If you want to accumulate a large amount of money before retirement, start investing at an early age. Based on your expected rate of return and investment tenor, your corpus is likely to grow manifold. The power of compounding drives this significant growth.
Compounding is a powerful financial phenomenon. A small, consistent Systematic Investment Plan (SIP) grows disproportionately higher in the later years than in the initial ones, maximising total wealth. This happens because the returns earned early on are reinvested. They get added back to the principal, and that higher principal earns a return in the following years.
Typically, investors use SIPs to invest smaller tranches over a long period of time. This strategy helps accumulate a large corpus for retirement. A SIP is simply the process of investing in mutual funds in small tranches every month or fortnight.
Let us calculate the required size of your monthly SIP to accumulate a retirement corpus of ₹2 crore.
Scenario 1: If the rate of return is 12%
If you plan to stay invested for 20 years and want your mutual funds to deliver 12% a year, then you need to invest ₹20,217 a month to accumulate ₹2 crore. This way, your total investment would turn out to be ₹48.52 lakh.
As the table above shows, if you plan to invest for 15 or 10 years, your monthly contribution would be ₹40,034 and ₹86,942, respectively. This results in a total investment of ₹72.06 lakh and ₹1.04 crore, respectively.
Scenario 2: If the rate of return is 10%
If you want your investments to deliver 10% a year, you need to invest a higher monthly contribution via SIPs. Over a 20-year period (as the table below shows), you would need an SIP of ₹33,302, resulting in a total investment of ₹71.93 lakh.
Over a 15- and 10-year period, you would need an SIP of ₹48,254 and ₹97,635, respectively, resulting in a total investment of ₹86.86 lakh and ₹1.17 crore, respectively.
Note: This story is for informational purposes only. Please speak to a SEBI-registered investment advisor before making any investment-related decision
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