Market information and stock returns the nepalese evidence

Master of Philosophy in Management 6th Batch
Presentation on
Market Information and Stock Returns: The
Nepalese Evidence
By
Sudarshan Kadariya
Tribhuvan University
June 18, 2012
06/18/2012
Sudarshan Kadariya, Contact:
su.kadariya@gmail.com
1

Presentation Plan
 Background & Motivation
 Research Gap, Research Questions & Objectives
 Research Methodology
 Major Findings
 Conclusions
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Background & Motivation
 From the past decades, the financial markets have been
suffering from the unforeseen and sudden economic
turbulences that have been directly or indirectly influences
the stock returns.
 To identify these market influences, the separate
discipline – the investment management was formed and
developed chronologically through speculative,
professionalism, and scientific phase (Francis, 1986).
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 Some studies became popular in firm specific variables
which was focused towards predicting stock returns. For
instance,
Stattman (1980), Chan, et.al (1991), Brav, et.al (2000), Daniel and
Titman (2006) among others documented the book-to-market
equity effects
Earnings-to-price effects by Basu (1977), Jafee, et.al (1989), Fama
and French (1995) and La Porta (1996) among others
Banz (1981), Vassalou and Xing (2004), and Fama and French
(2008) depicted the size effects, similarly,
Cash flows effects by Berk, et.al (1999) and Vuolteenaho (2002)
among others
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But, in the later period, the focus has been shifted
towards the behavioral aspects. For instance,
Einhorn, et al. (1978) documented that people have great
confidence in their fallible judgment.
Einhorn (1980) further conformed the overconfidence in judgment
Similarly, Ikenberry, et.al (1995), Odean (1999), Kaniel, et.al (2008),
Foucault, et.al (2011), and Doskeland and Hvide (2011), among
others, proved that the investor behavior is the major aspect for
stock returns movements.
In sum, the recent focus has been shifted towards the
intangibles rather than the fundamental effects on stock
returns.
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Discussion (i) – Return Decomposition
TotalReturn
Figure 1: Graphical presentation shows the breakdown of a firm’s past return into tangible and
intangible returns suggested by Daniel and Titman (2006)
Log(Pt-5)
t-5 t
Log (Pt)
Log (Pˆ)
Log (Pt-5)
IntangibleReturnTangibleReturn
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Tangible Information Intangible Information
Market Information
Total Stock Returns
Tangible Returns Intangible Returns
LEADS
Figure 2: Conceptual Framework of market information and stock returns (the broader
perspective)
Discussion (ii) – Market Info.&Returns (BP)
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Figure 3: Conceptual Frameworks of Market Information and Stock Returns (the specific
perspective)
Tangible /
Quantitative
Information
Intangible /
Qualitative
Information
Market Information
Tangible
Returns
Intangible
Returns
Total Stock Returns
LEADS
B/M
Equity
Investor
Behavior
Market
Behavior Market
Reaction
Media
Effects
Psycholog
y
Sentiments Over-
confidence
News
Effects
Values
Size Stock
returns
Earnings
Cash Flow
Discussion (iii) – Market Info.&Returns (SP)
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Figure 6: Good News
Regular Information Flow
Risk
Return
Rf
Figure 4:
Normal/Informational
Irregular Information Flow
Risk
Return
Rf
Figure 5: Bad News
Bad News Events
Risk
Return
Rf
Good News Events
Discussion (iv) – New Events & Returns
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Research Gap, Research Questions
& Objectives
Financial economists and investors have been spending
considerable time searching for best investment
strategies that could help to yield sustainably above an
average market returns but the reliable one is yet to be
found.
Chan (2003), Vassalou and Xing (2004), Daniel and Titman (2006),
Foucault, et.al (2011), Sun and Wei (2011), Doskeland and Hvide
(2011), among others focused on firm specific accounting
variables.
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 Merton (1987), Mitchell and Mulherin (1994), Maheu and
McCurdy (2004), Boyd, et.al (2005), Zhang (2006), Tetlock (2007),
Fang and Peress (2009), Hirshleifer, et.al (2009), Engelberg and
Parsons (2011), among others focused on the intangibles
(news and media, political party led government, lag variables, past
performance of the firm, stock market behavior and investors’
sentiments, etc.)
Moreover, Van Rooij, et al. (2007) documented a significant
association between financial literacy and investment
decisions, Bogan (2006) suggested an association between
stockholding and computer and Internet use.
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On the other hands, Lusardi and Mitchell (2006)
revealed the negative association between planning
for retirement and financial education.
These evidences also suggest that the additional
factors – investor awareness, financial education and
the financial literacy also work as market reactors.
Based on these review, the study found considerable
research gap on the area of stock returns and the
market information. Thus, the study is initiated.
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Research Questions: (11 RQs)
What is the relationship between past tangible information
and future returns?
Is there relationship between intangible and future returns?
Is there association between the fundamentals to price
scaled variables with the future returns?
Do the stock prices overreact to the past performance?
What are the most predictable fundamental accounting
growth measures in stock exchange?
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How long the past fundamentals help to predict the future
returns?
What are the news effects on stock returns? What is the
bad news effect? What is the good news effect? and what is
the informational news effect?
Is there political leadership influence on Nepalese stock
market? What are the effects of NC led government? CPN-
UML led government? , UCPN(M) led government?, and
other parties government?
What are the opinions of Nepalese stock investors on
investment alternatives, decision making, market prices and
stock returns?
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What are the factors affecting investment decision making in
equity investment?, and,
What are the opinions of stock investors on various issues
like:
stock returns,
fundamental measures,
mutual funds,
central depository system,
portfolio management services,
credit rating agencies,
sources of investment funds,
rate of interest,
the trading behavior on different conditions, and
on the various emerging issues in stock market
performance?
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Objectives:
To evaluate the relationship between stock returns and
fundamental measures.
To determine the news effects – bad news, good news and
informational news, on stock returns.
To examine the political leadership effects on stock returns.
To determine the factors affecting stock investment in
Nepalese stock market, and
To examine investor opinions on various issues: investor
education and personality type, preferences, trading behavior
and practices, sources of funds for investment, risk perception,
level of investor awareness, investor reactions and judgments on
previous findings of the similar studies.06/18/2012
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Methodology
Research Design
Descriptive, and
Causal-comparative
Nature of Database
Secondary data, and
Primary data
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Firm
specific
variables
Market
returns
Financial
news
Political
leadership
Secondary
data
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Sources of secondary database (four types)
i. For firm specific variables: EPS, MPS, cash dividend, size, BPS, sales
volume, and cash-flow suggested by Daniel and Titman (2006).
 Population: NEPSE listed enterprises
(176 enterprises with 1443 firm years: Both the manufacturing and non-
manufacturing enterprises including delisted securities are employed.)
 Sample: All the listed enterprises (data collection is
based on availability of historical data sources)
(146 enterprises with 826 firm years)
 Data type: Quantitative - annual
 Data sources: SEBON files (hard and soft) along with the
financial disclosure of concern enterprises.
 Data collection: From Mid-July, 1994 to Mid-July, 2010
Note:
The firm year is defined as the difference between the mid-July 2010 and listing date of the enterprise.
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Table 1: Overview of sector-wise observations
SN Sector
Observable Observed Proportion
Percentage
Enterprises Firm Yrs Enterprises Firm Yrs Selection Obs.
A Commercial Banks 23 201 23 179 100.00 89.05 21.67
B Development Bank 40 139 37 125 92.50 89.93 15.13
C Finance Companies 61 486 59 378 96.72 77.78 45.76
D Insurance Companies 19 179 18 87 94.74 48.60 10.53
E Manufacturing firms 18 265 1 9 5.56 3.40 1.09
F
Others (hydro, hotels,
trading, telecom & film)
15 173 8 48 53.33 27.75 5.81
Total 176 1443 146 826 82.95 57.24 100.00
 Total number of observations constitute 57.24 % of total
observable firm year
Even though the highest observable firm year for manufacturing
sector, the observed number constitute the least (9 of 265)
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ii. For market returns (suggested by Daniel and Titman, 2006)
Data types: Quantitative - annual,
monthly and daily data series
Data collection: From Mid-July, 1994 to Mid-
July, 2010
Data sources: NEPSE files (hard and soft)
Notes:
• The annual average index is calculated by averaging the index of July 16th of
previous year and July 15th of subsequent year.
• The annual period is describes the period covering July 16th to July 15th or, the
Nepali calendar year.
i & ii - Data collected in August and September 201106/18/2012
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iii. For daily financial news: Similarly, for news effects – bad news,
good news and informational news suggested by Domer (2005), Lee, et.al
(1994) and Tetlock (2007).
Data types: Qualitative and Quantitative –
news headlines, contents and
news heading counts – annual,
monthly and daily basis
(Total 1683 news headings with 536 bad news, 734 good news, and 413
informational news)
Data collection: From Mid-July, 1994 to Mid-
July, 2010 (6029 days)
Data sources: Kantipur daily
(library - Kantipur Pub. and TU Central library)
Note: “Kantipur” is selected because its publication was started (Thursday, February 18, 1993) prior to
the establishment of NEPSE (Thursday, January 13, 1994).
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Appendix C
SN Date News Count News
१ Thursday, January 13, 1994 0 नेप्से शुरु भएको दिन
२ Friday, January 14, 1994 1 नेपालमा स्टक एक्सचेन्ज
७ Wednesday, January 19, 1994 1 सेयर बजारको भबबष्य उज्जल
११ Sunday, January 23, 1994 1 नेकोन अयर शेयर ननष्कासन उत्साहजनक सुरुाा
१२ Monday, January 24, 1994 1 शेयर बजारमा न ब्र ा : नया प्रणाली सक्रीय
. . . .
. . . .
३००० Sunday, March 31, 2002 1 शेयर कारोबारमा अस्स्िर ा कायमै, बेच्नेको चापले
मुल्यमा ह्रास
३००७ Sunday, April 07, 2002 1 शेयर बबक्रीको चाप घटेपनि मूल्य बृद्दि
३००८ Monday, April 08, 2002 1 बंगलािेश बैंकले लाभांश दिने
३०१४ Sunday, April 14, 2002 1 शेयर बबक्रीको चाप घटेपनि मूल्य बृद्दि जारी
३०२१ Sunday, April 21, 2002 1 शेयर कारोबारमा सुधारको क्रम जारी
. . . .
. . . .
६०१३ Wednesday, June 30, 2010 1 नेप्सेमा गगरााट कायमै
६०१४ Thursday, July 01, 2010 1 नेप्से सामान्य बढ्यो
६०१५ Friday, July 02, 2010 1 नेप्सेमा १५ अंकको बृद्दि
६०१८ Monday, July 05, 2010 1 टेललकमको शेयरले घट्यो नेप्से
Total News Headings 1683
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Appendix D
SN Bad News SN Good News SN Information Only
1 Ignorance of stock exchange
rules and regulation by the
listed companies
