a possibility of including a dynamic component in behavioural scoring modelling which enables making decisions related to limit, collection and recovery strategies, retention and attrition, as well as providing an insight into the profitability, pricing or term structure of the loan. In this paper, we compare survival analysis and neural networks in terms of modelling and results. The neural network architecture is designed such that its output is comparable to the survival analysis output. Six neural network models were created, one for each period of default. A radial basis neural network algorithm was used to test all six models. The survival model used a Cox modelling procedure. Further, different performance measures of all models were discussed since even in highly accurate scoring models, misclassification patterns appear. A systematic comparison '3 + 2 + 2' procedure is suggested to find the most effective model for a bank. Additionally, the survival analysis model is compared to neural network models according to the relative importance of different variables in predicting the time to default. Although different models can have very similar performance measures they may consist of different variables. The dataset used for the research was collected from a Croatian bank and credit customers were observed during a 12-month period. The paper emphasizes the importance of conducting a detailed comparison procedure while selecting the best model that satisfies the users' interest.

Existing theories of the term structure of swap rates provide an analysis of the Treasury-swap spread based on either a liquidity convenience yield in the Treasury market, or default risk in the swap market. Although these models do not focus on the relation between corporate yields and swap rates (the LIBOR-swap spread), they imply that the term structure of corporate

a b s t r a c t Traumatic brain injury (TBI) in children results in damage to the developing brain, particularly in severely injured individuals. Little is known, however, of the long-term structural aspects of the brain following childhood TBI. This study investigated the integrity of the brain 10 years post-TBI using magnetic resonance imaging volumetrics in a sample of 49 participants with mild, moderate and severe TBI, evaluated against a normative sample of 20 individuals from a pediatric database with comparable age and gender distribution. Structural integrity was investigated in gray and white matter, and by manually segmenting two regions of interest (hippocampus, amygdala), potentially vulnerable to the effects of childhood TBI.

In this paper, we propose a DSGE model with the term structure of interest rates drawing on the framework introduced by Andrés et al. (2004) and . In particular, we reproduce segmentation in financial markets by introducing bonds of different maturities and bond adjustment costs non-zero at the steady state, introducing a structural liquidity frictions among bonds with different maturities: agents are assumed to pay a cost whenever they trade bonds. As a result, the model is able to generate a non-zero demand for bonds of different maturities, which become imperfect substitutes, due to differential liquidity conditions. The main properties of the model are analysed through both simulation and estimation exercises. The importance of the results are twofold. On one hand, the calibrated model is able to replicate the stylized facts regarding the yield curve and the term premium in the US over the period 1987:3-2011:3, without compromising its ability to match macro dynamics. On the other hand, the estimation, besides providing an empirical support to the theoretical setting, highlights the potentialities of the model to analyze the term premium in a microfounded macro framework. The results match very closely the behavior of actual yields, reflecting the recent activity of the Fed on longer maturities bonds.

An important issue in interest rate modeling is the number and nature of the random factors driving the evolution of the yield curve. This paper uses principal component analysis to examine (1) the inherent dimension of historical yield curve changes indicated by the significance of eigenvalues of the covariance matrix, (2) the practical dimension determined by a variance threshold, (3) the shape of the yield curve change associated with the first principal component, and (4) the persistence of this shape over time. We find that although the first two components explain 93% of the sample variation within a 90% confidence interval, the remaining components make statistically significant contribution to the covariance matrix. Consequently, we can establish a practical limit on the dimension only if we are willing to designate a threshold error variance. Further, our results on the persistence of the shape of the yield curve shift associated with the first component depend upon this threshold. If all components are included, the hypothesis that the shape persists between two sample time periods is rejected. On the other hand, if all but the first six components are eliminated, the hypothesis is not rejected.

In this paper we analyze the slope of the term structure of credit spreads. We investigate the explanatory role of interest rate, market and idiosyncratic equity variables, that recent empirical literature has highlighted as important determinants of credit spread levels. This study extends the analysis further and assesses their impact on credit slopes. We find that these factors impact credit spreads at short and long maturities in a significantly different way. A closer inspection of the credit spread slope also reveals that it is a useful indicator of the direction of changes in future short-term credit spreads. This evidence has important implications for the trading and risk management of portfolios of bonds with different maturities. J a n -0 0 J u l -0 0 J a n -0 1 J u l -0 1 basis points CS Level CS Slope CS Curvature . Time series of level, slope, and curvature of the credit spread term structure for A-rated financial bonds (basis points).

