An Kutluk

DepartmE-mail: Receive CopyrigEurasianreprodu

ABSTR

In this sor will bthe dailythe dailyreturns dependeindicatoExchang KeyworOrdered JEL: C2 1. INTR The commethods"NSI", wof the rlagged a With a which wvalue "Nfalling dependevariable The Oreconom How did

P

n Early

k Kagan Su

ment of Ecokutluk@ist

ed June 14th

ght © 2015 n Academy

uction in any

RACT

study, the tebe constanty stock retuy stock retuare negativ

ent vari-ablors. The ordge).

rds: Stock d Choice

25,C35,G15

RODUCTI

mputation as describedwhich repre

respective teare determin

rising NSI were consulNSI", the s"NSI" the ent variablee (-1), (0) an

rdered Choimic cycles:

d the prices

Published Onlin

Warnin

mer

onometrics, tanbul.edu.th, 2014; rev

Kutluk Kay of Sciency medium, p

echnical indt at the follourns. If the durns are conve, the indle of order

dered choice

Exchange;

5,G1

ON

and interpred in the meesents a conechnical indned.

(New Stocklted in the mhares with indicator v

es and theirnd (+1) the

ice method

s develop in

e January 2015http://dx.doi.o

g Model

Faculty of Etr vised July 12

agan Sumerces Licenseprovided the

dicators are uowing day. daily stock rnstant, the indicator is cred choice e models ar

ISE; Techn

etation of tethodology. nclusion vadicators of

k Indicator)model catega constant alue (-1). Dr categorizause of this m

dology is us

the past pe

Eurasi2015

5 (http://socialsorg/10.4236/ea

l for Tec

Economics,

2th, 2014; r

. This is ane, which pee original w

used in foreThe indica

returns are ndicator is ccoded as “−

models whre ap-plied t

nical Analy

the technicaWith the c

alue as depea share wit

) the indicatgory three "NSI" the

During the ation the Ormodel up pu

sed among

eriod Pt?

ian Academy o5                       

sciences.eurasiaas.2015.54022

chnical T

, Istanbul U

revised Aug

n open acceermits unre

work is prop

ecasting whators are genpositive, thcoded as “0−1”. These hich indepeto all of the

ysis; Techni

al indicatorcomputationendent variath the techn

tor value (+for the comindicator vdissolution

rdered Choiut close.

other thin

of Sciences So     Volume:1 

anacademy.org

Trading I

University, Is

gust 10th, 20

ss article diestricted useperly cited.

ether stock nerated by e indicator ” and at leaindicator

endent variae stocks of I

cal Indicato

rs take placn of the daable, the indnical indica

+1) was assimputation oalue (0) and

n this modeice model,

ngs with the

ocial Sciences                     S:

g) 

Indicato

stanbul, Tur

014

istributed ue, distribut

prices will taking into is coded as

ast if the davalues expables are tISE (Istanb

ors; Early W

ce accordinaily indicatdividual par

ators of the

igned to theof the new ind the shareel was usedwhereby li

e determina

Journal 1 ‐ 20 

ors

rkey

under the ion, and

rise, fall account

“+1”; if ily stock

press the technical bul Stock

Warning;

ng to the or value rameters one day

e shares, indicator es with a d for the ining the

ation by

  

2 

 

 

What fo King, N

PP

Pc

A generthe varivalues (

The comLikeliho Like alrthe futuestimatiprice hi The foll

T

r E T

The chatrends panalysis

Tbaaia

               1 GOURI

Press; S.

 

 An E

or a price hi

Nerlove, Ott

Pt* as condPt-q* and Pt Pt* as condcompared.

ral error coriable for P(Table 1):

Rising Consta Falling

mputation oood method

ready with ture developmion the concstory.

lowing acce

The share pSupply and rates etc. Easy share The change

anges at suppursued by ts instead of

The fundambasic knowapplication analysis is pindicators leactions supp

                      IEROUX Chr

141-142

Early Warning

story is exp

enwaelter a

itionally discompared itionally dis

rrection mePt* for chan

ant g

of the Orderd.

the technicament of the clusion valu

eptance of th

prices are ded demand oc

price fluctues at trends d

pply and demthe share prfundamenta

mental analyledge. In coof the techn

preferred. Teads to the ply and dem

                       ristian (2000)

g Model with

pected in the

and Oudiz h

stributed reg

stributed reg

chanism is nges of exp

P

Table-1

red Logit an

al analysis oconclusion

ues of share

he model is

etermined bccur by exte

uations are ndue to chan

mand are rerices. The teal analysis a

ysis is time-ontrast to it nical analys

The confrontfact that you

mand are aff

: Econometri

Technical Ind

e coming pe

have in their

garded and

garded and

used derivepectation, is

Pt*\Pt+1* = - -1: Values of

nd Ordered

on the basisn values is me shows de

s at the basis

by supply anernal factors

neglected; dnges at supp

esponsible fechnical anaccording to

-consuming simple basi

sis. For this tation of theu display hofected.

cs of Qualita

dicators: The C

eriod Pt*?1

r work:

with that ad

with the ex

ed by usings "trichotom

= - - f Pt*\Pt+1

Probit mod

s the conclumentioned ependence a

s of technic

nd demand.s i.e. inflatio

do recognizely and dem

for the fact nalysts call to following

and dependic knowledgreason by s

e investors womogeneou

ative Depende

Case of ISE (I

daptive exp

xtrapolative

Pt*. E(Pt)mous" and t

+ = -

dels is base

usion valuesestimated. Wand it becom

al models:

on, interest r

e trends witand.

that it comethe applicatreasons:

dent to its uge is sufficiesmall investwith similar

us actions an

ent Variables;

Istanbul Stock

actations m

models for

) representstakes the fo

+ + =

ed on the M

s of the pastWith this kinmes repetiti

rates, excha

th the share

es to the chtion of the t

user’s econoent for the tors the techr formationnd because

Cambridge U

k Exchange)

model for

Pt-q*, Pt

s thereby ollowing

Maximum

t periods nd of the ve share

ange

prices.

anges of technical

omic

hnical ns and of these

University

E

Eurasian

 

 

Tmti

Uwa

TW

a

o 2. MET The mathe follo SecurityResults Public oDispatcElection In requiemploym At all thwould fthe oppopoll, thedifferen The OrdMcElvelatent in The init y* = ’x

               2 GREEN3 BACKU

Working

Academy of S

The fundammake plans that the remincrease, soUsers of thewhich are hand yield stThe results With the tecSpeculativeanalysis proSpeculationof expressio

THODOLO

any of the Mowing exam

y evaluationof sample t

opinion pollhing from mn results wit

irement takment, part-t

hese cases,fail to the dosite directien arises: ifnce between

dered Probiey, 1975). Tnvolution.

tial equation

x +

                      NE, William H

US, David (1

paper series /

Sciences Socia

mental analypossible in

maining inveo that it come technical ahowever nottructure to aof the fundchnical anale price histooved with spns lead to thon lose.

