Bolek, Monika; Gniadkowska-Szymańska, Aga a; Pie aszewski, Pio
A icle
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM
lis ed companies
Financial In e ne Qua e ly
P o ided in Coope a ion wi h:
Uni e si y o In o ma ion Technology and Managemen , Rzeszów
Sugges ed Ci a ion: Bolek, Monika; Gniadkowska-Szymańska, Aga a; Pie aszewski, Pio (2025) :
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies, Financial In e ne
Qua e ly, ISSN 2719-3454, Sciendo, Wa saw, Vol. 21, Iss. 1, pp. 27-41,
h ps://doi.o g/10.2478/ iq -2025-0003
This Ve sion is a ailable a :
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Abs ac The aim o he a icle is o show di e ences in he g ow h p ocess ha ansla es in o g ow h
po en ial in g oups o en e p ises lis ed on he main and al e na i e ma ke s o he London S ock
Exchange. The s udy co e ed companies included in he Financial Times S ock Exchange 100 In-
dex (FTSE 100), as well as companies lis ed on he Al e na i e In es men Ma ke (AIM). Based
on he esul s o s a is ical analysis including co ela ion and eg ession analysis o panel da a, i
was ound ha companies lis ed on he al e na i e exchange (AIM) we e cha ac e ized by highe
g ow h po en ial and as e g ow h han hose lis ed on he main ma ke (FTSE 100). The added
alue o he a icle is ela ed o esul s indica ing ha he e is a di e ence in he g ow h p ocess
be ween companies aded on bo h ma ke s. This conclusion can be use ul o in es o s ex-
pec ing he g ow h o sha e alue in he in es men p ocess.
JEL classi ica ion: G32
Keywo ds: G ow h Po en ial, G ow h o Companies, Less De eloped and Ma u e Companies
Recei ed: 19.08.2024 Accep ed: 17.10.2024
Ci e his:
Bolek, M., Gniadkowska-Szymańska, A. & Pie aszewski, P. (2024). Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies. Financial
In e ne Qua e ly 21(1), pp. 27-41.
© 2025 Monika Bolek e al., published by Sciendo. This wo k is licensed unde he C ea i e Commons A ibu ion-NonComme cial-NoDe i a i es 3.0
License.
1 Uni e si y o Lodz, Facul y o Economics and Sociology, Depa men o Capi al Ma ke and In es men s, Poland, e-mail: [email protected],
ORCID: h ps://o cid.o g/0000-0003-4020-2988.
2 Uni e si y o Lodz, Facul y o Economics and Sociology, Depa men o Capi al Ma ke and In es men s, Poland, e-mail: aga-
a.gniadkowsk[email p o ec ed], ORCID: h ps://o cid.o g/0000-0002-7321-3360.
3 Uni e si y o Lodz, Facul y o Economics and Sociology, Depa men o Capi al Ma ke and In es men s, Poland, pio .pie aszews[email p o ec ed].pl,
ORCID: 0000-0002-0589-0327.
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
bi ious companies wi h he po en ial o become u u e
gian s, bu also wi h a highe isk o ailu e. Fo ecas ing
g ow h in bo h g oups may ha e di e en ules due o
di e ences in he companies and ma ke s on which
hey a e lis ed, consequen ly, i may in luence in es -
men decision-making.
The expec ed g ow h p ocess is ela ed o he
g ow h po en ial ha in es o s a e in e es ed in.
G ow h po en ial a ios a e based on in es o s’ expec-
a ions and should be ela ed o he u u e g ow h
(Danbol e al., 2011). The co ela ions be ween he
measu es o g ow h and measu es o g ow h po en ial
show whe he in es o s’ expec a ions mee he u u e
g ow h o companies. Ea lie esea ch (Pie aszewski e
al., 2023) ound ha companies included in he AIM
index a e mo e p edic able in e ms o business ope a-
ions (e.g., g ow h o asse s, equi y, and sales) and
companies included in he FTSE100 index in e ms o
ea nings g ow h. I can be concluded ha g ow h op-
po uni y measu es a e signi ican ly ela ed o he
g ow h o alue o companies as measu ed by EPS
g ow h. The EPS g ow h is lowe in smalle i ms as
measu ed by ma ke alue and we can conclude ha
ma u e companies wi h highe capi aliza ion a e alue
d i e s on a capi al ma ke . This s a emen was con-
i med by he esul s e e ing o he lowe impac o
asse s g ow h on he FTSE100 index included compa-
nies compa ed o he al e na i e AIM ma ke .
The a icle a emp s o show he di e ences be-
ween en e p ises acco ding o he exchange upon
which hey a e lis ed, which ansla es in o he g ow h
po en ial and he possibili y o p edic ing hei de elop-
men . In he esea ch pa he hypo hesis ha he e is
a di e ence ega ding he g ow h dynamics, po en ial,
consis ency and ac o s a ec ing he EPS g ow h in
bo h g oups o companies included in he FTSE100 and
AIM indices is es ed. The a icle consis s o an in o-
duc ion, a li e a u e e iew, a desc ip ion o he da a
and esea ch me hods, esul s, and conclusions.
