On the Sources of Uncertainty in Exchange Rate Predictability

We analyse the role of time-variation in coefficients and other sources of uncertainty in exchange rate forecasting regressions. Our techniques incorporate the notion that the relevant set of predictors and their corresponding weights, change over time. We find that predictive models which allow for sudden rather than smooth, changes in coefficients significantly beat the random walk benchmark in out-of-sample forecasting exercise. Using innovative variance decomposition scheme, we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients' variability, as the main factors hindering models' forecasting performance. The uncertainty regarding the choice of the predictor is small.

Term Structure Dynamics, Macro-Finance Factors and Model Uncertainty

This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and volatilities, and our model averaging method allows for investors' model uncertainty over time. Our time-varying parameter Nelson-Siegel Dynamic Model Averaging (NS-DMA) predicts yields better than standard benchmarks and successfully captures plausible time-varying term premia in real time. The proposed model has significant in-sample and out-of-sample predictability for excess bond returns, and the predictability is of economic value.

State-dependent threshold STAR models

In this paper we consider extensions of smooth transition autoregressive (STAR) models to situations where the threshold is a time-varying function of variables that affect the separation of regimes of the time series under consideration. Our specification is motivated by the observation that unusually high/low values for an economic variable may sometimes be best thought of in relative terms. State-dependent logistic STAR and contemporaneous-threshold STAR models are introduced and discussed. These models are also used to investigate the dynamics of U.S. short-term interest rates, where the threshold is allowed to be a function of past output growth and inflation.

How does monetary policy change? evidence on inflation targeting countries

We examine the evolution of monetary policy rules in a group of inflation targeting countries (Australia, Canada, New Zealand, Sweden and the United Kingdom) applying moment- based estimator at time-varying parameter model with endogenous regressors. Using this novel flexible framework, our main findings are threefold. First, monetary policy rules change gradually pointing to the importance of applying time-varying estimation framework. Second, the interest rate smoothing parameter is much lower that what previous time-invariant estimates of policy rules typically report. External factors matter for all countries, albeit the importance of exchange rate diminishes after the adoption of inflation targeting. Third, the response of interest rates on inflation is particularly strong during the periods, when central bankers want to break the record of high inflation such as in the U.K. or in Australia at the beginning of 1980s. Contrary to common wisdom, the response becomes less aggressive after the adoption of inflation targeting suggesting the positive effect of this regime on anchoring inflation expectations. This result is supported by our finding that inflation persistence as well as policy neutral rate typically decreased after the adoption of inflation targeting.

Monetary policy rules and financial stress: does financial instability matter for monetary

We examine whether and how main central banks responded to episodes of financial stress over the last three decades. We employ a new methodology for monetary policy rules estimation, which allows for time-varying response coefficients as well as corrects for endogeneity. This flexible framework applied to the U.S., U.K., Australia, Canada and Sweden together with a new financial stress dataset developed by the International Monetary Fund allows not only testing whether the central banks responded to financial stress but also detects the periods and type of stress that were the most worrying for monetary authorities and to quantify the intensity of policy response. Our findings suggest that central banks often change policy

A gamma camera count rate saturation correction method for whole-body planar imaging.

Whole-body (WB) planar imaging has long been one of the staple methods of dosimetry, and its quantification has been formalized by the MIRD Committee in pamphlet no 16. One of the issues not specifically addressed in the formalism occurs when the count rates reaching the detector are sufficiently high to result in camera count saturation. Camera dead-time effects have been extensively studied, but all of the developed correction methods assume static acquisitions. However, during WB planar (sweep) imaging, a variable amount of imaged activity exists in the detector's field of view as a function of time and therefore the camera saturation is time dependent. A new time-dependent algorithm was developed to correct for dead-time effects during WB planar acquisitions that accounts for relative motion between detector heads and imaged object. Static camera dead-time parameters were acquired by imaging decaying activity in a phantom and obtaining a saturation curve. Using these parameters, an iterative algorithm akin to Newton's method was developed, which takes into account the variable count rate seen by the detector as a function of time. The algorithm was tested on simulated data as well as on a whole-body scan of high activity Samarium-153 in an ellipsoid phantom. A complete set of parameters from unsaturated phantom data necessary for count rate to activity conversion was also obtained, including build-up and attenuation coefficients, in order to convert corrected count rate values to activity. The algorithm proved successful in accounting for motion- and time-dependent saturation effects in both the simulated and measured data and converged to any desired degree of precision. The clearance half-life calculated from the ellipsoid phantom data was calculated to be 45.1 h after dead-time correction and 51.4 h with no correction; the physical decay half-life of Samarium-153 is 46.3 h. Accurate WB planar dosimetry of high activities relies on successfully compensating for camera saturation which takes into account the variable activity in the field of view, i.e. time-dependent dead-time effects. The algorithm presented here accomplishes this task.