OGY: ORD

Multinomiamples are ca

ns3 tests ls military perth certain pr

en insuranctime work, u

although tdependent vaion. If one rf the effect wn 4 and 3, eq

it and LogitThe Ordered

n reads:

                       H. (2000): Eco

1998): Discre

/ 6736

al Sciences Jou

ysis helps tonto this secuestors becom

mes by it to sanalysis aret set up afteragain-reflectdamental analysis it is po

ory is not illupeculative s

he revaluatio

DERED CH

al Choice valled: 2

sonnel to plrograms

ce level by unemploym

the result isariable withregards for ewith 0, 1, 2qual the diff

t of models d Probit mo

onometric anal

te-time mode

ournal

o become aturity. The sume attentiveshare price e not on thor accordingt, instructedalysis illustrossible to usustrated witshares as paon of shares

HOICE MO

ariables are

lace qualific

consumers:ment.

s discrete, th ordinal naexample the

2, 3 or 4 is cference betw

finds a stroodel is set u

lysis; Prentice

els of bond p

ttentive on success of sue to these shincreases. se balances

g to tax law d. rate the cense short termth the funda

articularly ses, whereby t

ODELS

e automatica

cations after

: no partial,

the Multinoature. Usuale result of scoded, the lween 3 and

ong use as aup, like the

e Hall; S. 875-

pricing; Natio

2015, Vo

shares with uch a plan dehares and th

and succesprinciples th

ntral to longm data invesamental anaensitive to athe financia

ally arrange

r qualificati

full deman

omial Logit lly regressioample tests linear involu2.

an analysis e Binomial P

-887

nal Bureau o

olume: 1

low prices epends on t

heir offers th

ss estimationthe actual co

g-term price stment deci

alysis. The tanalyze metal indicators

ed. In the l

ion level

nd Occupati

and Probiton analysess or a publicution repres

stand (ZavoProbit mod

of Economic

3

and to the fact hus

ns, osting

change. isions. technical thod. s at force

literature

ion: Full

t models are into

c opinion sents the

oina and del, for a

Research,

  

4 

 

 

Usuallyobserve

Those opinion measurato the qugiven, tmost. 4 Assumebinomiato 0 anddisturbain practi The foll

For all p 0 < 1 <

               4 MITTE

Cambridg

y = 0 i

= 1 i

= 2 i

.

.

Prob(y

Prob(y

Prob(y

 

 An E

y y * the noes:

are unknn poll we canable factorsuestions withey select

ed is normal probit mod 1 normalizance. This trice.

lowing prob

positive pro

<2 < . . . <

                      LHAMMER

ge Univ. Press

if y* 0

if 0<y*1

if 1<y*

. .

. .

y = 0) = (-

y = 1) = (

y = 2) = (

Early Warning

n-observed

nown paramn see that a

s x and did th their ownthat one, w

mal distributodel (speciazes. The morivial modif

babilities re

obabilities is

J-1

                       Ron C. , JUD

s; S:563-598

1

2

-’x)

1 - ’x) -

2 - ’x) -

g Model with

variable re

meters, also ll asked pernot determin y*, if this which corre

ted with conal case J = 1)odel can be fication of th

sult in the c

s the result

DGE George G

8.

(- ’x)

(1- ’x)

Technical Ind

epresents. It

become rsons have tine not obseis permitte

esponds to

nstant varia), becomes distributed

the formula

case of norm

G. und MILLE

dicators: The C

t represents

estimated. their own feerved factord. With fiveits feelings

ance. From tthe averagealso with a does not se

mal distribut

ER Douglas J

Case of ISE (I

a form of t

During theeeling intenrs depende possible as during the

the same reae value and logistically

eem to make

tion:

J. (2000). Ec

Istanbul Stock

the censorsh

e view of nsity, those d. They can

answers for e given que

asons as in the varianc

y distributede a real diff

conometric fou

k Exchange)

hip. One

a public from the n answer example estion at

the e of

d ference

undations;

E

Eurasian

 

 

Figure Figure represenThe opt The marcoefficiparamet

The mar

[Pr

[Pr

[Pr

x

obx

obx

ob

               5 GREEN

Prob(y

Prob(y

Academy of S

1: Probabil

1 shows thnted above.timization ta

rginal effecents. For exter. The thre

rginal effec

(]2[

([]1[

]0[

x

yx

yx

y

                      NE, William H

y = 0) = 1-

y = 1) = (

Sciences Socia

lities with O

he effects of The log Lakes place a

cts of the Rexample theree probabili

cts of the ch

)(

()(

)(

x

x

x

                       H. (2000). Eco

(-’x)

- ’x) -

al Sciences Jou

Ordered prob

f the structLikelihood fas usual.

egressors x ae are three cities read:

ange of Reg

)]x

onometric ana

(- ’x)

ournal

bit models

ture. It is a function and

are not alikcategories.

gressors for

alysis; Prentic

generalized its deriva

ke for the deThe model

r the three p

e Hall; S:877

2015, Vo

d case of tative can be

termined prexhibits an

probabilities

.

olume: 1

the probit oe easily dete

robability anunknown b

s read: 5

5

of model ermined.

nd the border

  

6 

 

 

Figure Figure 2* is repconstaneffect o With thprevioulogic thhave. Opassed dependeare uncaccompnow arothe inter 3. TEC In the taas argumconclusdetermiand from                6 GREEN

 

 An E

2: Effects o

2 shows thepresented innt, is to the f the shift is

he acceptancus expressioe change kn

On the assumit with th

ence to the clear. In sumplished in thound to fewrpretation o

HNICAL I

able, Orderment. A newion values ned with thm it a "NSI

                      NE, William H

Early Warning

of the chang

e effect of thn the pulled

right, reprs a concentr

ce that fon, the derivnows case ] mption that he middle c

signs of thmmary it chis model v

w clear modof coefficien

INDICATO

ed probit isw indicator

of the inhe help of dE" (NSI Es

                       H. (2000): Eco

g Model with

ge of x with

he change od through curesented as ration on tho

or this x, muvative of Pro

the same siit is positiv

cell uncleae coefficien

can be saidvery carefuldel. Withoutnts is not cle

OR VARIA

s used for thr "NSI R" (Ndividual shdown statedstimated) is

onometric anal

Technical Ind

h forecast pr

of Regressourve. An inbroken cur

ose comple

ust Prob(y ob(y = 0) hign with Prove, it shifts arly, depennts, only thed that the inlly. With tht an appropear in Order

ABLES AND

he indicatorNSI REALhares. The d the formuderived.

lysis; Prentice

dicators: The C

robabilities

ors. The proncrease of xrve equal ately left cel

= 0) is poshas the contob(y = 2) [ the probab

ds on the e changes onterpretatio

he models rpriate numbered Probit m

D MODEL

rs as presen) is computindicator

ula for all at

e Hall; S. 878

Case of ISE (I

bability distx, during

a shift of thl.

itive sink. Atrary sign foor Prob(y =

bility into thtwo densi

of Prob(y = n of the coepresented er of compu

models. 6

LS

nted into theted, which r"NSI C" (t the IMKB

Istanbul Stock

stribution of and to he distributi

Alternativelor . With a= J) generallhe right cellities. Gener 0) and Prooefficients above it ac

utations the

e individualrepresents t(NSI calculB noting 25

k Exchange)

f y and y be kept

ion. The

ly to the a similar ly how l. Which rally, in

ob(y = J) must be

cts up to e kind of

l models the daily lated) is 0 shares

E

Eurasian

 

 

.

