fund

Best mutual fund SIP portfolios to invest in November 2024


Many mutual fund investors, especially new investors, are often confused about how to pick a bunch of schemes to take care of their various goals, especially for long-term goals like retirement. They keep looking for a ready-made mutual fund portfolio to achieve their long-term goals. Here is some help for such investors. We have put together a slew of schemes, based on risk profile, time horizon, and the amount you want to invest.

ETMutualFunds launched its recommended mutual fund portfolios to invest through SIPs in October 2016. Since then, we have been closely monitoring the schemes in these portfolios and coming up with updates on them regularly. We also inform our readers about poorly performing schemes and replacements for them. The schemes in these ready made portfolios are selected based on our in-house methodology mentioned at the end of this article.

ETMutualFunds’ best mutual fund SIP portfolios are meant for three different individual risk profiles: conservative, moderate and aggressive. We have also considered three SIP baskets – between Rs 2,000-5,000, between Rs 5,000-10,000 and above Rs 10,000 – while creating these portfolios. Take a look at our recommended portfolios.

Here are our recommended SIP portfolios for November 2024:

Recommended portfolio for conservative investors:

conservativeET Online

Recommended portfolio for moderate investors:

Moderate1ET Online

Recommended portfolio for aggressive investors:

AggressiveET Online

Methodology for equity funds:

ETMutualFunds has employed the following parameters for shortlisting the equity mutual fund schemes.
1. Mean rolling returns: Rolled daily for the last three years.

2. Consistency in the last three years: Hurst Exponent, H is used for computing the consistency of a fund. The H exponent is a measure of randomness of NAV series of a fund. Funds with high H tend to exhibit low volatility compared to funds with low H.

i) When H = 0.5, the series of returns is said to be a geometric Brownian time series. This type of time series is difficult to forecast.

ii) When H is less than 0.5, the series is said to be mean reverting.

iii) When H is greater than 0.5, the series is said to be persistent. The larger the value of H, the stronger is the trend of the series

3. Downside risk: We have considered only the negative returns given by the mutual fund scheme for this measure.

X =Returns below zero

Y = Sum of all squares of X

Z = Y/number of days taken for computing the ratio

Downside risk = Square root of Z

4. Outperformance: It is measured by Jensen’s Alpha for the last three years. Jensen’s Alpha shows the risk-adjusted return generated by a mutual fund scheme relative to the expected market return predicted by the Capital Asset Pricing Model (CAPM). Higher Alpha indicates that the portfolio performance has outstripped the returns predicted by the market.

Average returns generated by the MF Scheme =

[Risk Free Rate + Beta of the MF Scheme * {(Average return of the index – Risk Free Rate}

5. Asset size: For Equity funds, the threshold asset size is Rs 50 crore.

Methodology for debt funds:

1. Mean rolling returns: Rolled daily for the last three years.

2. Consistency in the last three years: Hurst Exponent, H is used for computing the consistency of a fund. The H exponent is a measure of randomness of NAV series of a fund. Funds with high H tend to exhibit low volatility compared to funds with low H.

i) When H = 0.5, the series of returns is said to be a geometric Brownian time series. This type of time series is difficult to forecast.

ii) When H is less than 0.5, the series is said to be mean reverting.

iii) When H is greater than 0.5, the series is said to be persistent. The larger the value of H, the stronger is the trend of the series

3. Downside risk: We have considered only the negative returns given by the mutual fund scheme for this measure.

X =Returns below zero

Y = Sum of all squares of X

Z = Y/number of days taken for computing the ratio

Downside risk = Square root of Z

4. Outperformance: Fund Return – Benchmark return. Rolling returns rolled daily is used for computing the return of the fund and the benchmark and subsequently the Active return of the fund.

5. Asset size: For Debt funds, the threshold asset size is Rs 50 crore.

Methodology for hybrid funds:

1. Mean rolling returns: Rolled daily for the last three years.

2. Consistency in the last three years: Hurst Exponent, H is used for computing the consistency of a fund. The H exponent is a measure of randomness of NAV series of a fund. Funds with high H tend to exhibit low volatility compared to funds with low H.

i) When H = 0.5, the series of returns is said to be a geometric Brownian time series. This type of time series is difficult to forecast.

ii) When H

iii) When H>0.5, the series is said to be persistent. The larger the value of H, the stronger is the trend of the series

3. Downside risk: We have considered only the negative returns given by the mutual fund scheme for this measure.

X = Returns below zero

Y = Sum of all squares of X

Z = Y/number of days taken for computing the ratio

Downside risk = Square root of Z

4. Outperformance

i) Equity portion: It is measured by Jensen’s Alpha for the last three years. Jensen’s Alpha shows the risk-adjusted return generated by a mutual fund scheme relative to the expected market return predicted by the Capital Asset Pricing Model (CAPM). Higher Alpha indicates that the portfolio performance has outstripped the returns predicted by the market.

Average returns generated by the MF Scheme =

[Risk Free Rate + Beta of the MF Scheme * {(Average return of the index – Risk Free Rate}

ii) Debt portion: Fund Return – Benchmark return. Rolling returns rolled daily is used for computing the return of the fund and the benchmark and subsequently the Active return of the fund.

5. Asset size: For Hybrid funds, the threshold asset size is Rs 50 crore

(Disclaimer: past performance is no guarantee for future performance.)



READ SOURCE

This website uses cookies. By continuing to use this site, you accept our use of cookies.