954 resultados para Rising interest rates


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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

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This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

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This paper studies monetary policy transmission using several statistical tools -- We find that the relationships between the policy interest rate and the financial system’s interest rates are positive and statistically significant, and transmission is complete eight months after policy shocks occur -- The speed of transmission varies according to the type of interest rates -- Transmission is faster for interest rates on loans provided to households, and is particularly rapid and complete for rates on preferential commercial loans -- Transmission is slower for credit card and mortgage rates, due to regulatory issues (interest rate ceilings)

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We start in Chapter 2 to investigate linear matrix-valued SDEs and the Itô-stochastic Magnus expansion. The Itô-stochastic Magnus expansion provides an efficient numerical scheme to solve matrix-valued SDEs. We show convergence of the expansion up to a stopping time τ and provide an asymptotic estimate of the cumulative distribution function of τ. Moreover, we show how to apply it to solve SPDEs with one and two spatial dimensions by combining it with the method of lines with high accuracy. We will see that the Magnus expansion allows us to use GPU techniques leading to major performance improvements compared to a standard Euler-Maruyama scheme. In Chapter 3, we study a short-rate model in a Cox-Ingersoll-Ross (CIR) framework for negative interest rates. We define the short rate as the difference of two independent CIR processes and add a deterministic shift to guarantee a perfect fit to the market term structure. We show how to use the Gram-Charlier expansion to efficiently calibrate the model to the market swaption surface and price Bermudan swaptions with good accuracy. We are taking two different perspectives for rating transition modelling. In Section 4.4, we study inhomogeneous continuous-time Markov chains (ICTMC) as a candidate for a rating model with deterministic rating transitions. We extend this model by taking a Lie group perspective in Section 4.5, to allow for stochastic rating transitions. In both cases, we will compare the most popular choices for a change of measure technique and show how to efficiently calibrate both models to the available historical rating data and market default probabilities. At the very end, we apply the techniques shown in this thesis to minimize the collateral-inclusive Credit/ Debit Valuation Adjustments under the constraint of small collateral postings by using a collateral account dependent on rating trigger.

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Includes bibliography

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Includes bibliography

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Includes bibliography

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The disconnect between rising short and low long interest rates has been a distinctive feature of the 2000s. Both research and policy circles have argued that international forces, such as global monetary policy (e.g. Rogoff, 2006); international business cycles (e.g. Borio and Filardo, 2007); or a global savings glut (e.g Bernanke, 2005) may be responsible. In this paper, we employ recent advances in panel data econometrics to document the disconnect and link it explicitly to the existence of a global latent factor that dominates the long end of the term spread for the recent period; the saving glut story emerges as the most likely contender for the global factor.

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Background: EUS is being increasingly utilized for the diagnosis of choledocholithiasis and microlithiasis, especially in patients with biliary colic. Simultaneously, there is also a rising interest in the use of EUS for therapeutic interventions. Objectives: Our goal was to assess the effectiveness of EUS-directed common bile duct (CBD) stone removal to compare its safety and effectiveness with ERCP-directed intervention. Design: interim results of a prospective, randomized, single-center blinded clinical trial. Setting: A single tertiary care referral center. Patients: Fifty-two patients with uncomplicated CBD stones were prospectively randomized to CBD cannulation and stone removal under EUS or ERCP guidance. Main Outcome Measurements and Interventions: Primary outcome measure was the rate of successful cannulation of the CBD. Secondary Outcome measures included Successful removal of stones and overall complication rates. Results: CBD cannulation followed by stone extraction was successful in 23 of 26 patients (88.5%) in the EUS group (1) versus 25 of 26 patients (96.2%) in the ERCP group (11) (95% CI, -27.65%, 9.88%). Overall, there were 3 complications in the EUS group and 4 complications in the ERCP group. Limitation: The current study is an interim report from a single center report and performed by a single operator. Conclusions: Our preliminary analysis indicates that Outcomes following EUS-guided CBD stone retrieval are equivalent to those following ERCP EUS-related adverse events are similar to those following ERCP. ERCP and EUS-guided stone retrieval appears to be equally effective for therapeutic interventions of the bile duct. Additional studies are required to validate these preliminary results and to determine predictors of success of EUS-guided stone removal. (Gastrointest Endosc 2009;69:238-43.)

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This paper investigates the robustness of a range of short–term interest rate models. We examine the robustness of these models over different data sets, time periods, sampling frequencies, and estimation techniques. We examine a range of popular one–factor models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that parameter estimates are highly sensitive to all of these factors in the eight countries that we examine. Since parameter estimates are not robust, these models should be used with caution in practice.

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Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

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Directed Research Internship

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The purpose of this paper is to study the determinants of equilibrium in the market for daily funds. We use the EONIA panel database which includes daily information on the lending rates applied by contributing commercial banks. The data clearly shows an increase in both the time series volatility and the cross section dispersion of rates towards the end of the reserve maintenance period. These increases are highly correlated. With respect to quantities, we find that the volume of trade as well as the use of the standing facilities are also larger at the end of the maintenance period. Our theoretical model shows how the operational framework of monetary policy causes a reduction in the elasticity of the supply of funds by banks throughout the reserve maintenance period. This reduction in the elasticity together with market segmentation and heterogeneity are able to generate distributions for the interest rates and quantities traded with the same properties as in the data.

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We test the real interest rate parity hypothesis using data for the G7 countries over the period 1970-2008. Our contribution is two-fold. First, we utilize the ARDL bounds approach of Pesaran et al. (2001) which allows us to overcome uncertainty about the order of integration of real interest rates. Second, we test for structural breaks in the underlying relationship using the multiple structural breaks test of Bai and Perron (1998, 2003). Our results indicate significant parameter instability and suggest that, despite the advances in economic and financial integration, real interest rate parity has not fully recovered from a breakdown in the 1980s.

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We investigate the effects of the financial crisis on the stationarity of real interest rates in the Euro Area. We use a new unit root test developed by Peseran et al. (2013) that allows for multiple unobserved factors in a panel set up. Our results suggest that while short-term and long-term real interest rates were stationary before the financial crisis, they became nonstationary during the crisis period likely due to persistent risk that characterized financial markets during that time. JEL codes: E43, C23. Keywords: Real interest rates, Euro Area, financial crisis, panel unit root tests, cross-sectional dependence.