Fed rates and movement of bank stocks in India

Ka maka , Subhash
A icle
Fed a es and mo emen o bank s ocks in India
Asian Jou nal o Economics and Banking (AJEB)
P o ided in Coope a ion wi h:
Ho Chi Minh Uni e si y o Banking (HUB), Ho Chi Minh Ci y
Sugges ed Ci a ion: Ka maka , Subhash (2025) : Fed a es and mo emen o bank s ocks in India,
Asian Jou nal o Economics and Banking (AJEB), ISSN 2633-7991, Eme ald, Leeds, Vol. 9, Iss. 2, pp.
261-283,
h ps://doi.o g/10.1108/AJEB-11-2024-0127
This Ve sion is a ailable a :
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Fed a es and mo emen o bank
s ocks in India
Subhash Ka maka
Depa men o Managemen S udies, Bank o India, Kolka a, India
Abs ac
Pu pose – The pu pose o his pape is o iden i y he changes in he s ock ma ke p ices o banks in India wi h
changes in FED a es in long un.
Design/me hodology/app oach – Using bo h bi a ia e g ange causali y and ANOVA along wi h binomial
logis ic eg ession he in luence o changes in FED a es on s ock ma ke p ices o bo h majo public sec o and
p i a e sec o banks ha e been de i ed.
Findings – P i a e banks wi h highe sha eholding o Fo eign Ins i u ions in es o s a e in luenced signi ican ly
as compa ed o public sec o banks.
Resea ch limi a ions/implica ions – The changes in FED a es and i s in luence o e he s ock p ices a e
ela ed di ec ly o he sha eholding pa e n o Fo eign Ins i u ional In es o s. The esul s sugges ha changes in
he FED a es ha e a di ec impac on he inancial sec o s ock p ices, whe e a posi i e ela ionship is obse ed.
P ac ical implica ions – Fo in es o s his p o ides a decisi e signal o ma ke - ela ed in es men s in public
sec o is-a- is he p i a e sec o banks and o he policy make s his may open he doo o policies ela ed o
o eign in es men s as well as policies ela ed o managing liquidi y posi ions.
O iginali y/ alue – By using eal da ase s and g ange causali y analysis his pape will help in unde s anding
he ela ionship be ween he banking s ocks in India and changes in FED a es.
Keywo ds Fed a es, G ange causali y, FDI, Public sec o banks, P i a e banks, Repo a e, Re e se epo
Pape ype Case s udy
1. In oduc ion
In e es a es play a key ole in he de elopmen o he economy and con olling he economic
ope a ions o a S a e. The changes in in e es a es p o ide an impo an ool h ough which he
cen al bank in a coun y akes he lead in he managemen o in la ion as well as ma ke
ope a ions and, o cou se economic g ow h. In e es a es also impac he low o c edi in he
economic sys em.
The mo emen o in e es a es has di ec implica ions o he inancial ma ke s including
s ock ma ke s. In India he Rese e Bank o India (RBI), he Cen al Bank egula es he
economy using he Cash Rese e Ra io (CRR), epo a es, e e se epo a es, S a u o y
Liquidi y Ra io (SLR) e c. The RBI also de e mines he Go e nmen Bond Ra es ha a e
loa ed by he Cen al and S a e Go e nmen s and p o ide a good in es men oppo uni y o
e ail in es o s as well as o banks and inancial ins i u ions o mee SLR equi emen s.
Asian Jou nal o
Economics and
Banking
261
JEL Classi ica ion — E42, E47, E52, G10, G18, G11
© Subhash Ka maka . Published in Asian Jou nal o Economics and Banking. Published by Eme ald
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imp o e he quali y o his pape .
Decla a ions:
A ailabili y o da a and ma e ial: The da ase s used and/o analyzed du ing he cu en s udy a e a ailable
om he co esponding au ho on easonable eques .
Compe ing in e es : The au ho decla es no compe ing in e es
Funding: This esea ch has no ecei ed any ex e nal unding
Au ho s’ con ibu ions: All au ho s ha e equally pa icipa ed in he esea ch. The au ho ha e ead and
ag eed o he inal e sion o he manusc ip
The cu en issue and ull ex a chi e o his jou nal is a ailable on Eme ald Insigh a :
h ps://www.eme ald.com/insigh /2615-9821.h m
Recei ed 22 No embe 2024
Re ised 6 Ma ch 2025
7 Ap il 2025
Accep ed 7 May 2025
Asian Jou nal o Economics and Banking
Vol. 9 No. 2, 2025
pp. 261-283
Eme ald Publishing Limi ed
e-ISSN: 2633-7991
p-ISSN: 2615-9821
DOI 10.1108/AJEB-11-2024-0127
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Ano he impo an ea u e o he bond ma ke is ha i has an in e se ela ionship wi h
s ock p ices, so when s ock p ices ise bond p ices all and ice e sa.
To mee liquidi y equi emen s in he banking sys em, comme cial banks bo ow om RBI
by selling hei secu i ies o he cen al bank which is also e med as epo. So, when he e is a
hike in he epo a e, he cos o bo owing o banks and o he inancial ins i u ions inc eases,
and i plays a majo ole in he inc easing in e es a es o a ious loans and ad ances.
Simila ly, he Fede al Fund Ra e is se by he Fede al Rese e, U.S., which e e s o he a e
a which comme cial banks bo ow and lend hei excess ese es o each o he o e nigh . By
moni o ing he FED a es he g ow h o he economy is moni o ed, which is decided by he
Fede al Open Ma ke Commi ee (FOMC). FED a es a e usually educed when he economy
begins o s uggle o dec ease he bo owing cos . When he economy is o e -hea ed, FED may
decide o inc ease a es, o inc ease he cos o c edi h oughou he economy. This change can
signi ican ly impac he bond and capi al ma ke s. Fo example when FED a es inc ease, he
s ock ma ke may become ela i ely less a ac i e.
FED a es a e also ha e an impac on s ock ma ke s in India, whe e a ise o decline causes
changes in s ock ma ke s. When he bo owing a e is low, an in es o bo ows in he U.S.
ma ke and in uses he capi al in he Indian ma ke . Con e sely, when he e is an in e es hike
ha has a posi i e impac on he U.S. easu y yield, he money mo es om Indian ma ke s.
The changes in he FED a es do no occu o e nigh bu he news s a s mo ing in he
ma ke s mon hs be o e any announcemen and acco dingly he equi y ma ke s a e a ec ed.
