We document evidence of the superior performance of portfolios constructed by agents with strong informational advantage. The portfolios constructed by such agents outperform the benchmark by average excess return of 1.22% on a monthly basis. Further evidence has been documented that these portfolios tend to give superior performance without any intentional diversification. Such portfolios may have high industrial concentration and relatively less number of stocks, however, they have exhibited excess returns over long periods. This result can be used as one of the explanations to portfolios biases like aggregate home equity bias, bias of individual investors to invest in assets that are highly correlated with non-financial income, bias to invest in employer stocks etc.

1. INFORMATION ASYMMETRIES
& PORTFOLIO
CONCENTRATION
DECEMBER, 2014
INDIAN INSTITUTE OF MANAGEMENT, LUCKNOW
Prabandh Nagar, Lucknow - 226013
Submitted By:
Syed Danish Hasan
(PGP 29194)
Under Guidance of
Dr. Ajay Garg

2. 1
Contents
I. Introduction.......................................................................................................................3
II. Review of Literature.......................................................................................................4
III. Gap .......................................................................................................................................9
IV. Hypothesis Development..............................................................................................9
V. Research Design............................................................................................................11
VI. Results...............................................................................................................................14
VII. Conclusion........................................................................................................................18

3. 2
Abstract
We document evidence of the superior performance of portfolios constructed
by agents with strong informational advantage. The portfolios constructed by
such agents outperform the benchmark by average excess return of 1.22%
on a monthly basis. Further evidence has been documented that these
portfolios tend to give superior performance without any intentional
diversification. Such portfolios may have high industrial concentration and
relatively less number of stocks, however, they have exhibited excess returns
over long periods. This result can be used as one of the explanations to
portfolios biases like aggregate home equity bias, bias of individual investors
to invest in assets that are highly correlated with non-financial income, bias
to invest in employer stocks etc.

4. 3
I. Introduction
Financial economists have debated the Efficient Market Hypothesis (EMH) for
decades. There have been instances of inefficiencies even in most developed
markets. Empirical evidence suggests that inefficiencies in the market give rise
to information asymmetries that if exploited by skilled investors, ensure
persistent excess returns. Further, a number of studies have concluded that the
investors often exhibit biased tendencies towards portfolio construction that
cannot be explained by modern portfolio theory. Excessive concentration,
investing in home equity more heavily, investing in assets that are strongly
correlated with financial income etc. are some of the most popular biases. In
this paper, we attempt to explain a rational justification for such irregularities in
the market place. Some literature suggests that the retail investors make their
decision arbitrarily and are more often than not guided by over confidence
making irrational choices. Our study, attempts to explain that there can be more
rational reasons for such biases like existence of information asymmetries in the
market place that encourage the participants to deviate from regular portfolio
theory to exploit most of the benefits derived from such inefficiencies. We
hypothesize that the portfolios constructed on basis of superior informational
advantage beat the market and it is acceptable for a market participant to violate
basic portfolio laws like diversification across industries, asset classes or

5. 4
geographies to earn excess returns in such instances. The proposed study is
divided into six sections. The first sections involves review of literature and
explores previous studies conducted in the area of information asymmetry,
portfolio concentration and equity biases. The second section lists the gap in the
area of study, which is the area we intend to cover in this paper. The following
section deals with the hypothesis development after studying existing literature
and initial examination. The fourth section lays down the research design, which
explains the variables chosen, the data used and its sources and detailed
methodology used to conduct the proposed study. The next section documents
the result of our study and its implications. The last sections concludes the study
with interpretations of the result in explaining the equity biases we had listed
earlier and summarized the performance of concentrated portfolios constructed
with superior informational advantage.
II. Review of Literature
In this section of our paper, we intend to explore previous studies conducted in
the area of portfolio concentration, information asymmetries and the ability of
investors to earn excess returns. The ability to earn excess returns consistently
demonstrate instances of inefficiencies or existence of some informational
advantage in the markets.