A company’s g ow h is ela ed o i s alue manage-
men , and he e o e he expec ed g ow h should be
included in e e y s a egy (Doyle, 2009). Acco ding o
Lo i e al. (2003), alue is also ela ed o i s in e nal
g ow h, which may be balanced and s able (e.g., in ma-
u e companies) o as and dynamic (e.g., in younge
companies). A company’s g ow h is mos o en de-
sc ibed as quan i a i e (Pa on, 2005; Ba inge e al.,
2005), while i s de elopmen is quali a i e (Vaismo adi
e al., 2016). A company’s de elopmen is ela ed o
expanding i s compe encies (T oisi e al., 2020), and
he e is also a eedback loop be ween g ow h and de-
elopmen . Mille and Modigliani (1958) ecognized
The g ow h o en e p ises is impo an in hei al-
ua ion, whe e ac o s ha in luence his p ocess a e
aken in o accoun . The esea ch p oblem in he p e-
sen ed a icle co e s he opic o en e p ises ha a e
di ided acco ding o hei le el o de elopmen . Ma-
u e companies a e hose ha a e included in he
FTSE100 index, while less ma u e, smalle i ms a e
lis ed on he al e na i e exchange and a e included in
he AIM index. Smalle companies can ope a e in he
niche, o hey can g ow quickly on he basis o hei
inno a i e p oduc wi h he inancing ob ained on he
al e na i e s ock exchange. Capi al suppo ing he com-
me cializa ion p ocess can lead o a apid inc ease in
asse s when in es men p ojec s a e implemen ed and,
as a consequence, sales and ea nings pe sha e (EPS)
g ow h, i he in es men s a e e icien . G ow h unde -
s ood in his way should ansla e in o an inc ease in
he undamen al alue and hus he ma ke p ice, i he
ma ke is e icien . Taking in o accoun he g ow h p o-
cess in he g oup o less ma u e en e p ises, in es o s
expec ha he capi al hey in es will b ing highe
bene i s in he o m o a es o e u n in he u u e,
he e o e, he g ow h po en ial in his g oup should be
highe . Howe e , he g ow h p ocess may be di e en
depending on he ype o company and, consequen ly,
he s ock exchange on which i is lis ed. The p esen ed
esea ch co e s en e p ises included in he Financial
Times S ock Exchange 100 Index (FTSE100) and in he
Al e na i e In es men Ma ke (AIM) index. The main
di e ences be ween companies included in he FTSE
100 and he AIM index on he London S ock Exchange
lie in hei size, s age o de elopmen , and egula ions.
FTSE 100 companies a e la ge, well-es ablished compa-
nies wi h a s ong ack eco d. These a e ypically blue
-chip companies ha a e household names in he UK
and o en globally. The FTSE 100 comp ises he 100
la ges companies by ma ke capi aliza ion lis ed on he
London S ock Exchange and a e unde s ic e lis ing
equi emen s, including inancial pe o mance bench-
ma ks and co po a e go e nance s anda ds. These
companies a e gene ally conside ed less ola ile due o
hei es ablished na u e. On he o he hand, companies
included in he AIM index a e smalle , wi h high g ow h
po en ial. These can be young, inno a i e companies o
es ablished i ms looking o aise capi al o expansion.
The AIM is a much b oade ma ke wi h o e 800 com-
panies lis ed and he e a e less s ingen lis ing equi e-
men s compa ed o he FTSE 100, making i easie o
smalle companies o lis . This ma ke is gene ally con-
side ed mo e ola ile due o he highe g ow h po en-
ial and inhe en isks associa ed wi h smalle compa-
nies. The FTSE 100 is like he P emie League o UK
s ocks - es ablished gian s wi h a p o en ack eco d.
The AIM is like he Championship League - smalle , am-
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
human esou ces and echnology (Beck e al., 2006).
In es o s may be in e es ed in suppo ing inno a i e
ideas, con ibu ing o job c ea ion, o making a posi i e
impac in hei communi y. This can be pa icula ly ue
o impac in es o s o hose who a e in e es ed in
socially esponsible in es ing (Skalicka e al., 2023;
Khanka e al., 2022). Howe e , in es o s mus ca e ully
e alua e he isks and ewa ds be o e making an in-
es men and should ha e a clea unde s anding o he
business and i s g ow h po en ial (Zinecke e al.,
2022).
La ge companies ha e mo e esou ces and can
le e age economies o scale o main ain a compe i i e
ad an age (Nos a abadi e al., 2019). Bocken e al.
(2019) p esen ed se e al easons why la ge companies
end o g ow mo e slowly and mo e s eadily while
men ioning ma ke sa u a ion, bu eauc acy, isk a e -
sion and ocus on p o i abili y. Howe e , ma u e com-
panies can s ill achie e signi ican g ow h h ough s a-
egic in es men s, me ge s and acquisi ions, and o he
ini ia i es ha le e age hei esou ces and ma ke
posi ion (Al ino e al., 2021). Wennbe g (2013) ound
ha la ge companies end o g ow mo e slowly han
smalle ones. Howe e , smalle companies had highe
g ow h a es han la ge ones. Fo s Connolly e al.
(2021) ound ha small businesses end o ha e highe
g ow h a es han la ge businesses in he ea ly s ages
o hei de elopmen . Howe e , hey also ound ha
la ge businesses end o ha e mo e s able g ow h
a es o e he long e m. Roh e al. (2022) ound ha
la ge i ms end o be less inno a i e han smalle
i ms.
These s udies sugges ha while la ge companies
may g ow mo e slowly and mo e linea ly han small
companies, hey can s ill achie e signi ican g ow h
h ough s a egic in es men s, me ge s and acquisi-
ions, and o he ini ia i es ha le e age hei esou ces
and ma ke posi ion. Howe e , la ge companies may
be mo e isk-a e se and less inno a i e han smalle
ones, which can a ec hei abili y o achie e apid
g ow h (Di Vaio e al., 2020; S eimikiene e al., 2021).
