FINANCIAL MARKETS AND
CAPITAL INSTUTIONS
PHD FINANCE
HÜSEYİN ÇETİN
OKAN UNIVERSITY
PORTFOLIO MANAGEMENT
DEFINITION
•
The art and science of making decisions about
investment
mix and policy, matching investments to
objectives
, asset allocation for individuals
and
institutions
, and balancing risk against performance
.
Portfolio
management is
about
strengths,
weaknesses
,
opportunities
and threats in the choice of
debt
vs. equity,
domestic
vs. international, growth
vs.safety
, and many other
tradeoffs
encountered in the
attempt
to maximize return at a
given appetite
for
risk
(
Investpodia
)
ACTIVE AND PASSIVE PORTFOLIO
MANAGEMENT
•
T
here
are two forms of portfolio management:
passive
and active. Passive management simply
tracks
a market index, commonly referred to as
indexing
or index investing. Active management
involves
a single manager, co

managers, or a
team
of managers who attempt to beat the market
return
by actively managing a fund's portfolio through
investment
decisions based on research and decisions
on
individual
holdings
.
ADL MATRIX
Groupama
Emeklilik A.Ş. E.Y. Fonları
•
Büyüme amaçlı olan bu fon, portföyünün en az %80'ini İMKB'de
işlem gören hisse senetlerine yatırarak sermaye kazancı elde etmeyi
amaçlar.
Portfoyün
geri kalan kısmı ise ters repo veya devlet tahvili
içermektedir.
•
Strateji:
Fon portföyüne likiditesi fazla , büyüme potansiyeli yüksek,
sektöründe geleceği olan şirketlerin hisse senetlerine yatırım
yapılarak sermaye kazancı elde edilmesi amaçlanmaktadır.
•
Fon portföyünün büyük bir kısmı hisse senetlerinden oluştuğu için
makro ekonomik risk, sektör riski, firma riski ve likidite riski
taşımaktadır. Fon yönetiminde risklerden korunmak amacı ile
çeşitlendirme yapılmakta, riskler dağıtılarak asgariye indirilmektedir.
•
Yatırımcı Profili:
Hisse senedi riski almak isteyen ve yüksek getiri
hedefleyen, agresif risk profiline sahip yatırımcılara uygun olan
emeklilik yatırım fonudur.
Ziraat Yatırım Menkul Değerler A.Ş.
Yatırım Fonları
•
Yüksek oranda hisse senedi
taşıyan,risk
ve
getiri düzeyi yüksek bir fondur. Hisse senetleri
ağırlıklı olarak IMKB 30 ve kısmen de IMKB
100 den seçilmektedir. Ziraat Yatırım Menkul
Değerler A.Ş
nin
kurucusu olduğu yatırım
fonları içinde risk düzeyi en yüksek olan
yatırım fonudur. Önerilen yatırım süresi
minimum 9 aydır.
•
Yatırımcının başlangıç yatırımının belirli bir
bölümünün, tamamının ya da başlangıç
yatırımının üzerinde belirli bir getirinin
izahnamede
belirlenen esaslar çerçevesinde
belirli vade ya da vadelerde yatırımcıya geri
ödenmesinin, uygun bir yatırım stratejisine
dayanılarak en iyi gayret esası çerçevesinde
amaçlandığı ve şemsiye fon şeklinde kurulan
fonlar “KORUMA AMAÇLI FON” olarak
adlandırılır.
•
Anapara Koruma Amaçlı Yatırım Fonları
yatırımcılara, anaparalarının koruma altında
olduğu bir ortamda, farklı yatırım
enstrümanlarına yatırım yaparak getiriye ortak
olma şansı tanır. Anapara koruma amaçlı yatırım
fonları, genellikle 6 ay veya daha uzun vadelidir.
Satış işlemleri belirli dönemlerde halka arz
yöntemiyle yapılır. Halka arz döneminden sonra
fona yeni giriş yapılamazken, fondan çıkışlar belirli
koşullar altında genellikle mümkündür.
EFFICIENT FRONTIER
SHARPE RATIO
•
A
ratio
developed
by
Nobel
laurate
William
F.Sharpe
to
measure
risk
adjusted
performance
.
The
Sharpe
ratio
is
calculated
by
subtracting
risk
free
rate
such
as
that
of
the
10
year
U.S.
Treasury
bond
from
the
rate of
return
for
a
portfolio
and
dividing
the
result
by
the
standart
deviation
of
portfolio
returns
.
•
Sharpe
indicated
that
there
can be
correlation
between
financial
asset
prices
and
market
index
. He
constructed
regression
model in
order
to
proof
his
theory
.
•
ri
=
ai
+
b(m)
+ i
•
ri
: Finansal varlık getirisi
•
ai
: Regresyon sabiti
•
bi
: Finansal varlık getirisinin piyasa getirisine olan
hassasiyeti (sistematik riskin ölçüsü
•
olan beta katsayısı)
•
r(m)
: Piyasa (endeks) getirisi
•
i : Hata terimi (finansal
varlığın
, piyasa getirisinden
bağımsız
, sistematik olmayan riski)
SHARPE RATIO RISK ADJUSTMENT
•
The Sharpe ratio tells us whether a portfolio's
returns are due to smart investment decisions
or a result of excess risk. This measurement is
very useful because although one portfolio or
fund can reap higher returns than its peers, it
is only a good investment if those higher
returns do not come with too much additional
risk. The greater a portfolio's Sharpe ratio, the
better its risk