This is an attempt to empirically investigate the risk and return relationship of individual stocks traded at Karachi Stock Exchange (KSE), the main equity market in Pakistan. The analysis is based on daily as well as monthly data of 49 companies and KSE 100 index is used as market factor covering the period from July 1993 to December 2004. The

In this paper we solve a two-factor convertible bonds model that ÿts the observed term structure, calibrates the volatility parameters to market data and allows for correlation between the state variables. We propose the method of characteristics together with ÿnite elements for time and space discretization. An empirical investigation into the pricing of National Grid Group's convertible issue produced prediction errors of less than 5% for 215 successive trading days. ? (J. Hatgioannides). 0165-1889/03/$ -see front matter ? 2002 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 5 -1 8 8 9 ( 0 2 ) 0 0 0 8 3 -0

Many finance questions require a full characterization of the distribution of returns. We propose a bivariate model of returns and realized volatility (RV), and explore which features of that time-series model contribute to superior density forecasts over horizons of 1 to 60 days out of sample. This term structure of density forecasts is used to investigate the importance of: the intraday information embodied in the daily RV estimates; the functional form for log(RV ) dynamics; the timing of information availability; and the assumed distributions of both return and log(RV ) innovations. We find that a joint model of returns and volatility that features two components for log(RV ) provides a good fit to S&P 500 and IBM data, and is a significant improvement over an EGARCH model estimated from daily returns.

This paper develops and estimates a macro-finance model that combines a canonical affine no-arbitrage finance specification of the term structure with standard macroeconomic aggregate relationships for output and inflation. From this new empirical formulation, we obtain several important results: (1) the latent term structure factors from finance no-arbitrage models appear to have important macroeconomic and monetary policy underpinnings, (2) there is no evidence of monetary policy inertia or a slow partial adjustment of the policy interest rate by the Federal Reserve, and (3) both forward-looking and backward-looking elements play important roles in macroeconomic dynamics

This paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies 2 stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market price of variance risk makes it optimal for an investor to take short positions in a short-term variance swap contract, long positions in a long-term variance swap contract, and short positions in the stock index. * Egloff, [email protected], QuantCatalyst,

This paper investigates the ability of the Federal Reserve to manipulate the overnight rate without open market operations (which Demiralp and Jorda (2000) term the announcement effect), using high-frequency, open-market-desk data. Using similar data, Hamilton (1997) takes advantage of forecast errors in the Treasury balance to compute the elasticity of the federal funds rate to these errors and thus to obtain a measure of the liquidity effect. Similarly, one can view daily deviations of the federal funds rate from target as forecast errors in the reserve need (see Taylor, 2000). By analyzing the manner and the type of operation the Fed uses to maintain the federal funds rate close to its targeted value and by observing the pattern of operations on the days surrounding a change in this target, we provide evidence of the announcement effect. Furthermore, we show that the discipline of the FOMC schedule dictates, not only the process of expectations formation in the overnight rate, but also the price adjustment process of term rates.

This paper evaluates the tactical asset allocation (TAA) capabilities, strategies and behaviour of Australian investment managers who invest assets across multiple asset classes. Specifically, we analyse the behaviour of balanced, growth and capital stable fund managers with regard to their asset allocation activity across defensive (cash, domestic bonds, overseas bonds) and growth (domestic equities, international equities, property) asset classes, over the period December 1989 to February 2001. Overall, our evidence suggests that active managers have been unable to deliver investors with superior returns through tactical asset allocation. While the most successful asset class, domestic equities, has been value enhancing, international shares and domestic fixed interest have generally detracted value. Finally, across all asset classes examined, our findings suggest that asset allocation into domestic equities is the most influenced by public economic information variables, with shortterm interest rates, the term structure and dividend yield all having a significant explanatory role.

