COMOVEMENT ANALYSIS OF CPO (CRUDE PALM OIL) AND SBO (SOYBEAN OIL) FUTURES PRICE USING WAVELET COHERENCE METHOD
Among the commonly-used analysis method from econophysics is wavelet analysis/wavelet coherence method. Wavelet analysis is a time series analysis method that transforms the time series data into a series of small wave function called wavelet according to a mother wavelet in order to study its...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/80589 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Among the commonly-used analysis method from econophysics is wavelet analysis/wavelet
coherence method. Wavelet analysis is a time series analysis method that transforms the time
series data into a series of small wave function called wavelet according to a mother wavelet
in order to study its volatility and comovement. As a method that relies on transformation of
data, wavelet analysis should be affected by the parameter choosen for data transformation.
This research aims to examine the effect of 2 transformation parameter namely basic scale
( ) and central frenquency ( ) of mother wavelet. Aside from that, this study also tries to
examine the volatility and comovement of 2 futures price namely, crude palm oil (CPO) and
soybean oil (SBO) after their sharp price increase during el nino in 2019 and Covid-19
pandemic in 2020-2021. According to parameter test, it was discovered that the small ,
, yields optimal transfromation result while
that are too big or too small produces
some level of overestimation in certain scale so
yields optimal result. According to
wavelet analysis using the optimal parameter, it is known that CPO product is more volatile
with higher risk profile than SBO and both futures show high and positive comovement with
SBO tends to lead CPO. |
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