A large literature has related the failure of interest rate parity in the foreign exchange market to the existence of a time-varying risk premium. Nevertheless, most modern open economy DSGE models imply a (near) perfect interest rate parity condition. This paper presents a stylized two-country incomplete-markets model in which countries have strong precautionary motives because they face international liquidity constraints, the presence of which successfully generates a time-varying risk premium: the country that has accumulated debt after experiencing relative worse times has stronger precautionary motives and its asset carries a risk premium. (author's abstract) / Series: Department of Economics Working Paper Series

The concomitance of prosperity and poverty come as an enigma in today's world.As some people in this world benefit greatly from advanced technologies andglobalization, others are still suffering heavily from poverty. One noticeable fact is thatalmost all developing countries have their own distinguished "poor area". Such poorareas seem to persist regardless of robust economic growth enjoyed by the overalleconomy.By decomposing the developing country into two regions, one rich coastal regionand one poor inland region, this research establishes a new classical general equilibrium3X2 Ricardian model to investigate how trade liberalization will affect the participationin the division of labor by poor individuals in the inland region in a developing countryand their associated welfare change under different trading conditions.Our model of division of labor on poverty delineates the interdependentrelationship between individuals in the poor inland region, the rich coastal region and thedeveloped country. Market integration plays a very important role in suchinterdependency. Low transaction efficiency is the bottle-neck constraint on the poorinland region's integration into international division of labor through international trade.Thus, it is critical for the poor inland region to improve the market transaction efficiencyin order to enjoy gains from trade.Our marginal and inframarginal analysis show that as an important part of tradeliberalization policy, tariff reduction may not always be a good policy choice for thedeveloping country to alleviate the poverty. Whether tariff reduction makes the inlandregion better off depends on the initial general equilibrium market structure and thedeveloping country's power of influencing its terms of trade. If the developing country islarge enough to determine the terms of trade in international trade with the developedcountry, the developing country may increase the welfare level of the poor inland regionby increasing its tariff rate. But the developed country will oppose it because the tariffrate increase in the developing country will hurt its welfare. Trade negotiation is thennecessary to determine the final tariff rate and the share of gains of trade to each countryand region.

This paper provides an overview of the finite difference method and its application to approximating financial partial differential equations (PDEs) in incomplete markets. In particular, we study German’s [6] stochastic volatility PDE derived from indifference pricing. In [6], it is shown that the first order- correction to derivatives valued by indifference pricing can be computed as a function involving the stochastic volatility PDE itself. In this paper, we present three explicit finite difference models to approximate the stochastic volatility PDE and compare the resulting valuations to those generated by an Euler- Maruyama Monte Carlo pricing algorithm. We also discuss the significance of boundary condition choice for explicit finite difference models.

MASTER THESIS ABSTRACT TITLE: Trading Strategy in Incomplete Market AUTHOR: Tomáš Bunčák DEPARTMENT: Department of Probability and Mathematical Statistics, Charles University in Prague SUPERVISOR: Andrea Karlová We focus on the problem of finding optimal trading strategies (in a meaning corresponding to hedging of a contingent claim) in the realm of incomplete markets mainly. Although various ways of hedging and pricing of contingent claims are outlined, main subject of our study is the so-called mean-variance hedging (MVH). Sundry techniques used to treat this problem can be categorized into two approaches, namely a projection approach (PA) and a stochastic control approach (SCA). We review the methodologies used within PA in diversely general market models. In our research concerning SCA, we examine the possibility of using the methods of optimal stochastic control in MVH, and we study the problem of our interest in several settings of market models; involving cases of pure diffusion models and a jump- diffusion case. In order to reach an exemplary comparison, we provide solutions of the MVH problem in the setting of the Heston model via techniques of both of the approaches. Some parts of the thesis are accompanied with numerical illustrations.