This paper shows how to build in a computationally efficient way a maximum simulated likelihood procedure to estimate the Cox-Ingersoll-Ross model from multivariate time series. The advantage of this estimator is that it takes into account the exact likelihood function while avoiding the huge computational burden associated with MCMC methods and without the ad hoc assumption that certain bond yields are measured without error. The proposed methodology is implemented and tested on simulated data. For realistic parameter values the estimator seems to have good small sample properties, compared to the popular quasi maximum likelihood approach, even using moderate simulation sizes. The effect of simulation errors does not seem to undermine the estimation procedure.

During the past decade, much new research has combined elements of finance, monetary economics and macroeconomics in order to study the relationship between the term structure of interest rates and the economy. In this survey, I describe three different strands of such interdisciplinary macro-finance term structure research. The first adds macroeconomic variables and structure to a canonical arbitrage-free finance representation of the yield curve. The second examines bond pricing and bond risk premiums in a canonical macroeconomic dynamic stochastic general equilibrium model. The third develops a new class of arbitrage-free term structure models that are empirically tractable and well suited to macrofinance investigations.

Plant hydraulic conductance, namely the rate of water flow inside plants per unit time and unit pressure difference, varies largely from plant to plant and under different environmental conditions. Herein the main factors affecting: (a) the scaling between whole-plant hydraulic conductance and leaf area; (b) the relationship between gas exchange at the leaf level and leaf-specific xylem hydraulic conductance; (c) the short-term physiological regulation of plant hydraulic conductance under conditions of ample soil water, and (d) the long-term structural acclimation of xylem hydraulic conductance to changes in environmental conditions are reviewed. It is shown that plant hydraulic conductance is a highly plastic character that varies as a result of multiple processes acting at several time scales. Across species ranging from coniferous and broad-leaved trees to shrubs, crop and herbaceous species, and desert subshrubs, hydraulic conductance scaled linearly with leaf area, as expected from first principles. Despite considerable convergence in the scaling of hydraulic properties, significant differences were apparent across life forms that underlie their different abilities to conduct gas exchange at the leaf level. A simple model of carbon allocation between leaves and support tissues explained the observed patterns and correctly predicted the inverse relationships with plant height. Therefore, stature appears as a fundamental factor affecting gas exchange across plant life forms. Both short-term physiological regulation and long-term structural acclimation can change the levels of hydraulic conductance significantly. Based on a meta-analysis of the existing literature, any change in environmental parameters that increases the availability of resources (either above- or below-ground) results in the long-term acclimation of a less efficient (per unit leaf area) hydraulic system.

It is a common problem in risk management today that risk measures and pricing models are being applied to a very large set of scenarios based on movements in all possible risk factors. The dimensions are so large that the computations become extremely slow and cumbersome, so it is quite common that over-simplistic assumptions will be made. In particular, in order to generate the large covariance matrices that are used in Value-at-Risk models, some very strong constraints are imposed on the movements in volatility and correlations in all the standard models. The constant volatility assumption is also imposed, because it has not been possible to generate large GARCH covariance matrices with mean-reverting term structures. This paper introduces a new method for generating large positive semi-definite covariance matrices. It is based on univariate GARCH volatilities of a few, uncorrelated key risk factors to provide more realistic term structure forecasts in covariance matrices. Alternatively the method can be used with exponentially weighted moving average key risk factor volatilities, where the smoothing constant is automatically determined by the correlation in the system. In addition to implementing multivariate GARCH of arbitrarily large dimension without the need for constrained parameterizations, advantages of this method include: the ability to tailor the amount of noise in the system so that correlation estimates are more stable; and the volatility and correlation forecasting of new issues or illiquid markets in the system.

We develop and test a fast and accurate semi-analytical formula for single-name default swaptions in the context of a shifted square root jump diffusion (SSRJD) default intensity model. The model can be calibrated to the CDS term structure and a few default swaptions, to price and hedge other credit derivatives consistently. We show with numerical experiments that the model implies plausible volatility smiles.

