Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.

Landfill Closure and Housing Values

The United States disposes roughly 60% of the municipal solid waste it generates each year in solid waste disposal facilities, commonly known as landfills. Hedonic pricing studies have estimated the external costs of landfills on neighboring housing markets, but the literature is silent on what happens to property values after the landfill closes. Original housing price data collected both before and after a landfill closure are used to estimate how a landfill closure affects neighboring property values. Results of both a hedonic pricing model and repeat-sales estimator are used in the analysis.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

Cobrança pelo uso da água e escassez de recursos hídricos: proposta de modelo de cobrança e aplicação na bacia do rio Atibaia

No Brasil, a Política Nacional de Recursos Hídricos apresenta a cobrança pelo uso da água como um instrumento de gestão de recursos hídricos de caráter econômico. Considerando esse caráter, a cobrança deve ter como objetivos: racionalizar o uso do recurso baseado na sua escassez; reconhecer a água como um bem de valor econômico, refletindo os custos ambientais advindos de sua utilização; e diminuir os conflitos entre os usos, induzindo uma alocação que considere o gerenciamento da demanda e as prioridades da sociedade. Além dessas metas, como instrumento de gestão de uma política que lista como primeiro objetivo \"assegurar à atual e às futuras gerações a necessária disponibilidade de água, em padrões de qualidade adequados aos respectivos usos\", a cobrança deve ser implementada de maneira que o agente usuário direcione seu comportamento no sentido da sustentabilidade ambiental. Mediante esses fundamentos, o que se pretende desenvolver neste trabalho é a aplicação de um modelo de cobrança sobre o uso da água que considera como princípio base a manutenção da qualidade ambiental medida pela adequada gestão da escassez de água e, compondo a busca dessa qualidade, a racionalização econômica e a viabilização financeira. Essa predominância do ambiente sobre aspectos econômicos vem no sentido de desqualificar argumentos segundo os quais, os impactos advindos dos usos da água serão corrigidos indefinidamente mediante investimentos financeiros em infra estrutura. Admitir que o desenvolvimento tem esse poder é supor equivocadamente que o meio econômico é limitante do meio ambiente e não o contrário. Esta constatação mostra qual é o problema da maioria das propostas de cobrança que valoram a água baseadas em custos de tratamento de resíduos e de obras hidráulicas. Por mais elaborados que sejam essas fórmulas de cobrança, chegando a ponto de se conseguir que fique mais caro, mediante um padrão ambiental corretamente definido, captar água ou lançar poluentes do que racionalizar usos, o preço da água não pode estar baseado em fatores cuja \"sustentabilidade\" pode acabar no curto prazo, dependendo do ritmo de crescimento econômico. A sustentabilidade dos recursos hídricos só será base da cobrança pelo uso da água se o valor cobrado for dificultando esse uso à medida que os recursos tornarem se escassos, e não quando os custos de medidas mitigadoras dessa escassez se tornarem muito elevados. Portanto, o modelo de cobrança proposto neste trabalho procura garantir que o agente econômico que está exaurindo o meio ambiente não possa ter capacidade de pagar por essa degradação, ajudando efetivamente a política de outorga do direito de uso da água na observância da capacidade de suporte do meio.

Modelos baseados em agentes aplicados à dinâmica de preços do mercado imobiliário

Um dos aspectos regulatórios fundamentais para o mercado imobiliário no Brasil são os limites para obtenção de financiamento no Sistema Financeiro de Habitação. Esses limites podem ser definidos de forma a aumentar ou reduzir a oferta de crédito neste mercado, alterando o comportamento dos seus agentes e, com isso, o preço de mercado dos imóveis. Neste trabalho, propomos um modelo de formação de preços no mercado imobiliário brasileiro com base no comportamento dos agentes que o compõem. Os agentes vendedores têm comportamento heterogêneo e são influenciados pela demanda histórica, enquanto que os agentes compradores têm o seu comportamento determinado pela disponibilidade de crédito. Esta disponibilidade de crédito, por sua vez, é definida pelos limites para concessão de financiamento no Sistema Financeiro de Habitação. Verificamos que o processo markoviano que descreve preço de mercado converge para um sistema dinâmico determinístico quando o número de agentes aumenta, e analisamos o comportamento deste sistema dinâmico. Mostramos qual é a família de variáveis aleatórias que representa o comportamento dos agentes vendedores de forma que o sistema apresente um preço de equilíbrio não trivial, condizente com a realidade. Verificamos ainda que o preço de equilíbrio depende não só das regras de concessão de financiamento no Sistema Financeiro de Habitação, como também do preço de reserva dos compradores e da memória e da sensibilidade dos vendedores a alterações na demanda. A memória e a sensibilidade dos vendedores podem levar a oscilações de preços acima ou abaixo do preço de equilíbrio (típicas de processos de formação de bolhas); ou até mesmo a uma bifurcação de Neimark-Sacker, quando o sistema apresenta dinâmica oscilatória estável.

