Impactos da votalidade cambial na atividade de turismo receptivo: novos desenhos de contratos

De 2002 a 2006 a moeda nacional brasileira, o real, vem sofrendo crescente valorização, tendência que afeta negativamente o setor exportativo no Brasil. Este trabalho refere-se o impacto desta valorização numa indústria específica do setor de exportação, a de turismo receptivo. São destacados os modelos de contratos atuais e analisada a proposição de um novo modelo de contrato, fechado em moeda nacional para as vendas internacionais, visando minimizar o risco cambial inerente à atividade. Os resultados indicam que a adoção deste novo modelo contratual eliminaria o risco cambial da parte da cadeia de distribuição situada no território nacional, trocando este por risco de demanda em função da flutuação do preço para o cliente final.

Ensaios em macroeconometria e finanças

This thesis is composed of three essays referent to the subjects of macroeconometrics and Önance. In each essay, which corresponds to one chapter, the objective is to investigate and analyze advanced econometric techniques, applied to relevant macroeconomic questions, such as the capital mobility hypothesis and the sustainability of public debt. A Önance topic regarding portfolio risk management is also investigated, through an econometric technique used to evaluate Value-at-Risk models. The Örst chapter investigates an intertemporal optimization model to analyze the current account. Based on Campbell & Shillerís (1987) approach, a Wald test is conducted to analyze a set of restrictions imposed to a VAR used to forecast the current account. The estimation is based on three di§erent procedures: OLS, SUR and the two-way error decomposition of Fuller & Battese (1974), due to the presence of global shocks. A note on Granger causality is also provided, which is shown to be a necessary condition to perform the Wald test with serious implications to the validation of the model. An empirical exercise for the G-7 countries is presented, and the results substantially change with the di§erent estimation techniques. A small Monte Carlo simulation is also presented to investigate the size and power of the Wald test based on the considered estimators. The second chapter presents a study about Öscal sustainability based on a quantile autoregression (QAR) model. A novel methodology to separate periods of nonstationarity from stationary ones is proposed, which allows one to identify trajectories of public debt that are not compatible with Öscal sustainability. Moreover, such trajectories are used to construct a debt ceiling, that is, the largest value of public debt that does not jeopardize long-run Öscal sustainability. An out-of-sample forecast of such a ceiling is also constructed, and can be used by policy makers interested in keeping the public debt on a sustainable path. An empirical exercise by using Brazilian data is conducted to show the applicability of the methodology. In the third chapter, an alternative backtest to evaluate the performance of Value-at-Risk (VaR) models is proposed. The econometric methodology allows one to directly test the overall performance of a VaR model, as well as identify periods of an increased risk exposure, which seems to be a novelty in the literature. Quantile regressions provide an appropriate environment to investigate VaR models, since they can naturally be viewed as a conditional quantile function of a given return series. An empirical exercise is conducted for daily S&P500 series, and a Monte Carlo simulation is also presented, revealing that the proposed test might exhibit more power in comparison to other backtests.

Cópulas: uma alternativa para a estimação de modelos de risco multivariados

Dentre os principais desafios enfrentados no cálculo de medidas de risco de portfólios está em como agregar riscos. Esta agregação deve ser feita de tal sorte que possa de alguma forma identificar o efeito da diversificação do risco existente em uma operação ou em um portfólio. Desta forma, muito tem se feito para identificar a melhor forma para se chegar a esta definição, alguns modelos como o Valor em Risco (VaR) paramétrico assumem que a distribuição marginal de cada variável integrante do portfólio seguem a mesma distribuição , sendo esta uma distribuição normal, se preocupando apenas em modelar corretamente a volatilidade e a matriz de correlação. Modelos como o VaR histórico assume a distribuição real da variável e não se preocupam com o formato da distribuição resultante multivariada. Assim sendo, a teoria de Cópulas mostra-se um grande alternativa, à medida que esta teoria permite a criação de distribuições multivariadas sem a necessidade de se supor qualquer tipo de restrição às distribuições marginais e muito menos as multivariadas. Neste trabalho iremos abordar a utilização desta metodologia em confronto com as demais metodologias de cálculo de Risco, a saber: VaR multivariados paramétricos - VEC, Diagonal,BEKK, EWMA, CCC e DCC- e VaR histórico para um portfólio resultante de posições idênticas em quatro fatores de risco – Pre252, Cupo252, Índice Bovespa e Índice Dow Jones

The trade-off between incentives and endogenous risk

Standard models of moral hazard predict a negative relationship between risk and incentives, but the empirical work has not confirmed this prediction. In this paper, we propose a model with adverse selection followed by moral hazard, where effort and the degree of risk aversion are private information of an agent who can control the mean and the variance of profits. For a given contract, more risk-averse agents suppIy more effort in risk reduction. If the marginal utility of incentives decreases with risk aversion, more risk-averse agents prefer lower-incentive contractsj thus, in the optimal contract, incentives are positively correlated with endogenous risk. In contrast, if risk aversion is high enough, the possibility of reduction in risk makes the marginal utility of incentives increasing in risk aversion and, in this case, risk and incentives are negatively related.

Evaluating Value-at-Risk models via Quantile regressions

This paper is concerned with evaluating value at risk estimates. It is well known that using only binary variables to do this sacrifices too much information. However, most of the specification tests (also called backtests) avaliable in the literature, such as Christoffersen (1998) and Engle and Maganelli (2004) are based on such variables. In this paper we propose a new backtest that does not realy solely on binary variable. It is show that the new backtest provides a sufficiant condition to assess the performance of a quantile model whereas the existing ones do not. The proposed methodology allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker & Xiao, 2002). Our theorical findings are corroborated through a monte Carlo simulation and an empirical exercise with daily S&P500 time series.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.