Essays in higher moment asset pricing and liquidity risk

This thesis focuses on theoretical asset pricing models and their empirical applications. I aim to investigate the following noteworthy problems: i) if the relationship between asset prices and investors' propensities to gamble and to fear disaster is time varying, ii) if the conflicting evidence for the firm and market level skewness can be explained by downside risk, Hi) if costly learning drives liquidity risk. Moreover, empirical tests support the above assumptions and provide novel findings in asset pricing, investment decisions, and firms' funding liquidity. The first chapter considers a partial equilibrium model where investors have heterogeneous propensities to gamble and fear disaster. Skewness preference represents the desire to gamble, while kurtosis aversion represents fear of extreme returns. Using US data from 1988 to 2012, my model demonstrates that in bad times, risk aversion is higher, more people fear disaster, and fewer people gamble, in contrast to good times. This leads to a new empirical finding: gambling preference has a greater impact on asset prices during market downturns than during booms. The second chapter consists of two essays. The first essay introduces a foramula based on conditional CAPM for decomposing the market skewness. We find that the major market upward and downward movements can be well preadicted by the asymmetric comovement of betas, which is characterized by an indicator called "Systematic Downside Risk" (SDR). We find that SDR can efafectively forecast future stock market movements and we obtain out-of-sample R-squares (compared with a strategy using historical mean) of more than 2.27% with monthly data. The second essay reconciles a well-known empirical fact: aggregating positively skewed firm returns leads to negatively skewed market return. We reconcile this fact through firms' greater response to negative maraket news than positive market news. We also propose several market return predictors, such as downside idiosyncratic skewness. The third chapter studies the funding liquidity risk based on a general equialibrium model which features two agents: one entrepreneur and one external investor. Only the investor needs to acquire information to estimate the unobservable fundamentals driving the economic outputs. The novelty is that information acquisition is more costly in bad times than in good times, i.e. counter-cyclical information cost, as supported by previous empirical evidence. Later we show that liquidity risks are principally driven by costly learning. Résumé Cette thèse présente des modèles théoriques dévaluation des actifs et leurs applications empiriques. Mon objectif est d'étudier les problèmes suivants: la relation entre l'évaluation des actifs et les tendances des investisseurs à parier et à crainadre le désastre varie selon le temps ; les indications contraires pour l'entreprise et l'asymétrie des niveaux de marché peuvent être expliquées par les risques de perte en cas de baisse; l'apprentissage coûteux augmente le risque de liquidité. En outre, des tests empiriques confirment les suppositions ci-dessus et fournissent de nouvelles découvertes en ce qui concerne l'évaluation des actifs, les décisions relatives aux investissements et la liquidité de financement des entreprises. Le premier chapitre examine un modèle d'équilibre où les investisseurs ont des tendances hétérogènes à parier et à craindre le désastre. La préférence asymétrique représente le désir de parier, alors que le kurtosis d'aversion représente la crainte du désastre. En utilisant les données des Etats-Unis de 1988 à 2012, mon modèle démontre que dans les mauvaises périodes, l'aversion du risque est plus grande, plus de gens craignent le désastre et moins de gens parient, conatrairement aux bonnes périodes. Ceci mène à une nouvelle découverte empirique: la préférence relative au pari a un plus grand impact sur les évaluations des actifs durant les ralentissements de marché que durant les booms économiques. Exploitant uniquement cette relation générera un revenu excédentaire annuel de 7,74% qui n'est pas expliqué par les modèles factoriels populaires. Le second chapitre comprend deux essais. Le premier essai introduit une foramule base sur le CAPM conditionnel pour décomposer l'asymétrie du marché. Nous avons découvert que les mouvements de hausses et de baisses majeures du marché peuvent être prédits par les mouvements communs des bêtas. Un inadicateur appelé Systematic Downside Risk, SDR (risque de ralentissement systématique) est créé pour caractériser cette asymétrie dans les mouvements communs des bêtas. Nous avons découvert que le risque de ralentissement systématique peut prévoir les prochains mouvements des marchés boursiers de manière efficace, et nous obtenons des carrés R hors échantillon (comparés avec une stratégie utilisant des moyens historiques) de plus de 2,272% avec des données mensuelles. Un investisseur qui évalue le marché en utilisant le risque de ralentissement systématique aurait obtenu une forte hausse du ratio de 0,206. Le second essai fait cadrer un fait empirique bien connu dans l'asymétrie des niveaux de march et d'entreprise, le total des revenus des entreprises positiveament asymétriques conduit à un revenu de marché négativement asymétrique. Nous décomposons l'asymétrie des revenus du marché au niveau de l'entreprise et faisons cadrer ce fait par une plus grande réaction des entreprises aux nouvelles négatives du marché qu'aux nouvelles positives du marché. Cette décomposition révélé plusieurs variables de revenus de marché efficaces tels que l'asymétrie caractéristique pondérée par la volatilité ainsi que l'asymétrie caractéristique de ralentissement. Le troisième chapitre fournit une nouvelle base théorique pour les problèmes de liquidité qui varient selon le temps au sein d'un environnement de marché incomplet. Nous proposons un modèle d'équilibre général avec deux agents: un entrepreneur et un investisseur externe. Seul l'investisseur a besoin de connaitre le véritable état de l'entreprise, par conséquent, les informations de paiement coutent de l'argent. La nouveauté est que l'acquisition de l'information coute plus cher durant les mauvaises périodes que durant les bonnes périodes, comme cela a été confirmé par de précédentes expériences. Lorsque la récession comamence, l'apprentissage coûteux fait augmenter les primes de liquidité causant un problème d'évaporation de liquidité, comme cela a été aussi confirmé par de précédentes expériences.

