• norsk
    • English
  • norsk 
    • norsk
    • English
  • Logg inn
Vis innførsel 
  •   Hjem
  • Handelshøyskolen BI
  • Student papers
  • Master of Science
  • Vis innførsel
  •   Hjem
  • Handelshøyskolen BI
  • Student papers
  • Master of Science
  • Vis innførsel
JavaScript is disabled for your browser. Some features of this site may not work without it.

Realized Volatility Modeling of S&P 500 Index Members and the Impact of Temporal Variations in the Mean Levels

Fredrik Våland, Fusdahl; Johansen, Fredrik Nordby
Master thesis
Thumbnail
Åpne
2941746.pdf (2.460Mb)
Permanent lenke
https://hdl.handle.net/11250/2827151
Utgivelsesdato
2021
Metadata
Vis full innførsel
Samlinger
  • Master of Science [1116]
Sammendrag
Using a daily panel dataset including almost all the stocks in the S&P 500 dating

back to 1985, we document strong similarities in the risk dynamics across stocks.

The similarities in risk dynamics are exploited by implementing volatility forecasting

models estimated using panel-based methods that aggregate information

across stocks and force the coefficients to be the same for each stock. The models

that exploit these commonalities in risk characteristics across assets produce

highly competitive out-of-sample risk forecasts compared to more conventional

individual asset-specific models that implicitly ignore the similarities in risk dynamics.

We estimate the models on the daily range of the highest and lowest

log intraday stock price, which has been shown to be a good alternative to the

high-frequency-based realized volatility (RV) estimator of the integrated volatility.

Further, we normalize the RV by the time-varying mean of the RV retrieved

from the Kalman Filter and -Smoother as an intermediate step before model

estimation. Normalizing the RV before using panel-based estimation methods

produces very promising out-of-sample risk forecasts compared to the widely

accepted Heterogeneous Autoregressive (HAR) model. Further, it improves the

out-of-sample predictive power of the unnormalized models. An important feature

of the panel-based models we present is the inclusion of a time-varying

mean of each stock. Including this feature mimics introducing an asset-specific

intercept for each stock and captures the differences in risk dynamics across assets,

as well as the temporal variations in the mean levels.
Beskrivelse
Masteroppgave(MSc) in Master of Science in Quantative Finance - Handelshøyskolen BI,2021
Utgiver
Handelshøyskolen BI

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit
 

 

Bla i

Hele arkivetDelarkiv og samlingerUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifterDenne samlingenUtgivelsesdatoForfattereTitlerEmneordDokumenttyperTidsskrifter

Min side

Logg inn

Statistikk

Besøksstatistikk

Kontakt oss | Gi tilbakemelding

Personvernerklæring
DSpace software copyright © 2002-2019  DuraSpace

Levert av  Unit