A hipótese de Samuelson no mercado futuro brasileiro: um estudo empírico

A pesquisa objetivou testar a existência, no mercado futuro brasileiro, do fenômeno que a literatura batizou como a Hipótese de Samuelson, que postula que a volatilidade dos retornos de preços futuros aumenta à medida que o vencimento do contrato respectivo se aproxima. Para testar a hipótese em foco, foram utilizados dados dos seguintes contratos futuros, negociados na BM&F - Bolsa de Mercadorias & Futuros : contrato futuro de Ibovespa, contrato futuro de dólar comercial, contrato futuro de boi gordo e contrato futuro de café arábica. O período abrangido estendeu-se de 30 de junho de 1994 a 30 de abril de 1998. Aplicação de quatro testes distintos a cada contrato não autoriza afirmar-se que a Hipótese de Samuelson se observa no mercado futuro brasileiro.

Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Volatility spillovers for spot, futures, and ETF prices in energy and agriculture

The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, much of the previous research has sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility spillovers. However, it must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which needs to be corrected. The paper not only considers futures prices as a widely-used hedging instrument, but also takes an interesting new hedging instrument, ETF, into account. ETF is regarded as index futures when investors manage their portfolios, so it is possible to calculate an optimal dynamic hedging ratio. This is a very useful and interesting application for the estimation and testing of volatility spillovers. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.

A study of stock market linkages between the US and frontier countries

My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.

Modeling conditional correlations of asset returns : a smooth transition approach

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Intraday Seasonalities and Macroeconomic News Announcements

Using a data set consisting of three years of 5-minute intraday stock index returns for major European stock indices and U.S. macroeconomic surprises, the conditional mean and volatility behaviors in European market were investigated. The findings suggested that the opening of the U.S market significantly raised the level of volatility in Europe, and that all markets respond in an identical fashion. Furthermore, the U.S. macroeconomic surprises exerted an immediate and major impact on both European stock markets’ returns and volatilities. Thus, high frequency data appear to be critical for the identification of news that impacted the markets.

Problemas inversos em engenharia financeira: regularização com critério de entropia

Esta dissertação aplica a regularização por entropia máxima no problema inverso de apreçamento de opções, sugerido pelo trabalho de Neri e Schneider em 2012. Eles observaram que a densidade de probabilidade que resolve este problema, no caso de dados provenientes de opções de compra e opções digitais, pode ser descrito como exponenciais nos diferentes intervalos da semireta positiva. Estes intervalos são limitados pelos preços de exercício. O critério de entropia máxima é uma ferramenta poderosa para regularizar este problema mal posto. A família de exponencial do conjunto solução, é calculado usando o algoritmo de Newton-Raphson, com limites específicos para as opções digitais. Estes limites são resultados do princípio de ausência de arbitragem. A metodologia foi usada em dados do índice de ação da Bolsa de Valores de São Paulo com seus preços de opções de compra em diferentes preços de exercício. A análise paramétrica da entropia em função do preços de opções digitais sínteticas (construídas a partir de limites respeitando a ausência de arbitragem) mostraram valores onde as digitais maximizaram a entropia. O exemplo de extração de dados do IBOVESPA de 24 de janeiro de 2013, mostrou um desvio do princípio de ausência de arbitragem para as opções de compra in the money. Este princípio é uma condição necessária para aplicar a regularização por entropia máxima a fim de obter a densidade e os preços. Nossos resultados mostraram que, uma vez preenchida a condição de convexidade na ausência de arbitragem, é possível ter uma forma de smile na curva de volatilidade, com preços calculados a partir da densidade exponencial do modelo. Isto coloca o modelo consistente com os dados do mercado. Do ponto de vista computacional, esta dissertação permitiu de implementar, um modelo de apreçamento que utiliza o princípio de entropia máxima. Três algoritmos clássicos foram usados: primeiramente a bisseção padrão, e depois uma combinação de metodo de bisseção com Newton-Raphson para achar a volatilidade implícita proveniente dos dados de mercado. Depois, o metodo de Newton-Raphson unidimensional para o cálculo dos coeficientes das densidades exponenciais: este é objetivo do estudo. Enfim, o algoritmo de Simpson foi usado para o calculo integral das distribuições cumulativas bem como os preços do modelo obtido através da esperança matemática.