Fo eign di ec in es men in a ious sec o s in India plays an impo an ole. Acco ding o
he In es India si e (in es india.go .in) he o al FDI equi y in low du ing FY: 2022–23 was
$70.97bn and he o al FDI equi y in lows was a $46.03bn. The coun ies wi h g ea es
con ibu ions o FDI equi y in lows o FY: 2022–2023 a e Mau i ius (26%), Singapo e (23%),
he USA (9%), he Ne he lands (7%) and Japan (6%).
Amongs , he sec o which is ha ing he highes in es men in FDI equi y in low du ing
FY: 2022–23 a e inance, banking, insu ance and o he se ices which accoun s o 16% o he
o al in es men . So, i becomes e y impo an o s udy he impac o FED a es on Banking
Sec o in India, since i is one o he mos p e e ed sec o o in es men .
India is an a ac i e des ina ion o o eign in es o s due o i s g ea e g ow h in he
banking sec o , good asse quali y e c. Acco ding o Islam and Belouci (2023) he size o a
ma ke de e mines FDI ollowed by openness, in as uc u e quali y, labo cos ,
mac oeconomic s abili y, human capi al and he g ow h p ospec s o he hos coun y.
Doy ch (2022) while s udying he impac o COVID 19 which caused an economic c isis
o a p olonged du a ion in es iga ed he impac o ou pu g ow h on accele a ion and
decele a ion. They ca ied ou a s udy on he FDI da a o 34 OECD coun ies du ing he pe iod
o 1995–2019 and concluded ha in inancial se ices FDI in lows a e coun e cyclical, while
manu ac u ing FDI ou lows a e p ocyclical. They obse ed ha FDI in anspo se ices is
de e mined by a ious ac o s, such as he con ol o co up ion in he home coun y.
FDI in he p i a e banking sec o is allowed up o 74% acco ding o he guidelines o RBI
and he go e nmen and he majo i y o he in es o s who hold i a e concen a ed in India’s
la ges p i a e sec o banks o which he op in es ee banks a e he ICICI Bank, he HDFC
Bank and he Ko ak Mahind a Bank (S&P Global Ma ke In elligence 24 h Sep embe , 2023).
Conside ing he ac s and igu es i is pe inen ha FDI in p i a e Sec o banks play a
pi o al ole in he coming days and i becomes e y impo an o s udy he impac o changes in
FED a es and changes in s ock ma ke p ices on in es o ’s sen imen s.
The pu pose o his pape lies in he ac ha e y ew s udies a e a ailable ocusing he
impac o changes in FED a es and changes in s ock p ices o majo banking s ocks in India,
o e he long e m. Al hough inancial se ices accoun o a ound 36% (As on 31s Oc obe ,
2023) in e ms o weigh age in NIFTY 50, which is conside ed he conglome a e o op 50
s ocks acco ding o ma ke capi aliza ion. Mo eo e , ou banks a e in he op en companies
and app oxima ely accoun ing o 27% weigh age (As on 31s Oc obe , 2023) in e ms o
ma ke capi aliza ion in NIFTY 50. The e o e, i is o p ime impo ance o s udy he long - e m
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impac o changes in he s ock p ices o he majo banking s ocks and FED a es in o de o
deciphe he pa e n o in es men s in hese s ocks in luenced by FED a es.
The objec i e o his pape is mani olds; i s ly, he pape a emp s o e eal he mechanism
ega ding how changes in FED a es in luences he majo banking s ocks in India on a long un.
Secondly, he pape also ocusses on he inhe en ole o FED a es in he o eign di ec
in es men s pa icula ly banking s ocks.
The pape is based on he hypo hesis whe he any change in he s ock ma ke p ices ollows
he change in FED a es o ice e sa whe e in he p esen con ex bi a ia e G ange causali y
models as subs an ia ed om di e en s udies ha e been used o de e mine ela ionship
be ween changes in in e es a es and s ock ma ke p ices in di e en ca ego ies o Banks.
The con ibu ions o his wo k a e as ollows. Fi s ly, hough pape s a e a ailable whe e
s ock e u ns ha e been co ela ed o changes in FED a es bu hei impac on banking s ocks
pa icula ly in eme ging economies like India ha e been a ely discussed. Mo eo e , he ole
o changes in FED a es and hei ami ica ions in he banking sec o in India being domina ed
by he public sec o and p i a e sec o banks ha e been discussed. These obse a ions p o ide
an a ena o de e mining he pe o mance o s ock e u ns o he banks wi h hike in FED a es.
Secondly, his pape has made he i s a emp o ela e how FDI in banks ha e been
playing a majo ole pa icula ly unde a well- egula ed inancial sys em whe e p i a e banks
wi h good pe o mance in e ms o pa ame e s a e g ea ly bene i ed. This may open he doo s
o FDI in o he banks no only o imp o e he e iciency o he banks bu o imp o e he
pe o mance on a global pla o m o become global banks. So, om an in es o ’s poin o iew
he ole o changes in FED a es a e impo an .
1.1 P ima y dis inc ion be ween his s udy and p io esea ch
Acco ding o ou su ey o he li e a u e, i is ound ha li e a u e a e mainly ocused on changes
in in e es a es and changes in s ock ma ke p ices o sec o al indices and i is some imes based
on how FED a es impac ou economy as a whole. Some o he ecen pape s (G owing impac
o U.S. mone a y policy on eme ging inancial ma ke s-E idence om India by Lakdawala)
poin ed ou ha U.S. mone a y policy decisions play a signi ican ole in he Indian S ock
ma ke s be o e he use o uncon en ional ools and ha e ec s a e becoming s onge o e ime.
Apa om hese ac s, e y ew s udies ha e in es iga ed he impac o FED a es on banking
s ocks in India, pa icula ly in long un. The e a e also ew pape s ela ed o how o eign
ins i u ional in es o s a e being impac ed h ough changes in FED a es. In his con ex , his
pape has made an a emp o b idge he gap in li e a u e whe e sha eholding pa e n pa icula ly
he sha eholding pa e n o Fo eign Ins i u ional In es o s (FII) ha e been co ela ed wi h
changes in FED a es. Fu he mo e, e y nascen li e a u e a e also a ailable o e eal impac o
changes in he FED a es on o e all s ock ma ke s and in pa icula inancial ma ke s. This pape
may be bene icial o policymake s and all s akeholde s conside ing how FED a e in e en ions
may a ec inancial i ms in India and will help in o mula ion o policies ela ed o FDI and
de elop a be e amewo k o in es men in public sec o banks in India o imp o e he
compe i i eness and pe o mance o hese banks as compa ed o hei p i a e pee s.