E

RSI

VOLUM

t

RS

NSI

The foll CCI PVT VOLUMMOMENVOLOSNSI (-1)LR Index

In the Oindicatenot effic The estcomputedependehelp of the "NS1) for fa With thLogit mmethodoindicato

xYi*

1

0iY

Pr(

Pr(

Pr(

Y

Y

Y

i

i

i

),(

Academy of S

1

.

.

VOLOt

UME

CCI

SI

VOLUM

CCI

lowing tech

PME ANTUM MIL V Nx (Pseudo-R

Ordered Proed. For thoscient.

timated pared. They rent variablethat far dow

SI R" with thalling prices

e computatimodels and O

olgy is desor "NSI E" t

x

1

whe

whe

whe

),,|1

),,|0

,,|1

x

x

x

i

i

i

Pr(log(1Yii

Sciences Socia

1

1

.

OSIL

MACDt

OSILATt

VOLOSI

ME

I

hnical indica

Commodity Price VolumActed quanMomentum Volume OscNSI one day

R²) Ta

bit tables une shares wi

rameter valuepresent th

e "NSI R" iswn aforemehe compariss.

ion of the eOrdered Procribed in dthe followin

n

n

n

2

1

*iY

(1

(

()

2

2

1

x

x

,|1( ii xY

al Sciences Jou

1

1.

.

WILLIt

tD

TOR

IL

MACD

OSILAT

ators were c

Channel Indme Trendntity

cillator y lagged

able-2: Tech

nder the parithout param

ues of the he arguments determinentioned meson with va

stimated paobit models

detail. Durinng method i

*

2*

1

i

i

Y

Y

)

()

)

1

x

x

l)),0

Yii

ournal

1

.

IAMS

MOMENRTU

PVt

WILLIA

TOR

consulted fo

dex OROMRSW

LRhnical Indic

arameter estmeter estima

technical it in each c

ed the indicaethod the indalues the val

arameter vals) is used. Ing the derivs used:

)x

0Pr(log( iY

1

1

.

.

Nt

UM

tVT

AMS

MOMEN

PVT

or the model

SILATOROC

MACDSI

WILLIAMS

R Statisticcators variab

imated valuated values,

indicators scase in the ator "NSI Cdicator "NSlues (+1) fo

lues the OrdIn the theorvative of th

)),,|0 ix

2015, Vo

)1(

1

.

.

NSIE

t

tROC

NSIE

NTUM

ROC

ls (Table 2)

StochastRate of CMacd RelativeWilliam Probabil

bles

ues the stand, the param

state above individual

C" and derivSI E". This ior rising, (0)

dered Choicetical part t

he indicator

Pr(log(1Yii

Y

olume: 1

1

1

tE

):

tic OscillatorChange

e Strenght Inms % R

lity (LR stat)

dard errors meter estimat

for all shamodels. F

ved from it indicator ca) for consta

ce models (the Orderedr "NSI P" f

(1)

,,|1 ii xY

7

r

dex

)

are bold tions are

ares that From the

with the an accept nt and (-

(Ordered d Choice from the

)

(2)

(3)

))

  

8 

 

 

The estiIn the e

and Lim

during t(0) the v On closfollowin

CCI-Va

With thvalues iCCI is istrong pdescribeExperieor minulisted inof boroKordsa should.

OSILAT

The Stoprice hirises wivalue si The Stoof the Sand D%down KD%-curslowed The form K% = - SGKF: OD: LoEY: Ma

 

 An E

imated paraequation (2)

mit_1 of val

the derivativvalue (+1),

ser inspecting results:

ariable (Com

he computatis determinein the chaptpurchase bes in the tenced investus sign at thn the table Oon new fact

at a high C

TOR-Variab

ochastic Osstory withinithin the fixinks within

ochastic OscStochastic O% curve). TK%-curve rerve howevedown K%-c

mula for the

(SGKF – E---------------- (EY - ED

Close valuewest value

aximum valu

Early Warning

ameter value 1 and 2lues. 1 rep

ve of NSI during the d

ion of the

mmodity Cha

tion of the Ced. The CCter "technicaehavior antheoretical tors buy at he CCI valuOrdered Logts Yapi, UsCCI value a

ble (Stochas

cillator (SOn a fixed pexed period tthe fixed pe

cillator is reOscillators ta

he slowed epresents thr is dotted curve.

e computati

ED) --------- * 10D)

e of the last of the shareue of the sh

g Model with

es are deter represent i

presents tha

E, assumesderivative o

signs (+/-)

annel Index

CCI the devCI takes valu

al indicatord a value part, invesstrong sale

ue changes git and Ordesas, Petkimand with the

stic Oscillato

O) compareseriod. With to its higheseriod on its

epresented akes place ddown K%-he sliding mrepresented

ion of the K

0

daily e within lasthare within t

Technical Ind

rmined within the tables

at point, at t

s. 2 represof NSI E, as

) of the in

x)

viation of thues betweenrs" is represof under -

stors shoules behavior

from shareered Probit

m, Cimentase remaining

or)

s the conclurise of the pst price levedeepest pric

on the basidue to a con-curve is remeans of thd. The D%-

K%-curve re

t five days tthe last five

dicators: The C

h the help ofs the Logit

the NSI C o

sents that possumes.

dividual pa

he share pricn +100 andented. A CC

-100 showsd buy at and a CCI

e to share. Wof models

s, Haznederg shares at

usion valueprices the cel. With casce level sink

is two diffenfrontation opresented ahe K%-curvcurve repre

eads:

the e days

Case of ISE (I

f the equatioand probit m

of the value

oint, at the

arameter es

ces from thd -100. The CI value of s a strong a high CCvalue aroun

With the anshowed up r Tugla; Ma low CCI

e of a shareonclusion vse of the prks.

rent curvesof these twoas a constanve within aesents the sl

Istanbul Stock

on (1) statemodels the

e (-1) the v

NSI C of th

stimated va

heir statisticcomputatio

f over +100 sales behav

CI value send -100. A

nalysis of ththat with th

Mardin Cimevalue to be

e with the ovalue of the rices the co

s. The interpo curves (Knt line. Thea fixed periliding mean

k Exchange)

d above. Limit_0

alue (0),

he value

alues the

average on of the shows a

vior. As ecurities. positive

he shares he shares ento and e bought

observed security nclusion

pretation K%-curve e slowed iod. The ns of the

E

Eurasian

 

 

If the cofive dayestimate

PVT-Va

The regquantitior case,added oquantityis added If the acvariablequantityconnectestimate

ROC (P

The pricthe com The foll Price RO If the pestimate

VOLUM

The actethe acteare morestimate The parsmall. T

Academy of S

onclusion vys, a rise oed value is p

ariable (Pric

garded relaties and price, the price/

or taken off.y of the oned or taken o

cted quantite shows a y are charation betweeed value (-)

Price Rate of

ce adjustmemparison to t

lowing form

(cureOC = -------

prices reached value is n

ME (Acted q

ed quantity ed quantity re buyers. Bed value is p

rameter estimThe reason f

Sciences Socia

value of the of the pricpositive (+)

ce-Volume-T

ionship of thes. With thequantity eq. With the re day laggedff. The perc

ty rises withstrong purc

acteristics foen acted qube derived

f Change)

ent rate (ROthe price of

mula shows

ent close – c----------------

close for

h a point, alnegative (-)

quantity)

represents and the pri

By the rise opositive (+)

mated valuefor it lies to

al Sciences Jou

last daily lies is forec.

