Journal of Futures Markets,
Год журнала:
2023,
Номер
43(11), С. 1615 - 1644
Опубликована: Июль 14, 2023
Abstract
While
there
is
a
large
literature
on
modeling
volatility
smile
in
options
markets,
most
such
studies
are
eventually
focused
the
forecasting
performance
of
model
parameters
and
not
applicability
models
trading
environment.
Drawing
analogy
like
term
structure
context
interest
rates
fixed‐income
we
evaluate
Dynamic
Nelson–Siegel
(DNS)
approach
to
dynamics
environment
against
competing
alternatives.
Using
model‐based
mispricing
as
our
sorting
criterion,
deploying
strategy
going
long
upper
deciles
short
lower
deciles,
show
that
dynamic
consistently
outperform
their
static
counterparts,
with
worst
outperforming
best
terms
percentage
mean
returns
from
portfolios
Sharpe
ratio.
Specifically,
find
DNS
outperforms
all
other
specifications
selected
criteria.
Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Май 15, 2023
Abstract
It
is
timely
and
crucial
to
research
the
effects
of
oil
price
volatility,
unpredictability,
geopolitical
instability
on
persistence
BRICS
economies.
Given
continually
shifting
global
markets
rising
tensions,
it
critical
comprehend
how
these
factors
impact
economies
countries.
We
can
support
in
remaining
resilient
ensuring
their
future
growth
success
by
learning
handle
overcome
issues.
This
study
examines
predictability,
unpredictability
affect
economies'
ability
endure
economic
success.
The
explores
dynamic
relationship
between
during
period
from
2004
2022
using
advanced
econometric
approaches,
such
as
panel
data
analysis
PSRT
autoregression.
results
show
that,
with
various
degrees
sensitivity
across
five
economies,
changes
have
a
major
nations.
Furthermore,
has
been
found
that
tends
make
negative
volatility
worse,
particularly
energy-dependent
Russia
Brazil.
2012
reform's
index
(OPVI)
stock
association
also
investigated
this
study.
recommends
nations
adopt
policies
lessen
shocks
risks,
including
increasing
energy
diversification
implementing
efficient
risk
management
plans
promote
long-term
growth.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Март 28, 2024
Abstract
The
use
of
sophisticated
computational
models
for
economic
forecasting
and
decision-making
is
on
the
rise.
Several
studies
have
compared
Hybridization
Adaptive
Fuzzy
Inference
System
(HAFIS)
which
proposed
in
this
research
to
traditional
approaches;
review
looks
at
them
all
show
how
HAFIS
better
several
areas,
including
precision,
flexibility,
responsiveness,
decision
support,
long-term
planning.
version's
accuracy,
strategic
making
plans
talents
are
more
suitable
as
included
system
evolves
phases.
thorough
exam
Economic
Uncertainty,
divided
into
3
principal
impacts:
Geopolitical
Events,
Market
Pressures,
Environmental
Factors,
critical
process
HAFIS.
All
these
items
integrate
form
unpredictable
surroundings
that
oil
commercial
enterprise
works
in.
facts
notoriously
misguided,
however
treated
by
means
a
mixture
rule
bases,
fuzzy
common
sense
operations.
complicated
Forecasting
Model,
includes
modern
Computational
Models,
middle
level
can
react
dynamically
various
troubles
posed
unpredictability
global
marketplace
tendencies.
fashions
adaptive
procedures
logic
decipher
complex
patterns
inside
enterprise's
fabric.
endorsed
method
portrayed
complete
flexible
technique
challenges
working
worldwide
market.
actual-world
data
within
simulation
evaluation
proved
outperformed
extra
techniques
predicting.
Because
its
flexibility
has
potential
generate
accurate
projections,
it
doubtlessly
beneficial
asset
everyone
involved
enterprise.
In
end,
will
be
assistance
professionals
industry
navigating
complexities
system.
This
accomplished
via
development
methodologies
demonstration
realistically
apply
such
actual
situations.
In
this
paper,
we
use
regression
equations
and
Monte
Carlo
simulations
to
study
the
dynamics
of
WTI
crude
oil
prices.
Our
research
takes
price
as
dependent
variable
looks
at
how
it
relates
nine
key
macroeconomic
variables,
most
which
have
do
with
supply.
We
recognize
importance
these
factors
affecting
by
using
knowledge
from
earlier
studies.
order
make
our
easier,
compile
historical
data
last
60
months
combine
chosen
indicators.
The
choice
variables
stem
their
critical
role
in
shaping
markets.
Through
a
multiple
model,
aim
establish
comprehensive
understanding
dependencies
between
prices
factors.
To
ensure
robustness
assess
multicollinearity
among
independent
emphasizing
that
while
they
are
related
prices,
should
not
exhibit
high
intercorrelations.
provides
valuable
framework
for
scenario
generation,
allowing
us
explore
potential
future
movements
based
on
identical
relationships.
By
unveiling
intricate
interplay
contributes
informed
decision-making
investors
policymakers.
Journal of Futures Markets,
Год журнала:
2023,
Номер
43(11), С. 1615 - 1644
Опубликована: Июль 14, 2023
Abstract
While
there
is
a
large
literature
on
modeling
volatility
smile
in
options
markets,
most
such
studies
are
eventually
focused
the
forecasting
performance
of
model
parameters
and
not
applicability
models
trading
environment.
Drawing
analogy
like
term
structure
context
interest
rates
fixed‐income
we
evaluate
Dynamic
Nelson–Siegel
(DNS)
approach
to
dynamics
environment
against
competing
alternatives.
Using
model‐based
mispricing
as
our
sorting
criterion,
deploying
strategy
going
long
upper
deciles
short
lower
deciles,
show
that
dynamic
consistently
outperform
their
static
counterparts,
with
worst
outperforming
best
terms
percentage
mean
returns
from
portfolios
Sharpe
ratio.
Specifically,
find
DNS
outperforms
all
other
specifications
selected
criteria.
