Reality check for volatility models

Asset allocation decisions and value at risk calculations rely strongly on volatility estimates. Volatility measures such as rolling window, EWMA, GARCH and stochastic volatility are used in practice. GARCH and EWMA type models that incorporate the dynamic structure of volatility and are capable of forecasting future behavior of risk should perform better than constant, rolling window volatility models. For the same asset the model that is the ‘best’ according to some criterion can change from period to period. We use the reality check test∗ to verify if one model out-performs others over a class of re-sampled time-series data. The test is based on re-sampling the data using stationary bootstrapping. For each re-sample we check the ‘best’ model according to two criteria and analyze the distribution of the performance statistics. We compare constant volatility, EWMA and GARCH models using a quadratic utility function and a risk management measurement as comparison criteria. No model consistently out-performs the benchmark.

Essays in macroeconomy and dynamic term-structure models

This thesis is composed of three articles with the subjects of macroeconomics and - nance. Each article corresponds to a chapter and is done in paper format. In the rst article, which was done with Axel Simonsen, we model and estimate a small open economy for the Canadian economy in a two country General Equilibrium (DSGE) framework. We show that it is important to account for the correlation between Domestic and Foreign shocks and for the Incomplete Pass-Through. In the second chapter-paper, which was done with Hedibert Freitas Lopes, we estimate a Regime-switching Macro-Finance model for the term-structure of interest rates to study the US post-World War II (WWII) joint behavior of macro-variables and the yield-curve. We show that our model tracks well the US NBER cycles, the addition of changes of regime are important to explain the Expectation Theory of the term structure, and macro-variables have increasing importance in recessions to explain the variability of the yield curve. We also present a novel sequential Monte-Carlo algorithm to learn about the parameters and the latent states of the Economy. In the third chapter, I present a Gaussian A ne Term Structure Model (ATSM) with latent jumps in order to address two questions: (1) what are the implications of incorporating jumps in an ATSM for Asian option pricing, in the particular case of the Brazilian DI Index (IDI) option, and (2) how jumps and options a ect the bond risk-premia dynamics. I show that jump risk-premia is negative in a scenario of decreasing interest rates (my sample period) and is important to explain the level of yields, and that gaussian models without jumps and with constant intensity jumps are good to price Asian options.

Country factors and the dynamic modeling of capital structure : an empirical study of latin american firms

Desenvolvemos modelos de ajuste parcial e de duration para testar a relevância de fatores específicos de países na determinação da estrutura de capital de empresas listadas nas bolsas de valores brasileira, chilena e mexicana. Utilizamos dados em painel, em um período que se estende do quarto trimestre de 1996 ao segundo trimestre de 2010, abrangendo 4403 observações relacionadas a 139 empresas diferentes. Os resultados obtidos sugerem que a dinâmica da estrutura de capital varia por país e que idiossincrasias locais são determinantes-chave dos níveis de alavancagem das empresas. Não detectamos comportamento explicado pela Teoria de Trade Off entre as empresas brasileiras, chilenas e mexicanas, o que indica que teorias alternativas possam comandar os processos de decisão de financiamento dos gestores latino americanos.

The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

Economic cycles and term structure: application to Brazil

The objective of this work is to describe the behavior of the economic cycle in Brazil through Markov processes which can jointly model the slope factor of the yield curve, obtained by the estimation of the Nelson-Siegel Dynamic Model by the Kalman filter and a proxy variable for economic performance, providing some forecasting measure for economic cycles

The long-run properties of a dynamic Mirrlees' model with aggregate shocks

Nós abordamos a existência de distribuições estacionárias de promessas de utilidade em um modelo Mirrlees dinâmico quando o governo tem record keeping imperfeito e a economia é sujeita a choques agregados. Quando esses choques são iid, provamos a existência de um estado estacionário não degenerado e caracterizamos parcialmente as alocações estacionárias. Mostramos que a proporção do consumo agregado é invariante ao estado agregado. Quando os choques agregados apresentam persistência, porém, alocações eficientes apresentam dependência da história de choques e, em geral, uma distribuição invariante não existe.