Sökning: "Option pricing"

Visar resultat 1 - 5 av 206 uppsatser innehållade orden Option pricing.

  1. 1. Option Modelling by Deep Learning

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Niclas Klausson; Victor Tisell; [2021-02-10]
    Nyckelord :Deep learning; deep hedging; generative adversial networks; arbitrage pricing;

    Sammanfattning : In this thesis we aim to provide a fully data driven approach for modelling financial derivatives, exclusively using deep learning. In order for a derivatives model to be plausible, it should adhere to the principle of no-arbitrage which has profound consequences on both pricing and risk management. LÄS MER

  2. 2. Differential Deep Learning for Pricing Exotic Financial Derivatives

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Erik Alexander Aslaksen Jonasson; [2021]
    Nyckelord :Deep Learning; Exotic Derivatives; Differential Machine Learning;

    Sammanfattning : Calculating the value of a financial derivative is a central problem in quantitative finance. For many exotic derivatives there are no closed-form solutions for present values, instead, computationally expensive Monte Carlo methods are used for valuation. LÄS MER

  3. 3. Pricing Put Options with Multilevel Monte Carlo Simulation

    Kandidat-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

    Författare :Jonathan Schöön; [2021]
    Nyckelord :Multilevel Monte Carlo Simulation”; ”European Put Option Pricing” ”Stochastic Differential Equations;

    Sammanfattning : Monte Carlo path simulations are common in mathematical and computational finance as a way of estimating the expected values of a quantity such as a European put option, which is functional to the solution of a stochastic differential equation (SDE). The computational complexity of the standard Monte Carlo (MC) method grows quite large quickly, so in this thesis we focus on the Multilevel Monte Carlo (MLMC) method by Giles, which uses multigrid ideas to reduce the computational complexity. LÄS MER

  4. 4. Implied volatility with HJM–type Stochastic Volatility model

    Master-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

    Författare :Thi Diu Cap; [2021]
    Nyckelord :Implied volatility surface; stochastic volatility model; HJM framework;

    Sammanfattning : In this thesis, we propose a new and simple approach of extending the single-factor Heston stochastic volatility model to a more flexible one in solving option pricing problems.  In this approach, the volatility process for the underlying asset dynamics depends on the time to maturity of the option. LÄS MER

  5. 5. Multilevel Monte Carlo Simulation for American Option Pricing

    Kandidat-uppsats, Mälardalens högskola/Akademin för utbildning, kultur och kommunikation; Mälardalens högskola/Akademin för utbildning, kultur och kommunikation

    Författare :Sabina Colakovic; Viktor Ågren; [2021]
    Nyckelord :Multilevel Monte Carlo simulation; Stochastic Differential Equations; Option pricing.;

    Sammanfattning : In this thesis, we center our research around the analytical approximation of American put options with the Multilevel Monte Carlo simulation approach. The focus lies on reducing the computational complexity of estimating an expected value arising from a stochastic differential equation. LÄS MER