A importância dos fluxos de caixa na análise da solvência, liquidez e visibilidade das empresas

Orientada por: Prof. Doutora Cláudia Lopes

A gestão de riscos de negócio e o seu reporte

Dissertação de Mestrado Apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Auditoria, sob orientação do Mestre Carlos Mendes.

O capital intelectual e a performance das empresas do PSI 20

Num contexto de crescente complexidade e disponibilidade de informação, a gestão do capital intelectual assume cada vez mais preponderância como vantagem competitiva para as empresas que procuram maximizar o valor gerado. Esta investigação usa como metodologia príncipal o VAIC (coeficiente intelectual do valor adicionado), para assim estudar a existência de relação entre capital intelectual e a performance bolsista e financeira das empresas do PSI20. O VAIC é decomposto nos seus três indicadores de eficiência, tais como: capital humano, capital estrutural e capital físico. Os dados contemplam quinze empresas e nove anos de análise (2003 - 2011). Elaborou-se uma abordagem que recorre à utilização de técnicas econométricas para reduzir potênciais falhas no tratamento de dados em painel. Os resultados da análise demonstram uma relação positiva entre a aposta em capital intelectual a performance bolsista e financeira, ou seja, a utilização e gestão eficientes do capital intelectual contribuem de forma significativa na avaliação bolsista e financeira das empresas do PSI20.

Aplicação do modelo de Elton-Gruber para a construção de carteira no índice PSI-20

Os mercados financeiros têm um papel fundamental na dinamização das economias modernas. Às empresas cotadas oferece o capital necessário para impulsionar o seu crescimento e aos investidores individuais proporciona a diversificação das suas carteiras, usufruindo desta forma do crescimento e da vitalidade da economia mundial. A gestão de carteiras de ativos financeiros constitui uma área que procura apresentar mecanismos para a obtenção de uma relação ótima entre retorno e risco. Neste sentido, inúmeros estudos têm contribuído de forma significativa para a eficiência e para a prática desta técnica. Esta dissertação pretende analisar a metodologia desenvolvida por Elton-Gruber para a construção de carteiras otimizadas e aplicar as técnicas subjacentes ao mercado acionista português. Para o efeito, serão realizadas pesquisas em fontes bibliográficas da especialidade e serão consultadas bases de dados de cotações históricas das ações e do índice de mercado nacional. A aplicação incidiu sobre ações cotadas no índice PSI-20 durante o período compreendido entre 2010 e 2014. No intuito de melhorar a compreensão das séries de retornos das amostras, o estudo de caráter quantitativo também recorreu à análise estatística. As evidências mostram que a carteira otimizada, no período em análise, contém apenas as ações da empresa Portucel. Este resultado estará condicionado pelos efeitos da crise financeira que iniciou em 2008.

Gamma stochastic volatility models

This paper presents gamma stochastic volatility models and investigates its distributional and time series properties. The parameter estimators obtained by the method of moments are shown analytically to be consistent and asymptotically normal. The simulation results indicate that the estimators behave well. The insample analysis shows that return models with gamma autoregressive stochastic volatility processes capture the leptokurtic nature of return distributions and the slowly decaying autocorrelation functions of squared stock index returns for the USA and UK. In comparison with GARCH and EGARCH models, the gamma autoregressive model picks up the persistence in volatility for the US and UK index returns but not the volatility persistence for the Canadian and Japanese index returns. The out-of-sample analysis indicates that the gamma autoregressive model has a superior volatility forecasting performance compared to GARCH and EGARCH models.

Evaluating interval forecasts of high-frequency financial data

A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated.

Structural effects and spillovers in HSIF, HSI and S & P500 volatility

We adopt a BEKK-GARCH framework and employ a systematic approach to jointly examine structural breaks in the Hong Kong cash index and index futures volatility and volatility spillovers from the S&P 500 cash and futures. Multiple switching dummy variables are included in the variance equations to test for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market. Abolishment of the up-tick rule, increase of initial margins and electronic trading of the Hang Seng Index Futures (HSIF) are found to have significant impact when US market spillovers are excluded from a restricted model. Volatility spillovers from the US market are found to have a significant impact and account for some mis-specification in the restricted model.