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.

Simple calvo economies with heterogeneous pricing

A motivação para este trabalho vem dos principais resultados de Carvalho e Schwartzman (2008), onde a heterogeneidade surge a partir de diferentes regras de ajuste de preço entre os setores. Os momentos setoriais da duração da rigidez nominal são su cientes para explicar certos efeitos monetários. Uma vez que concordamos que a heterogeneidade é relevante para o estudo da rigidez de preços, como poderíamos escrever um modelo com o menor número possível de setores, embora com um mínimo de heterogeneidade su ciente para produzir qualquer impacto monetário desejado, ou ainda, qualquer três momentos da duração? Para responder a esta questão, este artigo se restringe a estudar modelos com hazard-constante e considera que o efeito acumulado e a dinâmica de curto-prazo da política monetária são boas formas de se resumir grandes economias heterogêneas. Mostramos que dois setores são su cientes para resumir os efeitos acumulados de choques monetários, e economias com 3 setores são boas aproximações para a dinâmica destes efeitos. Exercícios numéricos para a dinâmica de curto prazo de uma economia com rigidez de informação mostram que aproximar 500 setores usando apenas 3 produz erros inferiores a 3%. Ou seja, se um choque monetário reduz o produto em 5%, a economia aproximada produzirá um impacto entre 4,85% e 5,15%. O mesmo vale para a dinâmica produzida por choques de nível de moeda em uma economia com rigidez de preços. Para choques na taxa de crescimento da moeda, a erro máximo por conta da aproximação é de 2,4%.

A (semi-)parametric functional coefficient autoregressive conditional duration model

In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.

Earnings dynamics and inequality in Venezuela: 1995-1997

In this paper, we decompose the variance of logarithmic monthly earnings of prime age males into its permanent and transitory components, using a five-wave rotating panel from the Venezuelan “Encuesta de Hogares por Muestreo” from 1995 to 1997. As far as we know, this is the first time a variance components model is estimated for a developing country. We test several specifications and find that an error component model with individual random effects and first order serially correlated errors fits the data well. In the simplest model, around 22% of earnings variance is explained by the variance of permanent component, 77% by purely stochastic variation and the remaining 1% by serial correlation. These results contrast with studies from industrial countries where the permanent component is predominant. The permanent component is usually interpreted as the results of productivity characteristics of individuals whereas the transitory component is due to stochastic perturbations such as job and/or price instability, among others. Our findings may be due to the timing of the panel when occurred precisely during macroeconomic turmoil resulting from a severe financial crisis. The findings suggest that earnings instability is an important source of inequality in a region characterized by high inequality and macroeconomic instability.

Term structure dynamics and no-arbitrage under the Taylor rule

A determinação da taxa de juros estrutura a termo é um dos temas principais da gestão de ativos financeiros. Considerando a grande importância dos ativos financeiros para a condução das políticas econômicas, é fundamental para compreender a estrutura que é determinado. O principal objetivo deste estudo é estimar a estrutura a termo das taxas de juros brasileiras, juntamente com taxa de juros de curto prazo. A estrutura a termo será modelado com base em um modelo com uma estrutura afim. A estimativa foi feita considerando a inclusão de três fatores latentes e duas variáveis ​​macroeconômicas, através da técnica Bayesiana da Cadeia de Monte Carlo Markov (MCMC).

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Risk sharing and the household collective model

When the joint assumption of optimal risk sharing and coincidence of beliefs is added to the collective model of Browning and Chiappori (1998) income pooling and symmetry of the pseudo-Hicksian matrix are shown to be restored. Because these are also the features of the unitary model usually rejected in empirical studies one may argue that these assumptions are at odds with evidence. We argue that this needs not be the case. The use of cross-section data to generate price and income variation is based Oil a definition of income pooling or symmetry suitable for testing the unitary model, but not the collective model with risk sharing. AIso, by relaxing assumptions on beliefs, we show that symmetry and income pooling is lost. However, with usual assumptions on existence of assignable goods, we show that beliefs are identifiable. More importantly, if di:fferences in beliefs are not too extreme, the risk sharing hypothesis is still testable.

Modelo de volatilidade estocástica com saltos aplicado a commodities agrícolas

Mensalmente são publicados relatórios pelo Departamento de Agricultura dos Estados Unidos (USDA) onde são divulgados dados de condições das safras, oferta e demanda globais, nível dos estoques, que servem como referência para todos os participantes do mercado de commodities agrícolas. Esse mercado apresenta uma volatilidade acentuada no período de divulgação dos relatórios. Um modelo de volatilidade estocástica com saltos é utilizado para a dinâmica de preços de milho e de soja. Não existe um modelo ‘ideal’ para tal fim, cada um dos existentes têm suas vantagens e desvantagens. O modelo escolhido foi o de Oztukel e Wilmott (1998), que é um modelo de volatilidade estocástica empírica, incrementado com saltos determinísticos. Empiricamente foi demonstrado que um modelo de volatilidade estocástica pode ser bem ajustado ao mercado de commodities, e o processo de jump-diffusion pode representar bem os saltos que o mercado apresenta durante a divulgação dos relatórios. As opções de commodities agrícolas que são negociadas em bolsa são do tipo americanas, então alguns métodos disponíveis poderiam ser utilizados para precificar opções seguindo a dinâmica do modelo proposto. Dado que o modelo escolhido é um modelo multi-fatores, então o método apropriado para a precificação é o proposto por Longstaff e Schwartz (2001) chamado de Monte Carlo por mínimos quadrados (LSM). As opções precificadas pelo modelo são utilizadas em uma estratégia de hedge de uma posição física de milho e de soja, e a eficiência dessa estratégia é comparada com estratégias utilizando-se instrumentos disponíveis no mercado.