The es o he pape is o ganized as ollows: sec ion 2 p esen some o he ela ed li e a u e
e iews. Sec ion 3 desc ibes he esea ch amewo k and me hodology, sec ion 4 p esen s he
indings and include ele an discussions. Sec ion 5 highligh s he conclusion o his esea ch
and policy implica ions.
Table 1 p o ides he meaning/de ini ions o some o he e ms used in his pape .
2. Rela ed li e a u e
The a ailable li e a u e ha e ocused on a ious me hodologies used o de i ing he
ela ionship be ween s ock ma ke s and in e es a es ac oss di e en con inen s. We ha e
classi ied he li e a u e e iew in o he ollowing sec ions:
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Mukhe jee (2007) ound ha he Indian s ock ma ke was ha ing low le els o
obus ness and e iciency when compa ed wi h o he s ock ma ke s like hose in New Yo k,
Tokyo and Hong Kong. Gu e al. (2022) we e o he iew ha a e age in e es a es ha e
hei nega i e impac on he e u ns o he s ock ma ke based on he s udies on Chinese
ma ke s. They sugges ed ha he policymake s should go o ma ke iza ion o he
in e es a es.
On he same lines, Sahu and Pandey (2020) sugges ed ha in he Indian ma ke , money
supply and s ock ma ke p ices a e closely ela ed and ha ing a signi ican posi i e impac
based on hei s udies on Indian s ock ma ke om 1996 o 2016. While s udying he impac o
in e es a es on he s ock ma ke s Ramsha an (2019) ound ha hey we e in e sely ela ed.
Ba ancea e al. (2021) while s udying he economic g ow h o A ican coun ies sugges ed
ha economic g ow h is p oxied by GDP g ow h a es and o he indica o s like impo s,
expo s and g oss domes ic sa ings.
Ugu lu e al. (2021) while s udying he ela ionship among in es o ’s sen imen s, mone a y
policies and s ock ma ke s in he U.S. de i ed a signi ican nega i e o m in e ms o
unce ain y in mone a y policies. Kim (2023) iden i ied ha a sha p hike in he FED a es leads
o mo emen o in es o s in he eme ging ma ke s.
Kau e al. (2023) while wo king on BRICS economy no ed ha o eign in es men s,
commodi y p ices and money supply a e he key ac o s o g eene g ow h in BRICS
economies.
Hillie and Loncan (2019) no ed ha a ma ke in eg a ion imp o es he well-go e ned
i ms. Acha ya e al. (2020) in es iga ed he ansmission o Cen al Bank’s liquidi y o
Table 1. De ini ions/desc ip ions o he e ms
Te m De ini ions/Desc ip ions
FED Ra es Fede al Funds Ra e is se by he Fede al Rese e, U.S. which e e s o he a e a
which comme cial banks bo ow and lend hei excess ese es o each o he
o e nigh
G ange Causali y The G ange causali y is de ined in e ms o whe he his o ical in o ma ion se on
a a iable can p edic ano he a iable
Fo eign Di ec In es men
(FDI)
Fo eign Di ec in es men is he in es o o a o eign company/ i m o owne ship
in a company which is o o he coun y
Public Sec o Banks
(PSBs)
Public Sec o Banks a e hose banks whe e majo i y owne ship lies wi h he s a e
P i a e Sec o Banks P i a e sec o Banks a e hose banks whe e majo i y o he s ake is held by
indi iduals/g oups
Cash Rese e Ra io(CRR) I is he pe cen age o he ce ain posi ion o deposi s which a e o be main ained
wi h he Cen al Bank in o de o main ain he liquidi y posi ion o he banks
SLR(S a u o y Liquidi y
Ra io)
I is he in es men ha a bank makes in liquid asse s like Go e nmen Secu i ies
(G-Sec), gold ins ead o cash o main ain he sol ency o he banks
Repo Ra e(Repu chase
Ra e)
I is he a e which inancial ins i u ions pays o he Cen al Bank/Rese e Bank o
India o loans secu ed by secu i ies. The RBI changes he a es in o de o egula e
he in e es o be cha ged in loans and deposi s and in luences he bo owing cos
o banks
Re e se Repo Ra e I is he a e which is paid by he Cen al Bank/Rese e Bank O India when banks
pa k hei excess liquidi y/money wi h RBI
Ni y 50 The Ni y 50 is a di e si ied 50 s ock index accoun ing o 13 sec o s o he
economy. The Ni y 50 Index ep esen s abou 59% o he ee loa ma ke
capi aliza ion o he s ocks lis ed on NSE(Na ional S ock Exchange) as on
Sep embe 29, 2023.(Sou ce: nse.india.com)
Ni y Bank Index I e e s o he di e si ied s ock index o Banks (Public Sec o Banks and P i a e
Sec o Banks)
Sou ce(s): Table by au ho
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bank deposi s and loan sp eads in Eu ope o he pe iod o Janua y 2006 o June 2010 and
we e o he iew ha du ing easing o he mone a y policies pu s cons ain s on he banks
capi al base.
Con ad (2021) while s udying he impac o impac o in e es a es and mone a y policy
on he s ock ma ke no ed ha any dec ease o in e es a es may ha e a di ec impac on he
sha e p ices o he i m. Thei conclusions we e in line wi h ex eme expansi e mone a y
policy wi h low, ze o o nega i e in e es a es encou age inancial bubbles on he s ock
ma ke .
Hi o a (2023) while wo king on how he money supply in he economy in luences demand
o s ocks ound ha du ing he COVID phase he changes in money supply and mone a y
policy may ha e he disconnec be ween s ock ma ke and eal economy. Tho becke (2023)
while wo king du ing he same pe iod no ed ha changes in mone a y policies by he FED had
in luenced on he s ock ma ke s and in pa icula he ola ili y o he s ock ma ke s inc eased
du ing he pandemic pe iod wi h he changes in policies.
Ga ga e al. (2022) in es iga ed he in la ion a ge ing o Rese e Bank o India (RBI)
du ing 2015 and how he ma ke pe cei ed such changes in he mone a y policies ha e been
discussed. On he same lines again Lakdawala e al. (2023) in es iga ed how he bond ma ke
esponded o Rese e Bank o India’s mone a y policy a he s a o pandemic and hey no ed
ha due o measu es aken by RBI he in e es a es in long e m bond ma ke s had emained
high du ing he ea ly phase o he COVID 19 pandemic.
Kedia and Vashish (2017) while deciphe ing he ela ion be ween in e es a es and s ock
ma ke s s essed upon he ac ha he e is no ela ionship ega ding in la ion, policy in e es
a es and exchange a es.
