Detail práce

Forecasting realized volatility: Do jumps in prices matter?

Autor: Mgr. Lipták Štefan
Rok: 2014 - letní
Vedoucí: doc. PhDr. Jozef Baruník Ph.D.
Konzultant:
Typ práce: Rigorózní
Jazyk: Anglicky
Stránky: 83
Ocenění:
Odkaz:
Abstrakt: This thesis uses Heterogeneous Autoregressive models of Realized Volatility
on ve-minute data of three of the most liquid nancial assets { S&P 500
Futures index, Euro FX and Light Crude NYMEX. The main contribution
lies in the length of the datasets which span the time period of 25 years (13
years in case of Euro FX). Our aim is to show that decomposing realized
variance into continuous and jump components improves the predicatability
of RV also on extremely long high frequency datasets. The main goal is to
investigate the dynamics of the HAR model parameters in time. Also, we
examine whether volatilities of various assets behave di erently.
Results reveal that decomposing RV into its components indeed improves
the modeling and forecasting of volatility on all datasets. However, we found
that forecasts are best when based on short, 1-2 years, pre-forecast periods
due to high dynamics of HAR model's parameters in time. This dynamics
is revealed also in a year-by-year estimation on all datasets. Consequently,
we consider HAR models to be inappropriate for modeling RV on such long
datasets as they are not able to capture the dynamics of RV. This was indi-
cated on all three datasets, thus, we conclude that volatility behaves similarly
for di erent types of assets with similar liquidity.

Partneři

Deloitte

Sponzoři

CRIF
McKinsey
Patria Finance