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Title: On the usage of option contracts to maximize revenues under value investing axioms
Author: Andrés-Carcasona, Marc  
Tutor: Aslanidis, Nektarios  
Abstract: Value investors usually consider that each financial product has an intrinsic value and that the market price will, eventually, tend towards that value. Under this philosophy, investors following this school of thought usually buy assets that are underpriced with respect to their intrinsic values in hopes of selling it in the future at a higher price. This is what is known as a buy and hold strategy. In this thesis, we present an analysis of whether option contracts, a derivative financial product, can be used to increase the revenues obtained under the same market conditions. To do so, we use a series of analytical tools based on the theory of stochastic differential equations and Monte Carlo simulations. We consider different stochastic models for the market such as a linear drift and volatility one, a geometric Brownian motion, a constant elasticity of variance model and a Schwartz's model. To generate Monte Carlo samples the Euler method is employed. The results obtained indicate that, indeed, revenues can be increased with this kind of strategies, yet depending on some hyperparameters of each strategy the uncertainty can also increase or even lead to greater losses than the buy and hold one. Therefore, they should be correctly tuned according to the investors risk-aversion profile. Finally, we apply this strategy in a real market, the S\&P500 ETF, to validate that the theoretical results still hold in a more realistic situation. To tune the hyperparameters in this real situation we perform a parameter estimation in a Bayesian framework using a nested sampling algorithm.
Keywords: value investing
option contracts
stochastic differential equation
Monte Carlo simulation
Bayesian inference
nested sampling
Document type: info:eu-repo/semantics/bachelorThesis
Issue Date: 15-Jun-2023
Publication license:  
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