Studies in Economics and Finance,
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 25, 2024
Purpose
This
paper
aims
to
investigate
the
relationship
between
investor
attention
and
market
activity
(return,
volatility
volume)
using
a
sample
of
14
clean
energy
cryptocurrencies
(hereafter
green
cryptocurrency),
namely,
Chia,
Cardano,
Stellar,
Tron,
Ripple,
Nano,
IOTA,
EOS,
Bitcoin
Green,
Alogrand,
Hedara,
Polkadot,
FLOW
Tezos.
Design/methodology/approach
use
26040
crypto-day
observations
range
econometric
techniques,
including
Dynamic
Granger
causality,
Panel
vector
autoregression
(VAR),
Impulse
response
function
decomposition
forecast
error
variance.
Findings
Based
on
observations,
this
finds
bidirectional
causal
all
measures
activity,
return,
absolute
volatility,
squared
volume.
The
panel
VAR
impulse
demonstrate
that
in
crypto
ecosystem,
especially
volume,
is
considerably
responsive
changes
proxied
by
Google
search
volume
(GSV)).
findings
also
significant
asymmetric
effect
return
since
past
negative
shocks
“or
bad
news”
are
more
likely
grab
investor’s
attention.
All
all,
our
study
emphasizes
crucial
role
ecosystem.
Originality/value
(i)
research
first
shed
light
cryptocurrency
market.
(ii)
uses
wide
offer
comprehensive
picture
(iii)
causality
which
provides
several
advantages
over
conventional
approach.
(iv)
provide
novel
empirical
evidence
prevalent
influence
PLoS ONE,
Год журнала:
2025,
Номер
20(2), С. e0318647 - e0318647
Опубликована: Фев. 7, 2025
Earlier
studies
used
classical
time
series
models
to
forecast
the
nonlinear
connectedness
of
conventional
crypto-assets
with
CO2
emissions.
For
first
time,
this
study
aims
provide
a
data-driven
Nonlinear
System
Identification
technique
Using
daily
data
from
January
2,
2019,
March
31,
2023,
we
investigate
among
crypto-assets,
sustainable
and
emissions
based
on
our
proposed
model,
Multiple
Inputs
Single
Output
(MISO)
Autoregressive
Exogenous
(NARX).
Intriguingly,
forecasting
accuracy
model
improves
inclusion
exogenous
input
variables
(conventional
crypto-assets).
Overall,
results
reveal
that
exhibit
slightly
stronger
compared
crypto-assets.
These
findings
suggest
that,
some
extent,
solution
environmental
issues
related
However,
further
improvements
in
through
technological
advances
are
required
develop
more
energy-efficient
decentralised
finance
consensus
algorithms,
aim
reshaping
cryptocurrency
ecosystem
into
an
environmentally
market.