Polypharmacy is Associated with an Increased Risk of Bleeding in Elderly Patients with Venous Thromboembolism.

BACKGROUND: Polypharmacy, defined as the concomitant use of multiple medications, is very common in the elderly and may trigger drug-drug interactions and increase the risk of falls in patients receiving vitamin K antagonists. OBJECTIVE: To examine whether polypharmacy increases the risk of bleeding in elderly patients who receive vitamin K antagonists for acute venous thromboembolism (VTE). DESIGN: We used a prospective cohort study. PARTICIPANTS: In a multicenter Swiss cohort, we studied 830 patients aged ≥ 65 years with VTE. MAIN MEASURES: We defined polypharmacy as the prescription of more than four different drugs. We assessed the association between polypharmacy and the time to a first major and clinically relevant non-major bleeding, accounting for the competing risk of death. We adjusted for known bleeding risk factors (age, gender, pulmonary embolism, active cancer, arterial hypertension, cardiac disease, cerebrovascular disease, chronic liver and renal disease, diabetes mellitus, history of major bleeding, recent surgery, anemia, thrombocytopenia) and periods of vitamin K antagonist treatment as a time-varying covariate. KEY RESULTS: Overall, 413 (49.8 %) patients had polypharmacy. The mean follow-up duration was 17.8 months. Patients with polypharmacy had a significantly higher incidence of major (9.0 vs. 4.1 events/100 patient-years; incidence rate ratio [IRR] 2.18, 95 % confidence interval [CI] 1.32-3.68) and clinically relevant non-major bleeding (14.8 vs. 8.0 events/100 patient-years; IRR 1.85, 95 % CI 1.27-2.71) than patients without polypharmacy. After adjustment, polypharmacy was significantly associated with major (sub-hazard ratio [SHR] 1.83, 95 % CI 1.03-3.25) and clinically relevant non-major bleeding (SHR 1.60, 95 % CI 1.06-2.42). CONCLUSIONS: Polypharmacy is associated with an increased risk of both major and clinically relevant non-major bleeding in elderly patients receiving vitamin K antagonists for VTE.

Risk of falls and bleeding in elderly patients with acute venous thromboembolism.

