China Finance Review International,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 23, 2024
Purpose
This
paper
aims
to
enhance
the
predictability
of
stock
returns.
Existing
studies
have
used
investor
sentiment
forecast
However,
it
is
unclear
whether
high-frequency
intraday
can
forecasting
performance
low-frequency
Design/methodology/approach
Thus,
we
employ
MIDAS
model
and
extracted
from
Internet
forum
Chinese
A-shares
returns
at
daily
frequency.
Findings
The
results
illustrate
that
data
are
better
than
in
predicting
returns,
non-trading
hours
has
been
proved
superior
those
trading
hours.
Originality/value
First,
our
study
adds
growing
literature
on
sentiment.
We
first
construct
a
proxy
for
using
postings
collected
forum.
Second,
confirm
stronger
predictive
ability
Third,
also
contribute
comparison
MIDAS-class
models.
good
U-MIDAS
confirmed
empirical
applications.
Transportation Research Part E Logistics and Transportation Review,
Год журнала:
2024,
Номер
189, С. 103686 - 103686
Опубликована: Июль 23, 2024
Prediction
of
bunker
fuel
spot
prices
at
a
port
and
understanding
the
dependence
on
key
determinants
is
an
arduous
challenging
activity.
The
present
work
strives
to
analyze
temporal
spectrum
daily
Very
Low
Sulphur
Oil
(VLSFO),
critical
fuel,
in
five
European
Ports,
Amsterdam,
Antwerp,
Gothenburg,
Hamburg,
Rotterdam.
lack
prior
research
allied
domain
has
motivated
undertake
modeling
VLSFO
through
lens
applied
predictive
analytics.
Least
Square
Boosting
(LSBoost)
Facebook
Prophet
algorithms
are
used
draw
forecasts
multivariate
framework
leveraging
constructs
related
same
different
ports,
economic
indicator,
etc.
dynamics
have
been
explicitly
examined
during
Russia-Ukraine
military
conflict.
Additionally,
Explainable
Artificial
Intelligence
(XAI)
frameworks
demystify
influence
chosen
explanatory
variables
granular
scale.
overall
findings
espouse
effectiveness
accurately
estimating
any
selected
heavily
depends
ports.
