Can Valuation-Based Investing Improve NIFTY 50 SIP Returns?

A regular NIFTY 50 SIP sends the same contribution into equity every month. It asks very little of you: keep the schedule.

Now consider a different rule. When the market looks expensive under a valuation model, part or all of that month's contribution waits in an arbitrage allocation. When the model reads cheaper, the contribution goes into equity, sometimes joined by money accumulated earlier.

Does that extra decision improve the historical result enough to justify the complication? Let's separate the rule from the evidence.

Start with two buckets and one score

The equity bucket follows NIFTY 50. The other bucket represents an arbitrage allocation. Arbitrage funds seek to capture price differences between related positions; they are not savings accounts and their returns are not guaranteed.

The Nifty Terminal Indicator combines valuation and market measures into a score from 0 to 100. A lower score means relatively expensive under this model. A higher score means relatively cheap.

The score is a model's reading of the market, not a forecast of next month's price. An expensive market can continue rising, and a cheap market can keep falling.

Here is the rule the historical model tested

Think of one expensive month. The model sends the new contribution to arbitrage, but it does not sell the existing equity portfolio. If the market falls, that existing equity can still fall with it.

Now imagine a later reading above 70. The model invests that month's fresh contribution in equity and moves the accumulated arbitrage balance across too. The timing of those readings determines the path.

This table describes the backtest rules. It is not a personal instruction to make those transactions.

Before the result, check what was simulated

The saved study uses ₹10,000 monthly contributions, the NIFTY 50 total-return series and historical Indicator readings. It repeats the simulation over several holding periods.

The arbitrage bucket grows at an assumed 6.50% annual rate. It does not use a particular arbitrage fund's realised NAV journey. That matters: the simulation smooths out fluctuations that a real fund can experience.

There is also a comparison limitation. The saved strategy and NIFTY 50 exports contain different sample counts. We can read their summaries side by side, but we cannot call the difference a matched-date win rate.

Choose a holding period

3 years5 years7 years10 years

Indicator rule19.04%

NIFTY 50 SIP16.53%

Separate sample summaries, not a matched-date contest: the two exports contain different numbers of periods. The model assumes 6.50% annual growth for arbitrage and excludes investor taxes and transaction costs.

Explore all the numbers

Strategy	Average XIRR	Median XIRR	Lowest XIRR	Loss periods	Tested periods	Average final value
Indicator rule	19.04%	14.82%	−13.13%	132	5,881	₹4,80,719
NIFTY 50 SIP	16.53%	14.68%	−21.60%	489	5,888	₹4,64,765

Values retain the original calculation precision until display. Download the evidence (JSON)

Showing 3 years.

Shorter periods: the model still had losses

In the three-year strategy sample, 132 of 5,881 periods had a negative result. The lowest annualised XIRR was −13.13%.

The separately saved NIFTY 50 sample had 489 losses in 5,888 periods, with a lowest XIRR of −21.60%. These summaries suggest a less severe downside pattern for the rule in this historical test. They do not establish protection against the next fall.

Switch to five years. The strategy export recorded no negative results in 5,385 periods. Its lowest annualised result was 0.86%. That is positive before investor costs and inflation; it is not a guarantee of preserving purchasing power.

Longer periods: put the difference in context

At ten years, the saved average final values were ₹26,55,338 for the Indicator rule and ₹25,47,281 for the regular NIFTY 50 SIP. Each simulation assumed total contributions of ₹12 lakh.

The averages differ by approximately ₹1.08 lakh. But these are averages from two different sets of periods, not an amount every investor received or a promised benefit of following the rule.

The ten-year average XIRRs were 14.75% and 14.08%. Averages are useful summaries; they hide the path, the variation and the work required to follow the strategy.

What does the extra rule cost?

A rule can reduce discretionary decisions, but it still needs execution. Waiting outside equity can miss gains. Moving money can introduce tax and exit-load consequences. A model can also fit its historical sample better than it performs on new data.

Explore the Indicator and its methodologySee how the score is constructed and how the model describes historical valuation zones.

Data sources and the limits of this study

The figures use the saved dynamic_strategy_sip_rolling_v3 and nifty_50_sip_rolling exports. Download the evidence behind the chart and table. This is a historical research snapshot, not a live portfolio record.

The accompanying model code uses a fixed 6.50% arbitrage assumption and NIFTY 50 total-return prices. Investor taxes, exit loads and real-fund execution are not represented in these summaries. The saved files do not record every input version used in the test. A new comparison using the same dates and real fund costs is still needed to check how much of the difference survives.

A positive result in every observed period is still a result from a limited historical sample. Neither the equity allocation nor the arbitrage allocation offers a guaranteed outcome.

The arbitrage fund comparison asks a separate question about actual fund NAV histories. It does not replace the assumption inside this backtest.