A study on time-varying quantile and its applications

This Thesis is the result of my Master Degree studies at the Graduate School of Economics, Getúlio Vargas Foundation, from January 2004 to August 2006. am indebted to my Thesis Advisor, Professor Luiz Renato Lima, who introduced me to the Econometrics' world. In this Thesis, we study time-varying quantile process and we develop two applications, which are presented here as Part and Part II. Each of these parts was transformed in paper. Both papers were submitted. Part shows that asymmetric persistence induces ARCH effects, but the LMARCH test has power against it. On the other hand, the test for asymmetric dynamics proposed by Koenker and Xiao (2004) has correct size under the presence of ARCH errors. These results suggest that the LM-ARCH and the Koenker-Xiao tests may be used in applied research as complementary tools. In the Part II, we compare four different Value-at-Risk (VaR) methodologies through Monte Cario experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust method ologies have higher probability to predict VaRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate VaR for returns of São Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.

Solving the non-convexity problem in some shopping-time and human-capital models

Several works in the shopping-time and in the human-capital literature, due to the nonconcavity of the underlying Hamiltonian, use Örst-order conditions in dynamic optimization to characterize necessity, but not su¢ ciency, in intertemporal problems. In this work I choose one paper in each one of these two areas and show that optimality can be characterized by means of a simple aplication of Arrowís (1968) su¢ ciency theorem.

Um estudo da gênese das dynamic capabilities: o caso da tecnologia bancária no Brasil

Este trabalho analisa o desenvolvimento de dynamic capabilities em um contexto de turbulência institucional, diferente das condições em que esta perspectiva teórica costuma ser estudada. É feito um estudo de caso histórico e processual que analisa o surgimento das Dynamic Capabilities nos bancos brasileiros, a partir do desenvolvimento da tecnologia bancária que se deu entre os anos 1960 e 1990. Baseando-se nas proposições da Estratégia que analisam as vantagens competitivas das empresas através de seus recursos, conhecimentos e Dynamic Capabilities, é construído um framework com o qual são analisados diversos depoimentos dados ao livro “Tecnologia bancária no Brasil: uma história de conquistas, uma visão de futuro” (FONSECA; MEIRELLES; DINIZ, 2010) e em entrevistas feitas para este trabalho. Os depoimentos mostram que os bancos fizeram fortes investimentos em tecnologia a partir da reforma financeira de 1964, época em que se iniciou uma sequência de períodos com características próprias do ponto de vista institucional. Conforme as condições mudavam a cada período, os bancos também mudavam seu processo de informatização. No início, os projetos eram executados ad hoc, sob o comando direto dos líderes dos bancos. Com o tempo, à medida que a tecnologia evoluía, a infraestrutura tecnológica crescia e surgiam turbulências institucionais, os bancos progressivamente desenvolveram parcerias entre si e com fornecedores locais, descentralizaram a área de tecnologia, tornaram-se mais flexíveis, fortaleceram a governança corporativa e adotaram uma série de rotinas para cuidar da informática, o que levou ao desenvolvimento gradual das microfundações das Dynamic Capabilties nesses períodos. Em meados dos anos 1990 ocorreram a estabilização institucional e a abertura da economia à concorrência estrangeira, e assim o país colocou-se nas condições que a perspectiva teórica adotada considera ideais para que as Dynamic Capabilities sejam fontes de vantagem competitiva. Os bancos brasileiros mostraram-se preparados para enfrentar essa nova fase, o que é uma evidência de que eles haviam desenvolvido Dynamic Capabilities nas décadas precedentes, sendo que parte desse desenvolvimento podia ser atribuído às turbulências institucionais que eles haviam enfrentado.

A time-varying markov-switching model for economic growth

This paper investigates economic growth’s pattern of variation across and within countries using a Time-Varying Transition Matrix Markov-Switching Approach. The model developed follows the approach of Pritchett (2003) and explains the dynamics of growth based on a collection of different states, each of which has a sub-model and a growth pattern, by which countries oscillate over time. The transition matrix among the different states varies over time, depending on the conditioning variables of each country, with a linear dynamic for each state. We develop a generalization of the Diebold’s EM Algorithm and estimate an example model in a panel with a transition matrix conditioned on the quality of the institutions and the level of investment. We found three states of growth: stable growth, miraculous growth, and stagnation. The results show that the quality of the institutions is an important determinant of long-term growth, whereas the level of investment has varying roles in that it contributes positively in countries with high-quality institutions but is of little relevance in countries with medium- or poor-quality institutions.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.