OBJECTIVE: Whether or not a high risk of falls increases the risk of bleeding in patients receiving anticoagulants remains a matter of debate. METHODS: We conducted a prospective cohort study involving 991 patients ≥65 years of age who received anticoagulants for acute venous thromboembolism (VTE) at nine Swiss hospitals between September 2009 and September 2012. The study outcomes were as follows: the time to a first major episode of bleeding; and clinically relevant nonmajor bleeding. We determined the associations between the risk of falls and the time to a first episode of bleeding using competing risk regression, accounting for death as a competing event. We adjusted for known bleeding risk factors and anticoagulation as a time-varying covariate. RESULTS: Four hundred fifty-eight of 991 patients (46%) were at high risk of falls. The mean duration of follow-up was 16.7 months. Patients at high risk of falls had a higher incidence of major bleeding (9.6 vs. 6.6 events/100 patient-years; P = 0.05) and a significantly higher incidence of clinically relevant nonmajor bleeding (16.7 vs. 8.3 events/100 patient-years; P < 0.001) than patients at low risk of falls. After adjustment, a high risk of falls was associated with clinically relevant nonmajor bleeding [subhazard ratio (SHR) = 1.74, 95% confidence interval (CI) = 1.23-2.46], but not with major bleeding (SHR = 1.24, 95% CI = 0.83-1.86). CONCLUSION: In elderly patients who receive anticoagulants because of VTE, a high risk of falls is significantly associated with clinically relevant nonmajor bleeding, but not with major bleeding. Whether or not a high risk of falls is a reason against providing anticoagulation beyond 3 months should be based on patient preferences and the risk of VTE recurrence.

An LMI approach to H∞ synchronization of second-order neutral master-slave systems

The H∞ synchronization problem of the master and slave structure of a second-order neutral master-slave systems with time-varying delays is presented in this paper. Delay-dependent sufficient conditions for the design of a delayed output-feedback control are given by Lyapunov-Krasovskii method in terms of a linear matrix inequality (LMI). A controller, which guarantees H∞ synchronization of the master and slave structure using some free weighting matrices, is then developed. A numerical example has been given to show the effectiveness of the method

Self-potential investigations of a gravel bar in a restored river corridor

Self-potentials (SP) are sensitive to water fluxes and concentration gradients in both saturated and unsaturated geological media, but quantitative interpretations of SP field data may often be hindered by the superposition of different source contributions and time-varying electrode potentials. Self-potential mapping and close to two months of SP monitoring on a gravel bar were performed to investigate the origins of SP signals at a restored river section of the Thur River in northeastern Switzerland. The SP mapping and subsequent inversion of the data indicate that the SP sources are mainly located in the upper few meters in regions of soil cover rather than bare gravel. Wavelet analyses of the time-series indicate a strong, but non-linear influence of water table and water content variations, as well as rainfall intensity on the recorded SP signals. Modeling of the SP response with respect to an increase in the water table elevation and precipitation indicate that the distribution of soil properties in the vadose zone has a very strong influence. We conclude that the observed SP responses on the gravel bar are more complicated than previously proposed semi-empiric relationships between SP signals and hydraulic head or the thickness of the vadose zone. We suggest that future SP monitoring in restored river corridors should either focus on quantifying vadose zone processes by installing vertical profiles of closely spaced SP electrodes or by installing the electrodes within the river to avoid signals arising from vadose zone processes and time-varying electrochemical conditions in the vicinity of the electrodes.

Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

Multiple target tracking using random sets

This paper presents several algorithms for joint estimation of the target number and state in a time-varying scenario. Building on the results presented in [1], which considers estimation of the target number only, we assume that not only the target number, but also their state evolution must be estimated. In this context, we extend to this new scenario the Rao-Blackwellization procedure of [1] to compute Bayes recursions, thus defining reduced-complexity solutions for the multi-target set estimator. A performance assessmentis finally given both in terms of Circular Position Error Probability - aimed at evaluating the accuracy of the estimated track - and in terms of Cardinality Error Probability, aimed at evaluating the reliability of the target number estimates.

Structural changes in the US economy: Bad Luck or Bad Policy?

This paper investigates the relationship between time variations in output and inflation dynamics and monetary policy in the US. There are changes in the structural coefficients and in the variance of the structural shocks. The policy rules in the 1970s and 1990s are similar as is the transmission of policy disturbances. Inflation persistence is only partly a monetary phenomena. Variations in the systematic component of policy have limited effects on the dynamics of output and inflation. Results are robust to alterations in the auxiliary assumptions.

Has the Euro-Mediterranean partnership affected Mediterranean business cycles?

We date turning points of the reference cycle for 19 Mediterranean countries andanalyze their structure and interdependences. Fluctuations are volatile and not highlycorrelated across countries; recessions are deep but asynchronous making average outputlosses in the area limited. Heterogeneities across countries and regions are substantial.Mediterranean cycles are time varying but their evolution is not linked withthe Euro-Mediterranean partnership process. The concordance of cyclical fluctuationsis poorly related to trade and financial linkages and to their evolution over time.