adjusted performance has been.
SHARPE RATIO
FUND A AND FUND B
•
Since
Fund
A has
higher
volatility
compare
to
Fund
B,
Sharpe
Ratio
is
used
for
Fund
A
and
Return Analysis is done
for
Fund
B.
SYSTEMATIC RISK
•
Systematic
risk is
sort
of market risk.
By
diversifying
shares
the
risk can not be
plummeted
due
to
the
external
factors
such
as
political
movements,wars
,
international
trade
restriction
,
tax
rate
increases
,
inflation
UNSYSTEMATIC RISK
•
That
risk
derives
from
internal
problems
of
company
.
The
risk can be
minimized
by
the
usage
of
statistical
and
mathematical
methodologies
.
Unsystematic
risk can be
derived
from
the
clash
between
shareholders
and
board of
governors
,
contracts
,
auction
win
or
loss
.
BETA
•
In
CAPM,
asset
systematic
risk is
measured
by
Beta. Beta is
equal
to
:
covariance
between
market
portfolio
and
financial
asset
divided
by
market
portfolio
variance
.
Beta
equals
to
1=
middle
risk
group
Beta
smaller
then
1=
low
risk
group
Beta
bigger
then
1=
higher
risk
group
TREYNOR RATIO BETA RISK
ARBITRAGE PRICING MODEL
•
At APT model,
pricing
is done
by
market
participants
.
If
there
is a
deviance
from
equilibrium
price
there
will
be
arbitrage
.
Market
participants
get
the
asset
in
low
price
and
wait
the
asset
to
become
higher
then
sell
the
share
back
.
With
arbitraging
strategy
prices
of
asset
can
converge
to
equilibrium
point
.
FACTOR DEFINITION
•
Research
indicates
that
four
basic
factor
can
be
significant
to
describe
asset
pricing

Unexpected
change
in
inflation

Unexpected
change
in
industrial
production

Unexpected
change
in risk
premiums

Unexpected
change
in
short
term
and
long
term
interest
rates
.
REGRESSION IN ARBITRAGE PRICING
ONE FACTOR ARBITRAGE MODEL
•
Investors
short
sells
the
X
financial
asset
; at
the
same
amount
takes
buys
Y
financial
asset
.
•
At
the
first
phase
profit
depends
on
expected
Y
return
minus
expected
X
return
.
•
Those
buying
and
selling
transaction
decrease
Y
price
.
Until
profits
converges
to
zero
,
trade
continues
.
•
To
sum
,
financial
assets
which
are
at
the
same
risk
converges
to
same
expected
return
.
JENSEN PERFORMANCE
MEASUREMENT
JENSEN MEASUREMENT
•
Jensen
measurement
takes
Finansal
Asset
Market
Line
(FVPD)
into
account
.
PORTFOLIO MANAGER PERFORMANCE
JENSEN THRESHOLD
•
a
distance
is
Jensen
distance
.
if
a=0
portfolio
manager
does
not
have
extra
revenue
from
portfolio
so
extra
revenue
will
not be
taken
.
if
a>0 Portfolio
manager
performance
is
above
the
expectation
.
So
portfolio
manager
gains
extra
revenue
.
if
a<0 Portfolio
manager
has
poor
performance
in
portfolio
management
and
he can
get
warning
from
senior
management
.
EFFICIENCY FRONTIER
MARKOWITZ THEORY
•
Markowitz
argues
that
one
portfolio
return
and
risk can be
correlated
via
Mean

