Forecasting the term structure when short-term rates are near zero

This paper compares the experience of forecasting the UK government bond yield curve before and after the dramatic lowering of short-term interest rates from October 2008. Out-of-sample forecasts for 1, 6 and 12 months are generated from each of a dynamic Nelson-Siegel model, autoregressive models for both yields and the principal components extracted from those yields, a slope regression and a random walk model. At short forecasting horizons, there is little difference in the performance of the models both prior to and after 2008. However, for medium- to longer-term horizons, the slope regression provided the best forecasts prior to 2008, while the recent experience of near-zero short interest rates coincides with a period of forecasting superiority for the autoregressive and dynamic Nelson-Siegel models. © 2014 John Wiley & Sons, Ltd.

Do U.S. and Colombian macro factors improve the forecasting ability of unrestricted VAR models of the local term structure of interest rate?

Este estudio empírico compara la capacidad de los modelos Vectores auto-regresivos (VAR) sin restricciones para predecir la estructura temporal de las tasas de interés en Colombia -- Se comparan modelos VAR simples con modelos VAR aumentados con factores macroeconómicos y financieros colombianos y estadounidenses -- Encontramos que la inclusión de la información de los precios del petróleo, el riesgo de crédito de Colombia y un indicador internacional de la aversión al riesgo mejora la capacidad de predicción fuera de la muestra de los modelos VAR sin restricciones para vencimientos de corto plazo con frecuencia mensual -- Para vencimientos de mediano y largo plazo los modelos sin variables macroeconómicas presentan mejores pronósticos sugiriendo que las curvas de rendimiento de mediano y largo plazo ya incluyen toda la información significativa para pronosticarlos -- Este hallazgo tiene implicaciones importantes para los administradores de portafolios, participantes del mercado y responsables de las políticas

Forecasting exchange rates in the presence of instabilities

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

Governed by the cycle : direct and inverted interest-rate sensitivity of emerging market corporate debt

An innovative approach to quantify interest rate sensitivities of emerging market corporates is proposed. Our focus is centered at price sensitivity of modeled investment grade and high yield portfolios to changes in the present value of modeled portfolios composed of safe-haven assets, which define risk-free interest rates. Our methodology is based on blended yield indexes. Modeled investment horizons are always kept above one year thus allowing to derive empirical implications for practical strategies of interest rate risk management in the banking book. As our study spans over the period 2002 – 2015, it covers interest rate sensitivity of assets under the pre-crisis, crisis, and post-crisis phases of the economic cycles. We demonstrate that the emerging market corporate bonds both, investment grade and high yield types, depending on the phase of a business cycle exhibit diverse regimes of sensitivity to interest rate changes. We observe switching from a direct positive sensitivity under the normal pre-crisis market conditions to an inverted negative sensitivity during distressed turmoil of the recent financial crisis, and than back to direct positive but weaker sensitivity under new normal post-crisis conjuncture. Our unusual blended yield-based approach allows us to present theoretical explanations of such phenomena from economics point of view and helps us to solve an old controversy regarding positive or negative responses of credit spreads to interest rates. We present numerical quantification of sensitivities, which corroborate with our conclusion that hedging of interest rate risk ought to be a dynamic process linked to the phases of business cycles as we evidence a binary-like behavior of interest rate sensitivities along the economic time. Our findings allow banks and financial institutions for approaching downside risk management and optimizing economic capital under Basel III regulatory capital rules.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

What are the economic prospects of developing aquaculture in Queensland to supply the low price white fillet market? Lessons from the US channel catfish industry