Kumuda e al. (2016) analyzed he ela ionship be ween in e es a es and s ock p ices in
he con ex o India o a 10 yea pe iod om 2005 o 2014 whe e hey obse ed ha six sec o s
(au o, bank, FMCG, inancial se ices, IT and Pha ma) ou o 11 sec o s we e signi ican ly
impac ed by he policy in e es a es.
Ba ancea (2021) while s udying he impac o inancial pe o mance on he asse s and
liabili ies o banks in Eu ope du ing 2006–2020 eco ded ha he e is a s ong impac on he
banks asse s and liabili ies ela ed o inancial indica o s.
Lakdawala (2021) while s udying he impac o US mone a y policies on he Indian s ock
ma ke de i ed signi ican e ec s which ha e become obus o e he pe iod o ime. They also
ound ha he decisions ega ding in es men s we e mainly d i en by he o eign ins i u ional
in es o s, which also play an impo an ole in he s ock ma ke .
Kau e al. (2021) iden i ied a ious li e a u e ela ed o s udy o mac oeconomic a iables
on he economic g ow h o BRICS coun ies whe e GDP has been p oxied as measu e o
economic g ow h; o s udy he mac oeconomic a iables a ec ing he s ock ma ke o BRICS
na ions h ough con en analysis. The s udy has helped o ul ill he esea ch gaps ha con ine
he in luence o mac oeconomic a iables and es ic he g ow h o BRICS coun ies.
Guo e al. (2022) concluded ha impac o Fede al unds a e (FFR) is mos ly powe ul
when sen imen -d i en o e alua ion is ollowed by a co ec ion. They sugges ed ha
mone a y easing su p ises du ing sen imen -waning phases boos he s ock ma ke by
alle ia ing in es o s’ ea .
Balci e al. (2022a) used geome ic coa se g aining me hod on s ock ma ke indices o show
changes ac oss he ma ke s du ing h ee inancial c isis pe iods.
Balci e al. (2022b) used ne wo k induced so se s o in es iga e he e icacy o hese
me hods du ing a ious economic s ess pe iods o s udy he in e ac ion in s ock ma ke s.
Ni (2023) while s udying he impac o inc ease in he FED a es no ed ha any inc ease in
he a es had a nega i e impac on he economic ac i i ies and in es men s mo es ou om
o eign coun ies. So, i he FED a es emain inc easing he o eign coun ies may compensa e
he ou lows h ough changes in hei mone a y policies.
Ba ancea e al. (2023) while s udying co up ion pe cep ion index impac s he coun ies
and hei bounda ies.
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2.1 Empi ical li e a u e and hypo heses de elopmen
In o de o de ine he ela ionship be ween he policy in e es a es, in la ion, exchange a es and
money supply o o he ac o s which emana e om changes in mone a y policies and he s ock
ma ke s a ious au ho s ha e adop ed a ious me hodologies like G ange Causali y models,
Johansen`s app oach o co-in eg a ion and Toda and Yamamo o G ange causali y es e c.
Depending upon he na u e o he s udy and ype o da a co-in eg a ion me hods ha e been used
he mos bu G ange causali y models ha e also yielded good esul s. Some o he pape s ha e
elied upon he au o eg ession models o ha e signi ican esul s. Va ious au ho s ha e used
Bayesian eg ession models as well as some ha e used panel coin eg a ion es s o good esul s.
Fi s o all i is equi ed o es ablish he na u e o he a iables, depending upon a ious es
esul s like au oco ela ion es and mul icollinea i y es s, p ope me hods o u he analysis
a e o be selec ed. In his pape , he combina ion o binomial eg ession and coin eg a ion es s
ha e been ca ied ou in o de o es ablish he esul s which ha e been ob ained h ough
ANOVA. Since, ANOVA esul s may no be as use ul and obus as compa ed o binomial
eg ession based on p opo ions o p obabili y and coin eg a ion me hods, bo h hese es s ha e
been ca ied ou . Fu he mo e, o check obus ness o he esul s omnibus likelihood es s ha e
been also ca ied ou so ind ou he a iables which a e impo an .
The de ails o me hodologies adop ed in a ious pape s may be summa ized as:
I we ake a close look a Table 2 i is en isaged ha mode n pape s ely upon no only he
coin eg a ion echniques bu also on he p obabili y based eg ession models. So, conside ing
he a ious models p oposed by a ious au ho s, in his pape G ange Causali y model along
wi h panel coin eg a ion me hods ha e been used. Apa om coin eg a ion models, binomial
logis ic eg ession has been used being a p obabili y-based app oach.
3. Me hodology
The Me hodology used in pape may be depic ed in o m o lowcha as Figu e 1 (By Au ho ).
Based on he li e a u e e iews, Bi a ia e G ange Causali y model wi h Box and Cox
ans o ma ion ha e been used a e Binomial logis ic eg ession. The Du bin and Wa son’s
s a is ic ha e been calcula ed wi h p alues o de ec whe he any au oco ela ion exis s in he
da a o no . The de ailed discussions on he me hodology used and i s implica ions a e
elabo a ed in his sec ion.
3.1 G ange ’s causali y
The G ange causali y is de ined in e ms o whe he his o ical in o ma ion se on a a iable
can p edic ano he a iable. In heo y, he adi ional G ange causali y es is a join
es ic ion es and s ic ly elies on he assump ion ha he unde lying da a gene a ing p ocess
is s a iona y.
Co ela ion may be de ined as he mu ual ela ionship be ween wo a iables o wo o
mo e p ocesses based and i is no expec ed by chance alone.
Causali y which may be e e ed o cause and e ec , is he ela ionship be ween wo
p ocesses, he i s o which ( he cause) is pa ially o o ally esponsible o he second, while
he second is pa ially o o ally dependen on he i s . (Rossi, 2013).
The causal e ec o wo a iables X and Y can be de e mined wi h he use o he G ange
causali y es , named a e he B i ish econome ician Si Cli e G ange . This es makes use o
S uden ’s -s a is ic and F-s a is ic es s and iden i ies whe he he alues o he a iable X
p o ide s a is ically signi ican in o ma ion abou he e olu ion o he u u e alues o he
a iable Yassuming ha X and Ya e ha ing s a iona y ime se ies o da a (S a iona i y in ime
se ies da a e e s o he ac ha s a is ical p ope ies o he ime se ies do no change
o e ime).