This pape examines companies lis ed on he Lon-
don S ock Exchange (LSE) and included in he AIM and
FTSE100 indexes. Da a come om Bloombe g’s da a-
base. The analysis includes da a on he FTSE 100 1971–
2019 and AIM 1980–2019 (up o he ou b eak o COVID
-19). Da a o he AIM and FTSE100 indices a e ana-
lyzed om he beginning o he public ading, which is
due o he asymme y o he sample. Sha e p ices ha e
been adjus ed o e lec changes in capi al om sub-
sc ip ion igh s, di idends, and di isions. The da abase
con ains 2584 obse a ions (yea -on-yea ) o he
FTSE100 and 1794 obse a ions o AIM.
ha a company’s alue comp ises he alue o asse s
and he lows hey gene a e, as well as he alue o he
g ow h po en ial. Fo he company o g ow, u u e in-
es men p ojec s mus ha e a a e o e u n ha ex-
ceeds he cos o capi al (Chen 2019; I awan e al.,
2023). Long- e m g ow h po en ial depends on he
company’s e u n on equi y and he e ained ne p o i
a e (B uso e al., 2021; Lucky, 2019; Rahim e al.,
2021; Kamila e al., 2021). A key ac o ha a ec s
g ow h po en ial and i s possibili ies is company size
(Pe dana e al., 2022), which he e o e de e mines i s
g ow h and i s s abili y (Baska an e al., 2019; Holliday,
2001).
Small companies a e ypically cha ac e ized by
g ea e lexibili y and agili y o quickly pi o hei busi-
ness s a egies and seize new oppo uni ies, which can
lead o as e g ow h (Ghe ghina e al., 2020; Fi iasa i,
2020; Sapu a e al., 2022). Howe e , as no ed by
Achim e al. (2022), his can also esul in mo e chao ic
and unp edic able g ow h pa e ns, as small companies
which may no ha e es ablished p ocesses and s uc-
u es in place o handle apid expansion. In es o s who
ocus on small companies a e o en willing o ake on
mo e isk in exchange o po en ially highe a es o
e u n (Cô é e al., 2022; Fisch e al., 2021). As a esul ,
in es o s can demand a highe a e o e u n o com-
pensa e o he addi ional isk (Salm e al., 2016; Bake
e al., 1977; Me ikas e al., 2004). Small businesses a e
o en in he ea ly s ages o g ow h and may no ha e
a p o en ack eco d o ma ke posi ion, inc easing
he isk o in es o s (D’Angelo, 2019). In exchange o
aking on his isk, in es o s ypically expec highe
e u ns when in es ing in small businesses as hey ha e
he po en ial o signi ican g ow h and can p o ide
in es o s wi h a g ea e e u n on hei in es men i
he business is success ul (Smi h e al., 1994; OECD,
2010a, 2011a). As shown by Dunne and Hughes (1994),
la ge companies end o g ow mo e slowly and s eadily
because hey ha e al eady es ablished hemsel es on
he ma ke and ha e a solid cus ome base. They may
also ha e mo e es ablished p ocesses and s uc u es in
place o manage g ow h, which can make i easie o
hem o scale up in a sus ainable way (Lazonick, 2017;
Chesb ough, 2019).
In gene al, bo h small and ma u e companies a e
cha ac e ized by hei own unique s eng hs and weak-
nesses when i comes o g ow h (Klein e al., 2021).
Small companies may be mo e nimble and able o ake
ad an age o new oppo uni ies, bu hey also ace
g ea e unce ain y and isk. La ge companies may
g ow mo e slowly, bu hey also ha e mo e s abili y
and esou ces o wea he ma ke luc ua ions
(Weingae ne e al., 2014). Some o he ac o s ha
can in luence small business g ow h include business
s a egy, inancial managemen , ma ke condi ions,
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
The g ow h a es o ea nings pe sha e a e de e -
mined as ollows:
(2)
whe e: EPSn is ea nings pe sha e in n yea s a e yea
0. Ea nings g ow h is calcula ed in ela ion o asse size
(TA) since ea nings can be nega i e and a ec he e-
sul s.
The desc ip i e s a is ics o he g ow h indica o s
o bo h g oups o companies a e p esen ed in Tables
1 and 2.
Howe e , due o he lack o he equi ed da a,
hese da abases did no allow us o calcula e he
g ow h oppo uni y indica o s o all company/yea
obse a ions. In his pape , he g ow h o companies is
ep esen ed by he g ow h o asse s, equi y, sales, and
EPS. The g ow h a e o asse s, equi y, and sales o
one, h ee, i e, eigh , and en yea s is calcula ed by
he ollowing o mula:
(1)
Whe e: n = 1, 3, 5, 8, 10, acco dingly, and Xn deno es
he o al asse s, equi y, o sales a he end o n yea s
a e he yea in which he o al ea nings equal X0.
