Estimating the stochastic discount factor without a utility function

Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the serial-correlation ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns, does not depend on any parametric function representing preferences, is suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles, and can be a basis to construct an estimator of the risk-free rate. For post-war data, our estimator is close to unity most of the time, yielding an average annual real discount rate of 2.46%. In formal testing, we cannot reject standard preference speciÖcations used in the literature and estimates of the relative risk-aversion coe¢ cient are between 1 and 2, and statistically equal to unity. Using our SDF estimator, we found little signs of the equity-premium puzzle for the U.S.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE transactions data, with special attention to IBM price durations. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

Estimação conjunta das elasticidades: preço da escolha da marca e da quantidade comprada com dados escaneados

O objetivo geral desta tese é estimar a elasticidade-preço da demanda de forma conjunta, decomposta em elasticidade-preço da escolha da marca e da quantidade comprada, e discutir as implicações desta decomposição para uma categoria específica de produto. Para isto foram usados dados escaneados de uma amostra de domicílios no contexto varejista brasileiro. Oito hipóteses foram testadas por meio de dois modelos. O primeiro refere-se à decisão de escolha da marca, em que foi empregado o modelo logit condicional baseado na maximização da utilidade do domicílio. O segundo envolveu equações de demanda, obtidas pelo modelo clássico de regressão linear. Ambos foram especificados de forma que se pudesse testar a dependência das duas decisões de compra. No que diz respeito à validação, o modelo de escolha da marca demonstrou uma satisfatória capacidade de previsão, comparativamente aos modelos analisados na literatura. Implicações gerenciais incluem específicas decisões e ações de preço para as marcas, já que a natureza da decomposição das elasticidades-preço varia entre marcas.

DCE: the dynamic conditional execution in a multipath control independent architecture

This thesis presents DCE, or Dynamic Conditional Execution, as an alternative to reduce the cost of mispredicted branches. The basic idea is to fetch all paths produced by a branch that obey certain restrictions regarding complexity and size. As a result, a smaller number of predictions is performed, and therefore, a lesser number of branches are mispredicted. DCE fetches through selected branches avoiding disruptions in the fetch flow when these branches are fetched. Both paths of selected branches are executed but only the correct path commits. In this thesis we propose an architecture to execute multiple paths of selected branches. Branches are selected based on the size and other conditions. Simple and complex branches can be dynamically predicated without requiring a special instruction set nor special compiler optimizations. Furthermore, a technique to reduce part of the overhead generated by the execution of multiple paths is proposed. The performance achieved reaches levels of up to 12% when comparing a Local predictor used in DCE against a Global predictor used in the reference machine. When both machines use a Local predictor, the speedup is increased by an average of 3-3.5%.

Dynamic hedging in Markov regimes

This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.

Modelos de risco de mercado com fat tail : análise empírica de value at risk and expected shortfall para ativos financeiros brasileiros

O objetivo deste trabalho foi mostrar modelagens alternativas à tradicional maneira de se apurar o risco de mercado para ativos financeiros brasileiros. Procurou-se cobrir o máximo possível de fatores de risco existentes no Brasil; para tanto utilizamos as principais proxies para instrumentos de Renda Fixa. Em momentos de volatilidade, o gerenciamento de risco de mercado é bastante criticado por trabalhar dentro de modelagens fundamentadas na distribuição normal. Aqui reside a maior contribuição do VaR e também a maior crítica a ele. Adicionado a isso, temos um mercado caracterizado pela extrema iliquidez no mercado secundário até mesmo em certos tipos de títulos públicos federais. O primeiro passo foi fazer um levantamento da produção acadêmica sobre o tema, seja no Brasil ou no mundo. Para a nossa surpresa, pouco, no nosso país, tem se falado em distribuições estáveis aplicadas ao mercado financeiro, seja em gerenciamento de risco, precificação de opções ou administração de carteiras. Após essa etapa, passamos a seleção das variáveis a serem utilizadas buscando cobrir uma grande parte dos ativos financeiros brasileiros. Assim, deveríamos identificar a presença ou não da condição de normalidade para, aí sim, realizarmos as modelagens das medidas de risco, VaR e ES, para os ativos escolhidos, As condições teóricas e práticas estavam criadas: demanda de mercado (crítica ao método gausiano bastante difundido), ampla cobertura de ativos (apesar do eventual questionamento da liquidez), experiência acadêmica e conhecimento internacional (por meio de detalhado e criterioso estudo da produção sobre o tema nos principais meios). Analisou-se, desta forma, quatro principais abordagens para o cálculo de medidas de risco sendo elas coerentes (ES) ou não (VaR). É importante mencionar que se trata de um trabalho que poderá servir de insumo inicial para trabalhos mais grandiosos, por exemplo, aqueles que incorporarem vários ativos dentro de uma carteira de riscos lineares ou, até mesmo, para ativos que apresentem risco não-direcionais.

