774 resultados para Expectations hypothesis


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Mode of access: Internet.

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El cumplimiento de la hipótesis de expectativas (HE) ha sido contrastado en varios países por medio de diferentes métodos. En Colombia no se ha estudiado de manera conjunta las relaciones de largo plazo entre las tasas cero cupón. El presente trabajo busca contrastar el cumplimiento de la hipótesis de expectativas estimando un modelo multivariado con corrección de errores, de acuerdo a la metodología propuesta por Hall, Anderson y Granger (1992). La significancia de la prima por liquidez en las relaciones de largo plazo y las pruebas estadísticas del modelo favorecen el contraste de la HE. Sin embargo, la existencia de dos relaciones de cointegración y el rechazo de las relaciones teóricas esperadas indican el incumplimiento de la HE en Colombia.

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El desarrollo del mercado financiero en Colombia, ha hecho que la integr ación con los merados financieros internacionales sea cada vez más evidente. Es por esto que el estudio del grado de relación de nuestras tasas de interés con las tasas de interés de las tasas internacionales, cobra relevancia. Este estudio, busca evidencia sobre el cumplimiento de la hipótesis de paridad descubierta de intereses y la hipótesis de expectativas racionales, a través del uso de las curvas cero cupón de Colombia y Estados Unidos, siguiendo la metodología derivada del estudio de Bekaert (2002). Se encuentra que el cumplimiento de ambas hipótesis, simultáneamente, no es un hecho común entre los diferenc iales de tasas de Colombia y Estados Unidos. Además, en algunos casos, se encuentra que las hipótesis no se cumplen entre las tasas de interés de la misma nacionalidad.

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In this paper we examine the order of integration of EuroSterling interest rates by employing techniques that can allow for a structural break under the null and/or alternative hypothesis of the unit-root tests. In light of these results, we investigate the cointegrating relationship implied by the single, linear expectations hypothesis of the term structure of interest rates employing two techniques, one of which allows for the possibility of a break in the mean of the cointegrating relationship. The aim of the paper is to investigate whether or not the interest rate series can be viewed as I(1) processes and furthermore, to consider whether there has been a structural break in the series. We also determine whether, if we allow for a break in the cointegration analysis, the results are consistent with those obtained when a break is not allowed for. The main results reported in this paper support the conjecture that the ‘short’ Euro-currency rates are characterised as I(1) series that exhibit a structural break on or near Black Wednesday, 16 September 1992, whereas the ‘long’ rates are I(1) series that do not support the presence of a structural break. The evidence from the cointegration analysis suggests that tests of the expectations hypothesis based on data sets that include the ERM crisis period, or a period that includes a structural break, might be problematic if the structural break is not explicitly taken into account in the testing framework.

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The literature on bond markets and interest rates has focused largely on the term structure of interest rates, specifically, on the so-called expectations hypothesis. At the same time, little is known about the nature of the spread of the interest rates in the money market beyond the fact that such spreads are generally unstable. However, with the evolution of complex financial instruments, it has become imperative to identify the time series process that can help one accurately forecast such spreads into the future. This article explores the nature of the time series process underlying the spread between three-month and one-year US rates, and concludes that the movements in this spread over time is best captured by a GARCH(1,1) process. It also suggests the use of a relatively long term measure of interest rate volatility as an explanatory variable. This exercise has gained added importance in view of the revelation that GARCH based estimates of option prices consistently outperform the corresponding estimates based on the stylized Black-Scholes algorithm.

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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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Introduction Different types of hallucinations are symptomatic of different conditions. Schizotypal hallucinations are unique in that they follow existing delusional narrative patterns: they are often bizarre, they are generally multimodal, and they are particularly vivid (the experience of a newsreader abusing you personally over the TV is both visual and aural. Patients who feel and hear silicone chips under their skin suffer from haptic hallucinations as well as aural ones, etc.) Although there are a number of hypotheses for hallucinations, few cogently grapple the sheer bizarreness of the ones experienced in schizotypal psychosis. Methods A review-based hypothesis, traversing theory from the molecular level to phenomenological expression as a distinct and recognizable symptomatology. Conclusion Hallucinations appear to be caused by a two-fold dysfunction in the mesofrontal dopamine pathway, which is considered here to mediate attention of different types: in the anterior medial frontal lobe, the receptors (largely D1 type) mediate declarative awareness, whereas the receptors in the striatum (largely D2 type) mediate latent awareness of known schemata. In healthy perception, most of the perceptual load is performed by the latter: by the top-down predictive and mimetic engine, with the bottom-up mechanism being used as a secondary tool to bring conscious deliberation to stimuli that fails to match up against expectations. In schizophrenia, the predictive mode is over-stimulated, while the bottom-up feedback mechanism atrophies. The dysfunctional distribution pattern effectively confines dopamine activity to the striatum, thereby stimulating the structural components of thought and behaviour: well-learned routines, narrative structures, lexica, grammar, schemata, archetypes, and other procedural resources. Meanwhile, the loss of activity in the frontal complex reduces the capacity for declarative awareness and for processing anything that fails to meet expectations.