6. 5
To begin with, we find that Coval, Hirshleifer, and Shumway (2002) document
that individual investors that have performed abnormally well in the past
continue to perform abnormally well in the future. Thus, it appears that some
skillful individual investors might be able to exploit market inefficiencies to earn
abnormal profits.
Another study by Ivković and Weisbenner (2004) find that households exhibit a
strong preference for local investments and further show that, on average,
individuals’ investments in local stocks outperform their investments in non-local
stocks, suggesting that investors are able to exploit local knowledge. The excess
return is particularly large for stocks not included in the S&P 500 Index, in regard
to which informational asymmetries between local and non-local investors may
be the largest.
The empirical literature studying the performance of individual investors finds
that, on average, households’ stock investments perform poorly. For example,
Odean (1999) reports that individual investors’ purchases tend to underperform
their sales by a significant margin. Barber and Odean (2000, 2001) further show
that, on average, individual investors who hold common stocks pay a substantial
penalty in performance for trading actively. These results are consistent with the
hypothesis that individual investors are overconfident and trade excessively.

7. 6
Consistent with Odean (1999), we find that, on average, the stocks bought by
individual investors underperform the stocks they sell by a wide margin.
However, we find that the reverse is true for households with concentrated
investments. This result is particularly strong for households with large account
balances. The purchases of diversified investors with account balances of at least
$100,000 underperform their sales by 1.8 percentage points per year. On the
other hand, the purchases of concentrated investors with such large account
balances outperform their sales by 3.0 percentage points per year. The excess
return associated with concentration is stronger for investments in local stocks
and stocks that are not included in the S&P 500 Index (which tend to have less
analyst coverage and national media attention), potentially reflecting
concentrated investors’ ability to exploit informational asymmetries.
In sum, these findings are consistent with the hypothesis that skilled investors
can exploit informational asymmetries by concentrating their portfolios in the
stocks about which they have particularly favorable information.
The empirical literature has documents a number of portfolio biases among retail
investors that are beyond rational explanation of portfolio economics. The
“equity home bias” being perhaps the best known example. The term refers to
the observation that aggregate national portfolios are strongly biased towards
holding domestic equity assets and generally exhibit a low propensity for

8. 7
investing in foreign equity assets (see among others French and Poterba (1991),
Tesar and Werner (1998), and Ahearne et al. (2004)). This can be justified on
many grounds. Equity investment in foreign companies requires understanding
of different accounting practices and legal environments. Domestic investors are
exposed to a wide array of sources of local news that can convey useful
information about the performance of domestic companies. In addition,
geographical proximity allows for face-to-face contacts with local corporate
executives, employees and other individuals that may have valuable private
information.
A number of other portfolio biases have also been identified at the individual
investor level. Huberman and Sengmueller (2004), Poterba (2003), Benartzi
(2001), find that investors overinvest in the stock of their own employer or in
the stock of other companies in the same industry. Ivkovi´c and Weisbenner
(2005) and Huberman (2001) find that investors exhibit a “local bias” – the
tendency to overinvest in assets that are geographically close to the investor’s
place of residence. Massa and Simonov (2006) show that investors tilt their
portfolios away from the market portfolio, and towards assets with a significantly
higher correlation with their non-financial income. Goetzmann and Kumar (2008)
show that the stocks individual investors hold are highly correlated with each
other, which suggests that they are driven by the same risk factors. All these

9. 8
findings indicate that retail agents tends to concentrate their investments in
assets that are closely related to their domicile, work place, profession etc.
Such aggressive investments in non-financial income related assets go against
the law of diversification and can be a result of over confidence of these investors
with regard to assets they presume they have a superior understanding about.
On the other hand, such concentration can be an outcome of informational
advantage which is then a rational justification.
Another important study in the area of informational asymmetries and portfolio
biases explain the relationship between agent’s capacity to process information
and portfolio concentration. Rosen Valchev (2014) finds that that portfolio
concentration has a non-monotonic relationship with an agent’s capacity to
process information. Agents with a low capacity find it optimal to specialize in
acquiring information about only one asset and thus allocate any extra
information capacity to the same asset, while agents with a high capacity choose
to spread their efforts across a variety of different assets. Thus, the resulting
information asymmetry and hence the degree of portfolio concentration is
increasing in the capacity for information acquisition when the capacity is low,
and decreasing when it is high.