The impact of AIDS on income and human capital

This paper studies the impact of HIV/AIDS on per capita income and education. It explores two channels from HIV/AIDS to income that have not been sufficiently stressed by the literature: the reduction of the incentives to study due to shorter expected longevity and the reduction of productivity of experienced workers. In the model individuals live for three periods, may get infected in the second period and with some probability die of Aids before reaching the third period of their life. Parents care for the welfare of the future generations so that they will maximize lifetime utility of their dynasty. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, thirty percent poorer than they would be without AIDS. Schooling will decline in some cases by forty percent. These figures are dramatically reduced with widespread medical treatment, as it increases the survival probability and productivity of infected individuals.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE price duration data on the IBM stock. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

Reusing values in a dynamic conditional execution architecture

A Execução Condicional Dinâmica (DCE) é uma alternativa para redução dos custos relacionados a desvios previstos incorretamente. A idéia básica é buscar todos os fluxos produzidos por um desvio que obedecem algumas restrições relativas à complexidade e tamanho. Como conseqüência, um número menor de previsões é executado, e assim, um número mais baixo de desvios é incorretamente previsto. Contudo, tal como outras soluções multi-fluxo, o DCE requer uma estrutura de controle mais complexa. Na arquitetura DCE, é observado que várias réplicas da mesma instrução são despachadas para as unidades funcionais, bloqueando recursos que poderiam ser utilizados por outras instruções. Essas réplicas são geradas após o ponto de convergência dos diversos fluxos em execução e são necessárias para garantir a semântica correta entre instruções dependentes de dados. Além disso, o DCE continua produzindo réplicas até que o desvio que gerou os fluxos seja resolvido. Assim, uma seção completa do código pode ser replicado, reduzindo o desempenho. Uma alternativa natural para esse problema é reusar essas seções (ou traços) que são replicadas. O objetivo desse trabalho é analisar e avaliar a efetividade do reuso de valores na arquitetura DCE. Como será apresentado, o princípio do reuso, em diferentes granularidades, pode reduzir efetivamente o problema das réplicas e levar a aumentos de desempenho.