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The low predictive power of implied volatility in forecasting the subsequently realized volatility is a well-documented empirical puzzle. As suggested by e.g. Feinstein (1989), Jackwerth and Rubinstein (1996), and Bates (1997), we test whether unrealized expectations of jumps in volatility could explain this phenomenon. Our findings show that expectations of infrequently occurring jumps in volatility are indeed priced in implied volatility. This has two important consequences. First, implied volatility is actually expected to exceed realized volatility over long periods of time only to be greatly less than realized volatility during infrequently occurring periods of very high volatility. Second, the slope coefficient in the classic forecasting regression of realized volatility on implied volatility is very sensitive to the discrepancy between ex ante expected and ex post realized jump frequencies. If the in-sample frequency of positive volatility jumps is lower than ex ante assessed by the market, the classic regression test tends to reject the hypothesis of informational efficiency even if markets are informationally effective.

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Ever since its initial introduction some fifty years ago, the rational expectations paradigm has dominated the way economic theory handles uncertainty. The main assertion made by John F. Muth (1961), seen by many as the father of the paradigm, is that expectations of rational economic agents should essentially be equal to the predictions of relevant economic theory, since rational agents should use information available to them in an optimal way. This assumption often has important consequences on the results and interpretations of the models where it is applied. Although the rational expectations assumption can be applied to virtually any economic theory, the focus in this thesis is on macroeconomic theories of consumption, especially the Rational Expectations–Permanent Income Hypothesis proposed by Robert E. Hall in 1978. The much-debated theory suggests that, assuming that agents have rational expectations on their future income, consumption decisions should follow a random walk, and the best forecast of future consumption level is the current consumption level. Then, changes in consumption are unforecastable. This thesis constructs an empirical test for the Rational Expectations–Permanent Income Hypothesis using Finnish Consumer Survey data as well as various Finnish macroeconomic data. The data sample covers the years 1995–2010. Consumer survey data may be interpreted to directly represent household expectations, which makes it an interesting tool for this particular test. The variable to be predicted is the growth of total household consumption expenditure. The main empirical result is that the Consumer Confidence Index (CCI), a balance figure computed from the most important consumer survey responses, does have statistically significant predictive power over the change in total consumption expenditure. The history of consumption expenditure growth itself, however, fails to predict its own future values. This indicates that the CCI contains some information that the history of consumption decisions does not, and that the consumption decisions are not optimal in the theoretical context. However, when conditioned on various macroeconomic variables, the CCI loses its predictive ability. This finding suggests that the index is merely a (partial) summary of macroeconomic information, and does not contain any significant private information on consumption intentions of households not directly deductible from the objective economic variables. In conclusion, the Rational Expectations–Permanent Income Hypothesis is strongly rejected by the empirical results in this thesis. This result is in accordance with most earlier studies conducted on the topic.

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This work aims to test the equilibrium relations of two international macroeconomics models for Colombia, Chile, Mexico and Brazil. The first model is the rational expectation hypothesis (REH) where three key relations will be tested: Purchasing Power Parity (PPP), Uncovered Interest Rate Parity (UIP) and the Fisher Parity condition. The second model follows the line of though of Imperfect Knowledge Economics (IKE) where two equilibrium relations will be tested. According to IKE, even under the assumption that agents are rational, the presence of speculative behavior in financial markets helps explain the long swings often observed in the behavior of exchange rates. The results support the view that the predictions of the IKE model hold for Colombia, while those of the REH hold for both Brazil and Mexico. Mixed findings are obtained for Chile.

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In the past 20 years, decentralization has been proposed as a strategy for enhancing public participation. Aid-providing organizations, such as the World Bank, stimulated decentralization processes in several countries in the hope that this would promote civic empowerment, diminish corruption, enhance efficiency, and improve public service delivery. This assumption forms the basis for a comparative analysis into the relation between decentralization and participation at the local level in Brazil, Japan, Russia and Sweden. A multi-level regression analysis using the data of the Democracy and Local Governance Project was undertaken in order to test the 'one size fits all' and the 'diversity in development' hypotheses. The results show that the second hypothesis was corroborated. Perceived autonomy had a different impact on openness to participation depending on the country considered; in one country (Japan), perceived autonomy diminished public officials' willingness to be open to public participation.

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The purpose of this research study was to investigate if the determination of school readiness as it was evaluated by Broward County kindergarten teachers on the Florida's Expectations of School Readiness checklist can be attributed to the effects of gender, chronological age on school entry, racial or ethnic background, attending public preschool, native language other than English, or socioeconomic status.^ This is a descriptive study in which the number of expectations passed or failed for each of the identifier categories was compared. The Chi-squared distribution was used to evaluate the null hypothesis that "chronological age at entry to school, gender, race or ethnicity, native language other than English, public preschool experience, and socioeconomic status have no effect on the determination of readiness for school". Results were confirmed using t-tests, ANOVA, and linear regression models. The cohort of 1555 Broward County students in the study were evaluated using the Florida's Expectations for School Readiness checklist and were determined not ready for school during the initial data collection year 1996-1997.^ The determination of school readiness was significantly dependent on the gender, and racial or ethnic background of the students in the cohort. The socioeconomic status and native language other than English designations were significant for students only in the areas of preacademic, academic and literacy development. Chronological age on entry to school or attendance in public preschool prior to entry in kindergarten for the cohort was not significant in the determination of readiness for school.^ Given the fact that this study followed only students that were determined not ready for school, it is recommended that a second cohort of both "ready" and "not ready" students be studied. ^

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We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.