Size And PE Factor Toward Vietnams Stocks Return
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An Analysis on Relations of Price-Earnings Ratios and Market Capitalization to Anomaly Returns
Advisor: Le Hong Nhung, MBA Student: Ton That Hue Tri
- International University -- School of Business Administration -
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Value Investment
Style Investment Growth Investment
Technical Analysis
Market Neutral
Event-Driven
Distress Investment
Global MacroContrarian
Tape Reading
Gorilla Trading
Day Trading
Scalping Trading
Merger ArbitrageLong/Short
Short Bias
Volatility Arbitrage 130-30 Funds
Fixed Income Arbitrage
Quantitative Directional
Triangular Arbitrage
Interest Rate Parity
Size Value Factors Sectors Liquidity
P/E P/B P/CF Leverage
Size Effect P/E Effect
Combination Effect of P/E and Size
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Content
Chapter 1 - IntroductionChapter 2 - Literature ReviewChapter 3 - Study Design & MethodologyChapter 4 - Result Analysis & Discussion Chapter 5 - ConclusionAppendices
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Chapter 1 - Introduction
Background ContextObjectivesImplications of the Study
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00 01 02 03 04 05 06 07 08 090
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Back Ground Context
Chapter 1 – IntroductionBackground ContextObjectivesImplications of the Study
Chapter 2 - Chapter 3 - Chapter 4 - Chapter 5 - Appendices
I don’t know what happened there
Nothing happened here
People got top of the world here, and …
People committed suicide here.
Vietnam’s stock market is breath-taking!!!
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Objectives
Chapter 1 – IntroductionBackground ContextObjectivesImplications of the Study
Chapter 2 - Chapter 3 - Chapter 4 - Chapter 5 - Appendices
Investigate P/E Effect
Investigate Size Effect
Investigate Combination Effect of P/E and Size
3 Main Targets
2 Sub Targets
Find correlations between Size and P/E
Give comment to Efficient Market Hypothesis
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Implications of the Study
Chapter 1 – IntroductionBackground ContextObjectivesImplications of the Study
Chapter 2 - Chapter 3 - Chapter 4 - Chapter 5 - Appendices
Test the applicable characteristic of theories from advanced countries
Proof for Efficient Market Hypothesis
For Academic Community
Meaningful information for investment strategy
Anchor to develop style investment strategies
For Investment Community
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Chapter 2 - Literature Review
Efficient Market HypothesisAnomalies and Theories on Anomaly MeasurementsEmpirical Researches on Price-earnings RatioEmpirical Researches on Market Capitalization
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Efficient Market Hypothesis
Chapter 1 -Chapter 2 – Literature Review
Efficient Market HypothesisTheories on AnomaliesEmpirical Researches on P/E RatioEmpirical Researches on Size
Chapter 3 - Chapter 4 - Chapter 5 - Appendices
- Security prices fully reflect all available information in the market in an unbiased and rapid manner -
Eugene Fama (1960s)
Assumptions:(1) Large number of profit maximizers(2) New information come randomly(3) Profit maximizers adjust prices rapidly
to new information
Three forms of EMH:
Weak-form
Semistrong-form
Strong-form
Debate!!!
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Theories on Anomalies
Chapter 1 - Chapter 2 – Literature Review
Efficient Market HypothesisTheories on AnomaliesEmpirical Researches on P/E RatioEmpirical Researches on Size
Chapter 3 - Chapter 4 - Chapter 5 - Appendices
Beta
Asset Return
Risk-free rate of return
SML
CAPM – Treynor (1961), Sharpe (1964), Lintner (1965), Mossin (1965)
Expected Returni = RFR + βi(Market Return – RFR)
Difference between expected returns and actual returns Anomaly
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Researches on P/E Ratio
Chapter 1 - Chapter 2 – Literature Review
Efficient Market HypothesisTheories on AnomaliesEmpirical Researches on P/E RatioEmpirical Researches on Size
Chapter 3 - Chapter 4 - Chapter 5 - Appendices
Nicholson (1960) Low P/E companies
beat the market!