Portfolio efficiency tests with conditioning information using empirical likelihood estimation

We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.

An SDF approach to hedge funds’ tail risk: evidence from Brazilian funds

The main purpose of this paper is to propose a methodology to obtain a hedge fund tail risk measure. Our measure builds on the methodologies proposed by Almeida and Garcia (2015) and Almeida, Ardison, Garcia, and Vicente (2016), which rely in solving dual minimization problems of Cressie Read discrepancy functions in spaces of probability measures. Due to the recently documented robustness of the Hellinger estimator (Kitamura et al., 2013), we adopt within the Cressie Read family, this specific discrepancy as loss function. From this choice, we derive a minimum Hellinger risk-neutral measure that correctly prices an observed panel of hedge fund returns. The estimated risk-neutral measure is used to construct our tail risk measure by pricing synthetic out-of-the-money put options on hedge fund returns of ten specific categories. We provide a detailed description of our methodology, extract the aggregate Tail risk hedge fund factor for Brazilian funds, and as a by product, a set of individual Tail risk factors for each specific hedge fund category.

Evaluating the impact of securities regulation on venture capital markets /

"Planning Office, National Bureau of Standards."

The effects of non-trading on the illiquidity ratio

Using a simulation analysis we show that non-trading can cause an overstatement of the observed illiquidity ratio. Our paper shows how this overstatement can be eliminated with a very simple adjustment to the Amihud illiquidity ratio. We find that the adjustment improves the relationship between the illiquidity ratio and measures of illiquidity calculated from transaction data. Asset pricing tests show that without the adjustment, illiquidity premia estimates can be understated by more than 17% for NYSE securities and by more than 24% for NASDAQ securities.

Consumption Risk and the Cross-Section of Government Bond Returns

Peer reviewed

Consumption Risk and the Cross-Section of Government Bond Returns

Peer reviewed

Measuring House Price Bubbles

We thank John Clapp, Martijn Dröes, Mika Kortelainen, and Song Shi for helpful comments. Financial support from the Academy of Finland, the OP‐Pohjola Group Research Foundation, the Kluuvi Foundation, and the Emil Aaltonen Foundation is gratefully acknowledged.

Essays in Industrial Organization

This dissertation extends the empirical industrial organization literature with two essays on strategic decisions of firms in imperfectly competitive markets and one essay on how inertia in consumer choice can result in significant welfare losses. Using data from the airline industry I study a well-known puzzle in the literature whereby incumbent firms decrease fares when Southwest Airlines emerges as a potential entrant, but is not (yet) competing directly. In the first essay I describe this so-called Southwest Effect and use reduced-form analysis to offer possible explanations for why firms may choose to forgo profits today rather than wait until Southwest operates the route. The analysis suggests that incumbent firms are attempting to signal to Southwest that entry is unprofitable so as to deter its entry. The second essay develops this theme by extending a classic model from the IO literature, limit pricing, to a dynamic setting. Calibrations indicate the price cuts observed in the data can be captured by a dynamic limit pricing model. The third essay looks at another concentrated industry, mobile telecoms, and studies how inertia in choice (be it inattention or switching costs) can lead to consumers being on poorly matched cellphone plans and how a simple policy proposal can have a considerable effect on welfare.

Macroeconomic Risk Factors and the Role of Mispriced Credit in the Returns from International Real Estate Securities

The benefits of diversification from international real estate securities are generally well established. However, the drivers of international real estate securities returns are insufficiently understood. We jointly examine the empirical implications of three major international asset pricing models that account for broad macroeconomic risk factors. In addition, we develop the hypothesis that an indicator of mispriced credit is significant in explaining the time series variation in international real estate securities returns. We employ the returns generated by a large sample of firms from 20 countries over the period 1999 to 2011 to test our hypothesis. We find support for the predictions of the major international asset pricing models. We also find evidence in favour of our hypothesised link between local credit conditions and the performance of international real estate securities.