SBI MAGNUM TAXGAIN 1993 SCHEME-Part 1

Investment Objective
The prime objective of scheme is to deliver the benefit of investment in a portfolio of equity shares, while offering tax rebate on such investments made in the scheme under section 80 C of the Income-tax Act, 1961. It also seeks to distribute income periodically depending on distributable surplus.
Asset Allocation
Instrument % of Portfolio of Plan A & B Risk Profile
Equity,PCD’s and FCD’s and bonds 80-100% Medium to High
Money market instruments 0 – 20% Low
Scheme Highlights
1. There is a statutory lock-in period of three years for investments in a Tax Saving Scheme (irrespective of the fact whether the investors claim the rebate u/s 80C or any other section or not).

2. Dividends may be declared depending on distributable profits of the scheme. Facility to reinvest dividend proceeds into the scheme at NAV.

3. Switchover facility to any other open-ended schemes of SBI Mutual Fund at NAV related prices available after the statutory lock-in period.

Launch Date

Minimum Application

March 31, 1993 Rs. 500 and Multiples of Rs 500

Entry Load

Exit Load

Investments below Rs. 5 crores – 2.25% Investments of Rs.5 crores and above – NIL
Nil

SIP

SWP
Rs.500/month – 12 months Rs.1000/month – 6months Rs.1500/quarter – 12 months
A minimum of Rs. 500 can be withdrawn every month or quarter by issuing advance instructions to the Registrars at any time. This facility is available only after the lock-in period of three years.
Nav’s
Plan

Latest Nav

Date
Magnum Tax Gain Scheme – 1993 – Dividend 41.4 11/04/2008
Magnum Tax Gain Scheme – 1993 – Growth 50.95 11/04/2008

Related Posts Only (manually created not automatically generated)

Latest NAV of/for SBI Magnum TaxGain ELSS Scheme-Updated Daily
elss schemes comparision 16-may-2008
elss performance report nov 2007
elss comparision aug 2007
sbi magnum taxgain dividend history
sbi equity schemes form
sbi magnum taxgain equity linked savings scheme elss
sbi magnum taxgain elss equity linked savings scheme elss
sbi tax advantage fund series 1

Principal MF

Advertisements

ULIP vs MF(Part 2)

ULIP vs MF

If an insurance company comes up with a low-cost product, they fear losing out on business.

It’s not easy to choose the best Ulip. When a person needs to advise a client on which mutual fund to invest, he can check websites to know the best-performing schemes over three to five years.

But there is nothing like that available for Ulips.

Also, since the expense structure of each Ulip is different, any comparison between the performances of different Ulips is not possible.

So, why do people invest in Ulips? Last year more than Rs 31,000 crore came into Ulips, which now account for around 56% of the total new premia coming into insurance policies.

The idea of a packaged product that offers both equity returns and insurance it seems seduces investors.

The primary reason why people buy Ulips is because of mis-selling. Agents tell people they have the option of paying a premium for only three years, when the actual term of most Ulips is at least 10 years. It works as a good selling point.

Most Ulips have a cover continuation option, which essentially ensures that even if the individual is not able to continue paying premia anytime after the first three years, the policy continues.

The insurance agents, though, have turned this into a selling point, giving an impression to investors that they have an option to stop paying premia after three years, which is really not the case.

An investor who decides to stop paying premia after three years hardly benefits; after three years, the expenses are less and more of the premium gets invested.

ULIP vs MF(Part 1)

ULIP vs MF

Investor paid a premium of Rs20,000 to invest in a unit linked insurance plan (Ulip) in October 2005. At the end of one year, when he received the policy statement, he was surprised to see that the total value of his investment was just Rs9,075. He wondered where the balance Rs10,925 had gone.

Ulips are insurance policies which club insurance and investment. Usually, an individual taking a Ulip has 4-6 choices, ranging from funds investing 100 per cent in equity to those investing 100 per cent in debt securities.

Other than this, the policy-holder gets an insurance cover as well, for which the insurance company levies a monthly charge.

What investor did not know is that the entire Rs20,000 he had invested would not be invested.

There were expenses to be paid. In the first year of his ULIP Policy, the insurance company had made an allocation charge of 25 per cent of the premium paid. What this meant was that of the Rs20,000 he had paid, only Rs15,000 was invested.

Other outgos(charges), like policy administration charge, and fund management charge, had ensured that instead of his money growing in value, it had shrunk.

The premium allocation charge in the first year of the policy varies from 15 per cent to 71 per cent of the premium paid, depending on the Ulip chosen. So, why do Ulips have such a high upfront charge?

Historically, insurance commissions have always been high. The insurance industry tends to justify this practice, using the defence that selling insurance is tougher than selling other financial products.

While this itself is arguable, in any case, since these commissions are deducted from the investment, it is the investor who suffers.

Five pointers to Mutual Fund performance

Five pointers to Mutual Fund performance

More often than not meritocracy of investments is often decided by the returns. Quite simply then a fund generating more returns than the other is considered better than the other.