0
0
n
n
XX
XX
+
−
=
0
0
n
n
EPS EPS
EPS TA
+
−
=
Table 1: S a is ical cha ac e is ics o u u e g ow h measu es o he FTSE100 companies
N Mean Median SD Min Max Q1 Q3
gTAS1 2356 0.071000 0.025900 0.13150 -0.171300 0.70280 0.000000 0.119000
gTAS3 2196 0.264700 0.161600 0.37740 -0.295300 2.09300 0.035700 0.370900
gTAS5 2034 0.506600 0.323000 0.66500 -0.318600 3.64840 0.096600 0.684600
gTAS8 1791 0.975400 0.593900 1.19370 -0.339400 6.20710 0.189600 1.259400
gTAS10 1634 1.372200 0.831400 1.62820 -0.304700 8.97480 0.284700 1.788000
gSA1 2372 0.066900 0.032200 0.11890 -0.228400 0.52180 0.000000 0.124200
gSA3 2210 0.229700 0.166100 0.32020 -0.360100 1.55060 0.029100 0.353100
gSA5 2049 0.418300 0.290900 0.52880 -0.422900 2.37110 0.057300 0.635300
gSA8 1807 0.786700 0.516500 0.91760 -0.378500 4.27950 0.129300 1.156400
gSA10 1650 1.084400 0.717000 1.22530 -0.394900 6.00300 0.201400 1.583200
gEQ1 2356 0.071800 0.026700 0.19810 -0.541000 1.12100 0.000000 0.133800
gEQ3 2195 0.251900 0.170600 0.49310 -0.999400 2.52830 0.000000 0.390700
gEQ5 2034 0.447600 0.302800 0.77040 -1.614700 4.34440 0.001200 0.675600
gEQ8 1791 0.831100 0.523500 1.25180 -3.754700 6.42340 0.050900 1.153000
gEQ10 1633 1.164100 0.702300 1.65470 -3.856600 7.82630 0.118600 1.630000
gEPS1 2303 0.000017 0.000001 0.00006 -0.000166 0.00032 0.000000 0.000023
gEPS3 2143 0.000057 0.000014 0.00014 -0.000320 0.00079 -0.000004 0.000077
gEPS5 1983 0.000100 0.000023 0.00022 -0.000354 0.00120 -0.000003 0.000123
gEPS8 1745 0.000183 0.000034 0.00039 -0.000317 0.00251 -0.000003 0.000203
gEPS10 1592 0.000247 0.000040 0.00053 -0.000318 0.00332 -0.000001 0.000261
No es: The g ow h a es a e in eal numbe s. They need o be mul iplied by 100 o ind he pe cen age. The mo e
han one-yea g ow h a es a e o al a es o hose ime ho izons, no annualized
Sou ce: Au ho ’s own wo k.
Table 2: S a is ical cha ac e is ics o u u e g ow h measu es o he AIM companies
N Mean Median SD Min Max Q1 Q3
gTAS1 1624 0.153800 0.0424 0.2844 -0.2454 1.5922 0.000000 0.2045
gTAS3 1466 0.597300 0.2838 0.9143 -0.3945 6.5258 0.077000 0.7428
gTAS5 1229 1.588500 0.6271 2.7831 -0.4624 21.6160 0.232800 1.5819
gTAS8 1074 2.338100 0.8463 4.0930 -0.4494 29.6548 0.315000 2.2797
ion wi hin he sample is highe o AIM companies
han o he FTSE100 companies – he s anda d de ia-
ion is highe , and he in e als be ween he minimum
and maximum alues a e wide .
The da a p esen ed in Tables 1 and 2 con i m ha ,
as expec ed, asse s, sales, equi y, and EPS g ow much
as e in he companies lis ed on he AIM han in he
FTSE100 companies; bo h he a e age and median
g ow h a es a e highe o all ime ho izons. The a ia-
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
(5)
whe e: Pg – alue o g ow h po en ial, Ps – sha e p ice,
EPS – ea nings pe sha e, ke – cos o equi y.
The highe he indica o , he g ea e he oppo -
uni y o g ow h, as e lec ed by he ma ke . This mod-
el should no be used when company p o i s a e nega-
i e. The nex measu e o g ow h oppo uni y, p o-
posed by O o (2000), is ela ed o he concep o alue
added. The highe he indica o s, he g ea e he po-
en ial o g ow h o he company being examined.
(6)
whe e: EVF – excess alue o he company, MVE – ma -
ke alue o equi y, BVE – book alue o equi y, and
BVD – book alue o deb .
The second model ep esen s he alue ha ex-
ceeds he alue (EVE – Exceeding Value o Equi y):
(7)
Whe e: EVE – excess alue o equi y.
These models ela e o g ow h oppo uni ies in-
cluded in sha e ma ke p ices. G ow h companies a e
expec ed o pay low di idends and will e ain a la ge
sha e o in es men e enues. Fo example, low di i-
dend yields (di idend-p ice a io D/P) can also be
a p oxy o high g ow h oppo uni ies; he lowe he
a io, he highe he g ow h oppo uni ies.
All g ow h po en ial measu es a e based on he
idea ha ma ke p ices e lec he companies’ p o-
spec s o g ow h. Tobin (1969) p oposed a ma ke
alue index o asse s and hei eplacemen cos s as
a measu e o g ow h po en ial.
(3)
whe e: TQ – Tobin’s Q, MVC – ma ke alue o capi al
in es ed in he company, ARC – asse eplacemen
cos .
Due o he p oblems associa ed wi h de e mining
he le el o eplacemen cos s, i is possible o modi y
he Tobin’s Q a io in line wi h Danbol e al. (2011):
(4)
whe e: TA – o al asse s, MVE – ma ke alue o equi y;
BVE, book alue o equi y.