Variance
model.
Within
a
particular
return
,
via
MV
model, he
minimizes
the
variance
in
portfolio
and
found
the
optimum
portfolio
theory
.
Between
18
th
November
2005
and
28
March
2008, 28
shares
were
used
in
the
period
of 509
days
.
MVS Model
was
the
most
successful
model.
Because
with
less
risk
investors
can
reach
same
return
compare
to
MV
and
MVSE
models
who
are
higher
risks
but
having
same
return
with
MVS model.
•
MVS model
choosen
SHARES CORRELATION MATRIX
MONTE CARLO SIMULATION
•
MCS is a technique that converts uncertainties
in input variables of a model into probability
distributions. By combining the distributions
and randomly selecting values from them, it
recalculates the simulated model many times
and brings out the probability of the output.
NEURAL NETWORK ALGORITHM
VantagePoint
Intermarket
Analysis
Software
•
The first network forecasts tomorrow’s high to help set stops for
entry and exit points.
•
The second network forecasts tomorrow’s low to help set stops for
entry and exit points.
•
The third network forecasts a 5

day moving average of closes two
days into the future to indicate the expected short

term trend
direction within the next two days.
•
The fourth network forecasts a 10

day moving average of closes
four days into the future to indicate the expected medium

term
trend direction within the next four days.
•
The fifth network indicates whether the market is expected to
change trend direction within the next two days, by making a top or
a bottom.
•
The first four networks at the primary level of
the network hierarchy make independent
market forecasts of the high, low, short

term
trend and medium

term trend. These
predictions are then used as inputs into the
fifth network, along with other
intermarket
data inputs, at the secondary level of the
network hierarchy, to predict market turning
points.
VantagePoint
Intermarket
Analysis
Software
•
Neural networks provide the data from
intermarket
analysis that can be used to
produce predicted moving averages for a few
days ahead. The blue line is the predicted 10

day moving average, the black line the actual
10

day moving average. Note that the blue
line often turns ahead of the black line, giving
traders an early alert to get into or out of a
position before the crowd.
•
With
VantagePoint
Intermarket
Analysis Software,
for
example
,
the
raw
data
inputs
involved
in
forecasting
moving
averages
for
euro
FX
futures
include
the
daily
open
,
high
,
low
,
close
,
volume
and
open
interest
for
euro
FX
plus
the
daily
open
,
high
,
low
,
close
,
volume
and
open
interest
data
for
nine
related
markets
:
•
∙
Australian
dollar
/U.S.
dollar
(AUD/USD)
•
∙
Australian
dollar
/
Japanese
yen (AUD/JPY)
•
∙ British pound
•
∙ Euro/
Canadian
dollar
(EUR/CAD)
•
∙ Gold
•
∙
Nasdaq
100 Index
•
∙ British pound/
Japanese
yen (GBP/JPY)
•
∙ British pound/U.S.
dollar
(GBP/USD)
•
∙
Japanese
yen
TAIWAN STOCK EXCHANGE NEUREAL
NETWORK ANALYIS
•
The Pearson correlation tested the relationship
between stock returns and each of the nine financial
variables: market capitalization, dividend yield, P/S
ratios, P/B ratios, price

to

cash flow ratios, short

term
rate of return, long

term rate of return, turnover rate
and earning to price ratios. The dependent samples
(paired samples)
t

test investigated the differences
between predicted stock returns (created through the
neural networks by using financial ratios and
behavioral finance proxies) and actual stock returns,
and compared the mean of monthly predicted stock
returns with the mean of monthly actual returns within
different industries
•
The results showed that all nine factors except the
price

to

cash flow ratio related significantly with stock
returns and helped explain average stock returns in the
Taiwan stock market during the 10 year testing period
(1999
–
2008). Financial ratios (market capitalization,
dividend yield, P/S ratio, and P/B ratio) and behavioral
finance proxies (short

term rate of return, long

term
rate of return, turnover rate, and E/P ratio) proved to
be important determinants of stock returns. The paired
samples
t

test results indicated that the predicted
stock returns based on fundamental analysis
approximated actual returns in the traditional industry
.
REFERENCES
•
http://www.ziraatportfoy.com.tr/yatirimci

okulu/portfoy

ve

senaryo

analizi/portfoy

optimizasyonu.aspx
•
http://vp.tradertech.com/lbm_library/intermarket_ana
lysis/journal_trading.asp
•
http://www.investopedia.com/terms/p/portfoliomana
gement.asp
•
http://gradworks.umi.com/33/74/3374769.html
http://www.arastirmax.com/bilimsel

makale/
markowitz

portfolio

theory

mean

variance

skewness

entropy

portfolio

selection
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