Hybrid Garch(1,1) European Option Pricing Model With Ensemble Empirical Mode Decomposition
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Date
2020Author
Njoroge, Isaac Mwaura
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
espite the option pricing importance in risk management and selection of portfolios,
it is challenging to accurately price options due to unpredictable feature of asset prices.
There are numerous risks in the nancial markets, mainly emanating from the inaccurate
computation of option prices. The inaccuracy is mostly attributed to volatility. Using
GARCH or other stochastic processes directly is unsuitable for option pricing. There is
the need to decompose original series with some properties to attain more nancial time
series aspects. E-E-M-D generally performs well in capturing volatility and option pricing
of nancial data with non-linearity and non-stationarity properties. We construct a hybrid
GARCH(1,1) model with the ensemble empirical mode decomposition in European option
pricing. Using E-E-M-D, we decompose the original daily returns into low frequency, high
frequency, and trend terms, and use these terms in the hybrid GARCH(1,1) European
option pricing model in options pricing. We obtain option prices for di erent maturities
by applying Monte Carlo simulation. Our empirical results clearly illustrates that the
hybrid GARCH(1,1) European option pricing model e ectively predicts volatility features
and performs better than BSM73 and GARCH-M(1,1). The performance of the hybrid
GARCH(1,1) European option pricing model incorporating just the low-frequency term
further depicts the signi cance of decomposing the original returns using E-E-M-D by
reducing option pricing errors signi cantly. Therefore, the hybrid GARCH(1,1) European
option pricing model is a highly innovative and e ective method of option pricing.
Publisher
University of Nairobi
Rights
Attribution-NonCommercial-NoDerivs 3.0 United StatesUsage Rights
http://creativecommons.org/licenses/by-nc-nd/3.0/us/Collections
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