The highe he alue o his index, he g ea e he
oppo uni ies o g ow h, assuming ha he di e ence
in he ma ke alue o he sha es and he book alue
de e mines he g ow h po en ial included in he sha e
ma ke p ice. Ano he indica o used o e alua e
g ow h p ospec s is he P/E a io. The highe he P/E
alue, he g ea e he company’s g ow h po en ial. This
a io should no be used when company p o i s a e
nega i e. The models o Kes e (1984) as well as
B ealey and Mye s (1981) we e based on decomposing
s ock p ices o he alue o exis ing asse s and he al-
ue o po en ial g ow h oppo uni ies.
N Mean Median SD Min Max Q1 Q3
gTAS10 936 3.126000 1.1412 5.6050 -0.3904 44.6250 0.401800 2.8920
gSA1 1566 0.142000 0.0597 0.2310 -0.2302 1.3191 0.000000 0.2116
gSA3 1413 0.504700 0.2884 0.7320 -0.4324 4.8911 0.087000 0.6320
gSA5 1263 1.010600 0.4953 1.6366 -0.4255 11.4243 0.182100 1.1202
gSA8 1043 1.777500 0.7981 2.8979 -0.4059 19.2373 0.339900 1.8821
gSA10 912 2.456200 0.9846 4.2731 -0.3996 28.7539 0.418500 2.6113
gEQ1 1624 0.160000 0.0461 0.3571 -0.5831 2.3496 0.000000 0.2107
gEQ3 1466 0.646300 0.2783 1.1209 -0.9542 7.6005 0.068900 0.7883
gEQ5 1308 1.255100 0.5338 2.2853 -1.8379 17.2332 0.149800 1.4035
gEQ8 1074 2.339900 0.9090 4.3753 -1.5143 37.9360 0.267300 2.4346
gEQ10 936 2.941100 1.1755 5.1514 -0.8459 45.1004 0.371100 2.9867
gEPS1 1521 0.000200 0.0000 0.0013 -0.0043 0.0100 0.000000 0.0003
gEPS3 1367 0.001200 0.0002 0.0044 -0.0092 0.0374 -0.000090 0.0010
gEPS5 1215 0.002300 0.0003 0.0073 -0.0075 0.0764 -0.000040 0.0015
gEPS8 1011 0.004200 0.0006 0.0124 -0.0079 0.0943 0.000005 0.0025
gEPS10 897 0.005720 0.0009 0.0163 -0.0078 0.1192 0.000040 0.0029
No e: as o Table 1
Sou ce: Au ho ’s own wo k.
MVC
TQ ARC
=
TA MVE BVE
TQ TA
+−
=
/
Se
g
S
P EPS k
P KBM P
−
=
( ) ( )
g
MVE BVD BVE BVD
P EVF MVE BVD
+ − +
=+
g
MVE BVE
P EVE MVE
−
=
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
(8)
In he abo e equa ion, gEPS e e s o he one-yea ,
wo-yea o h ee-yea g ow h o EPS, gi en by o mula
(7).
deno es a one-yea -lagged e u n on equi y,
is he na u al loga i hm o he ma ke alue, and GO0
ep esen s one o six g ow h po en ial measu es in-
cluded in he analysis.
Acco ding o Danbol e al. (2011), he one-yea
equi y e u n (ROE-1) was included in he eg ession o
co e he impac o he a e age e u n on income.
When he coe icien is nega i e and s a is ically signi i-
can , an a e age e e sal is obse ed. The ecen one-
yea e enue g ow h is added o con ol he pe sis-
ence o he e enue g ow h a e (i i is posi i e). How-
e e , bo h con ol a iables con ain simila in o ma ion
o some ex en , and depending on whe he he espec-
i e eg ession coe icien sign is posi i e o nega i e,
each a iable can explain he a e age e e se o esidu-
al income. The ecen annual g ow h o o al asse s is
S a is ical analysis shows ha mos measu es a e
highe in he mean and median o companies lis ed on
he AIM compa ed o he FTSE100 companies (D/P is
lowe because smalle and younge companies do no
pay di idends bu ein es ea nings in g ow h p ojec s).
This esul is accompanied by a highe a ia ion be-
ween yea s (measu ed by s anda d de ia ion) and
a wide ange be ween he minimum and maximum
a ios o companies aded on AIM ma ke . The s a is-
ics o he su eyed sample con i m ha he companies
included in he FTSE100 index a e la ge han hose
included in he AIM index.