Low P/E Outperform
No P/E Effect
P/E Effect, but not from Low P/E
1960s McWilliam, Miller,Widmann,
Breen, Savage
Johnson, Fiore, & Zuber (1989)
Basu (1977) Low P/E still outperforms! After
several adjustments
Staff (2004) Canadian
Equity
Growth Stock
Cyclical Stock
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Holding Period Assumption
Researches on Size
Chapter 1 -Chapter 2 – Literature Review
Efficient Market HypothesisTheories on AnomaliesEmpirical Researches on P/E RatioEmpirical Researches on Size
Chapter 3 - Chapter 4 - Chapter 5 - Appendices
Smallest Firms
Outperform
Size Effect = Stable over
time!
Banz & Reinganum (1981)
Brown, Kleidon, & Marsh (1982)
No Size Effect during 1967-1979 in US Equity
Predictive power of Size is unstable
Stoll & Whaley (1983)
Transaction costReinganum (1983, 1992)
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Chapter 3 - Study Design & Methodology
The Study DesignData Collection Method The Study ConstructionHypothesis Testing
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The Study Design
Chapter 1 - Chapter 2 -Chapter 3 – Study Design &
MethodologyThe Study DesignData Collection Method The Study ConstructionHypothesis Testing
Chapter 4 - Chapter 5 - Appendices
Lowest PE Low PE Mod PE High PE Highest PE
Smallest MC
M1
Smallest-
Lowest
M6
Smallest-Low
M11
Smallest-Mod
M16
Smallest-High
M21
Smallest-
Highest
Small MCM2
Small-Lowest
M7
Small-Low
M12
Small-Mod
M17
Small-High
M22
Small-Highest
Mid MCM3
Mid-Lowest
M8
Mid-Low
M13
Mid-Mod
M18
Mid-High
M23
Mid-Highest
Big MCM4
Big-Lowest
M9
Big-Low
M14
Big-Mod
M19
Big-High
M24
Big-Highest
Biggest MC
M5
Biggest-
Lowest
M10
Biggest-Low
M15
Biggest-Mod
M20
Biggest-High
M25
Biggest-
Highest
P/E EffectSi
ze E
ffect
Study Design Summary: Stocks Studied: 161 (Excluded Fund Certificates) Time Scale: Mar 1st 2007 – Mar 1st 2010 Rebalancing Period: 3 months 12 times of rebalancing Total 420 equal weighted portfolios constructed
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Chapter 1 - Chapter 2 -Chapter 3 – Study Design &
MethodologyThe Study DesignData Collection Method The Study ConstructionHypothesis Testing
Chapter 4 - Chapter 5 - Appendices
Data Collection MethodStock’s Prices: Closing priceRisk Free Rate: Government 5-years bond quotesQuarterly Profit: Quarterly Reports, Unit used VND 1,000Outstanding Share Number: Market capitalization divided by closing price
Eliminate Look-Ahead Bias: Date of forming portfolios chosen at the beginning trading day of Mar, Jun, Sep, and Dec for Q1, Q2, Q3, and Q4 respectively
Eliminate IPO Effect: Stock must be traded 3 months prior to the portfolio forming dates
Eliminate Survivorship Bias: Stock, which is excluded from VNIndex for any reason (switch to HNX Index, bankruptcy, etc.), is still taken into portfolios prior to the event’s date
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The Study Construction
Chapter 1 - Chapter 2 -Chapter 3 – Study Design &
MethodologyThe Study DesignData Collection Method The Study ConstructionHypothesis Testing
Chapter 4 - Chapter 5 - Appendices
Data PhaseTickers collected
Tickers portfoliosData Collected
P/E and Size calculated
Study P/E Effect
Study Size EffectDivide P/E by scale of 5 & reallocate
Category daily returns calculated
Synthesize returns throughout 12 periods