1 Categorization of listed
companies - 'A', 'B'..
1 General information (e.g.
privatization process,
appointments, stock broker
licencing, resignation, etc)
2 Delisting information 2 Cash dividends 2 Analytical coverage
3 Decrease in NEPSE 3 Increase in NEPSE
index
3 Share allotment
4 Increase in cost of issuance 4 Listing information 4 IPO information
5 Withdrawal of foreign
investment/investor
5 Disclosure of sensitive
index as new index
5 SEBON & NEPSE rules &
regulation disclosure
.
. . . . .
.
. . . . .
37 Software problem in NEPSE 22 Stock market
exhibition
11 AGM information
38 Delay in share allotment 23 Ceasefire 12 OTC market information
39 Protest of stock investors 24 Positive circuit breaker 13 NRB/MOF regulations (Margin,
capital gain tax, etc)
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iv. For political leadership: political leadership effect – dummies
of political leadership suggested by Worthington (2006).
Data types: Qualitative – list of PMs, tenure
and their political parties
Data collection: From Mid-July, 1994 to Mid-July,
2010
Data sources: News collections and historical
records
Note:
The King’s regime is also assumed as a political leadership and placed into other parties’ categories.
iii & iv - Data collected in October and November 201106/18/2012
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Appendix E
S.N. Name Term start Term end Political Party
1 Girija Prasad Koirala Sunday, May 26, 1991 Wednesday, November 30,
1994
Nepali Congress
2 Man Mohan Adhikari Wednesday, November 30,
1994
Tuesday, September 12,
1995
Communist Party of
Nepal (Unified Marxist–
Leninist)
3 Sher Bahadur Deuba Tuesday, September 12,
1995
Wednesday, March 12, 1997 Nepali Congress
4 Lokendra Bahadur
Chand
Wednesday, March 12, 1997 Tuesday, October 07, 1997 Rastriya Prajatantra Party
(Chand)
5 Surya Bahadur Thapa Tuesday, October 07, 1997 Wednesday, April 15, 1998 Rastriya Prajatantra Party
. . . . .
. . . . .
14 Direct rule by King
Gyanendra Bir Bikram
Shah Dev
Tuesday, February 01, 2005 Tuesday, April 25, 2006 –
15 Girija Prasad Koirala Tuesday, April 25, 2006 Wednesday, May 28, 2008 Nepali Congress
16 Girija Prasad Koirala Wednesday, May 28, 2008 Monday, August 18, 2008 Nepali Congress
17 Pushpa Kamal Dahal
(alias Prachanda)
Monday, August 18, 2008 Monday, May 25, 2009 Unified Communist Party
of Nepal (Maoist)
18 Madhav Kumar Nepal Monday, May 25, 2009 Sunday, February 06, 2011 Communist Party of
Nepal (Unified Marxist–
Leninist)
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Sources of primary data (Survey)
A survey was started on 1st December and concluded on
31st December 2011.
Common stock investors were selected from different
brokers’ floor in Kathmandu valley.
The selection of the broker’s floor was based on the
random sampling procedure. Out of 39 brokerage firms in
Kathmandu valley, 10 were selected.
With due consideration of the behavioral nature of the
study, the time to approach to the stock investors is
strictly managed right at 12:00 noon when stock market
open for trading.06/18/2012
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The sample size is considered 364 stock investors
suggested by Cochran (1977) because of the undefined
population of Nepalese stock investors.
The structured questionnaires (both in Nepali and
English medium) with 36 questions (7 demographic and
29 others) were distributed.
The printed questionnaires were provided to the
respondents at the brokers’ floor.
Total 164 filled-up questionnaires were collected thus
the response rate is 45.06 percent.
Survey was conducted in December 2011
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Tools for data analysis
Tools for secondary data analysis:
Descriptive statistics
Correlation matrix analysis,
Regression analysis,
Kolmogorov-Smirnov test,
Stock returns decomposition procedure
The test of significance of econometric models using t-tests
and f-tests.
Detection and correction of autocorrelation, multicolinearity
and heterocedasticity are the major tools for analysis.
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Table 2: Data cleansing
SN OLS Assumptions Test
1 Normal distribution of error terms/dependent
variable
K-S
2 Dependent variable is a linear function of
independent variables and error terms
Plot
3 Independent variables are unrelated to error terms Correlation
4 Homoscedasticity i.e. equal variance of dependent
variables
Plot
5 Autocorrelation i.e. error terms Run
6 Multicollinearity of independent variables VIF
7 Outliers Plot
Note:
Regression analysis is "robust" in that it will typically provide estimates that are unbiased and efficient
even when one or more of the assumptions is not completely met.
06/18/2012
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Tools for primary analysis
Descriptive statistics of demographic variables
Frequency distribution
 Simple tabular presentation
Cross table analysis
Mean score analysis for Likert items
Test of association – chi-square test, and
Factor analysis which includes:
– Cronbach’s Alfa test
– Correlation matrix analysis
– Anti-image correlation matrix – the measure of sampling adequacy (MSA),
– Kaiser-Meyer-Olkin (KMO) and Bartlett's Test,
– The initial and rotated solution for factor analysis, and
– The scree plot
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Profile Analysis (Figure 7-18)
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Majority of the selected variables exhibit the downward movement.
Only 3 of 12 variables indicates the upward movements i.e. market
equity, sales to price ratio and the sales revenue.06/18/2012
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Table 3: Descriptive Statistics
Variables Unit N Mean Median Minimum Maximum
Quartile Std.
Dev.Q1 Q3
Earnings per share Rs 826 29.15 21.18 -444.08 626.00 11.02 36.69 48.87
Market price per share Rs 826 545.07 295.00 44.00 6830.00 174.75 626.75 716.68
Book value per share Rs 826 160.29 138.21 -364.00 1005.86 114.36 183.35 97.77
Cash dividend Percent 823 11.78 1.05 0.00 560.00 0.00 10.53 35.23
Market equity Million (Rs) 826 287.78 92.07 8.00 15000.00 48.00 320.00 815.04
Sales revenue Million (Rs) 825 3200.67 598.07 0.01 50094.73 269.82 1776.33 6776.75
Cash flow Million (Rs) 826 31.38 1.53 -9523.19 9327.70 -0.36 18.59 492.67
Book to market ratio Times 826 0.56 0.47 -1.44 4.91 0.23 0.76 0.53
Earnings to price ratio Times 826 0.07 0.06 -3.52 1.60 0.03 0.11 0.21
Cash flow to price
ratio in '000' 826 66.21 5.35 -17968.28 12777.67 -1.68 48.46 866.73
Sales to price ratio in Million 825 5.59 2.08 0.00 80.21 0.91 5.65 9.54
Stock returns Percent 822 5.59 2.08 0.00 80.21 0.91 5.65 9.54
 Average MPPS is more than 3 times of BVPS where the average stock returns is
5.59%
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Table 4: Correlation Matrix
LogMPPS LogBVPS LogSales LogCashFlow LogME LogRt LogCSI
LogEPS 0.41 0.57 0.22 0.10 -0.04 0.09 -0.08
(0.00) (0.00) (0.00) (0.02) (0.28) (0.09) (0.10)
LogMPPS 0.40 0.31 0.42 0.40 0.30 0.35
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
LogBVPS 0.07 0.14 -0.05 0.02 -0.07
(0.05) (0.00) (0.16) (0.64) (0.18)
LogSales 0.21 0.39 0.15 0.26
(0.00) (0.00) (0.00) (0.00)
LogCashFlow 0.61 0.08 0.30
(0.00) (0.18) (0.00)
LogME 0.18 0.58
(0.00) (0.00)
LogRt 0.06
(0.35)
 9 sets of variables have no significant correlation and the remaining
19 pairs have significant positive correlation at 95 percent confidence
level.06/18/2012
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α b1 b2 b3 Model Sig R-square
K-S Test
of residual
N
Panel A: Log (Bit/Mit) = α + b1 BMi0 + b2△Bi + b3△Mi + ut
bi -0.640 0.608 0.002 -0.001 0.000 0.95 0.05 437
p (0.000) (0.000) (0.000) (0.000)
Panel B: Log (Bit/Mit) = α + b1 LogBMi0 + b2Log△Bi + b3Log△Mi + ut
bi 0.081 0.883 0.120 -0.186 0.000 0.98 0.20 50
p (0.000) (0.000) (0.000) (0.000)
Priori (+) (+) (-)
 The priori for b1, b2 and b3 are positive, positive and negative resp.,
which is also proved by the database/evidence.
Table 5
Regression analysis for book to market decomposition
Major Findings (14 basic models with 148 estimated models)
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Table 6: B/M Decomposition: An Extension
K-S Test of DV
(p)
N
Panel B: r(t-i,t) = α + b1 log [Bt-i/Pt-i] + b2 [Bt/Bt-i] + b3 [Pt/Pt-i] + ut
(i=2)
bi -1.044 -0.175 0.003 1.068 0.000 0.882 0.146 401
p (0.000) (0.000) (0.739) (0.000)
(i=3)
bi -0.971 -0.230 -0.007 1.012 0.000 0.870 0.200 287
p (0.000) (0.000) (0.605) (0.000)
(i=4)
bi -0.959 -0.030 0.004 0.995 0.000 0.988 0.056 169
p (0.000) (0.157) (0.445) (0.000)
(i=5)
bi -0.955 -0.019 -0.001 0.998 0.000 0.971 0.087 89
p (0.000) (0.534) (0.829) (0.000)
Panel C: r(t-i,t) = α + b1 log [Bt-i/Pt-i] + b2 log [Bt/Bt-i] + b3 log [Pt/Pt-i] + ut
(i=2)
bi 0.109 -0.266 -0.094 2.006 0.000 0.822 0.161 403
p (0.000) (0.000) (0.145) (0.000)
(i=3)
bi 0.141 -0.281 -0.136 2.299 0.000 0.827 0.064 297
p (0.000) (0.000) (0.056) (0.000)
(i=4)
bi 0.033 -0.166 -0.076 3.106 0.000 0.964 0.074 124
p (0.003) (0.000) (0.024) (0.000)
(i=5)
bi 0.036 -0.038 -0.060 3.166 0.000 0.965 0.070 95
p (0.014) (0.298) (0.093) (0.000)
 Firm level stock returns is negatively affected by the lagged BM ratio and positively by
market price to lagged market price ratio but, for book to lagged book values it is
inconclusive.
 There is a significant lagged B/M effect for stock returns up to three years, while
transforming independent variables it extend up to 4 years06/18/2012
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Table 7: S/P Decomposition
Α b1 b2 b3
Model
Sig R-square
K-S Test of
Res/DV (p) N
Panel B: r(t-i,t) = α + b1 log [St-i/Pt-i] + b2 [St/St-i] + b3 [Pt/Pt-i] + ut
(i=2)
bi -0.894 -0.002 0.000 0.985 0.000 0.867 0.200 380
p (0.000) (0.718) (0.428) (0.000)
(i=3)
bi -0.801 -0.006 0.000 0.942 0.000 0.876 0.064 296
p (0.000) (0.411) (0.209) (0.000)
(i=4)
bi -0.803 0.005 0.000 0.923 0.000 0.848 0.061 210
p (0.000) (0.615) (0.283) (0.000)
(i=5)
bi -0.784 -0.006 0.000 0.964 0.000 0.885 0.053 155
p (0.000) (0.572) (0.171) (0.000)
Panel C: r(t-i,t) = α + b1 log [St-i/Pt-i] + b2 log [St/St-i] + b3 log [Pt/Pt-i] + ut
(i=2)
bi 0.001 0.000 0.020 2.533 0.000 0.998 0.200 57
p (0.642) (0.634) (0.000) (0.000)
(i=3)
bi 0.009 -0.001 -0.003 2.663 0.000 0.997 0.200 65
p (0.058) (0.356) (0.080) (0.000)
(i=4)
bi 0.022 0.000 -0.005 2.584 0.000 0.992 0.200 47
p (0.031) (0.810) (0.172) (0.000)
(i=5)
bi 0.183 -0.026 -0.050 3.620 0.000 0.977 0.200 113
p (0.000) (0.000) (0.000) (0.000)
 Consistent positive relation between firm returns and price to lagged price ratio whereas
inconclusive and least effects of lagged sales to price and sales to lagged sales ratio for stock
returns.
06/18/2012
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Table 8: C/P Decomposition
K-S Test of
Res/DV (p)
N
Panel B: r(t-i,t) = α + b1 log [Ct-i/Pt-i] + b2 [Ct/Ct-i] + b3 [Pt/Pt-i] + ut
(i=2)
bi -0.944 0.012 0.000 0.953 0.000 0.850 0.059 282
p (0.000) (0.055) (0.736) (0.000)
(i=2)
bi -0.993 0.005 0.000 1.014 0.000 0.985 0.061 247
p (0.000) (0.288) (0.074) (0.000)
(i=3)
bi -0.968 0.020 0.000 0.978 0.000 0.898 0.059 195
p (0.000) (0.146) (0.577) (0.000)
(i=4)
bi -0.998 0.000 0.000 1.001 0.000 0.999 0.089 84
p (0.000) (0.489) (0.000) (0.000)
(i=5)
bi -0.978 0.013 0.000 1.022 0.000 0.918 0.059 90
p (0.000) (0.464) (0.845) (0.000)
Panel C: r(t-i,t) = α + b1 log [Ct-i/Pt-i] + b2 log [Ct/Ct-i] + b3 log [Pt/Pt-i] + ut
(i=1)
bi -0.008 0.002 0.000 1.976 0.000 0.996 0.092 69
p (0.163) (0.077) (0.785) (0.000)
(i=2)
bi -0.123 0.050 0.031 2.885 0.000 0.967 0.085 132
p (0.003) (0.000) (0.001) (0.000)
(i=3)
bi -0.042 0.012 0.001 3.389 0.000 0.976 0.066 71
p (0.398) (0.284) (0.965) (0.000)
(i=4)
bi 0.017 0.009 -0.007 3.505 0.000 0.959 0.199 83
p (0.851) (0.660) (0.677) (0.000)
(i=5)
bi 0.072 -0.025 -0.030 4.349 0.000 0.963 0.093 67
p (0.557) (0.368) (0.246) (0.000)
 Consistent positive effect of price to lagged price ratio for firm returns whereas
inconclusive and least effects of lagged CF to price and CF to lagged CF ratio06/18/2012
39