Trend)

he prices toe price/quan

quilibrium oegarded rel

d cumulatedcentage is ca

h sinking prchase behavfor one PVTuantity and.

OC) shows tf the previou

the comput

close for x da----------------r x days

lso the RO.

the quantityices gives imf the inquir.

es of the VOthe extent o

ournal

ies in the prcast and tur

the acted qntity equilibof the one lationship od a certain palculated as

rices, the Pvior with loT value an

d rising pri

the percent us daily.

tation of the

ays) ------------ *

C value rea

y of the boumportant no

red quantity

OLUME ofof the acted

roximity of rned around

quantity is sbrium becomday laggedf the prices

percentage os a function

PVT value sow prices.

ny longer nces can a

change of t

e price adjus

100

aches a poi

ught and sootes to futu, the prices

f indicator fod quantity.

2015, Vo

the maximud. The sign

imilar to themes dependthe up-to-to the acted

of the up-to-of the price

inks. In thiSinking pr

not falling. minus sign

the price of

stment rate:

int. The sig

old shares. Ture events. W

rise. The si

for the regar

olume: 1

um value ofn of the pa

e equilibriuding upon pdate acted d quantity t-date acted e rise or cas

is situation rices and aFrom the

n of the pa

f the current

:

gn of the pa

The developWith sinkinign of the pa

rded shares

9

f the last arameter

um of the price rise quantity

the acted quantity

se.

the PVT a sinking negative arameter

t daily in

arameter

pment of ng prices arameter

are very

  

10 

 

 

MACD

With thbetween With thmeans aterm slexponenresult ishoweve With thdue to tthe signabove ccharacteThe sign

MOME

The Moof the Mrepresendifferenand witMomen Momen Summar"x" daysales de

RSI (Re

With thmeans omeans

 

 An E

(Moving Av

he help of tn two slidin

he computatare calculateiding meanntially slidis positive aner the result

e computatithe values onal line fromcuts down eristic for an is negativ

ENTUM

omentum inMomentum nted. The pnce lies in thth the ROC

ntum is com

Clontum = ----

C

rized the Ms is obtaine

ecisions are

elative Stre

he computatof the priceof the pr

Early Warning

verage Conv

the MACDng averages,

tion of the Med. Subsequns is takening means nd the MACis negative,

ion among oof the exponm down upthe signal

a rising pricve the param

dicates the pthe profit

price adjustmhe represenC with 0

mputed accor

ose value of --------------

Close value b

Momentum sd. If the Momet. The si

ength Index

tion of thise movemenrice movem

g Model with

vergence Div

trends can on whose b

MACD firsuently, fromn off, in ois larger thCD lies ove, the MACD

other thingsnentially sli, then a purline, then e level. On

meter estima

percent chaor loss, whment rate (Rntational forand on therding to the

the last dai--------------before x day

shows the yomentum a ign of the pa

x)

s characterints upward"ments dow

Technical Ind

vergence)

n be illustrabasis purcha

st a long-term the short torder to dehan the loner the zero-D is under th

s the signal iding meansrchase decia sales dec

ne can interpated value (-

ange of the phich a shareROC) showrm. The date ordinate formula sta

ily --------- * 1ys

yield of a shmaximum arameter es

istic numbe" (MAU M

wnward" (W

dicators: The C

ated. The Mase and sale

rm and a sherm expone

etermine thng-term expline. This inhe zero-line

line is deters of the lastision is metcision is mpret a rising-).

prices withie obtains w

ws a similartum line is the percen

ated down:

00

hare in the cvalue movetimated val

er becomes Moving AVEWAD Mov

Case of ISE (I

MACD showes decisions

hort term exentially slidihe MACD. ponentially ndicates a re.

rmined. Thit nine days.t. If howeve

met. A rising MACD va

in a fixed pewithin a cerr event as twith the Mt change i

comparisones reached aue is negati

with the hERAGE UPving AVER

Istanbul Stock

ws the relas can be met

xponentiallying means tIf the shosliding me

rise of the p

is signal lin. If the MAer the MAC

ng MACD alue as sale

eriod. With rtain periodthe Momen

Momentum ws represent

n to the pricand then dowive (-).

help of the P) and the RAGE dow

k Exchange)

ationship t.

y sliding the long-ort term eans, the prices. If

ne results ACD cuts CD from value is

es signal.

the help d, can be tum, the with 100 ted. The

ce before wnward,

"sliding "sliding

wn) the

E

Eurasian

 

 

developbetweenformulareverse

VOLOS

The volof for tbetweenlong-tercomputaparamet

WILLI

WilliampurchasOscillatWilliamat a vadecisionhelps wprices. T

NSI (-1

"NSI (-value -11) is" vsign of t In the OR² of thadditiondue to tnot be c In the cmeans cclose 1.

               7 LAITIL

Journal o

Academy of S

pment of then "0" and "1a of the RSIand. The si

SIL (Volum

lume Oscillthe price, fn the meansrm basis. Iation of theter estimate

IAMS (Will

ms ' %R reprses and inctor. In cont

ms lies ' %R alue between should be

with the annThe sign of

)

1)" represen1, it means tvalue of the the paramet

Ordered Loghe LR indexn are in the the calculaticorrect. 7

classical invclose 1 a str. On the as

                      LA Thomas

of Econometric

Sciences Socia

e prices det100". FollowI index is dgn of the pa

me Oscillat

lator (VOLOfor which as sliding at Influence p

e sliding meed value is p

liams’ % R

resents a Mcreased saletrast to thebetween 80

en 0 % ande met only inouncementf the parame

nts the matethat the valuone day la

ter estimate

git and Ordx (pseudo R

theoretical ion method

volution morong correlasumption th

                       (1993). A p

cs, 56; S:341

al Sciences Jou

termines. Thwing the detdetermined. arameter est

or)

OSIL) is simacted quanti

short noticparameters eans, the Fripositive (+).

