925 resultados para Interest rate futures


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Esta tesis lleva por título ”Tres ensayos sobre la multiplicidad de curvas de tipos de interés en el mercado interbancario” y está compuesta por tres artículos de investigación independientes en los que se analiza la evolución de los diferenciales del mercado interbancario del Euro en el periodo post-crisis. El objetivo es obtener información embebida en las cotizaciones de estos diferenciales emplenado distintas metodologías e identificar las variables que subyacen al fenómeno de la multiplicidad de curvas, caracterizando el papel que juegan a la hora de explicar esta evolución. El análisis se realiza según una aproximación cercana a la práctica de mercado (Capítulo 2), siguiendo técnicas de valoración de activos (Capítulo 3) y finalmente considerando métodos econométricos (Capítulo 4). El Capítulo 2, que incluye el primer ensayo, se centra en la evolución dinámica de las distintas curvas de tipos de interés surgidas a raíz de la crisis -diferenciadas por la periodicidad de pago del tipo de interés subyacente- a través del estudio de sus diferenciales respecto a la curva overnight. La metodología empleada es similar a la de Diebold and Li (2006) y se resume en tres factores principales que se interpretan como nivel, pendiente y curvatura. El análisis de componentes principales de estos factores para distintas periodicidades muestra que existen patrones comunes entre los factores de las diferentes curvas, en particular el primer componente principal explica el 90% de su variación. El estudio de los determinantes de estos factores revela importantes conclusiones sobre las fuentes de este patrón. En concreto, se observa que el nivel tiene una relación muy importante con el riesgo de crédito. Asimismo, el estudio del contenido informacional de los errores residuales del modelo -mediante el cómputo de la medida de ruido de Hu et al. (2013)- nos lleva a concluir que estos residuos tienen relación con la liquidez. El análisis de estos datos empleando téncicas VAR refuerza estos resultados...

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Tendo por base o trabalho realizado por Hyde e Sherif (2010) com dados do mercado inglês, foi desenvolvido estudo com o objetivo de avaliar a capacidade do spread de curto e longo prazo da taxa de juros de funcionar como indicador do crescimento futuro do consumo no Brasil. Tanto Hyde e Sherif (2010) como outros estudos realizados em países desenvolvidos indicaram relação positiva entre o spread de juros de curto e longo prazo e o crescimento do consumo. Entretanto, as análises empíricas realizadas neste estudo para o caso brasileiro, apresentaram resultados divergentes do esperado pela teoria, indicando relação negativa entre o spread de juros e o crescimento do consumo. Em algumas análises, os estudos não indicaram relação entre as variáveis. Foram discutidas possíveis razões para estes resultados contraintuitivos, tais como tamanho reduzido da amostra, nível da taxa de juros no Brasil e liquidez do mercado futuro de juros. Adicionalmente foram analisados os modelos teóricos C-CAPM (Consumption-based asset pricing model) e o modelo de consumo habitual desenvolvido por Campbell e Cochrane (1999) com a adaptação proposta por Wachter (2006). Os resultados encontrados no modelo C-CAPM divergiram do esperado, já que a estimativa do coeficiente relativo de aversão ao risco apresentou sinal negativo. Por outro lado, os resultados obtidos no modelo de Wachter (2006) ficaram em linha com o esperado na teoria, tanto em relação à significância dos parâmetros como aos respectivos sinais e magnitudes.

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As diretrizes de política monetária são definidas com base em resultados dos indicadores macroeconômicos divulgados ao mercado periodicamente. Os agentes deste mercado respondem rapidamente às alterações de cenário, com o objetivo de obter lucro ou evitar perdas financeiras expressivas. Com este motivacional, a proposta deste trabalho é avaliar como reage o mercado futuro de juros diante da divulgação de surpresas em determinados indicadores macroeconômicos, propondo um indicador de surpresa agregado para prever os impactos causados. Através dos dados extraídos da Bloomberg e da BM&F Bovespa, foi construída uma base de dados simplificada pela adoção de premissas para mensuração do impacto das surpresas divulgadas no preço do DI Futuro. A padronização dos parâmetros, a realização dos testes de média e as regressões otimizadas pelo método OLS possibilitaram ponderar os indicadores econômicos de acordo com a oscilação que os mesmos causam a este mercado. Por fim, o teste de comparação mostrou que o indicador de surpresa proposto foi mais eficiente nas previsões da reação do mercado do que um indicador que pondere de forma igualitária todos os indicadores macroeconômicos.

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This paper presents and implements a number of tests for non-linear dependence and a test for chaos using transactions prices on three LIFFE futures contracts: the Short Sterling interest rate contract, the Long Gilt government bond contract, and the FTSE 100 stock index futures contract. While previous studies of high frequency futures market data use only those transactions which involve a price change, we use all of the transaction prices on these contracts whether they involve a price change or not. Our results indicate irrefutable evidence of non-linearity in two of the three contracts, although we find no evidence of a chaotic process in any of the series. We are also able to provide some indications of the effect of the duration of the trading day on the degree of non-linearity of the underlying contract. The trading day for the Long Gilt contract was extended in August 1994, and prior to this date there is no evidence of any structure in the return series. However, after the extension of the trading day we do find evidence of a non-linear return structure.