The ela ionship be ween u u e ea nings g ow h
and he measu emen o g ow h oppo uni ies is also
in es iga ed in dep h using a mul i a ia e eg ession
model p oposed by Danbol e al. (2011). In addi ion o
measu ing g ow h po en ial, he model also includes
o he ac o s associa ed wi h e enue g ow h iden i ied
in he li e a u e. In each es ima ed linea eg ession,
he measu emen o he g ow h oppo uni ies is only
one o se e al explana o y a iables. These es ima es
will he e o e help o in es iga e whe he he le el o
g ow h oppo uni y has an inc emen al impac on e e-
nue g ow h, aking in o accoun o he ac o s ha may
be ela ed o ha g ow h. The eg ession models a e
p esen ed in he ollowing gene al o mula:
Table 3: S a is ical cha ac e is ics o g ow h oppo uni y measu es o he FTSE companies
Table 4: S a is ical cha ac e is ics o g ow h oppo uni y measu es o he AIM companies
N Mean Median SD Min Max Q1 Q3
TQ1 1511 2.23830 1.73090 1.61270 0.59790 10.43900 1.13420 2.76920
TQ2 1533 2.14420 1.71150 1.34900 0.61300 8.14310 1.13800 2.70400
P/E 1344 27.61540 18.95220 28.54120 3.31520 181.15900 11.91960 29.92010
MV/BV 1511 3.23530 2.39670 2.87410 0.25800 17.22690 1.21380 4.27470
D/P 1033 0.00027 0.00022 0.00019 0.00001 0.00109 0.00013 0.00035
KBM 781 0.99936 0.99969 0.00088 0.99418 0.99998 0.99929 0.99985
EVF 1511 0.35030 0.42230 0.36120 -0.67260 0.90420 0.11830 0.63890
EVE 1511 0.39890 0.59440 0.54080 -1.84480 0.96030 0.20870 0.77530
No e: as in Table 3
Sou ce: Au ho ’s own wo k.
1 0 2 1 3 0
4 0 5 0
ln
i i i i
i i i
gEPS GO ROE EPS
TA MV
−
= + + +
+ + +
1 1 1
/ROE EPS EQ
− − −
=
0 1 0 1
0 0 0
11
, ,ln
EPS EPS TA TA
EPS TA MV
TAS TA
−−
−−
−−
= =
N Mean Median SD Min Max Q1 Q3
TQ1 2299 1.80530 1.47790 0.99710 0.79030 6.81330 1.15090 2.07880
TQ2 2292 1.86100 1.54920 0.97080 0.82280 6.50520 1.20410 2.15820
P/E 2286 19.59890 17.13200 11.63400 4.74720 87.68540 12.14560 23.33060
MV/BV 2299 3.16610 2.20160 3.11400 0.08460 21.09090 1.26320 3.75720
D/P 2098 0.00036 0.00034 0.00018 0.00001 0.00099 0.00023 0.00045
KBM 1628 0.99993 0.99994 0.00004 0.99978 0.99999 0.99991 0.99996
EVF 2299 0.32020 0.32370 0.26350 -0.26530 0.85320 0.13110 0.51860
EVE 2299 0.47060 0.57290 0.37170 -0.69640 0.99940 0.24760 0.75260
No e: P/E, D/P, and KBM a e calcula ed only o posi i e ea nings
Sou ce: Au ho ’s own wo k.
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
The expec a ion o g ow h should be e lec ed by
di e en measu es, ega dless o which g ow h oppo -
uni y indica o is applied. The ma ix o Pea son co e-
la ion coe icien s be ween a ious a ios ha e lec
g ow h oppo uni y is p esen ed in Table 5. A posi i e
co ela ion be ween all measu es is expec ed, excep
o he one be ween D/P (which should be nega i e
due o i s e e se na u e) and he o he measu es. The
s a is ical signi icance o hese co ela ion coe icien s
is assessed wi h he - es and i s signi icance.
sligh ly mo e a bi a y, based on i s s ong p edic ion o
u u e abno mal p o i s obse ed in he li e a u e. Fi-
nally, he loga i hm o he cu en ma ke alue, lnMV,
is an indica o o company size. In he nex sec ion, he
esul s o he s a is ical analysis a e p esen ed. Pooled
OLS model was ound he mos sui able.
In his sec ion, he esul s o s a is ical analysis a e
p esen ed o he companies on he FTSE100 and he
AIM indexes.
Table 5: Co ela ion ma ix o a ious g ow h oppo uni y measu es o he FTSE100 companies
TQ1 TQ2 P/E P/BV D/P PgKBM PgEVF
TQ2 0.92***
P/E 0.24*** 0.21***
P/BV 0.76*** 0.69*** 0.20***
D/P -0.32*** -0.24*** -0.31*** -0.21***
PgKBM 0.31*** 0.25*** 0.56*** 0.27*** -0.35***
PgEVF 0.86*** 0.81*** 0.25*** 0.72*** -0.36*** 0.37***
PgEVE 0.68*** 0.63*** 0.25*** 0.66*** -0.32*** 0.38*** 0.92***
No e: */**/*** The coe icien s a e signi ican a he 10% / 5% / 1% le el
Sou ce: Au ho ’s own wo k.
he measu es ha ep esen he wo dis inc ly di e en
g oups ela ed o how hey a e calcula ed.
Company g ow h can be measu ed by di e en
means, bu all o hem should be co ela ed i he
g ow h is consis en . I he company execu es p o i a-
ble in es men p ojec s, he g ow h o asse s, equi y,
sales, and EPS should be s ongly co ela ed. The co e-
la ion coe icien s be ween all he di e en company
g ow h measu es a e p esen ed in Table 6.
All measu es a e signi ican ly co ela ed wi h each
o he and wi h he p edic ed sign. The absolu e alues
o he co ela ion coe icien s ange om 0.21 o 0.92.