R)

Momentum ine. Williame Stochastic0% and 100d 20% takeif the securit of Share -eter estimate

erial share pue sank andgged 0 or +d value is n

dered ProbitR²) and inste

part of thisof the pseu

odel the R²-ation. Dummhat in a giv

pseudo-R2 me

1-356

ournal

he relative terminationA rising Rtimated valu

milar to theity computce and the m

on the Vistigkeit and.

ndicator, byms ' %R is

c Oscillato0%, then sure place surity price mo- pries chaned value is p

price adjustmd the prices +1, then it knegative (-).

t models beead of the fs work. Theudo R². A c

-value betwmy Dependven interval

easure for lim

Strength inn of the MARSI value m

ue is negati

e Stochastices. The VOmeans of a

VOLOSIL rd the presen

y which levinterpreted

or has Willrplus sales frplus purchoves in the nge. A risinpositive (+)

ment of theof the curreknows a sin

ecame instef-Statistic the pseudo R²omparison w

ween 0 and dent variabll the correc

mited and qua

2015, Vo

ndex (RSI) cU and WADeans a sinkve (-).

Oscillator. OLOSIL sh

security qurepresent thntation meth

vels are reprd similarly liams ' %Rfind with thases. The preverse dire

ng Williams.

e one day laent daily cannking of the

ad of the cehe LR Statis² took very with classic

1 can move model do

ct probabilit

alitative depen

olume: 1

curve takesD with the h

king price h

It becomeshows the diuantity slidhe methodhod. The sig

resented wity as the StR a turned he regarded purchase an

rection. Thes % R mark

agged. If it tn rise. If thee prices me

ertainty mestic used. Dlow values

cal R²-value

ve, wherebyoes not suppties of an e

ndent varaibl

11

s a value help of a istory in

s instead ifference ing on a

d of the gn of the

th multi-tochastic sign. If

security, nd sales

e MACD ks rising

takes the e "NSI (-eant. The

easure of Details in s. This is es would

y a value ply value event are

le models;

  

12 

 

 

evenly dis not un 4. EMP Followiindices The maexchang CODEXU100

XU050

XU030

XKURY

XUTUM

XUSIN

XGIDA

XTEKS

XKAGT

XKMYA

XTAST

XMANA

XMESY

XUHIZ

XELKT

XULAS

XTRZM

XTCRT

XILTM

XSPOR

XUMAL

XBANK

XSGRT

XFINK

XHOLD XGMYO

XUTEK

XBLSM

XSVNM

XYORT

XIKIU

XYEKO

Followimodels.               8 PINDY

Hill S. 31

 

 An E

distributed, nusual with

PRICAL RE

ing the four(industry, s

ain sector age to note an

E INDICEISE NATIO

ISE NATIO

ISE NATIO

ISE CORP

ISE NATIO

ISE NATIO

A FOOD, B

S TEXTILE

T WOOD,

A CHEMIC

T NON-ME

A BASIC M

Y METAL P

ISE NATIO

T ELECTR

S TRANSP

M TOURIS

T WHOLE

TELECO

R SPORTS

ISE NATIO

K BANKS

T INSURA

K LEASING

D HOLDIN

REAL ES

ISE NATIO

M INFORM

M DEFENS

ISE INVES

ISE SECO

ISE NEW

ing tables c. (Table 3-4                      CK Robert S,

17

Early Warning

it is to be sh the estimat

ESULTS

r ISE (Istanbservice, fina

and sub secnd at the na

ES ONAL-100

ONAL-50

ONAL-30

PORATE GOV

ONAL - ALL S

ONAL - INDUS

BEVERAGE

E, LEATHER

PAPER, PRIN

CAL, PETROL

ETAL MINERA

METAL

PRODUCTS,

ONAL - SERV

RICITY

PORTATION

SM

ESALE AND R

OMMUNICATI

S

ONAL - FINAN

ANCE

G, FACTORIN

NG AND INVES

STATE INVES

ONAL TECHN

MATION TECH

SE

STMENT TRU

OND NATIONA

ECONOMY

contain som4)                        

, RUBINFELD

g Model with

set it possibtion of a lin

bul Stock Eancial and te

ctor indicesational mark

VERNMENT

SHARES

STRIALS

NTING

LEUM, PLAST

AL PRODUCT

MACHINERY

VICES

ETAIL TRADE

IONS

NCIALS

NG

STMENT

ST.TRUSTS

NOLOGY

HNOLOGY

USTS

AL

me of the si

D Daniel L. (

Technical Ind

le for R² annear probabi

Exchange) inechnology s

s cover secuket.

TIC

TS

Y

E

ignificant p

(1998). Econo

dicators: The C

n upper bordility model.

ndices are asector) and t

urities, whi

parameters

ometric mode

Case of ISE (I

der of. For t8

aforementionthe pertinen

ich are not

of variable

ls and econom

Istanbul Stock

this reason

ned the mant sub sector

t acted at th

es in ordere

mic forecasts;

k Exchange)

a low R²

in sector rs.

he stock

ed probit

McGraw-

E

Eurasian

 

 

SAMPREGRE

OUTP

N

CCI

OSILA(-1

PVT

ROC

VOLUM

MACD

MOMEN(-1

RSI(

VOLO(-1

WILLIA(-1

ISARE

LIMIT

LIMIT

LR i(Pseud

LRstatis

Proba(LR s

HAUSEKT

UNTSEKT

Academy of S

APLE SSION

PUTS

N 211

(-1)

ATOR 1) 0.0

(-1)

(-1) -9.3

ME(-1) 0.0

D(-1)

NTUM 1)

(-1)

OSIL 1)

AMS 1) 0.0

ET(-1) -0.0

T_0 -0.3

T_1 0.0

index do-R2) 0.2

R stic 1134

ability stat) 0.0

UPT TOR XUH

TER TOR XEL

Sciences Socia

ABANA ELEKT

Std.Dev

16

01 0.00

34 0.48

00 0.00

01 0.00

07 0.03

38 0.04

01 0.04

27

4.48

00

HIZ

LKT

Table-

al Sciences Jou

TRO

v Prob.

88

0.00 0.0

0.00 -10.

0.04

0.0

0.00 0.0

0.04 -0.3

0.00 -0.2

0.74 0.2

0.2

42.0

0.0

XUH

XEL

-3: Some O

ournal

AK ENERJİ

Std.Dev

8

04 0.02

23 2.47

00 0.00

01 0.00

30 0.17

29 0.17

29 0.17

24

00

00

HIZ

LKT

Of The Orde

İ AK

Prob.

1585

0.01

0.00 -4.29

0.00

0.00

-0.27

0.01 0.01

0.08 -0.07

0.09 -0.73

0.09 -0.33

0.20

648.4

0.00

XUH

XELK

red Probit O

2015, Vo

KTAŞ ELEKTR

Std.Dev

5

9 0.42

0 0.00

7 0.15

1 0.00

7 0.04

3 0.18

3 0.18

0

45

0

IZ

KT

Outputs

olume: 1

RİK A

Prob.

