mdh.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Pricing European Options Under Stochastic Volatilities Models
Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, Utbildningsvetenskap och Matematik. (MAM)ORCID-id: 0000-0001-8361-4152
Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, Utbildningsvetenskap och Matematik. (MAM)ORCID-id: 0000-0002-0139-0747
Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, Utbildningsvetenskap och Matematik. (MAM)
Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, Utbildningsvetenskap och Matematik. (MAM)ORCID-id: 0000-0003-4554-6528
2016 (Engelska)Ingår i: Engineering Mathematics I: Electromagnetics, Fluid Mechanics, Material Physics and Financial Engineering / [ed] Sergei Silvestrov; Milica Rancic, Springer, 2016, s. 315-338Kapitel i bok, del av antologi (Refereegranskat)
Abstract [en]

Interested by the volatility behavior, different models have been developed for option pricing. Starting from constant volatility model which did not succeed on capturing the effects of volatility smiles and skews; stochastic volatility models appearas a response to the weakness of the constant volatility models. Constant elasticity of volatility, Heston, Hull and White, Schöbel-Zhu, Schöbel-Zhu-Hull-Whiteand many others are examples of models where the volatility is itself a random process. Along the chapter we deal with this class of models and we present the techniques of pricing European options. Comparing single factor stochastic volatility models to constant factor volatility models it seems evident that the stochastic volatility models represent nicely the movement of the asset price and its relations with changes in the risk. However, these models fail to explain the large independent fluctuations in the volatility levels and slope. Christoffersen et al. in [4] proposed a model with two-factor stochastic volatilities where the correlation between the underlying asset price and the volatilities varies randomly. In the last section of this chapter we introduce a variation of Chiarella and Ziveyi model, which is a subclass of the model presented in [4] and we use the first order asymptotic expansion methods to determine the price of European options.

Ort, förlag, år, upplaga, sidor
Springer, 2016. s. 315-338
Serie
Springer Proceedings in Mathematics and Statistics, ISSN 2194-1009 ; 178
Nyckelord [en]
option pricing, European options, stochastic volatilitie, asymptotic expansion
Nationell ämneskategori
Sannolikhetsteori och statistik
Forskningsämne
matematik/tillämpad matematik
Identifikatorer
URN: urn:nbn:se:mdh:diva-33388DOI: 10.1007/978-3-319-42082-0_18Scopus ID: 2-s2.0-85015265267ISBN: 978-3-319-42081-3 (tryckt)ISBN: 978-3-319-42082-0 (tryckt)OAI: oai:DiVA.org:mdh-33388DiVA, id: diva2:1034032
Forskningsfinansiär
Sida - Styrelsen för internationellt utvecklingssamarbeteTillgänglig från: 2016-10-11 Skapad: 2016-10-11 Senast uppdaterad: 2017-09-04Bibliografiskt granskad
Ingår i avhandling
1. Asymptotic Methods for Pricing European Option in a Market Model With Two Stochastic Volatilities
Öppna denna publikation i ny flik eller fönster >>Asymptotic Methods for Pricing European Option in a Market Model With Two Stochastic Volatilities
2016 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Modern financial engineering is a part of applied mathematics that studies market models. Each model is characterized by several parameters. Some of them are familiar to a wide audience, for example, the price of a risky security, or the risk free interest rate. Other parameters are less known, for example, the volatility of the security. This parameter determines the rate of change of security prices and is determined by several factors. For example, during the periods of stable economic growth the prices are changing slowly, and the volatility is small. During the crisis periods, the volatility significantly increases. Classical market models, in particular, the celebrated Nobel Prize awarded Black–Scholes–Merton model (1973), suppose that the volatility remains constant during the lifetime of a financial instrument. Nowadays, in most cases, this assumption cannot adequately describe reality. We consider a model where both the security price and the volatility are described by random functions of time, or stochastic processes. Moreover, the volatility process is modelled as a sum of two independent stochastic processes. Both of them are mean reverting in the sense that they randomly oscillate around their average values and never escape neither to very small nor to very big values. One is changing slowly and describes low frequency, for example, seasonal effects, another is changing fast and describes various high frequency effects. We formulate the model in the form of a system of a special kind of equations called stochastic differential equations. Our system includes three stochastic processes, four independent factors, and depends on two small parameters. We calculate the price of a particular financial instrument called European call option. This financial contract gives its holder the right (but not the obligation) to buy a predefined number of units of the risky security on a predefined date and pay a predefined price. To solve this problem, we use the classical result of Feynman (1948) and Kac (1949). The price of the instrument is the solution to another kind of problem called boundary value problem for a partial differential equation. The resulting equation cannot be solved analytically. Instead we represent the solution in the form of an expansion in the integer and half-integer powers of the two small parameters mentioned above. We calculate the coefficients of the expansion up to the second order, find their financial sense, perform numerical studies, and validate our results by comparing them to known verified models from the literature. The results of our investigation can be used by both financial institutions and individual investors for optimization of their incomes.

Ort, förlag, år, upplaga, sidor
Mälardalen University, Västerås, Sweden, 2016
Serie
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 219
Nyckelord
Asymptotic Expansion, European Options, Stochastic Volatilities
Nationell ämneskategori
Matematik
Forskningsämne
matematik/tillämpad matematik
Identifikatorer
urn:nbn:se:mdh:diva-33475 (URN)978-91-7485-300-1 (ISBN)
Disputation
2016-12-07, Kappa, Mälardalens högskola, Västerås, 13:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2016-10-28 Skapad: 2016-10-26 Senast uppdaterad: 2017-09-28Bibliografiskt granskad
2.
Posten kunde inte hittas. Det kan bero på att posten inte längre är tillgänglig eller att du har råkat ange ett felaktigt id i adressfältet.

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopushttps://link.springer.com/chapter/10.1007/978-3-319-42082-0_18

Sök vidare i DiVA

Av författaren/redaktören
Canhanga, BetuelMalyarenko, AnatoliyMurara, Jean-PaulSilvestrov, Sergei
Av organisationen
Utbildningsvetenskap och Matematik
Sannolikhetsteori och statistik

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 154 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf