Estrutura a termo de volatilidade no mercado brasileiro e aplicação para risco de mercado

Com o objetivo de analisar o impacto na Estrutura a Termos de Volatilidade (ETV) das taxas de juros utilizando dois diferentes modelos na estimação da Estrutura a Termo das Taxas de Juros (ETTJ) e a suposição em relação a estrutura heterocedástica dos erros (MQO e MQG ponderado pela duration), a técnica procede em estimar a ETV utilizando-se da volatilidade histórica por desvio padrão e pelo modelo auto-regressivo Exponentially Weighted Moving Average (EWMA). Por meio do teste de backtesting proposto por Kupiec para o VaR paramétrico obtido com as volatilidades das ETV´s estimadas, concluí-se que há uma grande diferença na aderência que dependem da combinação dos modelos utilizados para as ETV´s. Além disso, há diferenças estatisticamente significantes entre as ETV´s estimadas em todo os pontos da curva, particularmente maiores no curto prazo (até 1 ano) e nos prazos mais longos (acima de 10 anos).

Testing consumption optimality using aggregate data

This paper tests the optimality of consumption decisions at the aggregate level taking into account popular deviations from the canonical constant-relative-risk-aversion (CRRA) utility function model-rule of thumb and habit. First, based on the critique in Carroll (2001) and Weber (2002) of the linearization and testing strategies using euler equations for consumption, we provide extensive empirical evidence of their inappropriateness - a drawback for standard rule- of-thumb tests. Second, we propose a novel approach to test for consumption optimality in this context: nonlinear estimation coupled with return aggregation, where rule-of-thumb behavior and habit are special cases of an all encompassing model. We estimated 48 euler equations using GMM. At the 5% level, we only rejected optimality twice out of 48 times. Moreover, out of 24 regressions, we found the rule-of-thumb parameter to be statistically significant only twice. Hence, lack of optimality in consumption decisions represent the exception, not the rule. Finally, we found the habit parameter to be statistically significant on four occasions out of 24.

The forward and the equity premium puzzles: two symptoms of the same illness?

The Forward Premium Puzzle (FPP) is how the empirical observation of a negative relation between future changes in the spot rates and the forward premium is known. Modeling this forward bias as a risk premium and under weak assumptions on the behavior of the pricing kernel, we characterize the potential bias that is present in the regressions where the FPP is observed and we identify the necessary and sufficient conditions that the pricing kernel has to satisfy to account for the predictability of exchange rate movements. Next, we estimate the pricing kernel applying two methods: i) one, du.e to Araújo et aI. (2005), that exploits the fact that the pricing kernel is a serial correlation common feature of asset prices, and ii) a traditional principal component analysis used as a procedure 1;0 generate a statistical factor modeI. Then, using on the sample and out of the sample exercises, we are able to show that the same kernel that explains the Equity Premi um Puzzle (EPP) accounts for the FPP in all our data sets. This suggests that the quest for an economic mo deI that generates a pricing kernel which solves the EPP may double its prize by simultaneously accounting for the FPP.

A notion of subgame perfect nash equilibrium under knightian uncertainty

We define a subgame perfect Nash equilibrium under Knightian uncertainty for two players, by means of a recursive backward induction procedure. We prove an extension of the Zermelo-von Neumann-Kuhn Theorem for games of perfect information, i. e., that the recursive procedure generates a Nash equilibrium under uncertainty (Dow and Werlang(1994)) of the whole game. We apply the notion for two well known games: the chain store and the centipede. On the one hand, we show that subgame perfection under Knightian uncertainty explains the chain store paradox in a one shot version. On the other hand, we show that subgame perfection under uncertainty does not account for the leaving behavior observed in the centipede game. This is in contrast to Dow, Orioli and Werlang(1996) where we explain by means of Nash equilibria under uncertainty (but not subgame perfect) the experiments of McKelvey and Palfrey(1992). Finally, we show that there may be nontrivial subgame perfect equilibria under uncertainty in more complex extensive form games, as in the case of the finitely repeated prisoner's dilemma, which accounts for cooperation in early stages of the game .

Welfare and growth effects of alternative fiscal rules for infrastructure investment in Brazil

This article studies the interplay between fiscal rules, public investment and growth in Brazil. It is investigated if it would make sense to raise public investment and, if so, under which fiscal rule it is best to do it — whether through tax financing, debt financing, or a reduction of public consumption. We construct and simulate a competitive general equilibrium model, calibrated to Brazilian economy, in which public capital is a component of the production function and public consumption directly affects individuals’ well-being. After assessing the impacts of alternative fiscal rules, the paper concludes that the most desirable financing scheme is the reduction of public consumption, which dominates the others in terms of output and welfare gains. The model replicates the observed growth slowdown of the Brazilian economy when we increase taxes and reduce public capital formation to the levels observed after 1980 and shows that the growth impact of the expansion of tax collection in Brazil was much larger than that of public investment compression.

