Data Analyst
Resume:
Hui
Huang
Linkedin:https://www.linkedin.com/in/hui- huang- kiki- 780774105
current
VISA:
F1
good
through
24/06/2020 1806
YOSKO
DR
Edison
NJ
08817
(732)
319- 3607
***********@*******.*** EDUCATION
Rutgers
University,
New
Brunswick,
NJ,
USA
2015- 2017 Master
of
Science, Financial
Statistics
&
Risk
Management
GPA:
4.00/4.00 Xiamen
University,
Xiamen,
Fujian
Province,
China 2011- 2015 Bachelor
of
Economics,
Mathematical
Statistics
GPA:
3.61/4.00 Bachelor
of
Arts,
Japanese
Language
and
Literature
GPA:
3.86/4.00 RESEARCH
PROJECTS
Simulation
(R,C++)
§ Provided
with
one- year
historical
closing
prices
data
of
an
anonymous
stock
and
used
simulation
methods
to
predict the
following
10
days
prices
and
corresponding
80%
significance
level.
§ Implement
high
frequency
augmentation
with
Metropolis- Hastings
Algorithm,
Bayesian
inference,
MCMC
algorithm and
Monte
Carlo
Integration.
§ Used
back- testing
to
determine
the
length
of
data
to
estimate
and
made
the
prediction. Horizontal
Comparison
between
Credit
Risk
Models
for
Commercial
Banking
Decesion- Making
(R,
Python)
§ Used
German
Individual
Credit
Applicants
data
to
implement
machine
learning
models,
including
classic
models
like LDA,
LVQ,
Logistic
Regression,
K- NN;
Tree- based
models
like
Single
tree,
bagging,
gradient
boosting,
random
forest, ada- boost,
bagging
ada- boost,
Support
Vector
Machine
with
different
kernels
and
Artificial
Neural
Network.
§ Compared
the
performance
of
different
models
according
to
Type
I&II
error. Oil
Prices
Value- at- Risk
Analysis
(R)
§ Built
time
series
models(GARCH
family
models,
SV
model,
GEV)
to
predict
mean
and
volatility
movement
of
oil
return to
get
1- day
VaR,
programmed
the
model
in
R.
§ Finished
the
final
report
in
LaTeX. Effect
of
Earnings
Announcements
on
Stock
Price
Returns
(R)
§ Built
a
regression
model
to
analyze
the
impact
of
the
order
of
quarterly
earnings
announcements
and
earnings surprise
on
stock
return
on
the
trading
day
following
the
announcement;
programmed
the
model
in
R
using Bloomberg
and
Wall
Street
Horizon’s
data.
§ Found
that
early
announcements
tend
to
have
a
positive,
but
small
impact
on
stock
return;
positive
and
negative earnings
surprises
tend
to
have
a
positive
and
negative
impact,
respectively,
on
stock
return. Portfolio
Optimization
When
Mean
Returns
and
Covariances
Are
Unknown
(Matlab)
§ Portfolio
optimization
using
sample
mean
and
covariance
estimates
has
been
found
to
perform
poorly. Lai,
and Chen
(2011)
compared
alternative
approaches
to
address
this
problem
and
proposed
a
method
of
their
own
which they
showed
to
be
significantly
better
than
the
alternatives
based
on
a
particular
data
set.
§ This
project
validated
their
findings
by
implementing
their
method
and
the
other
alternative
approaches
in
Matlab using
a
different
data
set.
Linear
Discriminant
Analyst
for
Mortgage
Approvals
Based
on
Default
Probability
Prediction
§ Used
STATA
to
develop
a
linear
discriminant
model
to
determine
whether
mortgages
should
be
approved
or
denied.
§
The
model
validated
James
Stock’s
analysis
as
reported
in
“Introduction
To
Econometrics”. TECHNICAL
AND
OTHER
SKILLS
IT
Skills:
R,
C++,
Python,
Hadoop,
Tableau,
SQLite,
STATA,
E- views,
Matlab,
SPSS,,
Bloomberg,
LaTeX,
MS
Ofiice Core
Domain
Expertise: Risk
Management,
Data
Mining,
Multivariate
Statistical
Analysis,
Regression,
Time
series. Communication:
Trilingual
in
English,
Mandarin
Chinese
and
Japanese
for
both
written
and
oral
communication. Workplace
and
Teaming:
innovative
problem
solver
and
idea
generator,
experienced
team
leader
and
member,
self- motivated,
detail
oriented,
and
committed
to
delivering
accurate
results HONORS
AND
ACTIVITIES
FRM
LEVEL
1 2016
Outstanding
Graduate
of
Xiamen
University 2015 National
Scholarship
(Ranked
1
st
in
the
Department
) 2013
Dean’s
list
of
Wang
Yanan
Institute
for
Studies
in
Economics 2015 Xiamen
University
Scholarship 2012
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