Structural monitoring is essential for ensuring the structural safety performance during the service life. The process is of paramount importance in case of the offshore jacket-type platforms due to the underwater structural parts subjected to the marine environmental conditions. This work is an experimental investigation on a laboratory model of a jacket platform with the objective of establishing a baseline finite element (FE) model for long-term structural health monitoring for this type of structures. A robust damage diagnosis system is also developed which is less sensitive to both the measurements and the modeling uncertainties. Experimental vibration tests are conducted on a physical platform model to obtain dynamic characteristics and then, the initial FE-model of the intact structure is developed to determine them numerically. Some differences between numerically and experimentally identified characteristics emerge due to various uncertainties in the FE-model and measured vibration data. To minimize these differences, initial FE-model is updated according to the experimental results. The updated FE-model is employed to predict the changes in the dynamic characteristics under variety of damage scenarios which are imposed by reducing the stiffness at the components of the model. Fuzzy logic system (FLS) and probabilistic analysis is developed for linguistic classification of damage and global damage diagnosis. Incorporation of the FLS fault isolation technique into FE-model updating method are proposed and evaluated for two different FLS methods to develop a vigorous damage diagnosis method. The efficiency of the technique is validated by different damage scenarios foreseen on the physical model. This technique is shown to be effective for diagnosing the presence of degradation and quantify it.

We implement a model for the estimation of expected bond returns (EBR) based on a discrete time Markov process of rating transition. We use US corporate bond transaction data and a rating agency transition matrix to extract the term structure of EBR. We describe some early results of the properties of this EBR model and outline our plans to explore

It is now widely accepted that stochastic mortality -the risk that aggregate mortality might differ from that anticipated -is an important risk factor in both life insurance and pensions. As such it affects how fair values, premium rates, and risk reserves are calculated.

For many years, stainless steel, cobalt-chromium, and titanium alloys have been the primary biomaterials used for load-bearing applications. However, as the need for structural materials in temporary implant applications has grown, materials that provide short-term structural support and can be reabsorbed into the body after healing are being sought. Since traditional metallic biomaterials are biocompatible but not biodegradable, the potential for magnesium-based alloys, which are biodegradable and bioabsorbable, in biomedical applications has gained more interest. Biodegradable and bioabsorbable magnesium-based alloys provide a number of benefits over traditional permanent implants. This paper summarizes the history and current status of magnesium as a bioabsorbable implant material. Also discussed is the development of a magnesium-zinc-calcium alloy that demonstrates promising degradation behavior relative to a commercially available Mg and magnesium-aluminum-zinc alloy.

We discuss extensions of reduced-form and structural models for pricing credit risky securities to portfolio simulation and valuation. Stochasticity in interest rates and credit spreads is captured via reduced-form models and is incorporated with a default and migration model based on the structural credit risk modelling approach. Calculated prices are consistent with observed prices and the term structure of default-free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds and the sensitivity of future portfolio valuation with respect to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) study of the structure of credit risk by investigating the impact of disparate risk factors on portfolio risk, and (iii) tracking of corporate bond indices via simulation and optimisation models. In particular, we study the effect of uncertainty in credit spreads and interest rates on the overall risk of a credit portfolio, a topic that has been recently discussed by Kiesel et al. [The structure of credit risk: spread volatility and ratings transitions. Technical report, Bank of England, ISSN 1268ISSN -5562, 2001], but has been otherwise mostly neglected. We find that spread risk and interest rate risk are important factors that do not diversify away in a large portfolio context, especially when high-quality instruments are considered.

The Svensson generalization of the popular Nelson-Siegel term structure model is widely used by practitioners and central banks. Unfortunately, like the original Nelson-Siegel specification, this generalization, in its dynamic form, does not enforce arbitrage-free consistency over time. Indeed, we show that the factor loadings of the Svensson generalization cannot be obtained in a standard finance arbitrage-free affine term structure representation. Therefore, we introduce a closely related generalized Nelson-Siegel model on which the no-arbitrage condition can be imposed. We estimate this new arbitrage-free generalized Nelson-Siegel model and demonstrate its tractability and good in-sample fit. ). The Svensson extension adds a second curvature term, which allows for a better fit at long maturities. Following Diebold and

Riding the yield curve, the fixed-income strategy of purchasing a longerdated security and selling before maturity, has long been a popular means to achieve excess returns compared to buying-and-holding, despite its implicit violations of market efficiency and the pure expectations hypothesis of the term structure. This paper looks at the historic excess returns of different strategies across three countries and proposes several statistical and macro-based trading rules which seem to enhance returns even more. While riding based on the Taylor Rule works well even for longer investment horizons, our empirical results indicate that, using expectations implied by Fed funds futures, excess returns can only be increased over short horizons. Furthermore, we demonstrate that duration-neutral strategies are superior to standard riding on a risk-adjusted basis. Overall, our evidence stands in contrast to the pure expectations hypothesis and points to the existence of risk premia which may be exploited consistently.