90

0.00 -21.53

0.00

0.08

0.54

0.00 0.01

0.06 -0.48

0.00 80.38

0.06 81.04

0.47

79.33

0.00

XUHIZ

XELK

13

AYEN ENERJİ

Std.Dev P

3 4.50

0.25

0.00

8 0.20

8 36.72

4 36.74

3

Z

T

İ

Prob.

0.00

0.03

0.01

0.02

0.03

0.03

  

14 

 

 

Stabilit

The stabshare prshares wat least are sele With thbeginninsecond p- for thethird of the entiare comafter thcollectio

1

0

ˆ

ˆ

H

H

A t-test

By the fof the es

 

 An E

ty of the pa

bility of therice changewere selectea sub sectocted. The ac

he examinatng of a thirpassage fine order, wit

f the collectire elevation

mputed. Theat far methons and thei

0

0ˆ

was accom

fulfillment stimated pa

Early Warning

CCI (-1) OSILATORPVT (-1) ROC (-1) VOLUME(MACD(-1)MOMENTRSI(-1) VOLOSIL(WILLIAMSISARET(-1

N (Mean)

LR index ((Average)

arameter es

e estimated pe, tested in ted. To the cor belongedccomplishe

tion of the d of the oldally only mth which a ions and aftns. Those oe estimated hod with thir stability i

mplished: t sta

of the condarameter val

g Model with

R(-1)

(-1) ) UM(-1)

(-1) S(-1) 1)

(Pseudo-R2)

Table-4:

stimated va

parameter vthe context riteria for c

d. Shares wid stability t

stability ofdest collecti

more half of tfurther par

terwards haonly with th

parameter vhe estimatedis tested.

ˆ

0ˆ

Sat

dition tstat<tt

lues of the r

Technical Ind

NumEf

Esti

)

Summary o

alues

values, in orof this wor

choice the nith the hightest results a

f the paramions of the pthe collectiorameter comalf of the colhe oldest anvalues withd parameter

table the H0 hregarded 32

dicators: The C

mber of fficient mations 33

108 58

250 214 75 27 16 49

247 247

1642

0.24

of Models

rder to be abrk. For this number of chest collectiare in the fo

meter valuesparameter cons was loc

mputation isllections are

nd recent coh the full cor values, re

hypothesis i shares was

Case of ISE (I

% of Total 13.2 43.2 23.2 100 85.6 30

10.8 6.4 19.6 98.8 98.8

ble to makefrom 250 sollections aons from eallowing:

s of the selcomputationcated - whics accomplise taken out ollections thollection numepresented d

is not rejects confirmed

Istanbul Stock

e prognoses shares altogand the affilach sub sec

lected sharen one takes ch recent coshed. After last of the c

he parameteumber are codown, with

ted and the d.

k Exchange)

over the gether 32 liation to ctor each

es at the out. In a llections Chow a

center of er values ompared

h smaller

stability

E

Eurasian

 

 

The estithe appestatistic 5. CON In summsmaller it more For all used. Tindicatoparametestimate108 momodels variablemodels models With thAnadoluis very snot reac

Model p

With abprognosaccompderived afterwar Point pprognosit "NSI "NSI CLimit_1accuracbetween For the (NSI cadetermithe "NSprognos

Academy of S

imated paraendix. The change of t

NCLUSION

mary we canas if is. NSlargely as i

technical inThe conclusors. The tecter values, ted parameteodels the O

the ROC ve, for 27 mo

the volumthe NSI(-1)

hose modelu Efes and Asmall with tched.

prognoses

bove the 3ses becomeplished. With

from theserds with the

prognoses asis "NSI C"E" derived" between L

1 on (+1). Ay is determn 54 to 72 p

execution alculated lownes. With t

SI of EU" vsticated upp

Sciences Socia

ameter valuresults dispthe estimate

N

n say that duSI C takes thf is.

ndicators wion values chnical indthereby altoer values of

OSILATOR variable, foodels the me OS IL va) variable.

ls, in whicAyen Enerjthese shares

2 shares se for one h these prog

e the "NSI Ee "NSI R" (N

and interva of values d

d. "NSI C" wLimit_0 andAfter deriv

mined. In thper cent.

of the intewer one limthe help of values (NSI per one bor

al Sciences Jou

es and stabplays that thed paramete

uring the dehe value (0)

with the comof 250 sha

dicators as ogether 250 f the 250 sh

variable, isor 214 modmoment arou

ariable, for

h the techni had extrems, one can m

elect for thperiod of gnoses the "E" (NSI estiNSI real) va

al prognosedetermined was under Ld Limit_1 "ative of "Nhe case of

rval prognomit) and "ththese two lprognostica

rder) is der

ournal

ility test dehe change oer values.

erivative of ), if it lies be

mputation ofares are raiargument models are

hares were cs efficient

dels the voluund variablr 247 mode

nical indicame parametmeet the acc

he stabilitythree mon

"NSI R" (Nimated). Thalues.

es are accowith the LiLimit_0 to "NSI E" is NSI E" it is

the point p

oses additiohe NSI CO"imit valuesated lower

rived. It wa

etermined foof the numb

f NSI E: NSIetween and

f the variabised for thewere used

e set up. It pclose. For 3for 58 modume variabe, for 16 m

els the WIL

ators represter values. Sceptance tha

y test of thnths (10 O

NSI calculatehe derived "

omplished. imit_0 and L"NSI P" onspecified ons comparedprognoses r

onally still value (NS, as during ones limit)

as checked

2015, Vo

or the selectber of colle

I C the valu. NSI C tak

bles one daye calculatio

for the departicipated3 models thdels the PV

ble, for 75 mmodels the RLLIAMS va

sent the arSince the nuat iterated p

e estimatedctober to 2ed) of value"NSI E" of

In the conLimit_1 is c

n (-1) is then (0) and w

d with "NSIresulted is p

the "NSI bI calculatedthe derivatand "NSI owhether the

olume: 1

ted 32 sharctions do n

ue (-1) assumkes the value

y lagged vaons of the teterminationd interestinghe CCI variVT variablemodels the

RSI variableariable and

rguments, Tumber of coparameter va

d paramete24. Januar

es is determvalues is co

ontext of thcompared a

en specifiedwith a "NSI I R" and pprognosis a

becomes CUd upper onetive of the "of EO" value "NSI R"-

15

es are in not cause

mes, if it e (+1), if

alues are technical n of the g that the able, for

e, for all MACD

e, for 49 for 247

Turkcell, llections alues are

r values y 2007) ined and ompared

he point and from d. With a

C" over rognosis accuracy

U" value e border) "NSI E", ues (NSI -value is

  

16 

 

 

within t(ever a from 70 The intbroadlyspeak wBeing ocannot binterval which respons With thobserveit an avwas obs62.5 perEU" andcent, i.e In princsafe procorrect prognosabout saabout th

 

 An E

these two vmodel per

0 to 96 per c

tervals - "Ny. With verywith the inton the otherbe made sa borders lieagain exteible.

he regardeded period of verage valueserved withr cent, resud "NSI EO"

e. with an av

ciple one canognoses canpoint progn

ses to talk cafe prognoshe point pro

Early Warning

values - betwshare)"NSI

cent.

