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Nesta dissertação desenvolvemos o Cálculo Estocástico para provar teoremas clássicos de Análise Complexa, em particular, o pequeno teorema de Picard. / In this dissertation we develop the Stochastic Calculus for to prove classical theorems in Complex Analysis, in particular, the little Picard\'s theorem.

Nesta dissertação desenvolvemos o Cálculo Estocástico para provar teoremas clássicos de Análise Complexa, em particular, o pequeno teorema de Picard. / In this dissertation we develop the Stochastic Calculus for to prove classical theorems in Complex Analysis, in particular, the little Picard\'s theorem.

The Black-Scholes model is one of the most important concepts in modern financial theory. It was developed in 1973 by Fisher Black, Robert Merton and Myron Scholes and is still widely used today, and regarded as one of the best ways of determining fair prices of options. In the classical Black-Scholes model for the market, it consists of an essentially riskless bond and a single risky asset. So far there is a number of straightforward extensions of the Black-Scholes analysis. Here we consider more complex products where each component in a portfolio entails several variables with constraints. This leads to elegant models based on multivariable stochastic integration, and describing several securities simultaneously. We derive a general asymptotic solution in a short time interval using the heat kernel expansion on a Riemannian metric. We then use our formula to predict the better price of options on multiple underlying assets. Especially, we apply our method to the case known as the one of two-color rainbow ptions, outperformance option, i.e., the special case of the model with two underlying assets. This asymptotic solution is important, as it explains hidden effects in a class of financial models.