Table 9: E/P Decomposition
K-S Test of
Res/DV (p)
N
Panel B: r(t-i,t) = α + b1 log [Et-i/Pt-i] + b2 [Et/Et-i] + b3 [Pt/Pt-i] + ut
(i=1)
bi -0.955 0.014 0.001 1.003 0.000 0.986 0.200 255
p (0.000) (0.030) (0.262) (0.000)
(i=2)
bi -0.894 0.032 0.001 0.993 0.000 0.961 0.200 134
p (0.000) (0.033) (0.462) (0.000)
(i=3)
bi -0.887 0.029 0.000 0.985 0.000 0.961 0.099 228
p (0.000) (0.027) (0.357) (0.000)
(i=4)
bi -0.825 -0.014 0.000 0.950 0.000 0.863 0.200 205
p (0.000) (0.701) (0.652) (0.000)
(i=5)
bi -0.829 -0.014 -0.001 0.962 0.000 0.887 0.050 156
p (0.000) (0.754) (0.350) (0.000)
Panel C: r(t-i,t) = α + b1 log [Et-i/Pt-i] + b2 log [Et/Et-i] + b3 log [Pt/Pt-i] + ut
(i=1)
bi 0.006 0.001 -0.004 1.918 0.000 0.994 0.200 180
p (0.025) (0.617) (0.114) (0.000)
(i=2)
bi -0.001 -0.003 -0.008 2.627 0.000 0.997 0.053 65
p (0.765) (0.369) (0.012) (0.000)
(i=3)
bi 0.002 -0.010 0.008 2.693 0.000 0.992 0.092 70
p (0.814) (0.148) (0.256) (0.000)
(i=4)
bi -0.018 -0.027 -0.026 3.655 0.000 0.967 0.200 149
p (0.567) (0.320) (0.234) (0.000)
(i=5)
bi 0.036 0.060 0.098 3.763 0.000 0.974 0.171 107
p (0.360) (0.075) (0.001) (0.000)
 Consistent positive
price to lagged price
effect for stock returns,
and inconclusive effect
of lagged E/P and
earnings to lagged
earnings ratio
 There is a significant
effect of lagged E/P ratio
for stock returns up to
three years
06/18/2012
40