The G ange -causali y es s assess he signi icance o he p oposed p edic o s in a
eg ession o he dependen a iable (y
þ h
), on o he lagged p edic o s (x
), whe e h is he
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o ecas ho izon. The G ange -causali y es is a simple F- es on he pa ame e ec o
α
h
whe e:
y
þh ¼ α
0
h x
þβ
0
h
z
þ
ε
þh
; whe e ¼ 1; ...::; T and Z a e con ol a iables wi h lags o
y : y ; y þ 1
I is assumed ha he eg esso s a e sui able p edic o s when he s a is ical es s ejec he null
hypo hesis ha he eg esso s a e insigni ican (i.e., when he F- es o es ing he hypo hesis
α
h 5 0
ejec s a s anda d signi icance le els).
3.1.1 The s a iona i y in he ime se ies da a can be analyzed wi h he help o wo impo an
s a is ical es s.
(1) Augmen ed Dickey Fulle Tes (ADF): The Dickey Fulle Tes (DF) is used o
de e mine whe e any au o eg essi e model is ha ing a uni oo which implies ha he
da a is no s a iona y. The null hypo hesis o DF es is ha he e is a uni oo in he ime
Table 2. Me hodologies in a ious pape s
Name o he
au ho s Yea
Model used and pe iod o
s udy Pu pose o s udy Resul s
Sampene
e al.
2021 Johansen Mul i a ia e
Coin eg a ion Me hod
(2000–2019)
Rela ionship be ween
In e es a e, a e o
In la ion, Exchange a e
and Money Supply and
s ock ma ke index
Signi ican long un co-
in eg a ion among
in e es a es and Ghana
Composi e s ock index
Chaudha y,
Bakhshi and
Gup a
2020 Gene alized Au o eg essi e
Condi ional
He e oscedas ici y (GARCH)
(Janua y–June2020)
Impac o COVID 19 on
e u n and ola ili y o
s ock ma ke
Posi i e and signi ican
impac ound in all he
indices in he ma ke
Ahmed 2008 Johansen`s app oach o
co-in eg a ion and Toda and
Yamamo o G ange causali y
es (Ma ch 1995–Ma ch
2007)
Rela ionship be ween
s ock ma ke p ices and
key mac oeconomic
a iables
In e es a e seems o lead
s ock p ices
Agg awal and
Aga wal
2017 G ange Causali y Model and
Johansen`s app oach o co-
in eg a ion es (Janua y 2008
o Decembe 2013)
Rela ionship be ween
in e es a es and s ock
ma ke s
In e es a es and s ock
ma ke s mo e oge he in
long un
Yada e al. 2021 Vec o E o Co ec ion
Model and Coin eg a ion es
(2000–2020)
Rela ionship be ween
s ock ma ke p ices and
key mac oeconomic
a iables
The e is a long un
associa ion be ween
mac oeconomic a iables
and s ock ma ke s
Sun and Yang 2018 Ma ko swi ching ec o au o
eg ession (MS-VAR) model
Iden i ica ion o
asymme ic e ec s o
China’s mone a y policies
on s ock ma ke s
China’s mone a y policy
has s onge e ec s on he
bull ma ke han bea
ma ke
William M.
B iggs
2023 Bayesian modelling Classical economic
p oblems
Pa ial solu ion o
eplica ion c isis
Ani a Kalia 2024 Bayesian eg ession Rela ionship be ween
p omo e ’s sha e pledging
and company’s di idend
payou policy
Signi ican nega i e
associa ion p omo e ’s
sha e pledging and
company’s di idend
payou policy
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se ies da a which implies ha he da a se ies is no s a iona y. The al e na i e
hypo hesis is ha he da a is s a iona y.
(2) Phillips–Pe on Uni Roo Tes s (PP)
The Phillips-Pe on (PP) uni oo es mainly deals wi h se ial co ela ion and
he e oskedas ici y in he e o s. In pa icula , whe e he ADF es s use a pa ame ic au o
eg ession o app oxima e he ARMA s uc u e o he e o s in he es eg ession, he PP es s
igno e any se ial co ela ion in he es eg ession.
Hypo hesis: Ho: The p ocess has a uni oo .
Ca ying Ou ANOVA and Binomial Reg ession
S a iona i y o da a
Signi ican
Non-Signi ican
Ca ying ou G ange
Causali y Tes wi h hypo hesis
aming o p edic ion o
whe he Independen a iable
can be p edic ed wi h ime lags
o dependen a iable.
Calcula ion o qua e ly
changes in FED a es and
A e age o closing s ock
p ices in %.
F aming o Hypo hesis o ADF Tes , PP es and
KPSS Tes o ind ou whe he he FED a es in
% a e o ming s a iona y da a se ies.
Rejec Null
Hypo hesis
Accep
Null
Hypo hesis
In e p e a ion
o esul s
Collec ion o he Mon hly FED Ra es om FRED
Economic Da a and he Closing S ock P ices o Banks (11
PSBs and 13P .Banks) om July2007- Decembe 2021
Figu e 1. Ou line o pape . Sou ce: By au ho
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As he compu ed p-p- alue is lowe han he le el o signi icance o 0.05, so we ejec he
null hypo hesis and accep he al e na i e hypo hesis in case i s and hi d cases excep in
cases whe e 5 1.
In he hi d case, he null hypo hesis is ejec ed and we conside he ime se ies as s a iona y.
So, conside ing he abo e es esul s i may be conside ed ha he da a has s a iona i y bu
he G ange causali y es pa icula ly he bi a ia e G ange causali y es has ce ain
limi a ions as discussed in Pa a 3.3. Fu he mo e, o con i m he esul s binomial logis ic
eg ession has been also ca ied ou .
Fi s , Analysis o a iance (ANOVA) is ca ied ou o de e mine he ela ionship be ween
pe cen age changes in closing p ices o banking s ocks and pe cen age changes in FED a es.
The ANOVA esul s ha e been p esen ed in Table 9.
F om he able, i is obse ed ha a signi ican ela ionship be ween he FED a e and Closing
p ice exis s in he case o Ci y Union Bank, Fede al Bank, ICICI Bank, HDFC Bank, IndusInd
Bank, Ka u Vysya Bank, Ko ak Mahind a Bank and Yes Bank whe e all o hese a e p i a e
banks. No signi ican ela ionship exis s in he case o Public Sec o Banks (PSB). The FII
sha eholding in hese banks has been 27.40% in Ci y Union Bank, 26.30% in Fede al Bank,
49.20% in HDFC Bank, 45.70% in ICICI Bank, 24.70% in IndusInd Bank, 14.80% in Ka u Vysya
Bank, 32.50% in Ko ak Mahind a Bank and 26.70% in Yes Bank (As o Feb ua y 2025). The
R-squa ed alue and Adjus ed R-squa e alue ha e been wo ked ou along wi h he F-S a is ics.
