Macroeconomic effects of monetary policy in the Eurozone

To study the macroeconomic effects of unconventional monetary policy across the different countries of the eurozone, I develop an identification scheme to disentangle conventional from non-conventional policy shocks, using futures contracts on overnight interest rates and the size of the European Central Bank balance sheet. Setting these shocks as endogenous variables in a structural vector autoregressive (SVAR) model, along with the CPI and the employment rate, estimated impulse response functions of policy to macroeconomic variables are studied. I find that unconventional policy shocks generated mixed effects in inflation but had a positive impact on employment, with the exception of Portugal, Spain, Greece and Italy where the employment response is close to zero or negative. The heterogeneity that characterizes the responses shows that the monetary policy measures taken in recent years were not sufficient to stabilize the economies of the eurozone countries under more severe economic conditions.

Transmission of macro-liquidity shocks to liquidity-sorted stock portfolios’ returns: The role of the financial crisis

This study examines the impact of macro-liquidity shocks on the returns of UK stock portfolios sorted on the basis of a series of micro-liquidity measures. The macro-liquidity shocks are extracted on the meeting days of the Bank of England Monetary Policy Committee relative to market expectations embedded in futures contracts on the 3-month LIBOR during the period June 1999- December 2009. We report definitive evidence that these shocks are transmitted to the cross-section of liquidity-sorted portfolios, with most liquid stocks playing a very active role. Our results emphatically document that the shocks-returns relationship has reversed its sign during the recent financial crisis; the standard inverse relationship between interest rate surprises and portfolios’ returns before the crisis has turned into positive during the crisis. This finding confirms the inability of interest rate cuts to boost returns in the shortrun during the crisis, because these were perceived by market participants as a signal of a deteriorating economic outlook.

Money Cycles

Operating overheads are widespread and lead to concentrated bursts of activity. To transfer resources between active and idle spells, agents demand financial assets. Futures contracts and lotteries are unsuitable, as they have substantial overheads of their own.We show that money – under efficient monetary policy – is a liquid asset that leads to efficient allocations. Under all other policies, agents follow inefficient “money cycle” patterns of saving, activity, and inactivity. Agents spend their money too quickly – a “hot potato effect of inflation”. We show that inflation can stimulate inefficiently high aggregate output.

Information revelation and market incompleteness

\documentstyle[portada,11pt]{article}This paper shows that the presence of private information in aneconomy can be a source of market incompleteness even when it is feasibleto issue a set of securities that completely eliminates the informationalasymmetries in equilibrium. We analyze a simple security design model in which avolume maximizing futures exchange chooses not only the characteristics ofeach individual contract but also the number of contracts. Agents have rationalexpectations and differ in information, endowments and, possibly, attitudestoward risk. The emergence of complete or incomplete markets in equilibriumdepends on whether the {\it adverse selection effect} is stronger or weakerthan the {\it Hirshleifer effect}, as new securitiesare issued and prices reveal more information. When the Hirshleifer effectdominates, the exchange chooses an incomplete set of financial contracts, andthe equilibrium price is partially revealing.

Speculative securities

A speculative security is an asset whose payoff depends on a random shock uncorrelated with economic fundamentals (a sunspot) about which some traders have superior information. In this paper we show that agents may find it desirable to trade such a security in spite of the fact that it is a poorer hedge against their endowment risks as the time oftrade, and has an associated adverse selection cost. In the specific institutional setting of innovation of futures contracts, we show that a futures exchange may not have an incentive to introduce a speculative security even when all traders favor it.

Sequential Machine learning Approaches for Portfolio Management

Cette thèse envisage un ensemble de méthodes permettant aux algorithmes d'apprentissage statistique de mieux traiter la nature séquentielle des problèmes de gestion de portefeuilles financiers. Nous débutons par une considération du problème général de la composition d'algorithmes d'apprentissage devant gérer des tâches séquentielles, en particulier celui de la mise-à-jour efficace des ensembles d'apprentissage dans un cadre de validation séquentielle. Nous énumérons les desiderata que des primitives de composition doivent satisfaire, et faisons ressortir la difficulté de les atteindre de façon rigoureuse et efficace. Nous poursuivons en présentant un ensemble d'algorithmes qui atteignent ces objectifs et présentons une étude de cas d'un système complexe de prise de décision financière utilisant ces techniques. Nous décrivons ensuite une méthode générale permettant de transformer un problème de décision séquentielle non-Markovien en un problème d'apprentissage supervisé en employant un algorithme de recherche basé sur les K meilleurs chemins. Nous traitons d'une application en gestion de portefeuille où nous entraînons un algorithme d'apprentissage à optimiser directement un ratio de Sharpe (ou autre critère non-additif incorporant une aversion au risque). Nous illustrons l'approche par une étude expérimentale approfondie, proposant une architecture de réseaux de neurones spécialisée à la gestion de portefeuille et la comparant à plusieurs alternatives. Finalement, nous introduisons une représentation fonctionnelle de séries chronologiques permettant à des prévisions d'être effectuées sur un horizon variable, tout en utilisant un ensemble informationnel révélé de manière progressive. L'approche est basée sur l'utilisation des processus Gaussiens, lesquels fournissent une matrice de covariance complète entre tous les points pour lesquels une prévision est demandée. Cette information est utilisée à bon escient par un algorithme qui transige activement des écarts de cours (price spreads) entre des contrats à terme sur commodités. L'approche proposée produit, hors échantillon, un rendement ajusté pour le risque significatif, après frais de transactions, sur un portefeuille de 30 actifs.