Table 10
Regression analysis of firm returns on price scaled variables
α b1 b2 b3 b4 Model Sig R-square
K-S Test of
Res (p)
N
r(t-i,t) = α + b0 [Bt-i/Pt-i] + b1 [St-i/Pt-i] + b2 [Ct-i/Pt-i] + b3 [Et-i/Pt-i] + ut
(i=1) bi -0.242 0.340 0.000 0.000 0.234 0.000 0.247 0.200 576
p (0.000) (0.000) (0.000) (0.531) (0.000)
(i=2) bi -0.269 0.354 0.000 0.000 0.262 0.000 0.289 0.067 502
p (0.000) (0.000) (0.000) (0.067) (0.000)
(i=3) bi -0.173 0.255 0.000 0.000 -0.019 0.000 0.114 0.200 319
p (0.000) (0.000) (0.000) (0.156) (0.887)
(i=4) bi 0.033 -0.049 0.000 0.000 0.217 0.019 0.041 0.053 289
p (0.426) (0.273) (0.050) (0.015) (0.148)
(i=5) bi 0.082 0.000 0.000 0.000 -0.338 0.539 0.013 0.200 236
p (0.159) (0.996) (0.580) (0.356) (0.180)
Maximum 3 years of
historical accounting
database are useful for
market predictability
Similarly, out of four price
scaled variables only two
namely, B/M and E/P ratios
have strong predictive power
On the other hands, S/P and
C/P ratios have no predictive
power for firm returns up to 5
lag years
06/18/2012
41