Run Regression each cla
ss to m
arket
alpha
Study Combination
Effect
Lowest
PELow PE Mod PE
High
PE
Highest
PE
Smallest
MCM1 M6 M11 M16 M21
Small
MCM2 M7 M12 M17 M22
Mid
MCM3 M8 M13 M18 M23
Big MC M4 M9 M14 M19 M24
Biggest
MCM5 M10 M15 M20 M25
Study Correlation of
P/E & Size
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Hypothesis Testing
Chapter 1 - Chapter 2 -Chapter 3 – Study Design &
MethodologyThe Study DesignData Collection Method The Study ConstructionHypothesis Testing
Chapter 4 - Chapter 5 - Appendices
Hypothesis Establishing:H0: μα = 0 – The mean of alpha is equal zeroH1: μα ≠ 0 – The mean of alpha is statistically significant different from zero
Test statistic applied: t-testPopulation variance is unknownt-test is robustt-test is more conservative to z-test
Significant Level: 0.05 level of significance
p-value approach: p-value chosen to be 5%
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Chapter 4 - Result Analysis & Discussion
P/E EffectSize EffectCombination Effect of Size and P/ECorrelation of Size, P/E & other Considerations
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P/E Effect
Chapter 1 - Chapter 2 -Chapter 3 -Chapter 4 – Result Analysis &
DiscussionP/E EffectSize EffectCombination Effect of Size and P/ECorrelation of Size, P/E & other
Considerations
Chapter 5 - Appendices
Mean Returns Standard Deviation Alpha (%) P-Value Reject?
PE1 -0.02% 2.13% 0.057815 8% Accept
PE2 -0.02% 2.13% 0.05762 7% Accept
PE3 -0.02% 2.08% 0.062083 4% Reject
PE4 -0.06% 2.03% 0.019601 46% Accept
PE5 -0.08% 2.03% -0.004459 87% Accept
Only PE3 – Moderate P/E is found to have reliable positive alpha of 0.06%
As P/E goes lower, mean returns tend to go higher along with alpha
Contradictory to Nichoson (1960), McWilliam (1966), Midler & Widmann (1966), Breen (1968), & Basu (1977)’s finding that low P/E outperform
Supportive to conclusion of Johnson, Fiore, & Zuber (1989) that there were some abnormal returns by using P/E but those not come from Low P/E
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Size Effect
Chapter 1 - Chapter 2 -Chapter 3 -Chapter 4 – Result Analysis &
DiscussionP/E EffectSize EffectCombination Effect of Size and P/ECorrelation of Size, P/E & other
Considerations
Chapter 5 - Appendices
Mean Returns Standard Deviation Alpha (%) P-Value Reject?
MC1 0.02% 2.16% 0.094004 3% Reject
MC2 -0.04% 2.14% 0.037867 29% Accept
MC3 -0.02% 2.08% 0.054579 9% Accept
MC4 -0.08% 2.04% -0.006336 82% Accept
MC5 -0.09% 2.10% -0.000776 97% Accept
As Size goes lower, mean returns tend to go higher along with alpha
Only MC1’s alpha of 0.09% satisfies 95% confidence interval with p-value = 3%
Strongly supportive to Size Effect found by Banz & Reinganum (1981), Reinganum (1983, 1992), and Stoll & Whaley (1983)’s finding that low Market Cap outperform
Is this finding contradictory to Brown, Kleidon, & Marsh (1982)? Not enough evidence to conclude Size Effect in HoSE is a long-run phenomenon or time-period effect
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Combination Effect
Chapter 1 - Chapter 2 -Chapter 3 -Chapter 4 – Result Analysis &
DiscussionP/E EffectSize EffectCombination Effect of Size and P/ECorrelation of Size, P/E & other
Considerations
Chapter 5 - Appendices
Mean Returns ϭ α (%) P-Value Reject?