NSI EU" any close inteterval border side the inafe statemenes in the hirnal factor

d 32 sharesf 3 months =e of 57,4 peh the 32 shalts in an av" values an verage value

n say that wn be accomnoses altogcan lie aparses to talk cognoses as w

g Model with

ween "NSI I R" is obs

nd "NSI EOervals (ex.: ers of safe nterval bordnts about thgh standard

rs of influe

s one could= -1 to "NSIer cent for 3res within terage valueagreement e of 89 per

with all secumplished. Su

ether with rt, there thecan lie aparwell as the in

Technical Ind

EU" and "Nerved withi

O" - failed "NSI EU"prognoses

ders far apahe point prd deviation ence, lying

d observe I EO" = +1 32 shares rethe period be of 20,1 pewith "NSI cent.

urities with ummarized approx.. 57e interval brt. With thentervals ma

dicators: The C

NSI PO" -.in these int

sometimes= +1 and with agree

art ("NSI Erognosis "Nand the Lim

g apart far

interval wibetween 9

esults. "NSIby 3 monthser cent. WheR" is determ

18 (= 0.201we can say

7 per cent oborders far

remaining ade. (Table 5

Case of ISE (I

With the rterval value

s very close"NSI EO"

ement of thEU" = -1 anNSI E". The

mit_0 and Lr, as specu

idth of "NSper cent andI EU" = +1s with a freen agreeingmined betw

* 0.89) of py that one wof all prognand with ap25 per cen

5)

Istanbul Stock

regarded 32es with a fr

ely and ag= +1)"NSI

he point prnd "NSI EOe reason forLimit_1 va

ulation beh

SI EU" wid 83 per cen

1 to "NSI Eequency frog the "NSI E

ween 61 and

per cent prowith 63 pernoses aboutpprox.. 18

nt can be sta

k Exchange)

2 models requency

ain very I E" can rognosis. O" = +1) r the far

alues, for havior is

ithin the nt. From O" = +1 m 5,5 to E", "NSI

d 100 per

obability r cent of t no safe per cent

atements

E

Eurasian

 

 

İŞ BANK

YAPI VE

İKTİSAT

VAKIF G

ALARKO

ENKA HO

KOÇ HO

ANADOL

ANADOL

MARET

PINAR SU

AYGAZ

BRİSA

ECZACIB

PETKİM

ÇELİK H

EREĞLİ

SARKUY

ARÇELİK

MAKİNA

T.DEMİR

ÇİMSA

İZOCAM

Academy of S

Stock

KASI (C)

KREDİ BANK

T FİN. KİR.

GMYO

O HOLDİNG

OLDİNG

LDİNG

LU SİGORTA

LU GIDA

U

BAŞI İLAÇ

HALAT

DEMİR CELİ

YSAN

K

A TAKIM

R DÖKÜM

M

Sciences Socia

Amo

in

K. Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

İK Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

Amo

in

al Sciences Jou

NSI ECorrect

ount 43

% 60.56

ount 46

% 64.79

ount 42

% 59.15

ount 39

% 57.35

ount 43

% 60.56

ount 56

% 72.73

ount 41

% 56.94

ount 39

% 54.17

ount 45

% 65.22

ount 47

% 65.28

ount 50

% 69.44

ount 45

% 62.50

ount 44

% 62.86

ount 49

% 69.01

ount 44

% 61.11

ount 46

% 63.89

ount 52

% 72.22

ount 51

% 70.83

ount 45

% 62.50

ount 39

% 54.17

ount 47

% 65.28

ount 44

% 61.11

ount 43

% 59.72

ournal

Interval Estimatio

Correct

67

94.37

67

94.37

66

92.96

64

94.12

66

92.96

76

98.70

69

95.83

51

70.83

67

97.10

71

98.61

71

98.61

70

97.22

66

94.29

71

100.00

70

97.22

72

100.00

70

97.22

68

94.44

68

94.44

66

91.67

71

98.61

71

98.61

71

98.61

n NSI E =

2015, Vo

= NSI EU = NSIEO

13

18.31

17

23.94

16

22.54

8

11.76

18

25.35

12

15.58

17

23.61

45

62.50

13

18.84

17

23.61

5

6.94

11

15.28

22

31.43

15

21.13

14

19.44

8

11.11

13

18.06

12

16.67

19

26.39

15

20.83

8

11.11

14

19.44

9

12.50

olume: 1

I NSI E = NSI EU

= NSI EO Correct

11

84.62

15

88.24

14

87.50

6

75.00

16

88.89

11

91.67

14

82.35

37

82.22

8

61.54

16

94.12

4

80.00

10

90.91

18

81.82

15

100.00

14

100.00

8

100.00

12

92.31

12

100.00

16

84.21

11

73.33

7

87.50

13

92.86

8

88.89

17

NSI PU =-1

NSI PO=+1 NSI P

Betwixt

43

60.56

35

49.30

37

52.11

48

70.59

37

52.11

53

68.83

38

52.78

7

9.72

39

56.52

34

47.22

60

83.33

38

52.78

36

51.43

56

78.87

43

59.72

49

68.06

42

58.33

37

51.39

42

58.33

44

61.11

47

65.28

43

59.72

41

56.94

  

18 

 

 

TRAKYA

AKAL TE

KORDSA

YÜNSA

GENTAŞ

KARTON

HÜRRİYE

ALCATE

ASELSAN

 

 An E

A CAM

EKSTİL

A SABANCI DU

Ş

NSAN

ET GZT.

EL TELETAŞ

N

Early Warning

Amo

in

Amo

in

UPONT Amo

in

Amo

in

Amoin

Amo

in

Amo

in

Amo

in

Amo

in

Ta

g Model with

ount 40

% 55.56

ount 44

% 61.11

ount 54

% 75.00

ount 42

% 58.33

ount 51 % 70.83

ount 40

% 55.56

ount 47

% 65.28

ount 50

% 69.44

ount 46

% 63.89

able-5: Poin

Technical Ind

68

94.44

70

97.22

69

95.83

70

97.22

72 100.00

70

97.22

72

100.00

70

97.22

71

98.61

nt and inter

dicators: The C

rval prognos

Case of ISE (I

18

25.00

13

18.06

18

25.00

9

12.50

15 20.83

4

5.56

8

11.11

21

29.17

15

20.83

ses

Istanbul Stock

16

88.89

12

92.31

17

94.44

8

88.89

15 100.00

3

75.00

8

100.00

19

90.48

15

100.00

k Exchange)

33

45.83

40

55.56

37

51.39

40

55.56

43 59.72

53

73.61

49

68.06

39

54.17

42

58.33

E

Eurasian

 

 