Table 11: Regression analysis of firm returns on B/M, E/P, past returns and share issuance measures
rt = α + b1 BP(t-i,t) + b2 EP(t-i,t) + b3 rB(t-i,t) + b4 r(t-i,t) + b5 ι(t-i) + ut
α b1 b2 b3 b4 b5 Model Sig R-square
K-S Test of
Res(p)
N
(i=0)
bi 0.053 -0.017 0.022 0.050 0.000 0.000 0.204 0.064 549
p (0.005) (0.492) (0.665) (0.011) (0.000)
(i=1)
bi -0.152 0.259 0.130 -0.065 0.019 0.000 0.000 0.304 0.200 398
p (0.000) (0.000) (0.023) (0.021) (0.197) (0.000)
(i=1)
bi -0.210 0.302 0.169 -0.049 0.033 0.000 0.237 0.200 398
p (0.000) (0.000) (0.005) (0.096) (0.027)
(i=2)
bi -0.031 0.162 -0.015 -0.103 -0.127 0.000 0.000 0.471 0.074 312
p (0.159) (0.000) (0.743) (0.000) (0.000) (0.000)
(i=2)
bi -0.071 0.201 -0.005 -0.103 -0.134 0.000 0.454 0.080 297
p (0.001) (0.000) (0.916) (0.000) (0.000)
(i=3)
bi 0.057 0.043 0.230 0.065 -0.241 0.000 0.000 0.235 0.057 276
p (1.631) (1.077) (2.053) (2.010) (-7.184) (-0.776)
(i=3)
bi 0.022 0.032 0.147 0.078 -0.229 0.000 0.255 0.200 254
p (0.471) (0.382) (0.142) (0.007) (0.000)
(i=4)
bi 0.171 -0.300 0.499 0.072 -0.221 0.000 0.000 0.160 0.200 202
p (0.001) (0.000) (0.004) (0.053) (0.000) (0.000)
(i=4)
bi 0.094 -0.232 0.443 0.065 -0.192 0.001 0.086 0.200 202
p (0.053) (0.001) (0.014) (0.091) (0.001)
(i=5)
bi 0.141 -0.114 -0.928 0.703 -0.299 0.000 0.000 0.229 0.200 165
p (2.433) (-1.516) (-3.266) (5.040) (-4.466) (3.129)
(i=5)
bi 0.195 -0.139 -0.901 0.622 -0.316 0.000 0.181 0.200 165
p (0.001) (0.072) (0.002) (0.000) (0.000)
Against the earlier findings,
B/M ratio exhibit the
fluctuating relation with firm
returns
In majority cases, the relationship between the
past returns and the current firm returns is
negative which suggest that the early winner
fail to achieve in later periods and vice-versa.06/18/2012
42

Table 12
Regression Analysis of Firm Returns on Book-to-Market and Book Returns
r(t-i, t) = b0 + b1 BP(t-i, t) + b2 ri
B
(t-i,t) + ui,t
α b1 b2 Model Sig R-square
K-S Test of
Res (p)
N
(i=0)
bi -0.024 0.052 0.012 0.001 0.030 0.200 430
p (0.096) (0.003) (0.420)
(i=1)
bi 0.046 -0.003 0.034 0.004 0.036 0.200 305
p (0.000) (0.838) (0.002)
(i=2)
bi 0.179 -0.107 0.078 0.000 0.100 0.200 285
p (0.000) (0.000) (0.000)
(i=3)
bi 0.089 -0.025 0.045 0.047 0.026 0.200 232
p (0.000) (0.222) (0.014)
(i=4)
bi 0.120 -0.071 0.069 0.005 0.049 0.200 212
p (0.000) (0.016) (0.002)
(i=5)
bi 0.087 -0.061 0.164 0.172 0.022 0.200 158
p (0.010) (0.152) (0.071)
 Even though book returns is not included in stock return calculations,
it is proved that there is positive relationship between them
And, in some cases, the strength of relationship is high and significant
06/18/2012
43

