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
• There 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 10day 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/yatirimciokulu/portfoy-ve-senaryo-analizi/portfoyoptimizasyonu.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-varianceskewness-entropy-portfolio-selection