M1 0.10% 2.39% 0.183 0% Reject
M2 -0.09% 2.35% -0.012 80% Accept
M3 -0.04% 2.38% 0.0392 42% Accept
M4 -0.07% 2.40% 0.0112 82% Accept
M5 -0.04% 2.44% 0.0527 19% Accept
M6 0.07% 2.50% 0.1525 1% Reject
M7 0.01% 2.39% 0.0894 6% Accept
M8 -0.05% 2.24% 0.0282 54% Accept
M9 -0.03% 2.25% 0.0469 28% Accept
M10 -0.08% 2.35% 0.0086 82% Accept
M11 -0.04% 2.45% 0.0373 50% Accept
M12 -0.02% 2.36% 0.0526 31% Accept
M13 0.06% 2.32% 0.1408 0% Reject
M14 -0.02% 2.21% 0.0558 20% Accept
M15 -0.12% 2.25% -0.032 33% Accept
M16 0.00% 2.40% 0.0663 27% Accept
M17 0.00% 2.40% 0.0783 15% Accept
M18 -0.04% 2.20% 0.0246 62% Accept
M19 -0.21% 2.31% -0.1285 0% Reject
M20 -0.07% 2.27% 0.0165 64% Accept
M21 -0.01% 2.38% 0.0486 44% Accept
M22 -0.06% 2.43% 0.0112 85% Accept
M23 -0.04% 2.37% 0.0366 47% Accept
M24 -0.12% 2.18% -0.0544 28% Accept
M25 -0.09% 2.27% -0.0076 84% Accept
Lowest
PELow PE Mod PE
High
PE
Highest
PE
Smallest
MCM1 M6 M11 M16 M21
Small
MCM2 M7 M12 M17 M22
Mid
MCM3 M8 M13 M18 M23
Big MC M4 M9 M14 M19 M24
Biggest
MCM5 M10 M15 M20 M25
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Correlation of Size, P/E, & Other Considerations
Chapter 1 - Chapter 2 -Chapter 3 - Chapter 4 – Result Analysis &
DiscussionP/E EffectSize EffectCombination Effect of Size and P/ECorrelation of Size, P/E & other
Considerations
Chapter 5 - Appendices
MC PEMC 1PE 0 1
No Significant relationship found in the correlation between Market Cap and P/E
No significant change in results after taking transaction cost into consideration
Mean Daily Transaction Cost = (((Buy cost)*8)/(5*52))
0.000923077% = ((0.03%*8)/(5*52))
The combination effect of Size and P/E is actually come from both factors!
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Chapter 5 - Conclusion
746 Daily Observations
161 chosen
companies
Prices, # of
Share, & Quarterly
Profits
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Study Result Outperformers Adjustments?
P/E Effect Moderate class Transaction costs: No change result
Size Effect Smallest cap class Transaction costs: No change result
Combination Effect
Generally positive in smallest cap with low and mod P/E
Negative in big cap and high P/E
Transaction costs: No change result
Correlation of P/E and Size
Not recognize No
Comment on Semistrong Form EMH
Anomalies appear in smallest cap and mod P/E
Transaction costs: No change result
Chapter 1 -Chapter 2 - Chapter 3 - Chapter 4 - Chapter 5 – ConclusionAppendices
Legend: Effect is proven Effect is not proven
Conclusion Table
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Thank You for Listening!
:1009080706050403020100
00
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Appendices
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Scope VNIndex 2007 – 2010
LimitationsSustainabilityPotential of Sample Selection
Bias
Suggestions for Further Studies
a lot!
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Key Concepts & TechniquesTrailing P/E = (Price Per Share) / (Most 4 recent quarters of EPS)
Market Cap = (No. of share outstanding) x (Closing price)
Arithmetic Return= ((Port value in time T+1) – (Port value in time T)) / (Port value in time T)
Mean Daily Arithmetic Return=(1/n) x (Return Day 1st + Return Day 2nd + … + Return Day nth)
Abnormal Return=(Actual Portfolio Return) – (Expected Portfolio Return)
Split AdjustmentTicker’s returns are adjusted to 0% at the split day
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Source of InformationStock’s Prices: VNDirect
Risk Free Rate: Hanoi Stock Exchange Website
Quarterly Profit: CafeF, Ho Chi MInh Stock Exchange Website, VNDirect, & Saigon Bank Berjaya
Outstanding Share Number: Vietstocks