Robustness and stabilization properties of monetary policy rules in Brazil

Based on three versions of a small macroeconomic model for Brazil, this paper presents empirical evidence on the effects of parameter uncertainty on monetary policy rules and on the robustness of optimal and simple rules over different model specifications. By comparing the optimal policy rule under parameter uncertainty with the rule calculated under purely additive uncertainty, we find that parameter uncertainty should make policymakers react less aggressively to the economy's state variables, as suggested by Brainard's "conservatism principIe", although this effect seems to be relatively small. We then informally investigate each rule's robustness by analyzing the performance of policy rules derived from each model under each one of the alternative models. We find that optimal rules derived from each model perform very poorly under alternative models, whereas a simple Taylor rule is relatively robusto We also fmd that even within a specific model, the Taylor rule may perform better than the optimal rule under particularly unfavorable realizations from the policymaker' s loss distribution function.

Mensuração de risco para empresas do ramo frigorífico

Este trabalho apresenta metodologia de mensuração e gestão de risco para empresas do ramo frigorífico. A ferramenta utilizada é conhecida como Earnings at Risk (EaR), e se adota uma visão top-down, que mostra a variação do resultado da empresa de acordo com variáveis explicativas de mercado e variáveis idiossincráticas. Através da eliminação de multicolinearidade entre essas variáveis com o uso da métrica de Análise de Componentes Principais (ACP), busca-se analisar como o novo EaR se comportaria frente ao enfoque usual, construído com um modelo de regressão linear múltipla. Variáveis dummy fazem parte do modelo de estimação do resultado futuro das empresas frigoríficas, relacionadas à ocorrência ou não de doenças que afetam o gado bovino, e à retirada de embargos econômicos de países importadores durante o período de análise. Ao fim do trabalho é verificado que as variáveis dummy não possuem relevância para a determinação de EaR, e que não se chega a conclusão de que o modelo de EaR com ACP se mostra melhor com menos variáveis, mantendo a mesma variância e significância estatística originais.

Consumo, poupança precaucionária, lei crédito consignado e impacto sobre alocação de ativos e distribuição de consumo

Esta tese é composta por três ensaios a respeito de consumo e poupança. O primeiro traz uma aplicação de poupança precaucionária para os Estados Unidos. O segundo e terceiro artigos fazem aplicações para o Brasil usando a POF 1995-96, 2002-03 e 2008- 09 para o segundo, e as duas últimas pesquisas para o terceiro. O segundo artigo avalia convergência nos padrões de gastos das famílias em duas cestas distintas de bens: uma de alimentos e outra para produtos eletroeletrônicos, enquanto o terceiro artigo explora a Lei de Crédito Consignado e seu impacto na forma de alocação da poupança precaucionária das famílias.

Efeitos de variáveis macroeconômicas no nível de liquidez de empresas brasileiras

Com a evolução dos mercados e a possibilidade de acesso a informações em tempo real, as empresas se encontram bastante expostas a variações em sua liquidez. Surge então uma necessidade de se estudar o que afeta sua operação e de que forma são afetadas por choques na economia. Este trabalho tem como objetivo investigar como variações de indicadores macroeconômicos, como por exemplo, mudanças na taxa de câmbio, no PIB, na inflação e na taxa de juros impactam no nível de liquidez corrente das empresas. Foram selecionados dados de empresas brasileiras ativas para o período de 2003 até 2011 (dados trimestrais), com ações negociadas na BM&FBovespa e não pertencentes ao setor financeiro e de seguros. Os resultados sugerem que o nível de liquidez das empresas é afetado por algumas variações de indicadores macroeconômicos. Verificou-se que variáveis como PIB, IBOVESPA e taxa de juros se relacionam positivamente com o índice de liquidez corrente. Já as variáveis câmbio e inflação se relacionam negativamente.

