This dissertation deals with the inference in a crude oil market, the West Texas Intermediate (WTI) crude oil, whose futures are quoted on the New York Mercantile Exchange Market (NYMEX). The purpose of the research underlying this dissertation is twofold: first, we were looking for an appropriate model for the WTI crude oil market. Second, we tried to develop a new technique for parameter estimation suitable for the models considered, allowing to get inference results when the price dynamics is described both under the historical and the risk-neutral probability measures.
L'oggetto di questa tesi è l'analisi del mercato del greggio WTI, i cui prezzi futures sono quotati sul mercato di New York (NYMEX). Lo scopo della ricerca è duplice: innanzitutto, proporre un modello appropriato per la descrizione della dinamica del WTI; quindi, sviluppare un algoritmo adatto per ottenere risultati di inferenza statistica, sia sotto la misura storica che risk-neutral, per i modelli trattati.
A particle filter approach to parameter estimation in stochastic volatility models with jumps for crude oil market
FILECCIA, GAETANO
Abstract
This dissertation deals with the inference in a crude oil market, the West Texas Intermediate (WTI) crude oil, whose futures are quoted on the New York Mercantile Exchange Market (NYMEX). The purpose of the research underlying this dissertation is twofold: first, we were looking for an appropriate model for the WTI crude oil market. Second, we tried to develop a new technique for parameter estimation suitable for the models considered, allowing to get inference results when the price dynamics is described both under the historical and the risk-neutral probability measures.File | Dimensione | Formato | |
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2013_03_PhD_Fileccia.pdf
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https://hdl.handle.net/10589/74303