10. 9
III. Gap
Literature exists for studies on the information asymmetries in the market and
relative portfolio construction. We explore the empirical evidence regarding the
portfolios constructed with superior information and their performance against
the benchmark portfolios or portfolio constructed by average informed investors.
We seek to test the evidence in Indian equity markets that the superior
information based portfolios outperform the market and unnecessary
diversification should be avoided as it dilutes the informational advantage in the
portfolio.
IV. Hypothesis Development
For the purpose of our study we divide agents for every security into two broad
heads:
1. Average (Informed) Agents: These agents have access only to publicly
available information for a given asset. Moreover, it is quite possible that
these agents do not assimilate all publicly available information due to
their processing constraints. The major constraints in this regard may be
cost of accessing information, time constraints etc.
2. Superior (Informed) Agents: These agents have access to information
beyond public domain. They may also have superior information

11. 10
processing capabilities involving quick access to information, expertise to
understand the asset traded etc. Such agents, in sum, have a sustainable
competitive advantage as participants in the financial markets against
their average informed counterparts.
It is on these grounds, that we hypothesize that the informed agents can
produce excess returns consistently due to their competitive advantage in the
market. The information asymmetry should theoretically place them ahead of
their less informed counterparts. Hence, the following hypothesis:
Hypothesis 1: Portfolios constructed by superior informed agents should
demonstrate greater returns than those produced by average informed agents.
Moreover, in order to test our hypothesis, we would need instances where the
superior informed agents had high informational advantage. It is for this
purpose, we need to identify instances of maximum information asymmetries in
the market place. Looking into literature in the area, a study by Ivković and
Weisbenner (2004) state that the excess return for investors investing in local
stocks, is particularly large for stocks not included in the S&P 500 Index, in
regard to which informational asymmetries between local and non-local investors
may be the largest. Thus, our second hypothesis in this regard:

12. 11
Hypothesis 2: Degree of information asymmetry is directly proportional to
magnitude of excess returns produced.
V. Research Design
This section deals with laying out the structure of the research done under three
broad heads, the variables chosen for the study, the source of the data and the
methodology to arrive at the results.
(a) Variables
For the purpose of our study, we chose relevant proxies for superior informed
agents and instances of high information asymmetries.
The proxy for superior informed agents in our study shall be management of a
company. It is assumed that the management has better insights in the business
it manages than an average informed investor that has access to public domain
information only. Further, management has an ability to better process the
information available regarding their company as compared to an average
investor due to advantages in cost of acquiring information and more relaxed
time constraints. Hence, the management of the company has better
understanding of the underlying business of a company and can better forecast
the operating performance of the business.

13. 12
The second proxy is for instances of high information asymmetries in the market
place. Literature suggests that the companies that are not a part of major indices
and have relatively less number of analysts following them have higher
information asymmetries. This is because a major part of the public domain
information and analysis is provided by analysts at brokerage houses and
investment funds for their clients. For smaller and relatively unknown companies,
the sources of reliable public information are few and may be sometimes limited
to only financial statements, annual reports and shareholder general meetings.
Thus, in such scenarios, the company’s traded volumes also remain low and
relatively higher percentage of the trades are performed by agents who have
some superior insights as a cause of their trade. Hence, we have companies with
relatively low trading volumes as proxies for assets that have high information
asymmetry.
(b) Data
Bloomberg Professional Services Terminal was used to collect data for the test.
Equity Screening was done to find companies that rank high on the decided ratio.
The screening criteria included companies that were a part of an Indian Stock
Exchange; had management buying a considerable stake in the company that it
gets reported and ranked in top 125 companies on the basis of decided ratio and
had the Bloomberg services covering them.

