Speculative bubbles and contagion: analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model

Revendo a definição e determinação de bolhas especulativas no contexto de contágio, este estudo analisa a bolha do DotCom nos mercados acionistas americanos e europeus usando o modelo de correlação condicional dinâmica (DCC) proposto por Engle e Sheppard (2001) como uma explicação econométrica e, por outro lado, as finanças comportamentais como uma explicação psicológica. Contágio é definido, neste contexto, como a quebra estatística nos DCC’s estimados, medidos através das alterações das suas médias e medianas. Surpreendentemente, o contágio é menor durante bolhas de preços, sendo que o resultado principal indica a presença de contágio entre os diferentes índices dos dois continentes e demonstra a presença de alterações estruturais durante a crise financeira.

Speculative bubbles and contagion: analysis of volatility's clusters during the DotCom bubble based on the dynamic conditional correlation model

Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

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.

International portfolio diversification: evidence from emerging markets

Taking into account previous research we could assume to be beneficial to diversify investments in emerging economies. We investigate in the paper International Portfolio Diversification: evidence from Emerging Markets if it still holds true, given the assumption of larger world markets integration. Our results suggest a wide spread positive time-varying correlations of emerging and developed markets. However, pair-wise cross-country correlations gave evidence that emerging markets have low integration with developed markets. Consequently, we evaluate out-of-sample performance of a portfolio with emerging equity countries, confirming the initial statement that it has a better a risk-adjusted performance over a purely developed markets portfolio.

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.

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.

A conditional likelihood ratio test for structural models

This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

The long-term effects of conditional cash transfers on child labor and school enrollment

This paper investigates the long-term e ects of conditional cash transfers on school attainment and child labor. To this end, we construct a dynamic heterogeneous agent model, calibrate it with Brazilian data, and introduce a policy similar to the Brazilian Bolsa Fam lia. Our results suggest that this type of policy has a very strong impact on educational outcomes, sharply increasing primary school completion. The conditional transfer is also able to reduce the share of working children from 22% to 17%. We then compute the transition to the new steady state and show that the program actually increases child labor over the short run, because the transfer is not enough to completely cover the schooling costs, so children have to work to be able to comply with the program's schooling eligibility requirement. We also evaluate the impacts on poverty, inequality, and welfare.