Rupee cost averaging scores over lump-sum

Rupee cost averaging scores over lump-sum
Investing tactical cash is a concern for many investors. This article discusses two methods of investing tactical cash- lump-sum investment and rupee-cost averaging
Many investors hold significant cash in their portfolio as a tactical move. By tactical cash, we mean cash held in a portfolio for investments to be made at a later date. This cash balance may have also come from profit-taking in the stock market in the recent past. The question is whether it is optimal to phase out investing such cash over a period of time or to make a lump-sum investment.

This article explains rupee cost averaging and compares it to lump-sum investment. It uses within-horizon risk to explain why rupee cost averaging is optimal for typical investors.

Rupee cost averaging


Rupee cost averaging means investing a fixed sum of money for a fixed period. Take an investor who holds Rs 10 lakh of tactical cash. Buying Rs 2.5 lakh worth of index funds each month for the next 4 months would amount to rupee cost averaging.

This strategy is often recommended on the grounds that it is better to average purchases than to time the market. Academic literature has, however, shown that lump-sum investment is superior.

One argument in favour of lump-sum investment is the positive equity risk premium. That is, expected return from equity asset class is higher than that from the bond asset class. It is, therefore, argued that lump-sum investing is better, as money can be expected to earn a higher return for a longer time period. So, which strategy is optimal?

Within-horizon risk


Proponents of lump-sum investment typically consider end-horizon risk. Suppose the investment horizon is five years. End-horizon risk refers to the risk that a portfolio will decline in value at the end of five years. The rationale is that short-term fluctuations are not important for the end-value of the portfolio.

But that does not hold water. Typical investors are concerned about within-horizon risk. This is the risk that a portfolio will decline in value during the horizon period. As one researcher states, “A stream may have an average depth of five feet, but a traveller wading through it will not make it to the other side if its midpoint is 10 feet deep.”

The implication is that an investor has to survive the within-horizon risk to reach his target returns. This argument can be best understood based on liability-driven investment.

Minimum Acceptable Return


Suppose an investor wants to buy a house. Assume that the portfolio has to generate a minimum acceptable return of 15 per cent each year to achieve the investment objective. The within-horizon risk is the risk that the portfolio could generate less than 15 per cent return in any year, leading to a shortfall in the end-value of the portfolio.

Lump-sum investment exposes the portfolio to a higher within-horizon risk. What if, for instance, a lump-sum exposure is taken just before a market crash? Rupee cost averaging averages the purchase price over a certain period of time. This substantially reduces the within-horizon risk.

Then, there is the behavioural bias. Investors prefer to minimise regret associated with a bad investment outcome. Following rule-based investment (rupee cost averaging) helps the investor distance herself from the bad outcome and experience less regret.

True, lump-sum investing provides superior returns in a trending market. But the regret of a bad outcome is also higher, as is the within-horizon risk. That makes rupee cost averaging optimal.

Conclusion


Though optimal, rupee cost averaging should not be spread over a long period of time. The strategy requires pre-defining the price range, time horizon and the amount invested.

Suppose an investor wants to accumulate Rs 10 lakh worth of index funds in four tranches between 4700 and 5200. She can do so at intervals of 125 points. Alternatively, Rs 2.5 lakh can be bought on the first and 15 of each month for two months. The optimal strategy would depend on the investment objectives, risk tolerance levels and the market condition.