The effect of default risk on trading book capital requirements for public equities : an irc application for the Brazilian market

Esse é um dos primeiros trabalhos a endereçar o problema de avaliar o efeito do default para fins de alocação de capital no trading book em ações listadas. E, mais especificamente, para o mercado brasileiro. Esse problema surgiu em crises mais recentes e que acabaram fazendo com que os reguladores impusessem uma alocação de capital adicional para essas operações. Por essa razão o comitê de Basiléia introduziu uma nova métrica de risco, conhecida como Incremental Risk Charge. Essa medida de risco é basicamente um VaR de um ano com um intervalo de confiança de 99.9%. O IRC visa medir o efeito do default e das migrações de rating, para instrumentos do trading book. Nessa dissertação, o IRC está focado em ações e como consequência, não leva em consideração o efeito da mudança de rating. Além disso, o modelo utilizado para avaliar o risco de crédito para os emissores de ação foi o Moody’s KMV, que é baseado no modelo de Merton. O modelo foi utilizado para calcular a PD dos casos usados como exemplo nessa dissertação. Após calcular a PD, simulei os retornos por Monte Carlo após utilizar um PCA. Essa abordagem permitiu obter os retornos correlacionados para fazer a simulação de perdas do portfolio. Nesse caso, como estamos lidando com ações, o LGD foi mantido constante e o valor utilizado foi baseado nas especificações de basiléia. Os resultados obtidos para o IRC adaptado foram comparados com um VaR de 252 dias e com um intervalo de confiança de 99.9%. Isso permitiu concluir que o IRC é uma métrica de risco relevante e da mesma escala de uma VaR de 252 dias. Adicionalmente, o IRC adaptado foi capaz de antecipar os eventos de default. Todos os resultados foram baseados em portfolios compostos por ações do índice Bovespa.

A bidimensional model of matching in the marriage market with women labor decision

We construct a frictionless matching model of the marriage market where women have bidimensional attributes, one continuous (income) and the other dichotomous (home ability). Equilibrium in the marriage market determines intrahousehold allocation of resources and female labor participation. Our model is able to predict partial non-assortative matching, with rich men marrying women with low income but high home ability. We then perform numerical exercises to evaluate the impacts of income taxes in individual welfare and find that there is considerable divergence in the female labor participation response to taxes between the short run and the long run.

Cherry picking with synthetic controls

The synthetic control (SC) method has been recently proposed as an alternative method to estimate treatment e ects in comparative case studies. Abadie et al. [2010] and Abadie et al. [2015] argue that one of the advantages of the SC method is that it imposes a data-driven process to select the comparison units, providing more transparency and less discretionary power to the researcher. However, an important limitation of the SC method is that it does not provide clear guidance on the choice of predictor variables used to estimate the SC weights. We show that such lack of speci c guidances provides signi cant opportunities for the researcher to search for speci cations with statistically signi cant results, undermining one of the main advantages of the method. Considering six alternative speci cations commonly used in SC applications, we calculate in Monte Carlo simulations the probability of nding a statistically signi cant result at 5% in at least one speci cation. We nd that this probability can be as high as 13% (23% for a 10% signi cance test) when there are 12 pre-intervention periods and decay slowly with the number of pre-intervention periods. With 230 pre-intervention periods, this probability is still around 10% (18% for a 10% signi cance test). We show that the speci cation that uses the average pre-treatment outcome values to estimate the weights performed particularly bad in our simulations. However, the speci cation-searching problem remains relevant even when we do not consider this speci cation. We also show that this speci cation-searching problem is relevant in simulations with real datasets looking at placebo interventions in the Current Population Survey (CPS). In order to mitigate this problem, we propose a criterion to select among SC di erent speci cations based on the prediction error of each speci cations in placebo estimations

Revisiting the synthetic control estimator

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. The SC relies on the assumption that there is a weighted average of the control units that reconstruct the potential outcome of the treated unit in the absence of treatment. If these weights were known, then one could estimate the counterfactual for the treated unit using this weighted average. With these weights, the SC would provide an unbiased estimator for the treatment effect even if selection into treatment is correlated with the unobserved heterogeneity. In this paper, we revisit the SC method in a linear factor model where the SC weights are considered nuisance parameters that are estimated to construct the SC estimator. We show that, when the number of control units is fixed, the estimated SC weights will generally not converge to the weights that reconstruct the factor loadings of the treated unit, even when the number of pre-intervention periods goes to infinity. As a consequence, the SC estimator will be asymptotically biased if treatment assignment is correlated with the unobserved heterogeneity. The asymptotic bias only vanishes when the variance of the idiosyncratic error goes to zero. We suggest a slight modification in the SC method that guarantees that the SC estimator is asymptotically unbiased and has a lower asymptotic variance than the difference-in-differences (DID) estimator when the DID identification assumption is satisfied. If the DID assumption is not satisfied, then both estimators would be asymptotically biased, and it would not be possible to rank them in terms of their asymptotic bias.