Esta dissertação revisa a literatura acadêmica existente sobre a teoria de opções utilizando os modelos de precificação com saltos. Os conceitos foram equalizados, a nomenclatura foi padronizada, sendo gerado um material de referência sobre o assunto. O pressuposto de lognormalidade com volatilidade constante não é aceito pelo mercado financeiro. É freqüente, no meio acadêmico, a busca de modelos que reproduzam os fenômenos observados de leptocurtose ou assimetria dos log-retornos financeiros e que possuam a mesma robustez e facilidade para manipulação analítica do consagrado modelo de Black-Scholes. Os modelos com saltos são uma alternativa para esse problema. Avaliou-se o modelo de Kou no mercado acionário brasileiro composto por um componente de difusão que segue um movimento browniano geométrico e um componente de saltos que segue um processo de Poisson com intensidade do salto descrito por uma distribuição duplamente exponencial. A simulação histórica do modelo aponta, em geral, uma superioridade preditiva do modelo, porém as dificuldades de calibração dos parâmetros e de hedge em mercados incompletos são as principais deficiências para o uso dos modelos com saltos. / This master dissertation reviews the academic literature about option pricing and hedging with jumps. The theory was equalized and the notation was standardized, becoming this document a reference document about this subject. The log-normality with constant volatility is not accepted by the market. Academics search consistent models with the same analytical capabilities like Black-Scholes? model which can support the observed leptokurtosis or asymmetry of the financial daily log-returns behavior. The jump models are an alternative to these issues. The Kou?s model was evaluated and this one consists of two parts: the first part being continuous and following a geometric Brownian motion and the second being a jump process with its jump intensity defined by a double exponential distribution. The model backtesting showed a better predictive performance of the Kou´s model against other models. However, there are some handicaps regarding to the parameters calibration and hedging.

Neste trabalho, apresentamos um método de simulação Monte Carlo para o cálculo do hedging dinâmico de opções do tipo europeia em mercados multidimensionais do tipo Browniano e livres de arbitragem. Baseado em aproximações martingales de variação limitada para as decomposições de Galtchouk-Kunita-Watanabe, propomos uma metodologia factível e construtiva que nos permite calcular estratégias de hedging puras com respeito a qualquer opção quadrado integrável em mercados completos e incompletos. Uma vantagem da abordagem apresentada aqui é a flexibilidade de aplicação do método para os critérios quadráticos de minimização do risco local e de variância média de forma geral, sem a necessidade de se considerar hipóteses de suavidade para a função payoff. Em particular, a metodologia pode ser aplicada para calcular estratégias de hedging quadráticas multidimensionais para opções que dependem de toda a trajetória dos ativos subjacentes em modelos de volatilidade estocástica e com funções payoff descontínuas. Ilustramos nossa metodologia, fornecendo exemplos numéricos dos cálculos das estratégias de hedging para opções vanilla e opções exóticas que dependem de toda a trajetória dos ativos subjacentes escritas sobre modelos de volatilidade local e modelos de volatilidade estocástica. Ressaltamos que as simulações são baseadas em aproximações para os processos de preços descontados e, para estas aproximações, utilizamos o método numérico de Euler-Maruyama aplicado em uma discretização aleatória simples. Além disso, fornecemos alguns resultados teóricos acerca da convergência desta aproximação para modelos simples em que podemos considerar a condição de Lipschitz e para o modelo de volatilidade estocástica de Heston. / In this work, we present a Monte Carlo simulation method to compute de dynamic hedging of european-type contingent claims in a multidimensional Brownian-type and arbitrage-free market. Based on bounded variation martingale approximations for the Galtchouk-Kunita- Watanabe decomposition, we propose a feasible and constructive methodology which allows us to compute pure hedging strategies with respect to any square-integrable contingent claim in complete and incomplete markets. An advantage of our approach is the exibility of quadratic hedging in full generality without a priori smoothness assumptions on the payoff function. In particular, the methodology can be applied to compute multidimensional quadratic hedgingtype strategies for fully path-dependent options with stochastic volatility and discontinuous payoffs. We illustrate our methodology, providing some numerical examples of the hedging strategies to vanilla and exotic contingent claims written on local volatility and stochastic volatility models. The simulations are based in approximations to the discounted price processes and, for these approximations, we use an Euler-Maruyama-type method applied to a simple random discretization. We also provide some theoretical results about the convergence of this approximation in simple models where the Lipschitz condition is satisfied and the Heston\'s stochastic volatility model.