A deepe analysis e eals clea ules be ween hese
ela ionships. All ma ke - o-book-based measu es
(P/BV, TQ, EVF, EVE) a e highly co ela ed wi h each
o he . The e is also a e y s ong ela ionship be ween
he wo measu es based on he p ice- o-ea nings con-
cep (P/E and KBM). The co ela ion is weake be ween
Table 6: Co ela ion coe icien s be ween a ious u u e g ow h measu es o he FTSE100 companies
gTAS1 gSA1 gEQ1
gSA1 0.470***
gEQ1 0.521*** 0.304***
gEPS1 0.222*** 0.207*** 0.221***
gTAS3 gSA3 gEQ3
gSA3 0.634***
gEQ3 0.602*** 0.431***
gEPS3 0.196*** 0.307*** 0.225***
gTAS5 gSA5 gEQ5
gSA5 0.740***
gEQ5 0.692*** 0.535***
gEPS5 0.230*** 0.342*** 0.272***
gTAS8 gSA8 gEQ8
gSA8 0.728***
gEQ8 0.693*** 0.545***
gEPS8 0.271*** 0.381*** 0.275***
gTAS10 gSA10 gEQ10
gSA10 0.726***
gEQ10 0.754*** 0.570***
gEPS10 0.284*** 0.318*** 0.278***
No e: */**/*** The coe icien s a e signi ican a he 10% / 5% / 1% le el
Sou ce: Au ho ’s own wo k.
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
ho izons. Fu he mo e, EPS g ow h is also s ongly e-
la ed o i m size (measu ed by lnMV0) – he co ela-
ion coe icien s in all eg essions a e s a is ically sig-
ni ican a he 1% le el. The e is also e idence o pe sis-
ence in ea nings a he han he e ec o mean e e -
sion, which is demons a ed by he posi i e signs o
s a is ically signi ican coe icien s a and in some e-
g essions. Addi ionally, he esul s in columns 9 and
10 demons a e ha he p opo ion o he a iance in
EPS ha is p edic able based on he independen a ia-
ble (coe icien o de e mina ion) ises wi h he ime
ho izon.
In he second s ep, he same analysis was epea ed
companies aded on he al e na i e exchange o he
LSE. The co ela ion coe icien s be ween a ious
g ow h oppo uni y measu es in AIM-lis ed companies
a e p esen ed in Table 7.
All co ela ion signs a e posi i e. The highes sig-
ni ican co ela ion is be ween o al asse s g ow h and
sales g ow h o equi y g ow h a e in each o he i e
pe iods conside ed (excep o one-yea g ow h a es,
wi h co ela ion coe icien s ha exceed 0.6 o 0.7).
Sales g ow h a es a e also qui e s ongly co ela ed
wi h equi y g ow h. Ea nings g ow h a es a e mo e
independen o size g ow h measu es.
A ela i e change in EPS indica es he g ow h o
a company’s u u e alue. The esul s o he eg ession
based on equa ion (8) and models ela ed o he de e -
minan s o u u e ea nings g ow h a e epo ed in Ap-
pendinx 1.
The inc emen al impac o he ma ke le el o
g ow h oppo uni y is epo ed in column 8. Shaded
cells indica e ha he coe icien o he g ow h oppo -
uni y measu e is signi ican and o he p edic ed sign.
Almos all measu es pe o m e y well in e e y ime
ho izon. The only excep ion is he di idend yield (D/P),
which is no signi ican in he 3, 5, and 10-yea ime
Table 7: Co ela ion ma ix o a ious g ow h oppo uni y measu es o he AIM companies
TQ1 TQ2 P/E P/BV D/P PgKBM PgEVF
TQ2 0.83***
P/E 0.28*** 0.26***
P/BV 0.87*** 0.73*** 0.27***
D/P -0.34*** -0.31*** -0.35*** -0.32***
PgKBM 0.15*** 0.11*** 0.17*** 0.15*** -0.11***
PgEVF 0.78*** 0.74*** 0.26*** 0.74*** -0.38*** 0.15***
PgEVE 0.62*** 0.59*** 0.23*** 0.64*** -0.34*** 0.14*** 0.93***
No e: */**/** The coe icien s a e signi ican a he 10% / 5% / 1% le el
Sou ce: Au ho ’s own wo k.
measu es (P/BV, TQ, EVF, EVE). The e is also a ela i ely
s ong ela ionship be ween D/P and o he measu es.
The co ela ion coe icien s be ween all he di e -
en measu es o company g ow h a e p esen ed in Ta-
ble 8.