Essays in heterogeneous agent macroeconomics

This thesis is comprised of three chapters. The first article studies the determinants of the labor force participation of elderly American males and investigates the factors that may account for the changes in retirement between 1950 and 2000. We develop a life-cycle general equilibrium model with endogenous retirement that embeds Social Security legislation and Medicare. Individuals are ex ante heterogeneous with respect to their preferences for leisure and face uncertainty about labor productivity, health status and out-of-pocket medical expenses. The model is calibrated to the U.S. economy in 2000 and is able to reproduce very closely the retirement behavior of the American population. It reproduces the peaks in the distribution of Social Security applications at ages 62 and 65 and the observed facts that low earners and unhealthy individuals retire earlier. It also matches very closely the increase in retirement from 1950 to 2000. Changes in Social Security policy - which became much more generous - and the introduction of Medicare account for most of the expansion of retirement. In contrast, the isolated impact of the increase in longevity was a delaying of retirement. In the second article, I develop an overlapping generations model of criminal behavior, which extends prior research on crime by taking into account individuals' labor supply decisions and the stigma effect that affects convicted offenders, lowering their likelihood of employment. I use the model to guide a quantitative assessment of the determinants of crime and of a counterfactual experiment in which an income redistribution policy is thought as an alternative to greater law enforcement. The model economy considered in this paper is populated by heterogeneous agents who live for a realistic number of periods, have preferences over consumption and leisure, and differ in terms of their age, their skills as well as their employment shocks. In addition, savings may be precautionary and allow partial insurance against the labor income shocks. Because of the lack of full insurance, this model generates an endogenous distribution of wealth across consumers, enabling us to assess the welfare implications of the redistribution policy experiment. I calibrated the model using the US data for 1980 and then use the model to investigate the changes in criminality between 1980 and 1996. The main results that come out of this study are: 1) Law enforcement policy was the most important factor behind the fall in criminality in the period, while the increase in inequality was the most important single factor promoting crime; 2) Stigmatization is not a free-cost crime control policy; 3) Income redistribution can be a powerful alternative policy to fight crime. Finally, the third article studies the impact of HIV/AIDS on per capita income and education. It explores two channels from HIV/AIDS to income that have not been sufficiently stressed by the literature: the reduction of the incentives to study due to shorter expected longevity and the reduction of productivity of experienced workers. In the model individuals live for three periods, may get infected in the second period and with some probability die of Aids before reaching the third period of their life. Parents care for the welfare of the future generations so that they will maximize lifetime utility of their dynasty. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, thirty percent poorer than they would be without AIDS. Schooling will decline in some cases by forty percent. These figures are dramatically reduced with widespread medical treatment, as it increases the survival probability and productivity of infected individuals.

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Conditional alphas and realized betas

This paper proposes a two-step procedure to back out the conditional alpha of a given stock using high-frequency data. We rst estimate the realized factor loadings of the stocks, and then retrieve their conditional alphas by estimating the conditional expectation of their risk-adjusted returns. We start with the underlying continuous-time stochastic process that governs the dynamics of every stock price and then derive the conditions under which we may consistently estimate the daily factor loadings and the resulting conditional alphas. We also contribute empiri-cally to the conditional CAPM literature by examining the main drivers of the conditional alphas of the S&P 100 index constituents from January 2001 to December 2008. In addition, to con rm whether these conditional alphas indeed relate to pricing errors, we assess the performance of both cross-sectional and time-series momentum strategies based on the conditional alpha estimates. The ndings are very promising in that these strategies not only seem to perform pretty well both in absolute and relative terms, but also exhibit virtually no systematic exposure to the usual risk factors (namely, market, size, value and momentum portfolios).

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.

Evidence of eligibility manipulation for conditional cash transfer programs

This paper assesses whether eligibility for conditional cash transfer programs have been manipulated, as well as the impact of this phenomenon on time allocation within households. To perform this analysis, we use data from the 2006 PNAD (Brazilian national household survey) and investigate the eligibility manipulation for the Bolsa Família (Family Stipend) program during this time period. The program assists families with a monthly per capita income of around R$120.00 (US$60.00). By applying the tests developed by McCrary (2008), we find suggestive evidence that individuals manipulate their income by voluntarily reducing their labor supply in order to become eligible to the program. Moreover, the reduction in labor supply is greater among women, especially single or divorced mothers. This evidence raises some concern about the unintended consequences related to the eligibility criteria utilized by Bolsa Família, as well as the program’s impact on individuals living in extreme poverty.

Effects on school enrollment and performance of a conditional transfers program in Mexico

We study the effects of a conditional transfers program on school enrollment and performance in Mexico. We provide a theoretical framework for analyzing the dynamic educational decision and process inc1uding the endogeneity and uncertainty of performance (passing grades) and the effect of a conditional cash transfer program for children enrolled at school. Careful identification of the program impact on this model is studied. This framework is used to study the Mexican social program Progresa in which a randomized experiment has been implemented and allows us to identify the effect of the conditional cash transfer program on enrollment and performance at school. Using the mIes of the conditional program, we can explain the different incentive effects provided. We also derive the formal identifying assumptions needed to provide consistent estimates of the average treatment effects on enrollment and performance at school. We estimate empirically these effects and find that Progresa had always a positive impact on school continuation whereas for performance it had a positive impact at primary school but a negative one at secondary school, a possible consequence of disincentives due to the program termination after the third year of secondary school.