A comparison of extreme value theory approaches for determining value at risk

This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

A note on estimating market–based minimum capital risk requirements: a multivariate GARCH approach

Internal risk management models of the kind popularized by J. P. Morgan are now used widely by the world’s most sophisticated financial institutions as a means of measuring risk. Using the returns on three of the most popular futures contracts on the London International Financial Futures Exchange, in this paper we investigate the possibility of using multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models for the calculation of minimum capital risk requirements (MCRRs). We propose a method for the estimation of the value at risk of a portfolio based on a multivariate GARCH model. We find that the consideration of the correlation between the contracts can lead to more accurate, and therefore more appropriate, MCRRs compared with the values obtained from a univariate approach to the problem.

An extreme value theory approach to calculating minimum capital risk requirements

This paper investigates the frequency of extreme events for three LIFFE futures contracts for the calculation of minimum capital risk requirements (MCRRs). We propose a semiparametric approach where the tails are modelled by the Generalized Pareto Distribution and smaller risks are captured by the empirical distribution function. We compare the capital requirements form this approach with those calculated from the unconditional density and from a conditional density - a GARCH(1,1) model. Our primary finding is that both in-sample and for a hold-out sample, our extreme value approach yields superior results than either of the other two models which do not explicitly model the tails of the return distribution. Since the use of these internal models will be permitted under the EC-CAD II, they could be widely adopted in the near future for determining capital adequacies. Hence, close scrutiny of competing models is required to avoid a potentially costly misallocation capital resources while at the same time ensuring the safety of the financial system.

O mercado de futuros no Brasil: teoria, organização, produtos e práticas operacionais

Nada mais atrativo no mundo empresarial do que fazer dinheiro. Mas nada mais custoso nesse universo do que desconhecer a importância econômica dos derivativos. Os instrumentos financeiros desse mercado possibilitam aos responsáveis pela administração dos riscos comercial e monetário de instituições financeiras e as empresas de produção de bens reais transferirem as incertezas de resultados futuros àqueles que desejam especular com essa possibilidade. O mercado de derivativos consiste na negociação de contratos baseados no resultado de ativos reais ou financeiros, bem como nas taxas de juro, câmbio e índices. Como as relações negociais dos derivativos estão baseadas em contratos, as partes - comprador e vendedor - têm compromissos entre si. O fator que os motiva a realizar uma negociação de derivativos é a divergência de expectativas quanto ao comportamento do preço do ativo objeto num determinado tempo. Esse é o elemento de risco, o qual pode ser transferido para o mercado de derivativos. Um hedging de compra ou de venda tem o objetivo de garantir um determinado preço futuro do ativo objeto. O mercado de derivativos têm vários tipos de contratos: futuros, a termo, de opções e de swaps. A ênfase maior de trabalho deste projeto foi focalizar às modalidades operacionais dos principais instrumentos de futuros, bem como a sua estrutura organizacional no mercado brasileiro. Procuramos tratar esse assunto de forma simples e didática, tornando-o acessível àqueles pouco familiarizados com os conceitos e as modalidades operacionais existentes no mercado futuro.

Normal backwardation é normal no mercado futuro brasileiro?

A pesquisa testa a existência, no mercado futuro brasileiro, do fenômeno que Keynes denominou de normal backwardation, isto é, a hipótese de que os preços futuros não são estimadores não viesados (unbiased estimators) do preço à vista esperado para o futuro. Quatro contratos futuros negociados na BM&F Bolsa de Mercadorias e Futuros foram estudados, a saber, futuro de Ibovespa, futuro de dólar comercial, futuro de boi gordo e futuro de café arábica, cobrindo o período de julho de 1994 a setembro de 1997. Cada contrato futuro citado foi submetido a quatro testes, sugeridos pelas implicações da hipótese de Keynes. Nossos resultados indicam que normal backwardation não é normal no mercado futuro brasileiro, repetindo as conclusões de vários estudos internacionais.

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.

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.

Relevância das diferenças entre contratos futuros e a termo: o caso do trio

Visando estudar as diferenças entre contratos futuros e contratos a termo no mercado cambial brasileiro, este trabalho foca no contrato de Dólar Futuro negociado na BM&FBOVESPA que, para vencimentos sem liquidez, é marcado a mercado pelo preço teórico dos contratos a termo. Uma simulação por Monte Carlo de uma carteira hedgeada contendo contratos de Dólar Futuro, DI Futuro e DDI Futuro mostra claramente que essa metodologia de marcação a mercado deveria ao menos ser revista

Impactos Operacionais das Alterações no Contrato Futuro de Milho da BM&F-Bovespa na Mitigação de Risco

O mercado de milho possui importante participação no cenário agropecuário nacional, pela relevância dentro da indústria de carnes. Destacam-se as estratégias de comercialização do grão, em especial as relacionadas à mitigação do risco de preço com o uso de contratos futuros. Objetiva-se identificar e interpretar os efeitos causados pela modificação no contrato futuro do milho negociado na BM&F-Bovespa, que em setembro de 2008 passou de entrega física para liquidação financeira, sobre o desempenho do mercado futuro do grão comercializado. Avaliam-se a liquidez dos contratos, a volatilidade dos preços futuros e físico do milho, bem como a convergência da base. Identificaram-se como possíveis efeitos da alteração contratual o aumento da liquidez do contrato futuro de milho e a redução da volatilidade dos preços, além da melhoria na convergência da base. Os resultados alinham-se com a teoria e evidenciam impacto positivo da implementação da liquidação financeira no contrato futuro de milho.