In this chapter, we consider a theoretical model for the pricing and valuation of guaranteed annuity conversion options associated with certain unit-linked pension contracts in the UK. The valuation approach is based on the similarity between the payoff structure of the contract and a call option written on a coupon-bearing bond. The model makes use of a one-factor Heath-Jarrow-Morton framework for the term structure of interest rates, in order to obtain a closed-form analytical solution to the fair valuation of the liabilities implied by these contracts. Mortality risk is incorporated via a stochastic model for the evolution over time of the underlying hazard rates. Numerical results are investigated and the sensitivity of the price of the option to changes in the key financial and mortality parameters is also analyzed.

The challenge of sustainable development presents our society with the need for long-term structural changes or transitions in sectors such as energysupply, mobility, agriculture and health-care. Based on a multi-phase and multi-level framework for transitions, we ask whether managing transitions is possible, and then outline an operational method for transition management.

Red and Blue America has become the spatial metaphor for an electoral divide on two main dimensions e a nonmetropolitan Red and a larger metropolitan Blue, and a traditionalist Red and a more modern Blue. In this paper, we evaluate the validity and consistency of this conventional wisdom, using both the 2000 and 2004 presidential elections results by county. While previous research has underscored the overall pattern and its accuracy, we choose instead to explore mainly the anomalous results: ''metropolitan'' or ''modern'' areas that President Bush carried, and ''nonmetropolitan'' and ''traditional'' areas that Democrats won. We develop a typology of the anomalous counties and carry out a simple analysis of characteristics that help show how and why they are anomalous. We then compare the 2000 and 2004 results to discover anomalous areas, counties which switched parties or which became more or less partisan. Trends between 2000 and 2004 suggest a weakening of the metropolitan and nonmetropolitan dimension but a deepening of the cultural one, although we note as well that most of the electorate does not place itself at these partisan extremes. We relate these findings to longer term structural changes in American society, and to Republican strategies to mobilize insecure voters. Finally, we lay out an agenda to look at a sample of counties, using qualitative methods, in order to understand these anomalous results.

We develop multi-period dynamic models for fixed-income portfolio management under uncertainty, using multi-stage stochastic programming with recourse. The models integrate the prescriptive stochastic programs with descriptive Monte Carlo simulation models of the term structure of interest rates.

It is now widely accepted that stochastic mortality -the risk that aggregate mortality might differ from that anticipated -is an important risk factor in both life insurance and pensions. As such it affects how fair values, premium rates, and risk reserves are calculated.

In the present paper we introduce a two-dimensional shifted square-root diffusion (SSRD) model for interest rate derivatives and single-name credit derivatives, in a stochastic intensity framework. The SSRD is the unique model, to the best of our knowledge, allowing for an automatic calibration of the term structure of interest rates and of credit default swaps (CDS's). Moreover, the model retains free dynamics parameters that can be used to calibrate option data, such as caps for the interest rate market and options on CDS's in the credit market. The calibrations to the interest-rate market and to the credit market can be kept separate, thus realizing a superposition that is of practical value. We discuss the impact of interest-rate and default-intensity correlation on calibration and pricing, and test it by means of Monte Carlo simulation. We use a variant of Jamshidian's decomposition to derive an analytical formula for CDS options under CIR++ stochastic intensity. Finally, we develop an analytical approximation based on a Gaussian dependence mapping for some basic credit derivatives terms involving correlated CIR processes.

We adopt a statistical approach to identify the shocks that explain most of the fluctuations of the slope of the term structure of interest rates. We find that one single shock can explain the majority of all unpredictable movements in the slope over a 10-year forecast horizon. Impulse response functions lead us to interpret this shock as news about future