14. 13
(c) Methodology
Our study involves construction of portfolios whose assets are selected based on
superior informational advantage and in circumstances where the gap of
information between superior informed and average informed agents is
maximum. To achieve this objective, we device the following ratio which shall
be used to select companies for our portfolio:
𝑀𝑎𝑛𝑎𝑔𝑒𝑚𝑒𝑛𝑡 𝐵𝑢𝑦 𝑉𝑜𝑙𝑢𝑚𝑒 𝑓𝑜𝑟 𝑆𝑒𝑐𝑢𝑟𝑖𝑡𝑦 𝑋 𝑖𝑛 𝑚𝑜𝑛𝑡ℎ 𝑌
𝑇𝑜𝑡𝑎𝑙 𝑉𝑜𝑙𝑢𝑚𝑒 𝑇𝑟𝑎𝑑𝑒𝑑 𝑜𝑓 𝑆𝑒𝑐𝑢𝑟𝑖𝑡𝑦 𝑋 𝑖𝑛 𝑚𝑜𝑛𝑡ℎ 𝑌
Examining all Indian securities on this parameter, we shall be selecting assets
that rank high on the stated ratio. The stated ratio ensures that the securities
that are thinly traded are and have relatively high management buy share for a
month get added to the portfolio. Further, it was ensured that the management
buy volume came from management buying from open market in anticipation of
capital appreciation indicating strong business prospects and not from exercise
of ESOPs that may be quite unrelated to business performance forecasts.
Such portfolios have been constructed for every month from November 2009 to
October 2014 creating 60 instances of portfolios constructed with such superior
informational advantage. Each of these 60 portfolios represent a different time
frame and their performance is tested against the performance of the benchmark
for the concerned time frame. The benchmark for the purpose of the study has

15. 14
been chosen as BSE 500 index as it makes a fair representation of the market
both in terms of number of stocks chosen and the breadth of the securities on
basis of market capitalization to industries covered.
The monthly returns achieved for each of the 60 portfolios were recorded and
compared against the benchmark return. Excess returns (Portfolio return –
Benchmark Return) was calculated for each of the 60 instances. The average of
these excess returns was calculated which represents the average performance
of these portfolios constructed on basis of this strategy of the specified.
This excess return was statistically tested for significance to see if the results
obtained are significant to prove that such portfolios offer superior return.
VI. Results
The t-test results on the significance of excess returns proves that the returns
of the constructed portfolio are superior of the returns obtained by the
benchmark at 99.9% confidence level. The summarized results of the test are
presented below:
Average Monthly Returns of Constructed Portfolio 2.96%
Average Monthly Returns of Benchmark 1.74%
Average Excess Returns 1.22%
Standard Deviation of Excess Returns 2.27%

16. 15
T-Stat for Significance of Excess Returns 4.181
Confidence Level of Significance of Results 99.98%
Thus, the study proves that the portfolios constructed with superior
informational advantage in instances of high information asymmetry beat the
market. Now, studying the implications of this result, the first conclusion is that
the market is not strongly efficient in the sense Fama (1970) defined strong
efficiency. This makes practical sense as strong efficiency in markets if proved
would make all insider trading and anti-trust laws useless.
Secondly, analyzing the portfolios so constructed, it should be kept in mind that
no conscious efforts were made to diversify them on the basis of industrial
composition, number of stocks etc. to reduce unsystematic risk. Hence, as
expected the standard deviations of the returns of these portfolios is more than
that of the benchmark. The standard deviation of the portfolios and the
benchmark was found as below:
Standard Deviation of Constructed Portfolio Returns 3.069%
Standard Deviation of Benchmark Returns 0.999%
However, it should be noted that the number of stocks in these portfolios is fairly
large and still the standard deviation of the returns in our constructed portfolio

17. 16
is significantly more than the standard deviation of the benchmark that too at
high confidence levels.
The number of stocks in each of the 60 constructed portfolios is given as under:
Portfolio Beginning No. of Stocks Portfolio Beginning No. of Stocks
November 2009 7 May 2012 44
December 2009 14 June 2012 59
January 2010 13 July 2012 49
February 2010 10 August 2012 60
March 2010 10 September 2012 67
April 2010 20 October 2012 57
May 2010 5 November 2012 51
June 2010 10 December 2012 58
July 2010 17 January 2013 51
August 2010 18 February 2013 77
September 2010 15 March 2013 109
October 2010 16 April 2013 106
November 2010 16 May 2013 72
December 2010 26 June 2013 80
January 2011 16 July 2013 97
February 2011 27 August 2013 123
March 2011 52 September 2013 107
April 2011 31 October 2013 83
May 2011 17 November 2013 62
June 2011 21 December 2013 71
July 2011 29 January 2014 73
August 2011 32 February 2014 66
September 2011 43 March 2014 102
October 2011 40 April 2014 116
November 2011 34 May 2014 66
December 2011 52 June 2014 57
January 2012 51 July 2014 50
February 2012 25 August 2014 43
March 2012 39 September 2014 48
April 2012 53 October 2014 46