So, om he ANOVA able, we conclude ha he ollowing banks ha e a signi ican
ela ionship:
Ci y Union Bank, Fede al Bank, ICICI Bank, HDFC Bank, IndusInd Bank, Ka u Vysya Bank, Ko ak
Mahind a Bank and Yes Bank.
Bu , since mul icollinea i y and au o eg ession a e p esen in he da a we go o binomial
logis ic eg ession o con i m he esul s o ANOVA. So, secondly, binomial eg ession is
ca ied ou o con i m he esul s o he ANOVA, since binomial eg ession is a p obabili y-
based es whe e esul s a e based on wo ou comes whe he he e is a ise o all in he
pe cen age o closing p ices o bank s ocks wi h a ise o all in FED a es, which is o be es ed.
In he p esen case since i is obse ed ha au oco ela ion and mul icollinea i y exis in he
da a, o ge be e esul s and o check he obus ness o he esul s, u he he omnibus
likelihood es is ca ied ou , o de e mine how he a iables (pe cen age change in closing
p ices) a e being in luenced by all o a ise in FED a es. The binomial eg ession has been
ca ied ou wi h he pe cen age all in closing p ices is- -a- is pe cen age ise in closing p ices
(indi idual banking s ocks) ha e been assigned alues “2” and “1” espec i ely, in a simila
manne he pe cen age all o ise in FED a es ha e been assigned alues “3” and “4”.The
o e all pe cen age qua e ly all and ise in closing p ices(including all he bank s ocks unde
Table 8. Resul s o he KPSS es
KPSS es (Le el/Lag sho /N)
KPSS es
(T end/Lag
sho /N
( 5 1))
KPSS es
(T end/Lag
sho /N-
0.1* )
E a (Obse ed alue) 0.056 0.164 0.052
E a (C i ical alue) 0.451 0.145 0.145
p- alue (one- ailed) 0.872 0.030 0.616
alpha 0.05 0.05 0.05
Tes in e p e a ion
H0: The se ies is s a iona y
Ha: The se ies is no s a iona y
Sou ce(s): Table by au ho
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s udy qua e ly) ha e been assigned he alues “5” and “6”. To con i m hese esul s o he
omnibus likelihood es , he G ange Causali y Tes has been conduc ed. The G ange
Causali y es has been ca ied ou conside ing he he e ogenei y in he da a. Simila ly, in he
case o binomial eg ession, he dependen a iable is he pe cen age ise o all in closing
p ices and he ac o s a e he pe cen age all o ise in closing p ices o indi idual inancial
ins i u ions/banks as well as he pe cen age all o ise in FED a es wi h hei assigned alues
as discussed ea lie in he ex . The esul s o binomial logis ic eg ession wi h omnibus
likelihood es esul s ha e been placed in Table 10 (sepa a ely o Public Sec o Banks and
P i a e Banks).
The esul s o binomial logis ic eg ession and omnibus likelihood (Table 11 o p i a e
banks and Table 12 o public sec o banks) es con i m ha in he case o Public Sec o Banks
excep o he S a e Bank o India (SBI), none o he o he banks a e no in luenced by any
changes in he FED a es. S a e Bank o India is he la ges bank in India wi h he la ges asse
size. The sha eholding o Fo eign Ins i u ional In es o s (FII) in SBI as o Decembe 2024 has
been 10.3% and he go e nmen sha eholding has been also lowes o he ex en o a ound 57%
(As o June 2024).
On he con a y, he p i a e bank’s esul s di e , whe e Fede al Bank, IDFC Bank,
IndusInd Bank and Ko ak Mahind a Bank a e being in luenced by changes in FED a es. The
FII sha eholding o almos all o hese banks anges be ween 25% and 32% (As o
Feb ua y 2025).
Table 9. Resul s o eg ession be ween changes in FED a es and changes in closing p ices
` Name o he bank
FII (Fo eign
ins i u ional
in es o s)
Sha eholding
in %(as o
Feb,2025)
Type o
bank
p- alue o
eg ession be ween
changes in FED
a es and closing
p ices(Omnibus
ANOVA Tes )
(Le el o
signi icance: 0.05)
R-squa e
alue
Adj.
R-squa e
F- es
alue
1 Bank o Ba oda 8.90% PSB 0.736 0.790 0.782 103.00
2 Bank o India 2.92% PSB 0.187 0.631 0.617 46.90
3 Bank o Maha ash a 1.54% PSB 0.389 0.268 0.241 9.91
4 Cana a Bank 11.10% PSB 0.725 0.803 0.796 112.00
5 Cen al Bank O India 0.44% PSB 0.210 0.088 0.052 2.44
6 Indian Bank 4.78% PSB 0.900 0.037 0.002 1.01
7 Indian O e seas Bank 0.02% PSB 0.495 0.523 0.506 30.20
8 Punjab Na ional Bank 5.70% PSB 0.152 0.677 0.665 57.60
9 S a e Bank O India 10.30% PSB 0.073 0.091 0.057 2.70
10 UCO Bank 0.02% PSB 0.953 0.490 0.472 26.40
11 Union Bank o India 6.46% PSB 0.188 0.090 0.055 2.53
12 Axis Bank 47.30% P . Bank 0.609 0.128 0.094 3.76
13 Ci y Union Bank 27.40% P . Bank 0.001 0.625 0.611 45.80
14 DCB Bank 10.86% P . Bank 0.438 0.017 0.019 0.470
15 Fede al Bank 26.30% P . Bank 0.009 0.802 0.795 111.00
16 ICICI Bank 45.70% P . Bank 0.001 0.723 0.713 71.70
17 HDFC Bank 49.20% P . Bank 0.028 0.654 0.642 52.10
18 IDFC Bank 27.10% P . Bank 0.085 0.730 0.721 74.50
19 IndusInd Bank 24.70% P . Bank 0.010 0.212 0.182 7.24
20 Ka u Vysya Bank 14.80% P . Bank 0.014 0.603 0.589 41.80
21 Ko ak Mahind a Bank 32.50% P . Bank 0.010 0.520 0.503 29.30
22 Sou h Indian Bank L d 11.46% P . Bank 0.187 0.564 0.548 35.60
23 Yes Bank 26.70% P . Bank 0.028 0.289 0.263 11.20
Sou ce(s): Table by au ho
