Journal of Futures Markets,
Journal Year:
2024,
Volume and Issue:
44(5), P. 699 - 719
Published: Feb. 4, 2024
Abstract
This
study
employs
a
time‐varying
parameter
vector
autoregression
methodology
with
the
Diebold
and
Yilmaz
spillover
index
to
scrutinize
temporal
fluctuations
in
volatility
spillovers
between
Chinese
coal
metal
markets.
The
analysis
is
conducted
from
dual
perspectives
of
security
indices
futures
prices.
findings
reveal
robust
correlation
markets,
market
serving
as
primary
conduit
for
into
market.
Furthermore,
this
investigates
time‐specific
impacts
decommissioning
policies,
COVID‐19
pandemic,
supply
crisis
on
coal–metal
spillovers.
indicate
that
these
three
unique
shocks
significantly
increase
overall
risk
Moreover,
during
exceptional
events,
extent
or
role
undergoes
varying
degrees
change.
On
basis
findings,
article
presents
pertinent
policy
recommendations.
Resources Policy,
Journal Year:
2023,
Volume and Issue:
85, P. 103860 - 103860
Published: July 8, 2023
This
study
uses
wavelet
coherence
and
frequency
connectedness
techniques
to
examine
the
time-frequency
dependence
risk
connectivity
between
oil
shocks
green
stocks.
The
results
show
that
on
mid-term
long-term
scales,
relationships
stock
markets
are
tighter
while
lead-lag
patterns
mixed
time-varying.
Total
spillovers
mostly
conveyed
over
time.
Risk
from
market
substantially
larger
in
market.
Furthermore,
global
crises
such
as
Great
Recession,
price
collapse,
COVID-19
pandemic
have
amplified
magnitude
of
spillovers.
Overall,
has
not
yet
developed
enough
potential
for
a
independence
conventional
energy
Hence,
participants
financial
who
different
time
horizons
asset
allocation
management
committed
investors
particular,
examination
can
be
quite
beneficial.
Quantitative Finance,
Journal Year:
2024,
Volume and Issue:
24(5), P. 627 - 642
Published: May 3, 2024
This
paper
combines
the
Generalized
Autoregressive
Conditional
Heteroskedasticity-Extreme
Value
Theory-Value
at
Risk
(GARCH-EVT-VaR)
method
in
conjunction
with
Time-Varying
Parameter
Diebold-Yilmaz
(TVP-VAR-DY)
model
to
investigate
contagion
of
extreme
risks
between
fossil
and
green
energy
markets
China.
Specifically,
study
concentrates
on
coal,
crude
oil,
natural
gas
as
representative
sectors
for
energy,
while
bonds,
investments,
power,
associated
new
are
chosen
representatives
sector.
Our
analysis
reveals
that
events
can
rapidly
propagate
markets,
particularly
during
significant
shifts
external
environment.
Notably,
exhibit
greater
susceptibility
severe
compared
their
counterparts,
indicative
instability
immaturity.
Moreover,
highlights
bond
market's
heightened
sensitivity
risks,
investments
playing
a
pivotal
role
propagating
such
throughout
system.
These
insights
underscore
intricate
dynamics
risk
emphasizing
need
comprehensive
management
strategies
both
sectors.