The farming of channel catfish (Ictalurus punctatus) is the largest (by volume and value) and most successful (in terms of market impact) aquaculture industry in the United States of America. Farmed channel catfish is the most consumed (in terms of volume per capita) fish fillet in the U.S. market. Within Australia, it has long been suggested by researchers and industry that silver perch (Bidyanus bidyanus) and possibly other endemic teraponid species possess similar biological attributes for aquaculture as channel catfish and may have the potential to generate a similar industry. The current teraponid industry in Australia, however, shows very little resemblance to the catfish industry, either in production style or market philosophy. A well established budget framework from the literature on U.S. channel catfish farming has been adapted for cost and climate conditions of the Burdekin region, Queensland, Australia. Breakeven prices for the hypothetical teraponid farms were found to be up to 50% higher than those published for catfish farms however were much lower than those reported for silver perch production in Australia using current, endemic styles of production. The breakeven prices for the hypothetical teraponid farms were most sensitive (in order of significance) to feed prices, production rates, interest rates, fingerling prices and electricity prices. At equivalent feed costs the costs of production between the hypothetical catfish farms in the Mississippi, U.S. and the hypothetical teraponid farms in the Burdekin, Australia were remarkably similar. The cost of feeds suitable for teraponid production in Australia are currently around double that of catfish feeds in the U.S. Issues currently hindering the development of a large scale teraponid industry in Australia are discussed.

Debt Maturity: Is Long-Term Debt Optimal?

We model and calibrate the arguments in favor and against short-term and long-term debt. These arguments broadly include: maturity premium, sustainability, and service smoothing. We use a dynamic-equilibrium model with tax distortions and government outlays uncertainty, and model maturity as the fraction of debt that needs to be rolled over every period. In the model, the benefits of defaulting are tempered by higher future interest rates. We then calibrate our artificial economy and solve for the optimal debt maturity for Brazil as an example of a developing country and the US as an example of a mature economy. We obtain that the calibrated costs from defaulting on long-term debt more than offset costs associated with short-term debt. Therefore, short-term debt implies higher welfare levels.

Nominal versus indexed debt: A quantitative horse race

The main arguments in favor and against nominal and indexed debts are the incentive to default through inflation versus hedging against unforeseen shocks. We model and calibrate these arguments to assess their quantitative importance. We use a dynamic equilibrium model with tax distortion, government outlays uncertainty, and contingent-debt service. Our framework also recognizes that contingent debt can be associated with incentive problems and lack of commitment. Thus, the benefits of unexpected inflation are tempered by higher interest rates. We obtain that costs from inflation more than offset the benefits from reducing tax distortions. We further discuss sustainability of nominal debt in developing (volatile) countries. (C) 2010 Elsevier Ltd. All rights reserved.

Financial leverage and tangibility of assets of Brazilian companies of agribusiness in the post-real plan period

This paper aims to study the relationship between the debt level and the asset structure of Brazilian companies of the agribusiness sector, since it is considered a current and relevant discussion: to evaluate the mechanisms for fund-raising and guarantees. The methodology of Granger`s Causality test and Autoregressive Vectors was used to conduct a comparative analysis, applied to a financial database of companies with open capital of Brazilian agribusiness, in particular the agricultural sector and Fisheries and Food and Beverages in a period of 10 years (1997-2007) from quarterly series available in the database of Economatica(R). The results demonstrated that changes in leverage generate variations in the tangibility of the companies, a fact that can be explained by the large search of funding secured by fiduciary transfer of fixed assets, which facilitates access to credit by business of the Agribusiness sector, increasing the payment time and lowering interest rates.

Inércia da taxa de juros : teoria e evidência para a economia brasileira (2005-2013)

