xcrptd from:
i khindanova z atakhanova s rachev / "garch-type processes in modeling energy prices"
in st rachev ed "handbook of computational and numerical methods in finance" 2005
.
3.3.1 arch models
3.3.2 garch models
3.3.3 garch-m
3.3.4 asymmetric garch
3.3.5 egarch
3.3.6 figarch
3.3.7 arma-garch
3.3.7.1 ar-garch
3.3.7.2 ma-garch
3.3.7.3 ar-egarch
3.3.7.4 arfima-garch
3.3.8 swarch:
.
switching-arch [swarch]
models
are developed for
modeling
conditional heteroskadisticity if
the regimes governing
volatility process change
during the time period under consideration
susmel and thompson 1997 find that swarch is best suited
to modeling natural gas prices, which were largely deregulated since
the end of the 1980s - beginning of the 1990s
.
susmel & thompson
analyze the recent history
of natural gas markets and volatility
of spot prices during a period of 20 years [1974-]
using swarch methodology. during the 1970s, the u.s.
natural gas market was strictly regulated
owners of gas reserves had long-term contracts with
regulated utilities. interstate pipeline companies transported
gas according to minimum volume obligations
and acted as regulated monopolists
that controlled purchase
and resale prices
.
some of
the interstate pipeline companies
were allowed to sell gas to large customers at unregulated prices
storage capacity
was mostly under control of the regulated utilities
as a result of oil shocks of the early 1970s
demand for natural gas rose
and resulted in rationing
customers in gas producing areas
were willing to pay a higher price than the regulated rate
since such consumers did not have to use interstate pipelines
they were not subject to regulated rates
as a consequence
pipeline companies were allowed to transport gas
directly purchased by the customers
there was established a schedule of rates
which increased with volume
.
this schedule
was abandoned in 1984
a slump of oil price in the early 1980s
forced further deregulation of the gas industry
those customers who had the ability to to switch to oil
refused to buy gas from the interstate pipelines at regulated rates
therefore, pipeline companies were allowed to deliver spot gas purchased
by large industrial customers
this eliminated
the need
for regulatory approval
of transportation transactions
and let the frequency of transactions grow
.
however, the rates remained regulated
for those customers not able to switch to alternative fuels. in 1985
several courts classified existing transportation procedures
as discrimination between customers
as a result, regulators required
interstate pipelines provide equal treatment
to all customers
.
at the same time
obligations from long-term contracts
still had to be met
regulators had to devise
a system of allocating the cost
of remaining purchase contracts between customers
.
the uncertainty regarding the use of the transportation system
was mostly removed by the natural gas decontrol act of 1989
as of 1995 both transportation and storage services became
wildely available on a flexible basis
.
thus the deregulation of the natural gas industry
took place as a sequence of numerous events
.
. .
.
study
objective
series
sample frequency [data range] source of data
best fitting model[s]

.
robinson & taylor 1998
impact of regulatory change on share prices of electric util
share prices of electr. co
daily [12.10.09 -3.11.96] n/a
arch[1]
.
deaves & krinsky 1992
risk premium & efficiency in crude oil market
nymex crude 1 & 3-mo futures
monthly
03-83-04.90
techtools
arch-m[1]
.
adrangi et al 2001
sources of nonlinearities in energy prices
nymex crude, heating, unleaded futures
daily 10.01.83-03.31.95 01.02.85-03.31.95 01.02.85-03.31.95 futures industry inst
garch[1,1] asym-garch[1,1]; egarch[1,1]
.
adrangi et al 2001a
link between prices of crude & diesel
alaskan n.s. crude spot; los angeles diesel spot
daily [n/a] n/a
bivariate garch[1,1]
.
ng & pirrong 1996
link between spot & future prices
ny heating oil spot, gulf of mx gasoline spot, nymex heating oil & gasoline nearby futures
daily [08-20-84-12.31.90 (oil); 12.04.84-12.31.90 (gasoline)]
bivar garch[1,1]
.
moosa & al-lughani 1994
test of unbiasedeness & efficiency of futures & efficiency of futures as forecasters of spot
wti crude: spot 3- & 6-mo futures
monthly [01.86-07.90] n/a
garch-m[1,1]
.
antoniou & foster 1992
introduction of futures & spot volatility
brent crude spot
daily [01.86-07.90 datastream
igarch[1,1]
.
morana 2001
forecasting
brent crude spot
daily [01.04.82-01.21.99] n/a
asym-garch[1,1]
.
wickham 1996
volatility of crude prices
dated brent blend crude
monthly [01.80-06.96] n/a
ar[4]; garch[1,1]
.
boyd & caporale 1996
volatility of natural resource prices & rates of econ growth
real prices of oil, bituminous coal, nonferrous metals, iron & steel ppi
monthly [01.47-12.91] citibase
ma[1]; ma[2]; garch[1,1]
.
abosedra & laopodis 1997
non-normality of crude prices distribution
crude oil spot
monthly [01.74-01.95] eia monthly energy review
ar[2]; egarch-m[1,1]
.
mazaheri 1999
modeling convenience yield
spot & nearby futures; crude, unleaded & heating oil
daily [1568obs; 2059obs; 2422obs] commodity systems inc
asym arfima garch[1,1]; arfima-egarch[1,1]
.
brunetti & gilbert 2000
link between nymex & ipe crude prices
nymex & pie 2nd delivery crude futures
monthly [06-88-03.99] n/a
bivariate figarch[1,1]
.
susmel & thompson 1997
modeling regime changes & time-varying volatility
natural gas spot
monthly [01.74-03.94] usde monthly energy review
swarch[2,2]
.
rachev & mittnik 2000
modeling nonnormality & time-varying volatility
amex oil index spot
daily [09.01.88-07.28.94] n/a
ar[4] stable-arch[1]
.
. .
.

swarch-of-the-month.oil.jpg