But this is just half the story.

What most of us would appreciate is the level of risk that a fund has taken to generate this return? So what is really relevant is not just performance or returns. What matters therefore are Risk Adjusted Returns.

The only caveat whilst using any risk-adjusted performance is the fact that their clairvoyance is decided by the past. Each of these measures uses past performance data and to that extent are not accurate indicators of the future.

As an investor you just have to hope that the fund continues to be managed by the same set of principles in the future too.

Standard Deviation

The most basic of all measures- Standard Deviation allows you to evaluate the volatility of the fund. Put differently it allows you to measure the consistency of the returns.
Volatility is often a direct indicator of the risks taken by the fund. The standard deviation of a fund measures this risk by measuring the degree to which the fund fluctuates in relation to its mean return, the average return of a fund over a period of time.
A security that is volatile is also considered higher risk because its performance may change quickly in either direction at any moment.
A fund that has a consistent four-year return of 3%, for example, would have a mean, or average, of 3%. The standard deviation for this fund would then be zero because the fund’s return in any given year does not differ from its four-year mean of 3%. On the other hand, a fund that in each of the last four years returned -5%, 17%, 2% and 30% will have a mean return of 11%. The fund will also exhibit a high standard deviation because each year the return of the fund differs from the mean return. This fund is therefore more risky because it fluctuates widely between negative and positive returns within a short period.

Beta

Beta is a fairly commonly used measure of risk. It basically indicates the level of volatility associated with the fund as compared to the benchmark.
So quite naturally the success of Beta is heavily dependent on the correlation between a fund and its benchmark. Thus if the fund’s portfolio doesn’t have a relevant benchmark index then a beta would be grossly inadequate.

A beta that is greater than one means that the fund is more volatile than the benchmark, while a beta of less than one means that the fund is less volatile than the index. A fund with a beta very close to 1 means the fund’s performance closely matches the index or benchmark.
If, for example, a fund has a beta of 1.03 in relation to the BSE Sensex, the fund has been moving 3% more than the index. Therefore, if the BSE Sensex increased 10%, the fund would be expected to increase 10.30%.Investors expecting the market to be bullish may choose funds exhibiting high betas, which increase investors’ chances of beating the market. If an investor expects the market to be bearish in the near future, the funds that have betas less than 1 are a good choice because they would be expected to decline less in value than the index.

R-Squared

The success of Beta is dependent on the correlation of a fund to its benchmark or its index. Thus whilst considering the beta of any security, you should also consider another statistic- R squared that measures the Correlation.

The R-squared of a fund advises investors if the beta of a mutual fund is measured against an appropriate benchmark. Measuring the correlation of a fund’s movements to that of an index, R-squared describes the level of association between the fund’s volatility and market risk, or more specifically, the degree to which a fund’s volatility is a result of the day-to-day fluctuations experienced by the overall market.

R-squared values range between 0 and 1, where 0 represents no correlation and 1 represents full correlation. If a fund’s beta has an R-squared value that is close to 1, the beta of the fund should be trusted. On the other hand, an R-squared value that is less than 0.5 indicates that the beta is not particularly useful because the fund is being compared against an inappropriate benchmark.

Alpha

Alpha = (Fund return-Risk free return) – Funds beta *(Benchmark return- risk free return).

Alpha is the difference between the returns one would expect from a fund, given its beta, and the return it actually produces. An alpha of -1.0 means the fund produced a return 1% higher than its beta would predict. An alpha of 1.0 means the fund produced a return 1% lower. If a fund returns more than its beta then it has a positive alpha and if it returns less then it has a negative alpha.
Once the beta of a fund is known, alpha compares the fund’s performance to that of the benchmark’s risk-adjusted returns. It allows you to ascertain if the fund’s returns outperformed the market’s, given the same amount of risk.
The higher a funds risk level, the greater the returns it must generate in order to produce a high alpha.

Normally one would like to see a positive alpha for all of the funds you own. But a high alpha does not mean a fund is doing a bad job nor is the vice versa true. Because alpha measures the out performance relative to beta. So the limitations that apply to beta would also apply to alpha.
Alpha can be used to directly measure the value added or subtracted by a fund’s manager.
The accuracy of an alpha rating depends on two factors: 1) the assumption that market risk, as measured by beta, is the only risk measure necessary; 2) the strength of fund’s correlation to a chosen benchmark such as the BSE Sensex or the NIFTY.

Sharpe Ratio

Sharpe Ratio= Fund return in excess of risk free return/ Standard deviation of Fund

So what does one do for funds that have low correlation with indices or benchmarks? Use the Sharpe ratio. Since it uses only the Standard Deviation, which measures the volatility of the returns there is no problem of benchmark correlation.
The higher the Sharpe ratio, the better a funds returns relative to the amount of risk taken.
Sharpe ratios are ideal for comparing funds that have a mixed asset classes. That is balanced funds that have a component of fixed income offerings.