Neste trabalho, apresentamos um método de simulação Monte Carlo para o cálculo do hedging dinâmico de opções do tipo europeia em mercados multidimensionais do tipo Browniano e livres de arbitragem. Baseado em aproximações martingales de variação limitada para as decomposições de Galtchouk-Kunita-Watanabe, propomos uma metodologia factível e construtiva que nos permite calcular estratégias de hedging puras com respeito a qualquer opção quadrado integrável em mercados completos e incompletos. Uma vantagem da abordagem apresentada aqui é a flexibilidade de aplicação do método para os critérios quadráticos de minimização do risco local e de variância média de forma geral, sem a necessidade de se considerar hipóteses de suavidade para a função payoff. Em particular, a metodologia pode ser aplicada para calcular estratégias de hedging quadráticas multidimensionais para opções que dependem de toda a trajetória dos ativos subjacentes em modelos de volatilidade estocástica e com funções payoff descontínuas. Ilustramos nossa metodologia, fornecendo exemplos numéricos dos cálculos das estratégias de hedging para opções vanilla e opções exóticas que dependem de toda a trajetória dos ativos subjacentes escritas sobre modelos de volatilidade local e modelos de volatilidade estocástica. Ressaltamos que as simulações são baseadas em aproximações para os processos de preços descontados e, para estas aproximações, utilizamos o método numérico de Euler-Maruyama aplicado em uma discretização aleatória simples. Além disso, fornecemos alguns resultados teóricos acerca da convergência desta aproximação para modelos simples em que podemos considerar a condição de Lipschitz e para o modelo de volatilidade estocástica de Heston. / In this work, we present a Monte Carlo simulation method to compute de dynamic hedging of european-type contingent claims in a multidimensional Brownian-type and arbitrage-free market. Based on bounded variation martingale approximations for the Galtchouk-Kunita- Watanabe decomposition, we propose a feasible and constructive methodology which allows us to compute pure hedging strategies with respect to any square-integrable contingent claim in complete and incomplete markets. An advantage of our approach is the exibility of quadratic hedging in full generality without a priori smoothness assumptions on the payoff function. In particular, the methodology can be applied to compute multidimensional quadratic hedgingtype strategies for fully path-dependent options with stochastic volatility and discontinuous payoffs. We illustrate our methodology, providing some numerical examples of the hedging strategies to vanilla and exotic contingent claims written on local volatility and stochastic volatility models. The simulations are based in approximations to the discounted price processes and, for these approximations, we use an Euler-Maruyama-type method applied to a simple random discretization. We also provide some theoretical results about the convergence of this approximation in simple models where the Lipschitz condition is satisfied and the Heston\'s stochastic volatility model.

Esta dissertação revisa a literatura acadêmica existente sobre a teoria de opções utilizando os modelos de precificação com saltos. Os conceitos foram equalizados, a nomenclatura foi padronizada, sendo gerado um material de referência sobre o assunto. O pressuposto de lognormalidade com volatilidade constante não é aceito pelo mercado financeiro. É freqüente, no meio acadêmico, a busca de modelos que reproduzam os fenômenos observados de leptocurtose ou assimetria dos log-retornos financeiros e que possuam a mesma robustez e facilidade para manipulação analítica do consagrado modelo de Black-Scholes. Os modelos com saltos são uma alternativa para esse problema. Avaliou-se o modelo de Kou no mercado acionário brasileiro composto por um componente de difusão que segue um movimento browniano geométrico e um componente de saltos que segue um processo de Poisson com intensidade do salto descrito por uma distribuição duplamente exponencial. A simulação histórica do modelo aponta, em geral, uma superioridade preditiva do modelo, porém as dificuldades de calibração dos parâmetros e de hedge em mercados incompletos são as principais deficiências para o uso dos modelos com saltos. / This master dissertation reviews the academic literature about option pricing and hedging with jumps. The theory was equalized and the notation was standardized, becoming this document a reference document about this subject. The log-normality with constant volatility is not accepted by the market. Academics search consistent models with the same analytical capabilities like Black-Scholes? model which can support the observed leptokurtosis or asymmetry of the financial daily log-returns behavior. The jump models are an alternative to these issues. The Kou?s model was evaluated and this one consists of two parts: the first part being continuous and following a geometric Brownian motion and the second being a jump process with its jump intensity defined by a double exponential distribution. The model backtesting showed a better predictive performance of the Kou´s model against other models. However, there are some handicaps regarding to the parameters calibration and hedging.