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Table 10. Binomial logis ic eg ession esul s
Model i measu es o public sec o banks (binomial logis ic eg ession)
O e all model es
Model De iance AIC BIC R
2
McF χ
2
d p
9.67E�10 26 51.6 1 73.3 12 <0.001
Model i measu es o p i a e banks (binomial logis ic eg ession)
O e all model es
Model De iance AIC BIC R
2
McF d p
1 16.8 44.8 72.7 0.774 13 <0.001
Sou ce(s): Table by au ho
Table 11. Omnibus likelihood a io es s (p i a e banks)
P edic o χ
2
d p
% change in FED a es (2) 0.8033 1 0.37
Axis Bank 0.5367 1 0.464
Ci y Union Bank 2.2134 1 0.137
DCB Bank 3.0123 1 0.083
Fede al Bank 3.936 1 0.037
ICICI Bank 1.3704 1 0.242
HDFC Bank 2.66 1 0.103
IDFC Bank 5.4534 1 0.02
IndusInd Bank 6.774 1 0.009
Ka u Vysya Bank 3.4868 1 0.062
Ko ak Mahind a Bank 4.7173 1 0.03
Sou h Indian Bank 0.0282 1 0.867
Yes Bank 0.23 1 0.631
Sou ce(s): Table by au ho
Table 12. Omnibus likelihood a io es s (public sec o banks)
P edic o χ
2
d p
% change in FED a es (2) 2.78E�13 1 1
Bank o Ba oda 1.75E�12 1 1
Bank o India 2.42E�12 1 1
Bank o Maha ash a 9.72E�11 1 1
Cana a Bank 6.77E�11 1 1
Cen al Bank o India 6.52E�11 1 1
Indian Bank 9.75E�11 1 1
Indian O e seas Bank 9.66E�11 1 1
Punjab Na ional Bank 1.33E�12 1 1
S a e Bank o India 12 1 <0.001
UCO Bank 7.97E�10 1 1
Union Bank o India 1.42E�10 1 1
Sou ce(s): Table by au ho
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To con i m he ANOVA esul s as well as he binomial eg ession esul s bi a ia e G ange
Causali y es has been ca ied ou whose de ails ha e been discussed in he ollowing
pa ag aphs.
We p esen he G ange ’s Causali y Tes esul s o di e en Banks conside ing he
ollowing hypo hesis:
H0. Any change in he qua e ly FED a es (X) ei he a ise o all does no g ange he
qua e ly change in Closing s ock p ices (Y) in % ei he a ise o a all.
H1. Any change in he qua e ly FED a es (X) ei he a ise o all does g ange he
qua e ly change in Closing s ock p ices (Y) in % ei he a ise o a all.
The esul s o he Bi a ia e G ange Causali y Tes wi h Box and Cox ans o ma ion and non-
seasonal lag o 1 a e p esen ed in he ollowing Table 13.
We ha e ca ied ou a Bi a ia e G ange Causali y es using he URL h p://www.wessa.ne /
wasp_g ange causali y.wasp/wi h R –Codes. The box and cox ans o ma ion has been ca ied
ou in he X se ies and Y se ies. The non-seasonal ime lags a e 1 in he es .
F om he able, i is amply clea ha a signi ican ela ionship is he e in he case o P i a e
Banks like Axis Bank, Ci y Union Bank, DCB Bank L d., HDFC Bank, Ka u Vysya Bank and
Ko ak Mahind a Bank. I we ake a close look a all he banks he FII sha eholding pa e n has
been also highe in his g oup as compa ed o o he banks.
So, om he esul s o binomial eg ession and Bi a ia e G ange causali y, we in e ha
he ollowing a e he banks whe e any qua e ly changes in FED a es ha e a signi ican impac
on changes in s ock p ices qua e ly:
(1) Fede al Bank
(2) ICICI Bank
Table 13. Resul s o he bi a ia e g ange causali y es
S
No Banks/Fis
Type o
banks Ni y
F- es
alue
Y 5
(X)
F- es
alue
X 5
(Y)
1 Bank O Ba oda PSB Ni y Bankex 3.46 0.558 0.35 0.068
2 Bank O India PSB 0.76 0.388 1.19 0.281
3 Bank o Maha ash a PSB 0.00 0.953 0.38 0.751
4 Cana a Bank PSB 0.09 0.767 0.83 0.368
5 Cen al Bank PSB 0.67 0.418 0.02 0.892
6 Indian Bank PSB 1.62 0.209 2.00 0.163
7 Indian O e seas Bank PSB 0.03 0.862 2.59 0.114
8 Punjab Na ional Bank PSB Ni y Bankex 0.03 0.866 0.65 0.422
9 S a e Bank o India PSB Ni y Bankex/Ni y 50 0.88 0.353 3.34 0.073
10 UCO Bank PSB 1.32 0.255 0.10 0.748
11 Union Bank O India PSB 0.00 0.992 0.92 0.343
12 Axis Bank P Bank Ni y Bankex/Ni y 50 0.90 0.347 8.20 0.006
13 Ci y Union Bank P Bank 1.67 0.202 6.11 0.017
14 DCB Bank L d P Bank 0.06 0.806 4.64 0.036
15 ICICI Bank P Bank Ni y Bankex/Ni y 50 1.13 0.292 1.08 0.303
16 HDFC Bank P Bank Ni y Bankex/Ni y 50 0.06 0.810 8.13 0.006
17 IDFC Bank P Bank Ni y Bankex 0.03 0.859 1.67 0.202
18 Ka u Vysya Bank L d P Bank 0.49 0.486 4.33 0.042
19 Ko ak Mahind a Bank P Bank Ni y Bankex/Ni y 50 0.74 0.394 9.93 0.003
20 Sou h Indian Bank P Bank 0.01 0.941 3.21 0.079
21 Yes Bank P Bank 0.12 0.727 3.04 0.087
Sou ce(s): Table by au ho
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(3) IndusInd Bank
(4) IDFC Bank
(5) Axis Bank
(6) Ci y Union Bank
(7) DCB Bank L d.
(8) HDFC Bank
(9) Ka u Vysya Bank
(10) Ko ak Mahind a Bank.
(11) S a e Bank O India
I we ecollec he ac s ega ding FII in banks which ha e been discussed in Table 9 is s ong
enough o p edic ha s ock ma ke p ices o banks wi h he highes FDI a e being a ec ed by
he qua e ly changes in FED a es. On he con a y, since in PSBs, he FDI is meage FED
a es ail o p edic he s ock ma ke p ices in ha way as in he case o he la ges P i a e
Banks. The obse a ions a e also a o able o some o he well-managed and well-capi alized
banks ha di ec he NIFTY Bankex and he o e all momen um o he inancial ma ke since
he majo i y o he banks a e in NIFTY 50.
