Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/147543
Title: AN EXAMINATION OF THE PREDICTIVE POWERS OF FILTERED HISTORICAL SIMULATION
Authors: CALVIN KURNIAWAN
Issue Date: 2017
Citation: CALVIN KURNIAWAN (2017). AN EXAMINATION OF THE PREDICTIVE POWERS OF FILTERED HISTORICAL SIMULATION. ScholarBank@NUS Repository.
Abstract: In this study, we examine how complexity in asset price forecasting models does not necessarily translate into accuracy. We present a comparison of prediction accuracy of two asset pricing models in this thesis – an Exponential Generalized Autoregressive Conditional Heteroskedastic Filtered Historical Simulation model and a simple median returns model – where we analyse daily return forecast errors of up to 2 years for both models. We also conduct tests of prediction accuracy using regressions of forecast errors on market volatility and other controls. The results show that the simple median returns method outperforms the EGARCH FHS, even in volatile periods, an environment that usually favours GARCH models.
URI: http://scholarbank.nus.edu.sg/handle/10635/147543
Appears in Collections:Bachelor's Theses

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
A0088263X_Calvin.pdf792.21 kBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

4
checked on Oct 11, 2018

Download(s)

2
checked on Oct 11, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.