The macroeconomics of price adjustments under information frictions and menu costs

Esta tese se dedica ao estudo de modelos de fixação de preços e suas implicações macroeconômicas. Nos primeiros dois capítulos analiso modelos em que as decisões das firmas sobre seus preços praticados levam em conta custos de menu e de informação. No Capítulo 1 eu estimo tais modelos empregando estatísticas de variações de preços dos Estados Unidos, e concluo que: os custos de informação são significativamente maiores que os custos de menu; os dados claramente favorecem o modelo em que informações sobre condições agregadas são custosas enquanto que as idiossincráticas têm custo zero. No Capítulo 2 investigo as consequências de choques monetários e anúncios de desinflação usando os modelos previamente estimados. Mostro que o grau de não-neutralidade monetária é maior no modelo em que parte da informação é grátis. O Capítulo 3 é um artigo em conjunto com Carlos Carvalho (PUC-Rio) e Antonella Tutino (Federal Reserve Bank of Dallas). No artigo examinamos um modelo de fixação de preços em que firmas estão sujeitas a uma restrição de fluxo de informação do tipo Shannon. Calibramos o modelo e estudamos funções impulso-resposta a choques idiossincráticos e agregados. Mostramos que as firmas vão preferir processar informações agregadas e idiossincráticas conjuntamente ao invés de investigá-las separadamente. Este tipo de processamento gera ajustes de preços mais frequentes, diminuindo a persistência de efeitos reais causados por choques monetários.

Moral hazard and nonlinear pricing in a general equilibrium model

The paper analyzes a two period general equilibrium model with individual risk and moral hazard. Each household faces two individual states of nature in the second period. These states solely differ in the household's vector of initial endowments, which is strictly larger in the first state (good state) than in the second state (bad state). In the first period households choose a non-observable action. Higher leveis of action give higher probability of the good state of nature to occur, but lower leveIs of utility. Households have access to an insurance market that allows transfer of income across states of oature. I consider two models of financiaI markets, the price-taking behavior model and the nonlínear pricing modelo In the price-taking behavior model suppliers of insurance have a belief about each household's actíon and take asset prices as given. A variation of standard arguments shows the existence of a rational expectations equilibrium. For a generic set of economies every equilibrium is constraíned sub-optímal: there are commodity prices and a reallocation of financiaI assets satisfying the first period budget constraint such that, at each household's optimal choice given those prices and asset reallocation, markets clear and every household's welfare improves. In the nonlinear pricing model suppliers of insurance behave strategically offering nonlinear pricing contracts to the households. I provide sufficient conditions for the existence of equilibrium and investigate the optimality properties of the modeI. If there is a single commodity then every equilibrium is constrained optimaI. Ir there is more than one commodity, then for a generic set of economies every equilibrium is constrained sub-optimaI.

Optimal growth in a two-sector model without discounting: a geometric investigation

We characterize optimal policy in a two-sector growth model with xed coeÆcients and with no discounting. The model is a specialization to a single type of machine of a general vintage capital model originally formulated by Robinson, Solow and Srinivasan, and its simplicity is not mirrored in its rich dynamics, and which seem to have been missed in earlier work. Our results are obtained by viewing the model as a specific instance of the general theory of resource allocation as initiated originally by Ramsey and von Neumann and brought to completion by McKenzie. In addition to the more recent literature on chaotic dynamics, we relate our results to the older literature on optimal growth with one state variable: speci cally, to the one-sector setting of Ramsey, Cass and Koopmans, as well as to the two-sector setting of Srinivasan and Uzawa. The analysis is purely geometric, and from a methodological point of view, our work can be seen as an argument, at least in part, for the rehabilitation of geometric methods as an engine of analysis.

Who is the cowboy in Washington?: beating google at their own game with neuroscience and cryptography

Who was the cowboy in Washington? What is the land of sushi? Most people would have answers to these questions readily available,yet, modern search engines, arguably the epitome of technology in finding answers to most questions, are completely unable to do so. It seems that people capture few information items to rapidly converge to a seemingly 'obvious' solution. We will study approaches for this problem, with two additional hard demands that constrain the space of possible theories: the sought model must be both psychologically and neuroscienti cally plausible. Building on top of the mathematical model of memory called Sparse Distributed Memory, we will see how some well-known methods in cryptography can point toward a promising, comprehensive, solution that preserves four crucial properties of human psychology.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables