Fund Manger’s Performance in Equity & Debt Schemes of Unit Trust of India

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Emperor International Journal of Finance and Management Research [EIJFMR] ISSN: 2395-5929

Emperor International Journal of Finance and Management Research [EIJFMR] ISSN: 2395-5929 Page 102

FUND MANGER’S PERFORMANCE IN EQUITY & DEBT SCHEMES OF

UNIT TRUST OF INDIA

Dr. G. UPPILI SRINIVASAN,

Assistant Professor – II, Exam Wing,

SASTRA University, Tanjore, Tamilnadu

Dr.K. KALAICHELVI,

Assistant Professor & Head, PG & Research Department of Commerce,

Bharathidasan University Constituent College, Orathanadu.

Mr. V.

ANANDAVEL,

Assistant Professor of Management Studies,

Kongu Engineering College, Perundurai.

Abstract

The performance of mutual fund portfolios

has been the subject of extensive

examination in the literature of finance.

Performance evaluation measures of this

sort have typically employed a one

parameter risk return benchmark like those

developed by different scholars. Such

investigations have effectively focused on

fund manager’s security selection skills

diversification etc. These are referred to as

micro security selection skills. Apart from

that portfolio manager’s performance might

also achieve better performance in terms of

return by engaging in successful macro

market timing activities. A fund manager

should be efficient enough to foresee these

changes in the market, or in other words,

enter into transactions in the market at the

most appropriate time. This is what is

referred to as the timing ability of the fund

manager. This paper also made an attempt to

evaluate the market timing ability of the

fund managers of UTI with reference to its

select schemes on the basis of Treynor &

Mazuy and Hendrickson and Merton

method. For this purpose the models

developed and tested by experts have been

made use of.

Keywords: Market Timing Ability, Fund

Managers, Open & Closed end Schemes

Inroduction

“The most important quality for an

investor is temperament, not intellect.”

- Warren Buffett

The Mutual fund market added a new

dimension in 1993 with the opening up of it

(9)

investors. Now-a-days private as well as

public, domestic as well as foreign sector,

38 Mutual funds players are in the market

with total investible funds for Rs. 6,13,979

crore and having a number of 882 schemes,

out of which 641 schemes are open ended.

Mutual funds are ideal vehicles for

individual investors who don’t have the

time, willingness or ability to manage their

own portfolio. Now these days’ different

types of Mutual fund schemes are available

in the market, which provide aggressive

return to an aggressive investor at a level of

risk. But an unknown investor is not aware

about how to mobilize funds in the market &

judge the ability of a fund manager. The

performance of mutual fund portfolios has

been the subject of extensive examination in

the literature of finance. Performance

evaluation measures of this sort have

typically employed a one parameter risk

return benchmark like those developed by

different scholars. Such investigations have

effectively focused on fund managers

security selection skills diversification (or

lack thereof) etc. These are referred to as

micro security selection skills. Fama (1972)

and Jensen (1972) addressed these issues

and pointed out the empirical measurement

problems involved in evaluating properly by

the constituents in investment performance

when portfolio risk levels are non stationary. “The four most dangerous words in

investing: „this time it‟s different.‟”

- Sir John Templeton

It may be possible that fund managers, in

addition to using stock selection techniques,

might also generate superior performance by

timing the market correctly. In an active

sense market timing implies altering the beta

of the portfolio return by balancing the bond

and equity composition of the mutual fund.

In a passive sense, it involves a shift in the

allocation between debt securities and equity

securities. This basically means, when the

market is unfavorable or in the down trend,

the fund managers should shift their

positions from equity to debts securities and

when the market is favourable or up trend, it

would be beneficial to liquidate debt and

commit to equity. A fund manager should

be efficient enough to foresee these changes

in the market, or in other words, enter into

transactions in the market at the most

appropriate time. This is what is referred to

as the timing ability of the fund manager. A

number of studies, as mentioned in the

review of literature have established some

evidence that mutual fund portfolios do not

in fact maintain a constant risk posture over

(10)

timing may well be a dimension of fund

manager’s decision process.

Review of Literature

Deepak Agrawal (2007) in his paper

provides an overview of mutual fund

activity in India. He also analyzes data at

both the fund-manager and fund-investor

levels. The study revealed that the

performance of the Mutual Fund Industry in

India is affected by saving and investment

habits of the people on one hand and on the

second side, the confidence and loyalty of

the fund Manager.

Soumya Guha Deb (2008) focuses on

return-based style analysis of equity mutual funds

in India using quadratic optimization of an

asset class factor model proposed by

William Sharpe The study analyzes the

relative performance of the funds with

respect to their style benchmarks. The

results of the study show that the funds have

not been able to beat their style benchmarks

on the average.

Rao D.N. and Rao S.B. (2009) conducted

research on the general perception among

Indian Investors and Fund Managers that

(A) Market outperforms Balanced and

Income Funds during Bull run (B) Balanced

and Income Funds outperform the stock

market during Bear run (C) Market

outperforms Balanced and Income Funds

over a long holding period (a minimum

period of three years). The objective of the

study was to empirically investigate whether

the above stated perceptions are valid in the

Indian context. For this purpose, six

hypotheses were tested. The performance of

the Balanced and 72 Income Funds were

analyzed in terms of Return, Risk, Return

per Risk and Sharpe ratio over the three

years, 2006, 2007 and 2008 during which

period the Indian Stock Market had

witnessed much volatility. Further, the

performances of these funds were compared

with that of the Market and Benchmark

Indices. The Null Hypotheses were rejected

leading to the acceptance of Alternate

Hypothesis in all the six cases, This led to

the conclusion that the Market outperformed

both the Balanced and Income Funds over

Bull Run and 3 year period while both the

funds outperformed the Market over Bear

run period which confirms the popular belief

of the Investors and Fund Managers in India.

Treynor and Mazuy (2010) evaluated the

performance of 57 fund managers in terms

of their market timing abilities and found

that, fund managers had not successfully

outguessed the market. The results

suggested that, investors were completely

dependent on fluctuations in the market. The

(11)

methodology for reviewing the performance

of mutual funds.

Deepthi Fernando et al. (2011), in a World

Bank Policy Research Working Paper

observe that, with few exceptions, mainly in

Asia, mutual funds grew explosively in most

countries around the world during the 1990s.

Some of the important findings of her study

are-Legal origin are significantly correlated

with mutual fund development. Equity funds

are more advanced in common law

countries, while bond funds are more

developed in countries with civil law

systems. Higher market returns and liquidity

and lower volatility have also contributed to

mutual fund growth.

Ajay Khorana, Henri Servaes, and Peter

Tufano (2012) studied the mutual fund

industry in 56 countries and examined where

this financial innovation has flourished. The

fund industry is larger in countries with

stronger rules, laws, and regulations and

specifically where mutual fund investors' rights

are better protected. The industry is also larger

in countries with wealthier and more educated

populations, where the industry is older, trading

costs are lower and in which defined

contribution pension plans are more prevalent.

The industry is smaller in countries where

barriers to entry are higher. These results

indicate that laws and regulations, supply-side

and demand-side factors simultaneously affect

the size of the fund industry.

Jensen (2012) developed a composite

portfolio evaluation technique concerning

risk-adjusted returns. He evaluated the

ability of 115 fund managers in selecting

securities during the period 1945-66.

Analysis of net returns indicated that, 39

funds had above average returns, while 76

funds yielded abnormally poor returns.

Using gross returns, 48 funds showed above

average results and 67 funds below average

results. Jensen concluded that, there was

very little evidence that funds were able to

perform significantly better than expected as

fund managers were not able to forecast

securities price movements.

Objectives of the Study

Performance assessment of financial

securities and mutual fund schemes is to be

based in analyzing the return and risk on

such securities. Several models have been

suggested by financial researchers, which

assess specific aspect of performance of

funds. The specific objectives of the study

are:

1. To assess performance in terms of

various abilities of fund managers

using appropriate models and by

(12)

2. To assess the select open ended and

closed end scheme’s performance

based on market timing ability of

fund managers.

3. To draw conclusions based on the

findings.

Methodology

The total number of schemes selected for the

study is 15. It is classified as open and

closed ended schemes. It is seen that the

maximum number of schemes outstanding at

any point of time during the study period.

All the schemes were considered for

analysis especially equity and debt schemes.

The schemes satisfying these criteria

numbered 15. The schemes selected for the

study, its classification and the percentage of

schemes selected to the total is show in table

1. This comprises of 71% of the open ended

schemes (10) and 29% of closed end

schemes (5). Out of 10 open ended schemes

(5) from equity and (5) from debt on the

other hand out of 7 closed end schemes all

from equity.

Table – 1 Scheme selected for the analysis

Types of schemes

Equity Debt Total

Open ended 5 5 10

Close ended 5 - 5

Total 10 5 15

Computed

Annual Reports of UTI

Data Collection

The study is based on secondary data. The

data were collected from published

documents and the annual reports of the UTI

schemes. The NAV resale prices and

repurchased prices announced by the

institution and published widely from time

to time were the basic data. Other necessary

information was also collected from the

Center for Monitoring Indian Economy

Reports and dailies like The Hindu,

Business Line and the Economics Times and

also from Association of Mutual funds

Industry (AMFI) newsletters. The relevant

literature was collected from related books,

journals and magazines. The collected data

were analysed to measure the performance

of UTI, applying the models developed by

experts.

Tools of analysis

In the process of measuring performance of

the schemes statistical tools as suggested by

earlier researchers have been used. The

analysis is made categorizing the data and

applying the recommended tools.

Particularly to analyse the market timing

ability of fund managers and schemes

Treynor & Mazuy model is applied.

(13)

The yield on 91 days T bills has been used

as a surrogate for risk free return as has been

the accepted practice in most of the studies

at the national and international level.

Market Return and Risk

For calculating market return and risk the

Bombay stock exchange index is treated as

the Benchmark portfolio for use in the

models. There are many other indices,

which are also eligible to be considered as

equivalent. But since this index covers

securities compatible with mutual funds, this

is considered as more appropriate and used

as the bench mark measure.

Scope and limitations of the study

Performance in general is multi faceted with

reference to UTI. Performance may be dealt

with regard to many aspects. They are first,

managerial efficiency involving the

functional efficiency of the managers like

finance, marketing, personal etc. Secondly

another aspect with specific reference to

UTI is its mobilization of funds through sale

of units or schemes. The third aspect is with

regards to the portfolio management

efficiency of the fund managers. This study

is confined to the third aspect namely

assessing the performance of market timing

ability of fund managers and schemes.

Analysis and discussion

Treynor & Mazuy suggested a slightly

difference methodology for testing market

timing ability. This test enables the

separation of the gains of market timing

skills from the gains of micro stock selection

skills.

(R

pt

– R

ft

) = α + β (R

mt

– R

ft

) + γ

(R

mt

– R

ft

)

2

+ e

it

Where Rpt is the return on fund period t.

Rmt is the return on the market index

in period t

Rft is the return on the risk less asset

in period t

E it is the residual return in period t

γt = max (0, Rmt - Rft)

α, β and γ are constants.

Table – 2 Number of schemes as per γ

values of treynor and mazuy model

Category Open ended

Closed end

objective γ

> 0

γ = 0

γ > 0

γ = 0

equity 4 1 3 2 debt 3 2 - - total 7 3 3 2 Source: Appendix

γ is the measure of the funds timing ability

and will be zero if there is no market timing.

If it is positive it means that market timing

ability exists. The calculated data was used

(14)

model and the γ values arrived at, relating to

the 15 schemes. The data has been

classified as number of schemes with

positive and zero γ values. It could be seen

from the table that, a total of 15 schemes 7

schemes show positive gamma values of

which are open ended schemes and 3are

closed end schemes. Out of 7 open ended

schemes 4 are equity, 3 are debt schemes.

Out of 3 schemes all 3 schemes are open

ended schemes. Of the 3 schemes 1 is

equity and 2 are debt schemes. Out of

5closed end schemes all are equity schemes.

Out of 5 schemes 3 schemes shows greater

than γ values. Remaining 2 schemes shows

equal to γ values.

A performance during the study periods

shows that there has been good timing

ability exhibited by the fund managers.

During the study period 70% of the schemes

show good market timing ability. The fund

managers have shown good timing ability in

the case of open ended schemes, but there

had been a decline in efficiency with regard

to equity schemes. What the results of the

application of these models indicate is that

the fund managers, though have shown good

timing ability it had been lesser during the

latter period. It is a partly good sign of fund

managers of the UTI.

Findings

1. 10 schemes show positive γ values,

which constitute 66% and shown good

timing ability during the study period.

2. Out of 15 schemes 10 schemes shows

positive γ values and remaining 5 schemes shows equal to γ values.

3. Out of 15 schemes 10 are open ended

and 4 are closed end schemes.

4. Out of 10 open ended schemes 4 are

equity, 3 are debt schemes.

5. Out of 5 closed end schemes all are

equity schemes.

6. Out of 15 schemes 5 schemes are shows

equal to γ values. Out of 5 schemes 3 are

open ended schemes and 2 are closed

end schemes. Out of 3 schemes 1 from

equity schemes and 2 are from debt

schemes. Out of 2 closed end schemes

both are equity schemes.

Conclusion

From the foregoing analysis a good

conclusion could be arrived at. What

the results of the application of these

models indicate is that the fund

managers shown good timing ability.

Better performance has been shown by

the market timing ability of fund

managers. Though the number of

schemes shown positive value the

(15)

schemes are negative. But the fact

remains that investor’s trust had not been

honoured which does not speak well

about the institution. With regard to

these schemes the basic ability of

analyzing the market and acting swiftly,

which is expected to be acquired from

out of experience in the stock market on

the part of the fund managers, has been

exhibited.

References

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Abilities of Indian Mutual Fund

Manager: An Empirical Study”, Applied

Finance, Vol.6, No.2, PP. 47-61.

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Performance of Indian Mutual Funds,"

Prabhandan Taniknigui, 1(1),

September, 2012, p.ll,

ssrn.com/abstract=1311761.

3. Bapna, Yogesh Mehta and Vishal Sood,

“Mutual Fund Performance”, Journal of

Business, 39, No.1, Jan, pp. 119-138.

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Sulla, Victor and Vittas, Dimitri, "The

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