以往財務理論在討論財務市場行為時，均是在完全市場( e market)的假 設上做分析。但是從現實的角度來看，由於時間 (time)與不確定(uncertainty) 等因素，導致市場往往是不完全的(incomplete)；亦即資產或證券的數目往往小 於未來各種可能發生的不確定狀態的數目。當各種不同狀態事件發生時,如果沒有足夠的 資產或證券工具來涵括(span)所有投資人所欲達成的跨時所得移轉，則有某些風 險因子不能以既有的財務工具來複製，此時投資人將無法完全地規避該項風險。 本文的分析方法屬於微分拓樸數學工具的應用。從基本可微分流行(differentiable manifold) 性質，我們可得到整體性的觀點，優於以往在歐氏空間，Hilbert 空 間等拓樸空間只考慮在局部的性質.首先由最基本平滑流形(smooth manifo-[念 切入，介紹平滑流形與歐氏空間的關係。再由市場均衡的定義找出均衡流形( equilibrium manifold)。結合Debreu(1970)與Balasko(1976,1988) 建立的正 規經濟，探討其性質.加入財務市場時，透過正規經濟的理論，證明不完全財物 市場均衡generic 存在性。最後，利用不完全財務市場均衡generic的存在性，證明單 一商品及多商品的資本資產定價(CAPM)；並且建立一以消費為基礎的資本資 產定價模式。

Cette thèse s’intéresse à différents problèmes de contrôle et d’optimisation dont il n’existe à ce jour que des solutions approchées. D’une part nous nous intéressons à des techniques visant à réduire ou supprimer les approximations pour obtenir des solutions plus précises voire exactes. D’autre part nous développons de nouvelles méthodes d’approximation pour traiter plus rapidement des problèmes à plus grande échelle. Nous étudions des méthodes numériques de simulation d’équation différentielle stochastique et d’amélioration de calculs d’espérance. Nous mettons en œuvre des techniques de type quantification pour la construction de variables de contrôle ainsi que la méthode de gradient stochastique pour la résolution de problèmes de contrôle stochastique. Nous nous intéressons aussi aux méthodes de clustering liées à la quantification, ainsi qu’à la compression d’information par réseaux neuronaux. Les problèmes étudiés sont issus non seulement de motivations financières, comme le contrôle stochastique pour la couverture d’option en marché incomplet mais aussi du traitement des grandes bases de données de médias communément appelé Big data dans le chapitre 5. Théoriquement, nous proposons différentes majorations de la convergence des méthodes numériques d’une part pour la recherche d’une stratégie optimale de couverture en marché incomplet dans le chapitre 3, d’autre part pour l’extension la technique de Beskos-Roberts de simulation d’équation différentielle dans le chapitre 4. Nous présentons une utilisation originale de la décomposition de Karhunen-Loève pour une réduction de variance de l’estimateur d’espérance dans le chapitre 2. / This thesis proposes different problems of stochastic control and optimization that can be solved only thanks approximation. On one hand, we develop methodology aiming to reduce or suppress approximations to obtain more accurate solutions or something exact ones. On another hand we develop new approximation methodology in order to solve quicker larger scale problems. We study numerical methodology to simulated differential equations and enhancement of computation of expectations. We develop quantization methodology to build control variate and gradient stochastic methods to solve stochastic control problems. We are also interested in clustering methods linked to quantization, and principal composant analysis or compression of data thanks neural networks. We study problems motivated by mathematical finance, like stochastic control for the hedging of derivatives in incomplete market but also to manage huge databases of media commonly known as big Data in chapter 5. Theoretically we propose some upper bound for convergence of the numerical method used. This is the case of optimal hedging in incomplete market in chapter 3 but also an extension of Beskos-Roberts methods of exact simulation of stochastic differential equations in chapter 4. We present an original application of karhunen-Loève decomposition for a control variate of computation of expectation in chapter 2.