Ah

AP

B B

E B

a B

EF

Ce

Ct

CVI

CM

D F

A F

AB

FV

FS

Ga

GC

GF

G I J J

P K

PF

KS

Academy of S

ACHELIS http://wwwALDRICH Probit ModBACKHAUBACKUS, Economic RBAUER Rianalysis & pBELARMINEfficiency EFinancial InCAMPBELeconometricCARMAN tactics and aCHIRISTOVolatility FInstitutions COLBY RoMarket IndiDAGANZOFOCARDI,Assoc. FRECKA TAproach toBusiness 35FRONE R. Variables; PFULLER RSecurity AnGILCHRISand FinanceGOURIEROCambridge GRAY CheFinance, DeGREENE, WIMKB (200JOHNSONJOSEPH EPredict and KALLUNKProportionaFinancial-EKEITH P.KStocks; Fin

Sciences Socia

Steven .equis.com/John H. an

dels; Sage UUS Klaus (2David (199

Research, Wichard J. anperformancNO AndensEstimates wnstitutions CLL John Y.cs of financPeter (199

advanced anOFFERSEN Forecasting

Center. obert W. anicators; Dow

O Carlos F (, Sergio an

Thomas J. ao Analysing5, 379-388. Michael (

Pace UniverRussell J. , Fnalysis; McGT Simon ane; NBER WOUX ChrisUniversity

erly W. and evelopmentWilliam H.

01). http://w, Norman L

E., MURPHOptimize I

KI Juha-Pekality of FinEconomics 6K., JONHSancial Anal

al Sciences Jou

RE

B. (200/free/taaz/.nd NELSON

University Pa2000). Mult98). Discre

Working papnd DAHLQUce; Wiley. so-Diaz and

with Stock PCenter. , LO Andr

cial markets97). Quantnalytical tecPeter F. anfor Financia

nd MEYERSw Jones-Irw(1991). Lognd JONAS,

and LEE Chg and Forec

1997). Regrsity Resear

FARRELL JGraw Hill.nd HIMME

Working Paptian (2000)Press. LINN J.F. , Sep. (2000). Ec

www.imkb.gLloyd (1997HY Jr. (199

nvestment Okka, TEPPancial Rati

6(6). ON GL. anlyst Journal,

ournal

EFERENC

01). Tech

N Forrest Dapers No: 0tivariate Anete-time moper series / 6UIST Julie

d FERNANPerformanc

rew W. ands; Princeton titative invechniques; Gnd FRANCal Risk Man

S Thomas Awin. gistics syste, Caroline

heng F. (19casting Fina

gression Morch MethodJames L. an

ELBERG Chper No. W66). Econome

(1988). Im

conometric gov.tr/endek

7). Discrete 94). StockOutcomes, O Martikai

ios: Implica

nd SMITH, Feb.

CES

hnical An

D. (1985). 07-045. nalysemethoodels of bon6736. R. (1999).

NDO Gascoe in Bankin

d MACKINUniv. Press

esting for tGlenlake Pub

IS X. Diebnagement?

A. (1988).

ems analysi(1997). M

83). A Seeancial Ratio

odels for Dids Forum. nd WODER

harles (199652. etrics of Qu

mproving Pu

analysis; Prksler.htm; .multivariat

k Market PrRevised Edinen and JUations for R

H R.E. (19

2015, Vo

nalysis fr

Linear Prob

oden; Springnd pricing; N

. Technical

on (1997). ng Firms; T

NLAY A. Cs. the global mbl. Co.

bold (1997).The Wharto

7th Encyclo

s; Springer.Modeling th

emingly Unros; Journal

iscrete and

RN Jr. (1987

98). Investm

ualitative De

ublic Financ

rentice Hall

te distributiorobability:

dition; IrwinUKKA ParttRatio Classi

975). Inflati

olume: 1

rom A

bability, Lo

ger. National B

l market in

Linking WThe Wharton

Craig (1997

markets: st

. How Relon School F

opedia of T

. he market;

nrelated Regof Econom

Limited De

7). Investm

ment, Funda

ependent V

ce for Devel

l.

ons; Wiley.Using Stat

n. ttunen (199ifications; A

ion cases C

19

to Z;

ogit, and

ureau of

dicators:

Weighting n School

7). The

trategies,

levant is Financial

Technical

Fabozzi

gressions mics and

ependent

ments and

amentals

ariables;

lopment;

. tistics to

6). The Applied-

Common

  

20 

 

 

KF

KI

Ld

LTI

MT

Nm

PMM

PT

PI

SD

Ya

o

Z  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 An E

KERAN MFederal ResKIEFER NiIstanbul StoLAITILA dependent vLO AndrewTechnical AImplementaMOORE GThe FinancNAGEL Hmodels; ForPAAP RichModel for Marketing-MPLUMMERTechnical APYNDICK Investment;STINEBRICDiscrete ChSUMER, KYoluyla Heand StatisticSUMER, Kof ISE (IstaZELTEMA

Early Warning

Michael W. serve Bank icholas M. (ok ExchangThomas (1varaible mo

w W. und MAnalysis: Cation; NBER

G.H. and Cial Analysts

H. and HATrschungberihard and FR

Brand ChMix VariabR Tony anAnalysis and

R. and SO; NBER MaCKNER T

hoice ModelK. K. (2006eteroskedisics e-Journa

K. K. (2013)anbul Stock

AN Daniel (1

g Model with

(1977). Eof St. Louis(1997). Fine. 1993). A odels; JournaMAMAYSKComputationR Working

CULLITY Js HandbookTZINGER icht WirtschRANSES Phoice with

bles; Journalnd WILLIAd the DynamOLIMANO acroeconom

Todd R. (ls; Journal o). White'in ite Altinda l, 4(1), 17-2). An Early Exchange)

1999). Mod

Technical Ind

Expectationss Jänner. nancial Eco

pseudo-Ral of Econo

KY Harry annal AlgorutPaper: 7613

J.P. (1988). k; Dow Jone

R. (1990).hafts UniverPhilip Hansh Different l of AppliedAM F. (1mics of Pric

A. (1993mics Annual(2000). Serof Applied EHeteroskedModel Tah

24. Warning M. dels for disc

dicators: The C

s, Money an

nometrics M

R2 measureometrics, 56nd WANG Jthms, Statis3. Security M

es-Irwin. . Diagnosrsität Wien s (2000). A

Long-Rund Economet991). Fo

ce; Wiley. 3). Econom. rially CorreEconometridisite Tutarhmini. Istan

Model with T

crete data; O

Case of ISE (I

nd the Stoc

Market Micr

for limite. Jiang (2000stical infere

Markets an

stics in somInstitut für

Adynamic Mn and Shotrics, 15. orecasting F

mic Instabil

elated Variics, 15. rli Kovaryannbul Unive

Technical In

Oxford scien

Istanbul Stock

ck Market;

rostructure

ed and qu

0). Founddaence, and E

nd Business

me discreteStatistik. Multinomia

ort-Run Ef

Financial M

lity and Ag

iables in D

ns Matrisi ersity Econ

ndicators: T

nce publica

k Exchange)

Review;

Models;

ualitative

ations of Emprical

s Cycles,

e choice

al Probit ffects of

Markets:

ggregate

Dynamic

Tahmini ometrics

The Case

ations.