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The standard model linking the swap rate to the rates in a contemporaneous strip of futures interest rate contracts typically produces biased estimates of the swap rate. Institutional differences usually require some form of interpolation to be employed and may in principle explain this empirical result. Using Australian data, we find evidence consistent with this explanation and show that model performance is greatly improved if an alternative interpolation method is used. In doing so, we also provide the first published Australian evidence on the accuracy of the futures-based approach to pricing interest rate swaps.

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Purpose – The purpose of this paper is to investigate the impact of foreign exchange and interest rate changes on US banks’ stock returns. Design/methodology/approach – The approach employs an EGARCH model to account for the ARCH effects in daily returns. Most prior studies have used standard OLS estimation methods with the result that the presence of ARCH effects would have affected estimation efficiency. For comparative purposes, the standard OLS estimation method is also used to measure sensitivity. Findings – The findings are as follows: under the conditional t-distributional assumption, the EGARCH model generated a much better fit to the data although the goodness-of-fit of the model is not entirely satisfactory; the market index return accounts for most of the variation in stock returns at both the individual bank and portfolio levels; and the degree of sensitivity of the stock returns to interest rate and FX rate changes is not very pronounced despite the use of high frequency data. Earlier results had indicated that daily data provided greater evidence of exposure sensitivity. Practical implications – Assuming that banks do not hedge perfectly, these findings have important financial implications as they suggest that the hedging policies of the banks are not reflected in their stock prices. Alternatively, it is possible that different GARCH-type models might be more appropriate when modelling high frequency returns. Originality/value – The paper contributes to existing knowledge in the area by showing that ARCH effects do impact on measures of sensitivity.

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An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important

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This paper considers the basic present value model of interest rates under rational expectations with two additional features. First, following McCallum (1994), the model assumes a policy reaction function where changes in the short-term interest rate are determined by the long-short spread. Second, the short-term interest rate and the risk premium processes are characterized by a Markov regime-switching model. Using US post-war interest rate data, this paper finds evidence that a two-regime switching model fits the data better than the basic model. The estimation results also show the presence of two alternative states displaying quite different features.

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The paper explores differences as well as commonalities in corporate risk management practices and risk exposures in the large non-financial Slovenian and Croatian companies. Comparative analysis of survey results have revealed that the majority of analysed companies in both Croatia and Slovenia are using some form of risk management to manage interest-rate, foreign exchange, or commodity price risk. Regarding the intensity of influence of financial risks on the performance of the analysed companies, the results have shown that the price risk has the highest influence among the Slovenian as well as the Croatian companies. Croatian companies are more affected by currency risk than the Slovenian companies, while the interest-rate risk has been ranged as less important in comparison with commodity price and currency risks. The survey’s results have clearly indicated that Croatian and Slovenian non-financial companies manage financial risks primarily with simple risk management instruments such as natural hedging. In the case of derivatives use, forwards and swaps are by far the most important instruments in both countries, but futures as representatives of standardised derivatives and structured derivatives are more important in the Slovenian than in the Croatian companies.

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We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

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Reducible diffusions (RDs) are nonlinear transformations of analytically solvable Basic Diffusions (BDs). Hence, by construction RDs are analytically tractable and flexible diffusion processes. Existing literature on RDs has mostly focused on time-homogeneous transformations, which to a significant extent fail to explore the full potential of RDs from both theoretical and practical points of view. In this paper, we propose flexible and economically justifiable time variations to the transformations of RDs. Concentrating on the Constant Elasticity Variance (CEV) RDs, we consider nonlinear dynamics for our time-varying transformations with both deterministic and stochastic designs. Such time variations can greatly enhance the flexibility of RDs while maintaining sufficient tractability of the resulting models. In the meantime, our modeling approach enjoys the benefits of classical inferential techniques such as the Maximum Likelihood (ML). Our application to the UK and the US short-term interest rates suggests that from an empirical point of view time-varying transformations are highly relevant and statistically significant. We expect that the proposed models can describe more truthfully the dynamic time-varying behavior of economic and financial variables and potentially improve out-of-sample forecasts significantly.

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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In an economy where cash can be stored costlessly (in nominal terms), the nominal interest rate is bounded below by zero. This paper derives the implications of this nonnegativity constraint for the term structure and shows that it induces a nonlinear and convex relation between short- and long-term interest rates. As a result, the long-term rate responds asymmetrically to changes in the short-term rate, and by less than predicted by a benchmark linear model. In particular, a decrease in the short-term rate leads to a decrease in the long-term rate that is smaller in magnitude than the increase in the long-term rate associated with an increase in the short-term rate of the same size. Up to the extent that monetary policy acts by affecting long-term rates through the term structure, its power is considerably reduced at low interest rates. The empirical predictions of the model are examined using data from Japan.

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Understanding the dynamics of interest rates and the term structure has important implications for issues as diverse as real economic activity, monetary policy, pricing of interest rate derivative securities and public debt financing. Our paper follows a longstanding tradition of using factor models of interest rates but proposes a semi-parametric procedure to model interest rates.