Table 13
An Analysis of Firm Returns on Price Scaled Variables with Fundamental Returns Measures
r(t-i, t) = y0 + y1BP(t-i,t) + y2SP(t-i.t) + y3CP(t-i,t) + y4EP(t-i,t) + y5.ri
B
(t-i,t) + y6.ri
S
(t-i, t) + y7.ri
C
(t-i, t) + y8. ri
E
(t-i, t) + ui,t
α y1 y2 y3 y4 y5 y6 y7 y8
Model
Sig
R-
square
K-S Test of
Res/DV (p)
N
(i=1)
bi 0.08 0.01 0.00 0.00 -0.03 -0.01 0.00 0.00 0.00 0.000 0.218 0.200 335
t (5.01) (0.69) (-4.20) (4.02) (-1.05) (-0.63) (6.94) (1.25) (1.27)
(i=1)
bi 0.07 -0.02 0.00 0.00 0.06 0.00 0.000 0.135 0.200 313
t (4.32) (-0.97) (-4.64) (4.55) (1.29) (0.40)
(i=1)
bi 0.06 0.02 -0.02 0.00 0.561 0.005 0.200 380
t (3.65) (1.36) (-0.55) (-0.12)
(i=2)
bi 0.21 -0.20 0.00 0.00 0.39 0.05 0.00 0.00 0.00 0.000 0.221 0.200 271
t (9.17) (-7.25) (-1.16) (0.71) (6.12) (3.76) (-0.78) (-0.28) (-2.28)
(i=2)
bi 0.18 -0.17 0.29 0.02 0.00 0.00 0.000 0.191 0.200 259
t (10.21) (-6.75) (5.56) (1.84) (-0.26) (-2.29)
(i=3)
bi 0.19 -0.15 0.00 0.00 0.26 0.00 0.00 0.00 0.00 0.000 0.234 0.200 235
t (6.91) (-4.53) (-1.65) (1.20) (4.18) (0.04) (5.95) (1.11) (-1.23)
(i=3)
bi 0.14 -0.08 0.20 0.005 0.038 0.051 275
t (6.01) (-2.86) (2.73)
(i=4)
bi 0.20 -0.23 0.00 0.00 0.47 0.03 0.00 0.00 0.00 0.000 0.151 0.085 232
t (4.80) (-4.47) (-1.47) (-0.33) (3.58) (1.39) (2.93) (-1.62) (-0.91)
(i=4)
bi 0.08 -0.09 0.31 0.03 0.001 0.100 0.200 160
t (2.80) (-2.35) (3.54) (2.19)
(i=5)
bi 0.06 -0.09 0.00 0.00 0.46 0.05 0.00 0.00 0.00 0.000 0.220 0.200 158
t (1.64) (-2.01) (-0.64) (-0.28) (2.81) (2.30) (4.85) (-0.10) (-0.93)
(i=5)
bi 0.04 -0.05 0.28 0.05 0.00 0.027 0.066 0.200 163
t (1.16) (-1.10) (1.66) (2.39) (-1.41)
B/M & E/P ratios have
strong predictive
power whereas S/P &
C/P have no predictive
power
The usefulness of
the historical data is
proved to be the
lagged 2 to 4 years
Among the
fundamental return
measures, only the
book returns has more
explanatory power
06/18/2012
44

Table 14
Regressions Analysis of Holding Period Stock Returns with Intangible Information
Α b0 b1 b2 b3 Model Sig R-square
K-S Test of
Residuals(p)
N
Panel A: ri(t) = α + b0 BP (t-i) + b1 rB(t-i,t) + b2 rI(B) + b3 ι (t-i,t) + ut
(i=1)
bi -0.154) 0.317 -0.108 0.033 0.000 0.000 0.245 0.057 435
t (-5.119) (8.705) (-3.794) (1.955) (-3.482)
(i=2)
bi -0.016 0.174 -0.113 -0.124 0.000 0.000 0.372 0.178 356
t (-0.550) (5.584) (-5.293) (-7.437) (-4.299)
(i=3)
bi 0.107 0.038 0.050 -0.186 0.000 0.000 0.201 0.200 302
t (2.506) (0.903) (1.359) (-4.860) (-3.936)
(i=4)
bi 0.304 -0.249 0.049 -0.136 0.000 0.000 0.239 0.200 209
t (5.670) (-4.275) (1.350) (-2.487) (-7.227)
(i=5)
bi 0.513 -0.495 0.334 -0.335 0.000 0.000 0.291 0.200 173
t (6.942) (-5.848) (2.478) (-4.954) (-5.536)
Panel B: ri(t) = α + b0 SP(t-i) + b1 rS(t-i,t) + b2 rI(S) + b3 ι (t-i,t) + ut
(i=1)
bi 0.027 0.000 0.000 0.020 0.000 0.000 0.253 0.053 445
t (1.476) (10.643) (-1.553) (1.187) (-11.322)
(i=2)
bi 0.066 0.000 0.000 -0.077 0.000 0.000 0.547 0.054 281
t (4.535) (9.971) (5.758) (-6.205) (-13.031)
(i=3)
bi 0.074 0.000 0.000 -0.119 0.000 0.000 0.338 0.200 296
t (2.881) (8.533) (-0.696) (-3.347) (-7.948
(i=4)
bi 0.117 0.000 0.000 -0.060 0.000 0.000 0.218 0.200 238
t (3.312) (5.604) (-0.223) (-1.029) (-7.446)
(i=5)
bi 0.108 0.000 0.000 -0.104 0.000 0.000 0.224 0.200 176
t (2.478) (4.105) (2.239) (-1.545) (-5.804)
Significant B/M effect except 3 lag
periods but relation is inconclusive
Intangibles using B/M shows –ve
effects except 1 lag
Share issuance measure have no
effect
No effect of S/P for returns
Intangibles using S/P shows –ve
effects except 1 lag
effect
06/18/2012
45

Α b0 b1 b2 b3 Model Sig R-square
K-S Test of
Residuals(p)
N
Panel C: ri(t) = α + b0 CP(t-i) + b1 rC(t-i,t) + b2 rI(C) + b3 ι (t-i,t) + ut
(i=1)
bi 0.071 0.000 -0.001 -0.023 0.000 0.000 0.157 0.113 406
t (4.549) (-0.779) (-1.651) (-1.584) (-8.370)
(i=2)
bi 0.065 0.000 0.000 -0.137 0.000 0.000 0.482 0.200 288
t (4.427) (4.444) (0.131) (-10.268) (-9.469)
(i=3)
bi 0.141 0.000 0.000 -0.180 0.000 0.000 0.190 0.079 302
t (5.445) (-0.198) (0.292) (-4.842) (-4.841)
(i=4)
bi 0.132 0.000 0.000 -0.150 0.000 0.000 0.217 0.081 215
t (4.402) (2.362) (1.439) (-2.749) (-6.283)
(i=5)
bi 0.118 0.000 0.000 -0.193 0.000 0.000 0.152 0.200 168
t (2.943) (0.722) (-0.757) (-2.839) (-4.073)
Panel D: ri(t) = α + b0 EP(t-i) + b1 rE(t-i,t) + b2 rI(E) + b3 ι (t-i,t) + ut
(i=1)
bi 0.066 0.131 0.000 -0.021 0.000 0.000 0.206 0.100 383
t (4.351) (2.746) (0.230) (-1.519) (-9.309)
(i=2)
bi 0.090 0.051 -0.001 -0.129 0.000 0.000 0.446 0.065 296
t (5.762) (1.215) (-1.489) (-9.823) (-8.884)
(i=3)
bi 0.128 -0.042 0.000 -0.136 0.000 0.000 0.440 0.081 219
t (6.702) (-0.621) (-1.301) (-5.561) (-8.960)
(i=4)
bi 0.142 -0.009 0.000 -0.148 0.000 0.000 0.136 0.200 226
t (3.616) (-0.056) (-0.035) (-2.434) (-4.821)
(i=5)
bi 0.206 -0.735 0.000 -0.207 0.000 0.000 0.216 0.200 164
t (4.333) (-3.181) (0.039) (-3.047) (-4.828)
No effect of C/P for returns
Intangibles using C/P shows –ve
effects
effect
Least effect of E/P for returns
Intangibles using E/P shows –ve
effects
Further, the share issuance
measure have no effect
06/18/2012
46