18. 17
We observe that the average number of stocks in the portfolio is 48.5 which is
quite high to diversify most of the component of unsystematic risk. The observed
beta of the portfolio is 2.65. Literature in portfolio theory suggests that it is
usually difficult to produce statistically significant alphas if we have large number
of stocks in a portfolio. However, the excess returns the portfolio has produced
have certainly backing of strong information asymmetries that the portfolio has
exploited resulting in superior returns.
Also, it can be argued that the risk adjusted returns of these portfolio should
also be statistically superior. However, it should be noted that the conventional
methods to measure risk here should not be used as they primarily rely on
standard deviation as a measure of risk. In our case, all risk measures based on
the variation of returns will yield low risk adjusted returns because of the nature
of our strategy. We had consciously chosen stocks that trade thinly which directly
implied that any trading will cause heavy price movements and thus high
volatility.
We should understand that the investments made by the management in their
company are essentially with a long term horizon and monthly deviation of
returns would not be much relevant. These investments are usually based on
long term forecasts regarding the performance of the business and hence the

19. 18
performance should also be measured over same horizon and not on a daily or
monthly basis.
VII. Conclusion
The result provides evidence that it can be economically rational for an investor
to invest in stocks he knows about well, i.e., in stocks in which he has a
competitive advantage based on strong information asymmetry and avoid
unnecessary diversification.
This result also explains several biases that have been documented that are
considered a deviation from rational portfolio economics. First, the home equity
biases in which national aggregate equity portfolios are heavily weighted with
domestic assets, could be rationally justified as domestic investors may be
having a competitive advantage on home stocks in terms of information and our
study documents that such a strategy also provides superior returns in the long
run. Similarly, tendency of investors to invest in assets highly correlated to their
non-financial income such as concentrated investment in industry one works in,
investment in employer’s equity or equity of employer’s competitors could be
explained on similar lines.
In sum, concentrated portfolios with strong informational advantage should be
preferred over well diversified portfolios constructed with public information.

20. 19
References
Barber, Brad, and Terrance Odean, 2000, Trading is hazardous to your wealth:
The common stock investment performance of individual investors, Journal of
Finance 55, 773-806.
Barber, Brad, and Terrance Odean, 2001, Boys will be boys: Gender,
overconfidence, and common stock investment, Quarterly Journal of Economics
116, 261-292.
Benartzi, Shlomo, 2001, Excessive extrapolation and the allocation of 401(k)
accounts to company stock, Journal of Finance 56 (5), 1747-1764.
Carhart, Mark M., 1997, On persistence in mutual fund performance, Journal of
Finance 52, 57-82.
Coval, Joshua D., David Hirshleifer, and Tyler Shumway, 2002, Can individual
investors beat the market?, Working Paper, University of Michigan.
Fama, Eugene F., and Kenneth R. French, 1992, The cross section of expected
returns, Journal of Finance 47, 427-465.
Fama, Eugene F., and J. MacBeth, 1973, Risk, return, and equilibrium: Empirical
tests, Journal of Political Economy 71, 607-636.

21. 20
French, Kenneth R., and James M. Poterba, 1991, Investor diversification and
international equity markets, American Economic Review 81, 222-226.
Ivkovi´c, Z. and S. Weisbenner, 2005, Local does as local is: Information content
of the geography of individual investors’ common stock investments, The Journal
of Finance, 60 (1), 267–306.
Kacperczyk, Marcin, Clemens Sialm, and Lu Zheng, 2004, On the industry
concentration of actively managed equity mutual funds, Journal of Finance,
forthcoming.
Kelly, Morgan, 1995, All their eggs in one basket: Portfolio diversification of US
households, Journal of Economic Behavior and Organization 27, 87-96.
Liang, Nellie and Scott Weisbenner, 2002, Investor behavior and the purchase
of company stock in 401(k) plans – The importance of plan design. NBER
Working Paper 9131.
Odean, Terry, 1998, Are investors reluctant to realize their losses?, Journal of
Finance 53, 1775-1798.
Odean, Terry, 1999, Do investors trade too much?, American Economic Review
89 (5), 1279-1298.
Zhu, Ning, 2002, The local bias of individual investors, Working Paper, Yale
School of Management.