Proposal description

1. Proposal Topic:
Industry Concentration and Cross section of Stock Return:
Evidence From Pakistan
Muhammad Jamil
Supervisor : Dr.S.M Younus Jafri

2. Introduction
• Pakistan Stock Exchange (PSX) has 36 sectors
• Out of these 36 sectors that constitute PSX index 28 are non
financial sectors
• Graph of these non financial sectors‘ Sales, Fixed asset(at
costs) and Market Capitalization-as percentage of Total sectors
sales, fixed assets and market capitalization- is shown on next
slide .

3. Largest Five sectors Sales Vs All other sectors
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
All other Sectors 0.45900.43300.42000.43200.43700.46300.43000.39800.39900.39300.37900.39900.38700.36200.37300.35400.4060
Largest Five sectors 0.54100.56700.58000.56800.56300.53700.57000.60200.60100.60700.62100.60100.61300.63800.62700.64600.5940
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Industry
Concentration

4. Largest Five sectors Fixed costs Vs All other Sectors
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
All other sectors 0.36 0.348 0.362 0.371 0.383 0.42 0.419 0.427 0.413 0.417 0.455 0.43 0.433 0.42 0.425 0.427 0.436
Largest five Sectors 0.64 0.652 0.638 0.629 0.617 0.58 0.581 0.573 0.587 0.583 0.545 0.57 0.567 0.58 0.575 0.573 0.564
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Industry
Concentration

5. Largest Five Sectors Market Capitalization Vs All other
sectors
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
%
Mkt
Cap
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Remaining Sectors firms 0.26490.26580.31590.34810.38150.33950.29780.30980.32920.35410.35420.31390.26400.26970.31220.38260.3998
Larghest 5 Sectors 0.73510.73420.68410.65190.61850.66050.70220.69020.67080.64590.64580.68610.73600.73030.68780.61740.6002

6. Industry Concentration
• This phenomenon where a few sectors dominate market in
term of some economic activity –industry concentration.
• Its an indirect measure of product market competition
• Also shows diversification of economy
• Industry concentration – a core topic of industrial organization
(IO)literature – and financial market link through (S/C/P) or
innovation
• In IO literature high concentration industry( Low competition)
earns higher than normal return . Known to has higher barrier
–to-entry that results into higher profitability and cash flow is
secure.

7. Industry Concentration and Stock Return
As these firms can pass-on costs shocks to end consumers.
On the other extreme firms in Low concentration sector(High
Competition) cash flow is easily taken away by existing firms
or by new entrant thus making it more volatile.
However, “creative destruction” or innovation usually take place
in competitive sector-
As these cash flows are generated in product market- where firms
may face different level of competition- and gets price in
financial marker
Or may be its behavioral bias

8. Problem Statement
• How do investors price these cash flow (Equity Prices) given
that firms operate in different competitive environment?
• Or does investor consider product market competition as a risk
factor while allocating capital among risky investments?
• The study is helpful in determining equity return which is an
essential ingredient in cost of capital and evaluating
performance of money manager.
• Its policy implication- easing industry barrier/more
competition.

9. Research Questions
• Does industry concentration premium exist in
Pakistan Stock Exchange?
• Can stock return be predicted using industry
concentration as risk factor?
• Is industry concentration premium remaining
significant after adding other known risk factors (Size
and Book/market)?

10. Literature Review
Industrial organization literature starting from Bain (1952) –
industry concentration and profitability
In finance Robinson(2006) claims that industry concentration has
negative relation with equity return- his propose channel is
idea of “ creative destruction” which happens in competitive
sectors- hence growth rate is priced
Hashem and Sue(2015) substantiated their findings in UK market
Gallagher (2015) finds results contrary-in Australian Market- to
previous studies conducted in USA and UK and claim that
difference is due to different local factors, market and political
conditions.
Edward et al(2018) using porter’s five factor model supported
Gallagher claims

11. (
Literature review Cont’d(Pakistan Context)
• Tests of CAPM conducted at Pakistan Stock Exchange do not
validate the CAPM( Khilji and Nabi (1996),
Uppal(1998),Ahmed and Zaman(2000),Attahullah(2002),
Iqbal and Haider(2005), Iqbal and Brooks(2007,2010),Javid
and Ahmed(2012), Khan(2013), Urooj(2018))
• Other factors apart from Market factor of CAPM added-
Multiple factor model(s)
• Mirza and Shabbir (2005) point out issue of Market Portfolio
domination by few sectors.
• Iqbal(2012) highlight that Pakistan economy –one of most
concentrated in region

12. Conceptual framework
High barrier to
entry /Low
barrier to entry
Less risky cash
flow/More risky
cash flow
Higher stock
Price/Lower
Stock price
Lower
return/Higher
return

13. Hypothesis
• H1: Level of industry concentration is negatively related to
stock returns.
• H2: There is a positive relationship between Book to market
equity and stock returns.
• H3: There is a negative relation between size of a firm and
stock returns

14. Methodology
 27 sectors are considered for current study.
 Data is from 1999 to 2018.
 Number of firms in sectors vary from year to year--- on
average there are 250 firms –after applying two filters
 Stock return is calculated as simple Percentage change return
◦ Rit= (Pt-Pt-1)/Pt
◦ To calculate Excess return monthly T-Bill return is
subtracted from above return