Table 15: News Effect on Average Market Returns
rm_avr = α + b0 bXt + b1 gXt + b2 iXt + ui
Model Constant bXt gXt iXt Sig. R2 K-S N
Panel A: Yearly database
1
bi 0.001 -0.014 0.012 0.00 0.710 0.200 16
t (0.015) (-4.576) (5.674)
2
bi 0.076 0.005 -0.009 0.09 0.310 0.190 16
t (0.424) (2.381) (-1.050)
3
bi 0.004 -0.014 0.012 0.000 0.00 0.710 0.200 16
t (0.035) (-4.109) (5.429) (-0.032)
Panel B: Monthly database
4
bi 0.026 -0.008 0.00 0.215 0.200 146
t (5.115) (-6.284)
5
bi 0.008 -0.010 0.007 0.00 0.331 0.200 151
t (1.447) (-7.746) (6.741)
6
bi 0.001 0.003 -0.002 0.00 0.092 0.063 141
t (0.155) (3.748) (-1.036)
7
bi 0.026 -0.007 0.000 0.00 0.239 0.200 134
t (4.822) (-6.118) (-0.051)
8
bi 0.011 -0.011 0.008 -0.001 0.00 0.424 0.200 145
t (1.853) (-9.135) (7.821) (-0.301)
Panel C: Daily database
9
bi 0.001 -0.006 0.00 0.116 0.200 1,331
t (5.592) (-13.174)
10
bi 0.000 -0.004 0.003 0.00 0.134 0.126 1,253
t (3.042) (-10.473) (8.635)
11
bi 0.000 -0.005 0.001 0.00 0.108 0.064 1,259
t (4.582) (-12.097) (2.438)
12
bi 0.000 -0.004 0.002 0.001 0.00 0.125 0.068 1,209
06/18/2012
47

Table 16: News Effect on Mid-July Market Returns
rm_midjuly = α + b0 bXt + b1 gXt + b2 iXt + ui
Model Constant bXt gXt iXt Sig. R2 K-S N
1
Bi 0.072 -0.020 0.015 0.00 0.750 0.200 16
T (-0.926) (-5.837) (6.190)
2
Bi 0.241 0.006 -0.016 0.17 0.240 0.200 16
T (1.044) (1.970) (-1.501)
3
Bi 0.141 -0.019 0.015 -0.004 0.00 0.760 0.200 16
T (1.036) (-5.122) (6.075) (-0.625)
4
Bi 0.031 -0.011 0.004 0.459 0.200 127
T (7.308) (-10.294)
5
Bi 0.006 -0.013 0.010 0.00 0.595 0.200 137
T (1.196) (-12.212) (11.590)
6
Bi -0.001 0.007 -0.006 0.00 0.228 0.200 141
T (-0.094) (6.289) (-2.581)
7
Bi 0.037 -0.009 -0.004 0.00 0.409 0.054 131
T (6.822) (-7.930) (-2.118)
8
Bi 0.019 -0.013 0.009 -0.004 0.00 0.489 0.200 149
T (2.995) (-10.241) (8.906) (-1.818)
9
Bi 0.001 -0.002 0.00 0.026 0.142 1,674
T (5.579) (-6.738)
10
Bi 0.000 -0.002 0.001 0.00 0.035 0.200 1,687
T (4.534) (-6.297) (4.447)
11
Bi 0.001 -0.002 -0.001 0.00 0.029 0.128 1,673
T (5.981) (-6.746) (-2.220)
Bi 0.000 -0.002 0.001 -0.001 0.00 0.036 0.149 1,689
There is –ve effect of
bad news, +ve effect of
good news and
inconsistent effect of
informational news for
market returns
The strength of good
news have relatively
weaker than bad news
and the informational
news on the other
hands, have marginal
effect for market
returns
06/18/2012
48

Table 17: Political Leadership Effect on Average Market Returns
rm_ave = α + b1D1 + b2D2 + b3D3 + ui
Model Constant b1D1 b2D2 b3D3 Sig. R2 K-S N
1
Bi 0.180 -0.283 -0.104 0.318 0.162 0.200 16
T (1.990) (-1.569) (-0.638)
2
Bi -0.051 0.074 0.027 0.062 0.000 0.176 0.096 148
T (-3.422) (4.648) (1.386) (3.841)
3
Bi -0.002 0.003 0.000 0.002 0.000 0.088 0.063 1,239
T (-4.850) (6.863) (-0.478) (4.902)
Table 18: Political Leadership Effect on Mid-July Market Returns
rm_midJul = α + b1D1 + b2D2 + b3D3 + ui
Model Constant b1D1 b2D2 b3D3 Sig. R2 K-S N
1
Bi 0.185 -0.402 -0.041 0.198 0.220 0.200 16
T (1.741) (-1.889) (-0.213)
2
Bi -0.058 0.088 0.033 0.068 0.000 0.193 0.086 144
T (-3.453) (4.910) (1.539) (3.727)
3
Bi -0.002 0.003 -0.001 0.002 0.000 0.086 0.111 1,715
T (-4.483) (7.005) (-1.887) (4.719)
There is lower
contribution of the NC
led government for
the market growth
where CPN-UML and
UCPN (M) leadership
have on an average
higher/positive
contribution for
average stock returns.
Support the findings
of Table 17
06/18/2012
49

Table 19: A Regression Analysis of Market Returns on News and Political Leadership from 1994:07 – 2010:07
Section A: rm_ave = α + b0 bXt + b1 gXt + b2 iXt + b4D1 + b5D2 + b6D3 + ui
Model
PanelA:Yearlydatabase
1
PanelB:Monthlydatabase
2
PanelC:Dailydatabase
3
(ANCOVA) bi t bi t bi t
Constant 0.041 (0.266) -0.028 (-1.656) -0.002 (-3.812)
b0 -0.014 (-3.083) -0.009 (-6.032) -0.003 (-7.165)
b1 0.012 (4.269) 0.007 (6.245) 0.002 (8.312)
b2 -0.001 (-0.183) 0.000 (0.184) 0.001 (2.081)
b4 0.036 (2.197) 0.003 (5.500)
b5 -0.002 (-0.012) 0.017 (0.912) 0.000 (-0.814)
b6 -0.051 (-0.447) 0.035 (2.099) 0.002 (3.775)
Sig. 0.014 0.000 0.000
R2 0.719 0.357 0.169
K-S 0.200 0.200 0.127
N 16 153 1,245
Section B: rm_midJul = α + b0 bXt + b1 gXt + b2 iXt + b4D1 + b5D2 + b6D3 + ui
Model
PanelA:Yearlydatabase
1
PanelB:Monthlydatabase
2
PanelC:Dailydatabase
3
(ANCOVA) bi t bi t bi t
Constant 0.148 (0.846) -0.012 (-0.748) -0.001 (-3.313)
b0 -0.019 (-3.856) -0.013 (-8.944) -0.001 (-2.299)
b1 0.015 (4.759) 0.010 (8.881) 0.002 (6.485)
b2 -0.004 (-0.570) -0.004 (-1.889) -0.001 (-2.792)
b4 0.034 (2.158) 0.003 (6.116)
b5 0.014 (0.083) 0.021 (1.164) -0.002 (-3.096)
b6 -0.009 (-0.069) 0.026 (1.624) 0.001 (3.530)
Sig. 0.007 0.000 0.000
R2 0.761 0.521 0.124
Bad news have
consistent –ve effect
for returns
Good news have
consistent +ve effect
for returns
Informational news
have inconclusive
effect for returns
Daily news as well as
leadership effect is
more stronger than
yearly and monthly
effects
Monthly series have
more predictive
power than yearly
and daily series
CPN-UML led
government is proved
to be a market friendly
government followed
by UCPN (M)06/18/2012
50