Fo he AIM companies, all measu es a e signi i-
can ly co ela ed wi h each o he and a e o he p e-
dic ed sign. The absolu e alues o he co ela ion co-
e icien s ange om 0.11 o 0.87. The highes co ela-
ion is obse ed be ween all ma ke - o-book-based
Table 8: Co ela ion coe icien s be ween a ious u u e g ow h measu es o he AIM companies
gTAS1 gSA1 gEQ1
gSA1 0.564***
gEQ1 0.753*** 0.414***
gEPS1 0.212*** 0.243*** 0.178***
gTAS3 gSA3 gEQ3
gSA3 0.623***
gEQ3 0.746*** 0.500***
gEPS3 0.237*** 0.228*** 0.177***
gTAS5 gSA5 gEQ5
gSA5 0.604***
gEQ5 0.746*** 0.465***
gEPS5 0.372*** 0.359*** 0.258***
gTAS8 gSA8 gEQ8
gSA8 0.666***
Monika Bolek, Aga a Gniadkowska-Szymańska, Pio Pie aszewski
Un eiling g ow h di e gence on LSE: FTSE100 s. AIM lis ed companies Financial In e ne Qua e ly 2025, ol. 21 / no. 1
Sample Cons . ROE-1 ΔEPS0 ΔTA0 lnMV0 GO0 R2 % Adj. R2 % F-s a . Wald
Explained a iable: One-yea EPS g ow h
TQ1 1311 0.077*** -0.0001 0.016 -6e-05 -0.018*** 0.0180*** 5.2 4.9 14.400*** 2.02***
TQ2 1328 0.068*** 8e-05 0.012 -3e-05 -0.016*** 0.0150*** 3.0 2.7 8.240*** 2.14***
P/E 1216 0.082*** 0.0002 -0.066 0.0030 -0.015*** 0.0005*** 2.3 1.9 5.800*** 2.60***
MV/BV 1322 0.088*** -0.0002* 0.020 -7e-05 -0.019*** 0.0110*** 5.6 5.2 15.500*** 1.98***
D/P 950 0.133*** 0.0001 -3.395** 0.0100** -0.018*** -84.2400*** 3.3 2.8 6.490*** 2.48***
KBM 1368 0.099*** -3e-05 0.007 -3e-05 -0.018** 0.0530*** 3.7 3.3 10.400** 2.14***
EVF 1311 0.096*** -0.0002 0.016 -6e-05 -0.019*** 0.0760*** 4.4 4.0 11.900*** 2.13***
EVE 1321 0.104*** -0.0002* 0.017 -6e-05 -0.018*** 0.0410*** 3.4 3.0 9.240*** 2.07***
Explained a iable: Th ee-yea EPS g ow h
TQ1 1172 0.336*** -0.0020*** 1.095*** -0.0030*** -0.073*** 0.0540*** 12.2 11.8 32.400*** 4.09***
TQ2 1190 0.303*** -0.0020*** 1.025*** -0.0030*** -0.071*** 0.0720*** 12.4 12.0 33.500*** 3.72***
P/E 1086 0.314*** 0.0005 -0.001 -0.0040 -0.061*** 0.0020*** 5.8 5.4 13.300*** 4.34***
MV/BV 1181 0.386*** -0.0020*** 1.041*** -0.0030*** -0.081*** 0.0350*** 14.0 13.7 38.340*** 4.19***
D/P 841 0.509*** 0.0003 3.582 -0.0100 -0.081*** -192.9000*** 7.3 6.7 13.170*** 4.57***
KBM 1220 0.432** -0.0020 1.017 -0.0030*** -0.079*** 0.1790** 12.2 11.9 33.900*** 4.01***
EVF 1172 0.407*** -0.0020*** 1.058*** -0.0030*** -0.082*** 0.2750*** 13.8 13.5 37.400*** 4.42***
EVE 1175 0.456*** 0.0020*** 0.990*** -0.0030*** -0.085*** 0.1570*** 13.2 12.8 35.400*** 4.32***
Va iable explained: Fi e-yea EPS g ow h
TQ1 1028 0.668*** -0.0020*** 0.025 -0.0002 -0.166*** 0.1310*** 15.0 14.6 36.100*** 4.65***
TQ2 1045 0.504*** -0.0020*** 0.120 -0.0004 -0.144*** 0.1600*** 16.4 16.0 40.700*** 4.77***
P/E 960 0.567*** 0.0020*** 0.028 -0.0020 -0.118*** 0.0030*** 7.5 7.1 15.600*** 5.67***
MV/BV 1034 0.718*** -0.0030*** 0.007 -0.0001 -0.158*** 0.0650*** 13.6 13.2 32.300*** 5.00***
D/P 741 0.872*** 0.0007 18.090** -0.0530** -0.141*** -404.5000*** 10.3 9.7 16.900*** 5.06***
KBM 1067 0.831*** -0.0020*** -0.016 -8e-05 -0.166*** 0.3810*** 12.7 12.3 30.800*** 5.39***
EVF 1028 0.833*** -0.0020*** 0.004 -0.0001 -0.179*** 0.5330*** 14.7 14.2 35.100*** 4.91***
EVE 1026 0.896*** -0.0020*** -0.070 6e-05 -0.177*** 0.2800*** 12.8 12.4 29.900*** 5.20***
Explained a iable: Ten-yea EPS g ow h
TQ1 753 1.356*** -0.0002 2.249 -0.0070 -0.373*** 0.3070*** 16.0 15.4 28.400*** 5.66***
TQ2 766 1.339*** -0.0020 2.115 -0.0060 -0.407*** 0.4170*** 19.3 18.8 36.300*** 7.13***
P/E 699 1.050*** 0.0040** 2.510 -0.0600 -0.214*** 0.0060*** 4.8 4.1 7.025*** 6.86***
MV/BV 759 1.576*** -0.0030** 1.389 -0.0040 -0.382*** 0.1620*** 17.2 16.6 31.200*** 5.99***
D/P 524 1.957*** 0.0010 -50.150*** 0.1460*** -0.324*** -978.3000*** 11.4 10.5 13.270*** 6.66***
KBM 782 1.972*** -0.0020 1.802 -0.0005 -0.425*** 0.9520*** 14.0 13.4 25.180*** 7.10***
EVF 753 1.817*** -0.0010 1.888 -0.0060 -0.414*** 1.1550*** 14.4 13.8 25.070*** 6.31***
EVE 752 2.161*** -0.0030* 1.392 -0.0040 -0.455*** 0.6190*** 13.9 13.3 24.100*** 6.92***
Appendinx 2: De e minan s o u u e ea nings g ow h (AIM) – Pooled OLS
No e: */**/*** The coe icien s o F-s a is ic a e signi ican a he 10% / 5% / 1% le el
Sou ce: Au ho ’s own wo k.