15. Sample size each year
# of firms
Year
245
1999
247
2000
248
2001
250
2002
254
2003
266
2004
265
2005
271
2006
275
2007
277
2008
282
2009
290
2010
291
2011
291
2012
296
2013
298
2014
306
2015

16. Industry Concentration Measure
• For Industry Concentration measure-Herfindahl –Hirschman
Index is used:
Where J is industry and i is any firm in industry
The maximum value of this index is 1( Just one firm in industry)
and minimum value is close to 0( larges number of firms –no
one firm dominates)

17. Herfindahl Index-sales based(1999)
Auto Assembler
sector(Sales)
Sales as % of
sector sales
Al-Ghazi Tractors Limited 4266.5 0.12380
Atlas Honda Ltd 3921.3 0.11378
Dewan Farooque Motors 0.00000
Ghani Automobile Ind 0.00000
Ghandhara Industries Limited 225.0 0.00653
Ghandhara Nissan Ltd 303.4 0.00880
Honda Atlas Cars Ltd 3009.0 0.08731
Hino Pak Motors Ltd 817.9 0.02373
Indus Motor Company Limited 7148.4 0.20742
Millat Tractors Limited 5407.7 0.15691
Pak Suzuki Motors Co Ltd 9115.8 0.26451
Sazgar Engineering Works Ltd 248.0 0.00720
Total Sector Sales 34463.0
Industry Concentration
Measure 0.1742

18. Industry Concentration- sales based year 1999
Sector
No
Industry Concentration(Sales) Ascending
order
sorted Ind
Contr
sorted
sector
No
Quintiles
1 Auto Assembler 0.0398 17 0.16721
2 Auto Parts Sector 0.0582 23 0.2453
3 Cement Sector 0.0824 3 0.3730
4 Cables and Electric Goods 0.0933 24 0.4835
5 Chemical sector 0.1586 16 0.9839
6 Engineering 0.16545 9
7 Fertilizer 0.1742 1
8 Food & Personal care products 0.2090 2
9 Glass $ Ceramic 0.2188 10
10 Miscellaneous 0.2410 6
11 Power Gen and Distribution 0.2446 25
12 Refinery 0.2462 19
13 Oil& Gas Exploration 0.2540 15
14 Oil& Gas Marketing 0.2627 27
15 Paper & Board 0.3245 4
16 Pharmaceutical 0.3688 14
17 Sugar 0.3758 12
18 Leather $ Tannery 0.4101 18
19 Synthetic & Rayon 0.4136 11
20 jute 0.4210 7
21 Transport 0.4274 8
22 Tech & Telecomm 0.4975 26
23 Textile Spinning 0.5321 5
24 Textile Comp 0.6116 13
25 Textile Weaving 0.7893 20
26 Tobacco 0.8286 21
27 Vanaspati & Allied Indus 0.9839 22

19. Sectors in each Quintile Porfolios
1st quintile portfolio(Most competitive) contains following sectors 17, 03, 23, 24, 06, 09
2nd quintile portfolio contains following sectors 1,2,10,06,25
3rd quintile portfolio contains following sectors 19,15,27,04,14
4th quintile portfolio contains following sectors 12,18,11,07,08,
5th quintile portfolio(Least Competitive) contains following sectors 26,05,13,20,21,22

20. Portfolio formation
• At end of each calendar year-starting from 1999- industries are
sorted into five quintile portfolios are formed , where Ist
quintile is (most competitive) and 5th quintile is Least
competitive
• And then for next year – return of each quintile portfolio is
calculated(both equal weighted and value weighted that in turn
is either firm value weighted or sector value weighted) and
differential return of quintile 5 and 1 is calculated.
– Differential Return=Quintile 5 return- Quintile 1 return

21. Result based on Sales Concentration-firm value weighted
return-2000
Diff(5th-1st
)
5th
Quintile
4th
Quintile
3rd
Quintile
2nd
Quintile
Ist
Quintile
Year
-0.003
0.004
-0.002
0.000
0.001
0.006
2000
-0.012
-0.014
-0.007
-0.001
-0.002
-0.002
2001
0.024
0.028
0.011
0.009
0.001
0.005
2002
0.014
0.021
0.007
0.010
0.002
0.007
2003
0.009
0.012
0.003
0.003
0.001
0.003
2004

22. Other Industry Characteristics
• Industries in different competitive environment must exhibit other
differential characteristics-in term of cost structure, capital
structure, profitability , cash holdings , short term investment and
R&D expenses and advertisement expenses – these characteristics
are calculated at firm level and average at portfolio level
• Analyzed using Fama-Macbeth regression

23. Average Quintile Portfolio industry Characteristics

24. B/M and size factor
• How does industry concentration premium behave in presence
of these two known factor
• These factor are calculated as follows:
• At end of each calendar year sort all firm using market
capitalization into 3 group(20th and 80th quintiles) then within
each quintile firms are again sorted in low and high book to
market ratio and following portfolios are calculated each year.

25. Size and B/M calculation
H P1
Small (S) M P2
L P3
H P4
Medium (M) M P5
L P6
H P7
M P8
Big (B) L P9

26. Size and B/M portfolio formation
SMB= 1/3[(P1-P7) + (P2-P8) + (P3-P9)]
HML=1/3[(P1-P3) + (P4-P6) + (P7-P9)]
So the proposed Model is
Return =α +β1(Rm)+ β2(SMB)+β3(HML) +β4(IC ) + ε