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A model of stock price movements

Gudmundsson, Johan LU (2016) FYSM32 20161
Department of Physics
Mathematical Physics
Abstract (Swedish)
The goal of the thesis is to model stock prices as a stochastic process which exhibits reversion towards an equilibrium point, where the equilibrium point is set by fundamental data points of the company. The stochastic model is compared to the standard approach of using Geometric Brownian motion to simulate stock prices.

The autocorrelations of a group of stocks are investigated. This has lead to the development of a method of modifying stochastic models of stock movements to include autocorrelation, by introducing an autoregressive term.


A method to achieve an index behaviour for a group of simulated stocks is developed, by the introduction of an index term. This can be added to stochastic models of stock movements.
Please use this url to cite or link to this publication:
author
Gudmundsson, Johan LU
supervisor
organization
course
FYSM32 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8884597
date added to LUP
2016-06-27 12:24:09
date last changed
2016-06-27 12:24:09
@misc{8884597,
  abstract     = {{The goal of the thesis is to model stock prices as a stochastic process which exhibits reversion towards an equilibrium point, where the equilibrium point is set by fundamental data points of the company. The stochastic model is compared to the standard approach of using Geometric Brownian motion to simulate stock prices. 

The autocorrelations of a group of stocks are investigated. This has lead to the development of a method of modifying stochastic models of stock movements to include autocorrelation, by introducing an autoregressive term. 


A method to achieve an index behaviour for a group of simulated stocks is developed, by the introduction of an index term. This can be added to stochastic models of stock movements.}},
  author       = {{Gudmundsson, Johan}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{A model of stock price movements}},
  year         = {{2016}},
}