There is no reliable patterns of the variables
&
There is no clarity that whether news leads
market returns or vice-versa
06/18/2012
51

Table 20: Respondents profile
Variables Demographic Characteristics Number Percentage
Panel A:
Gender
Female 12 7.3
Male 152 92.7
Total 164 100.0
Panel B:
Age of respondents
Below 25 13 7.9
25 to 40 100 61.0
Above 40 51 31.1
Total 164 100.0
Panel E:
Stock investment (size)
Less than Rs 5 lakh 51 31.1
5 to 10 27 16.5
10 to 25 39 23.8
More than 25 lakh 37 22.6
Undisclosed 10 6.1
Total 164 100.0
Panel F:
Experience
Less than 1 year 9 5.5
1 to 5 years 88 53.7
5 to 10 years 43 26.2
10 to 17 years 14 8.5
Above 17 years 5 3.0
Undisclosed 5 3.0
Total 164 100.0
Survey results
06/18/2012
52

Table 21
Investor's perception and awareness level
Panel A: Investor's perception
Options
MF CDS CRA PMS
Number % Number % Number % Number %
Not important 9 5.5 9 5.5 8 4.9 10 6.1
Less important 7 4.3 8 4.9 11 6.7 8 4.9
Neutral 14 8.5 10 6.1 19 11.6 21 12.8
Important 58 35.4 51 31.1 53 32.3 59 36.0
Most important 61 37.2 70 42.7 49 29.9 47 28.7
Undisclosed 15 9.1 16 9.8 24 14.6 19 11.6
Total 164 100 164 100 164 100 164 100
Panel B: Investor's Awareness
Options
MF CDS CRA PMS
Number % Number % Number % Number %
Not aware 25 15.2 17 10.4 33 20.1 24 14.6
Less aware 10 6.1 16 9.8 18 11.0 20 12.2
Neutral 21 12.8 22 13.4 29 17.7 30 18.3
Aware 60 36.6 64 39.0 44 26.8 45 27.4
Highly aware 37 22.6 33 20.1 26 15.9 30 18.3
Undisclosed 11 6.7 12 7.3 14 8.5 15 9.1
Total 164 100 164 100 164 100 164 100
 Majority investors perceived MF, CDS, CRA and PMS are most important mechanism for
market growth and development but they are not highly aware on any of them.06/18/2012
53

Table 22: Investor Judgment on various issues and evidences
Panel A: Investor judgment on the various issues
Statements N Mean
Agree Disagree I don't know Total
%Num. % Num. % Num. %
a) Investing in IPO is more risky than investing in Secondary market
(Loughran and Ritter, 1995)
160 1.875 22 13.4 136 82.9 2 1.2 97.6
b) Seasonal offerings do not maximize the shareholders' wealth 160 1.731 48 29.3 107 65.2 5 3.0 97.6
c) If reliable private info., it would be better to invest in single security 158 1.658 60 36.6 92 56.1 6 3.7 96.3
d) The most frequent trading is harmful for investors' wealth 159 1.792 42 25.6 108 65.9 9 5.5 97.0
e) News events lead some investors to react quickly
(Klibanoff, et.al, 1998)
159 1.170 139 84.8 13 7.9 7 4.3 97.0
Panel B: Investor judgment on the various evidences
Statements N Mean
St. agree Agree Disagree St. disagree Total
%Num. % Num. % Num. % Num. %
a) Stock market exhibit higher returns
following good news and lower on bad news
(Zhang, 2006)
157 1.904 52 31.71 74 45.12 25 15.24 6 3.66 95.7
b) Media effect, market noise, seasonal effect,
etc strongly influence men investor but not for
women (Biais et.al, 2005)
158 2.380 33 20.12 42 25.61 73 44.51 10 6.10 96.3
c) High information uncertainty enhance the
investor's overconfidence (Jiang et.al, 2004)
155 2.523 25 15.24 49 29.88 56 34.15 25 15.24 94.5
d) Investor under-react to public info. and
overreact to perceived private information
(Chan, 2003)
158 2.259 31 18.90 66 40.24 50 30.49 11 6.71 96.3
e) Investors respond mistakenly in initial phase
of the information disclosure (Ikenberry et.al,
1995)
156 2.340 26 15.85 59 35.98 63 38.41 8 4.88 95.1
Majority
agreed on
last issue &
disagree on
others
Majority
agreed on
only two
evidences
06/18/2012
54

Table 23
Factor analysis: The rotated solution
Statements
Components
1 2 3
X3 Brokers usually alter my investment decisions 0.768
X11 Media coverage largely influence my investment decisions 0.652
X15 My friends recommend/help me to decide most of my investment
alternatives
0.587
X8 I use dividend payment records while buying and selling stocks 0.839
X7 I use the average prices (6 months, 1 yr, 2 yrs, etc) to determine the
current prices
0.788
X10 It is important to look at debt and equity structure before investing 0.820
X5 I always evaluate the company profile & track records of management
while investing
0.677
X9 The prices move in a direction (increasing/decreasing) provides insight
about future price
0.457
ExternalFactor
Self-knowledge
Factor
FirmSpecificFactor
 Factor analysis concluded that there are three factors that affect the investment
decision making process.
 Namely, the external factor (Brokers, Media & Friends), self-knowledge factor
(using dividends & price records), and the firm specific factor (D-E structure,
Management & price movement)06/18/2012
55

Only the three years of historical accounting data are useful
to find the market signals.
Book to price and earnings to price ratios have strong
predictive power among the other price-scaled variables for
firm level stock returns.
There is negative effect of bad news, positive effect of good
news, and inconsistent effect of informational news for market
returns.
Based on the assumptions of the study, it is proved that CPN-
UML led government is a market friendly government compare
to others, and
There are three factors that influences the stock price
movement namely - the external factor, self-knowledge factor,
and firm specific factor.
Conclusions
06/18/2012
56

Thank you.
06/18/2012
57

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