Fu he mo e, in o de o del e in o he ela ionship be ween he changes in he FED a es
and closing s ock p ices, he p obabili ies o ise in he closing p ices wi h changes in FED
a es ha e been calcula ed. The esul s a e p esen ed in he ollowing able.
Table 14 ep esen s he p obabili ies o pe cen age ise in closing p ices wi h hike o all in
he FED a es. I is obse ed ha he e has been 67% ise in closing p ices wi h hike in FED
a es and 33% ise in closing p ices wi h all in FED a es.
4.3 Discussions
The esul s ha e been summa ized as:
(1) In case o changes in FED a es, qua e -wise has di ec implica ions on he qua e -
wise changes in he s ock p ices o banking s ocks pa icula ly he banks ha ing highe
ma ke capi aliza ion. Only hose banks ha ha e mode a e o high Fo eign Di ec
In es men in hei capi al s uc u e a e ha ing an impac . So, in he long un, he ou
la ges p i a e banks ope a ing in India iz. ICICI Bank, Axis Bank, Ko ak Mahind a
Bank and HDFC Bank’s qua e ly a e age s ock p ices a e in luenced by he changes
in FED a es.
(2) I is obse ed ha s ock p ices o PSBs excep S a e Bank o India a e no in luenced by
changes in FED a es in he long un and hey a e o ally ou o he he d. So, in he case
o India, he owne ship s uc u e o inancial ins i u ions pa icula ly he sha eholding
o Financial Ins i u ional In es o s (FIIs) do ha e a i al ole o play in case o s ock
Table 14. Es ima ed ma ginal means o ise in closing p ices
95% con idence in e al
Change in FED
a es P obabili y SE Lowe Uppe
Rise in FED a es 0.67 0.0821 0.492 0.805
Fall in FED a es 0.33 0.0993 0.263 0.634
Sou ce(s): Table by au ho
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ma ke p ices in he long un since FDI no ms a e amed wi h ce ain es ic ions in
in es men in PSBs.
(3) Ou esul s also sugges ha a e age qua e ly changes in he s ock p ices o he majo
banks a e in luenced by changes in FED a es. So, i is e y p ominen ha changes in
FED a es ha e a p o ound in luence on changes in he s ock ma ke p ices and any
change may p edic he u u e p ices o Banks ha ha e a good amoun o o eign
in es men .
5. Conclusion
5.1 Theo e ical implica ions and policy implica ions
The implica ions may be summa ized as:
(1) Qua e ly S ock p ices o new-gene a ion P i a e Banks which a e well-capi alized a e
in luenced by qua e ly changes in FED a es. So, well-managed and well-capi alized
new-age echnology-d i en p i a e banks ha ing he majo chunk o he ma ke sha e
a e o p ime impo ance which a e a ec ed by changes in FED a es. He e, he changes
a e ela ed di ec ly o he sha eholding pa e n whe e in es men by Fo eign Ins i u ional
In es o s is impo an . I pu in ano he way, in es o s a e always in e es ed in hose
banks ha a e paying good di idends which in u n is ela ed o he pe o mance o he
banks. Fu he mo e, he esul s sugges ha changes in he FED a es ha e a di ec
impac on he inancial sec o s ock p ices, whe e a posi i e ela ionship is obse ed.
This posi i e ela ionship is based on he heo y p oposed by Keynesian economis s
whe e e enue e ec s domina e o e he cos e ec s (Ga g, 2008).
(2) In he s udies, i is obse ed ha owne ship s uc u e has a ole o play pa icula ly s a e
owne ship o inancial ins i u ions. Limi ed s udies ha e been ca ied ou o ind ou
his heo y o how he owne ship s uc u e o inancial ins i u ions has an impac on he
s ock ma ke s conce ning FED a es. The domino e ec s o changes in he FED a es
a e e lec ed in he in e es a es and bo owing cos s o inancial ins i u ions and a
sound inancial ins i u ion.
(3) The FDI has inc eased mani olds in he las couple o yea s, pa icula ly in P i a e
Sec o Banks whe e he policymake s ha e allowed up o 74% FDI and he esul s a e
e y much e iden in ou s udies whe e in es o s a e in es ing h ough a ious
channels in s able and well-capi alized banks. The policymake s pa icula ly he
Rese e Bank o India and o he egula o s a e o make decisions o open doo s o FDI
in he public banking sec o o imp o e he compe i i eness in hese banks which may
also a ac FDI sho ly a pa wi h hei p i a e sec o coun e pa s.
5.2 Manage ial and policy con ibu ions
(1) When we compa e he changes in s ock ma ke p ices o a ious s ocks qua e ly wi h
qua e ly changes in FED a es, i is obse ed ha he mo emen o some o he p i a e
bank s ocks may be p edic ed om changes in FED a es in e alia changes in he
sha eholding pa e n. So, om an in es o ’s iewpoin , his is e y impo an when one
may make a judicious decision on ha ing long- e m e u ns om changes in he FED
a es and FII in es men pa e ns since he in es men pa e ns a e di ec ly co ela ed o
he pe o mance o he banks. In es men manage s dealing in in es men s on behal
o hei clien s may use hese pa e ns as obse ed in his pape o ake in o med
decisions based on changes in FED a es.
(2) When we compa e he changes in he FED a es and S ock p ices we obse e ha hose
banks whe e FII sha eholding is highes a e being in luenced much. I is also impo an
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o no e ha p ime-pe o ming banks wi h a good capi al base ha e been able o a ac
o eign in es o s and in luence he ma ke in long un as compa ed o o he s. These
esul s may be pe inen o policy make s, whe e hey may modi y policy o
in es men in public sec o banks as well as FDI pe cen age.
5.3 Limi a ions and u u e esea ch pe spec i es
The limi a ion o he pape lies in he ac ha we ha e compa ed he da a o banks only wi h
FED a es, bu he e a e also some good NBFCs (Non-Banking Financial Companies) and
insu ance companies which may be also compa ed. Fu he esea ch wo k may be ca ied ou
o ind ou how he changes in FED a es on sho un a ec s he closing p ices o he s ock.
Fu u e Scope lies in he ac how he changes in FED a es a e a ec ing he mu ual und ma ke
om whe e we may ge a iewpoin o in es o s a la ge.
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Co esponding au ho
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