Prediction of Green Sukuk Investment Interest Drivers in Nigeria Using Machine Learning Models
Journal of risk and financial management,
Journal Year:
2025,
Volume and Issue:
18(2), P. 89 - 89
Published: Feb. 6, 2025
This
study
developed
and
evaluated
machine
learning
models
(MLMs)
for
predicting
the
drivers
of
green
sukuk
investment
interest
(GSII)
in
Nigeria,
adopting
planks
hypothesised
determinants
adapted
from
variants
planned
behavioural
model
finance
theory.
Of
seven
leveraged
prediction,
random
forest,
which
had
highest
level
accuracy
(82.35%
testing
90.37%
training
datasets),
with
a
good
R2
value
(0.774),
afforded
optimal
choice
prediction.
The
forest
ultimately
classified
10
predictors
GSII,
underpinned
constructs
such
as
risk,
perceived
control,
information
availability,
growth,
highly
important;
21,
were
inclusive
all
measurement,
moderately
remaining
15
low
importance.
feature
importance
determined
by
an
indicator-specific
value,
can
help
(GS)
issuers
to
prioritise
most
important
interest,
suggest
contexts
ethical
policy
enhancement,
inform
insights
about
resource
allocation
pragmatic
recommendations
stakeholders
respect
funding
climate
change
mitigation
projects
Nigeria.
Language: Английский
Green Bonds: Financing the Future of Environmental Resilience
Neera Gupta,
No information about this author
Somil Lulla,
No information about this author
Chayan Shrishrimal
No information about this author
et al.
Approaches to global sustainability, markets, and governance,
Journal Year:
2025,
Volume and Issue:
unknown, P. 63 - 88
Published: Jan. 1, 2025
Language: Английский
Modeling and Analyzing Carbon Emission Market Volatility and Impact: Evidence from Guangdong Province, China
Systems,
Journal Year:
2024,
Volume and Issue:
12(11), P. 458 - 458
Published: Oct. 30, 2024
This
research
investigates
the
volatility
of
carbon
prices
in
Guangdong’s
emission
trading
market,
a
critical
element
China’s
broader
climate
strategy
aimed
at
reducing
greenhouse
gas
emissions
and
promoting
sustainable
development.
study
applies
ensemble
empirical
mode
decomposition
(EEMD)
to
analyze
complex
interactions
between
price
fluctuations
various
economic
factors,
including
energy
environmental
regulations.
By
decomposing
data,
we
identify
key
trends
cycles
within
providing
clearer
understanding
both
short-term
long-term
market
trends.
Our
findings
reveal
that
regulatory
policies
play
pivotal
role
shaping
dynamics,
with
shifts
regulations
leading
significant
volatility.
Additionally,
global
prices,
especially
oil
coal,
are
found
have
considerable
impact
on
movements,
further
complicating
market’s
stability.
underscores
interconnected
nature
domestic
international.
The
provide
valuable
insights
for
policymakers
participants,
underscoring
importance
stable
markets
transition
low-carbon
economy
achieving
sustainability
goals.
Language: Английский
Islamic Finance
Advances in finance, accounting, and economics book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 205 - 228
Published: May 31, 2024
This
study
explores
the
role
of
Islamic
finance
in
mitigating
adverse
effects
climate
change
on
human
well-being,
environment,
and
economy.
Emphasizing
necessity
integrating
sustainability
principles
into
financial
strategies
due
to
ecological
disruptions,
chapter
positions
as
a
distinctive
alternative
that
aligns
with
sustainability,
equity,
balance.
The
research
highlights
several
critical
areas:
comprehensive
examination
products,
balanced
assessment
environmental
impacts,
importance
community
involvement,
challenges
barriers
implementing
for
sustainable
practices.
offers
valuable
insights
how
can
contribute
mitigation,
providing
robust
foundation
addressing
global
issues.
Language: Английский