No âmbito da condução da política monetária, as funções de reação estimadas em estudos empíricos, tanto para a economia brasileira como para outras economias, têm mostrado uma boa aderência aos dados. Porém, os estudos mostram que o poder explicativo das estimativas aumenta consideravelmente quando se inclui um componente de suavização da taxa de juros, representado pela taxa de juros defasada. Segundo Clarida, et. al. (1998) o coeficiente da taxa de juros defasada (situado ente 0,0 e 1,0) representaria o grau de inércia da política monetária, e quanto maior esse coeficiente, menor e mais lenta é a resposta da taxa de juros ao conjunto de informações relevantes. Por outro lado, a literatura empírica internacional mostra que esse componente assume um peso expressivo nas funções de reação, o que revela que os BCs ajustam o instrumento de modo lento e parcimonioso. No entanto, o caso brasileiro é de particular interesse porque os trabalhos mais recentes têm evidenciado uma elevação no componente inercial, o que sugere que o BCB vem aumentando o grau de suavização da taxa de juros nos últimos anos. Nesse contexto, mais do que estimar uma função de reação forward looking para captar o comportamento global médio do Banco Central do Brasil no período de Janeiro de 2005 a Maio de 2013, o trabalho se propôs a procurar respostas para uma possível relação de causalidade dinâmica entre a trajetória do coeficiente de inércia e as variáveis macroeconômicas relevantes, usando como método a aplicação do filtro de Kalman para extrair a trajetória do coeficiente de inércia e a estimação de um modelo de Vetores Autorregressivos (VAR) que incluirá a trajetória do coeficiente de inércia e as variáveis macroeconômicas relevantes. De modo geral, pelas regressões e pelo filtro de Kalman, os resultados mostraram um coeficiente de inércia extremamente elevado em todo o período analisado, e coeficientes de resposta global muito pequenos, inconsistentes com o que é esperado pela teoria. Pelo método VAR, o resultado de maior interesse foi o de que choques positivos na variável de inércia foram responsáveis por desvios persistentes no hiato do produto e, consequentemente, sobre os desvios de inflação e de expectativas de inflação em relação à meta central.

Consignação em folha de pagamento : estudo sobre o papel da instituição nas implicações do uso da margem de consignação pelos servidores público

A utilização da margem de consignação é um fator indicativo de endividamento do servidor público, pois compromete parte de sua renda futura, diminuindo seu poder aquisitivo. A partir do ano de 2003 o governo brasileiro estimulou a oferta de crédito consignado, com taxas de juros mais atrativas, acarretando e um aumento do saldo de operações contratadas de 1.340,20% de 2004 a 2011. Devido as características do vínculo empregatício os servidores públicos se tornaram os principais tomadores de empréstimo consignado. Entretanto, o não entendimento da margem de consignação e a falta de educação financeira pode fazer com que o servidor entre em situação de dificuldade financeira, principalmente como sobreendividamento, que é a impossibilidade de pagar suas dívidas de créditos, podendo ter reflexo no desenvolvimento do trabalho. A fim de atingir o objetivo de identificar a atuação da instituição sobre as implicações do uso da margem de consignação pelos servidores públicos, foi realizado uma pesquisa de levantamento com abordagem quanti-qualitativa por meio de aplicação de questionário, obtendo um retorno de 210 respostas válidas. Os dados foram tabulados e analisados utilizando técnicas estatísticas como análise descritiva e tabelas de contingência observando os valores dos testes de qui-quadrado e V de Cramer. As conclusões indicam que a orientação financeira do servidor pode contribuir para utilização da margem de consignação de forma mais consciente evitando problemas financeiros e melhorando sua atuação no trabalho e que a instituição estudada poderia atuar de forma mais ativa sobre as implicações da margem de consignação. Por fim, foi recomendado como plano de intervenção da instituição a formulação de cursos sobre a educação financeira e sobre a margem de consignação, apresentado conceitos e casos cotidianos para melhor assimilação dos servidores, por meio do programa de capacitação dos servidores já existente na instituição

Effects and determinants of household debt in Portugal

As the amount of debt has gradually increased, particularly in recent years, Portugal is currently one of the European countries exhibiting one of the highest levels of overall indebtedness, including in both sovereign and private sectors. Indeed, this condition is the outcome of increasing levels of debt assumed not only by the government, but also by companies and families, being the later mostly due to mortgage loans and due charges. This paper focuses on the study of borrowing by Portuguese households. The research has been made in respect to the notion of debt, the consequences of recent developments in debt, among other factors. In order to analyse the factors that are most associated with debt, a study was developed using two multiple regression models, one using a longer time series and another shorter, evaluating the effect of several variables, such as consumption, savings, unemployment, inflation and interest rates, in order to check whether they could be associated with a higher level of debt.

Os swaps de taxas de juro como instrumentos de cobertura de risco nas demonstrações financeiras

Mestrado em Contabilidade

Derivados sobre taxas de juro: estudo de caso

Mestrado em Contabilidade e Análise Financeira

Os efeitos das variações das taxas de juro na volatilidade dos mercados bolsistas

Mestrado em Controlo de Gestão e dos Negócios