**Four of seven buy-day rules beat SIP. None of the thirty-six volatility-scaling variants do.

The premise

Every other strategy in this series tried to answer the same question: when should you deploy capital? Strategy 15 asks a simpler version: given that you are investing every month regardless, which day of the month gives you the best entry price? Strategy 19 asks something different: if you scale how much you deploy each month based on how volatile the market currently is, does that improve outcomes?

Neither strategy holds capital back for long periods. Neither requires a complex signal to fire. They are both modifications of SIP execution rather than alternatives to it.

How both strategies work

Both use the same framework: ₹10,000 contributed monthly, 0.03% transaction cost, all units held permanently. Benchmark is a capital-matched monthly SIP on Day 1. SIP XIRR: 11.9724%.

Strategy 15 - Intra-month buy day sweep: The monthly ₹10,000 is invested on a fixed day rule rather than Day 1. Seven rules are tested: Day 1, Day 5, Day 10, Day 15, Day 20, the last trading day of the month, and the monthly F&O expiry date (last Thursday before expiry settlement). There is no bank accumulation — every rupee is deployed every month on the chosen day.

Strategy 19 - Volatility-scaled deployment: Each month, the strategy calculates annualised realised volatility over a rolling window (20, 40, or 60 days). It computes the volatility's percentile rank over a historical lookback (36, 60, or 120 months). The deployment fraction for that month is then inversely scaled by this percentile — lower volatility means a higher fraction deployed from the bank, higher volatility means a lower fraction. Ceiling and floor parameters (10% or 20% floor, 75% or 100% ceiling) control the range. 36 variants are tested across these parameters.

Strategy 15: four rules outperform, one matters

F&O expiry is the best performing rule. XIRR 11.9977% versus SIP's 11.9724%. Alpha +0.025%. Final portfolio ₹3.2484 crore, trailing SIP's ₹3.2578 crore by ₹93,673. All 367 monthly contributions executed, zero skipped, zero idle bank.

Last day of the month is second. XIRR 11.9956%, alpha +0.023%, trailing SIP by ₹1.33 lakh.

Day 20 is third. XIRR 11.9848%, alpha +0.012%, trailing SIP by ₹1.09 lakh.

Day 15 is fourth. XIRR 11.9779%, alpha +0.006%, trailing SIP by ₹1.05 lakh.

Day 1 is the benchmark — XIRR 11.9724%, alpha 0.

Day 5 trails by ₹1.61 lakh. Day 10 trails by ₹2.50 lakh.

The pattern is clean: the later in the month you invest, the better the result, up to the last day. The F&O expiry edge is the peer-reviewed finding from the research synthesis that opened this project — expiry-related volatility tends to push prices temporarily lower, giving a marginally better entry. The data confirms it, but the magnitude is small. ₹93,673 over 30 years on ₹36.7 lakh of contributions is a 0.25% improvement on total wealth.

The early-month underperformance has a mechanical explanation. Day 5 and Day 10 tend to capture post-expiry recovery and mid-month drift — periods where prices have already adjusted from the expiry effect without offering any comparable discount. Day 1 sits right at the benchmark because it is the benchmark.

Strategy 19: zero for 36

Every volatility-scaling variant underperforms SIP. The best result, a 20-day vol window with 120-month historical lookback, 100% ceiling and 20% floor, produces XIRR 11.9428% — trailing SIP by ₹1.95 lakh. The worst, a 40-day window at 75% ceiling and 10% floor, trails by ₹3.90 lakh.

Average alpha by volatility window: -0.036% for 20-day windows, -0.043% for 60-day, -0.048% for 40-day. No window works. The 20-day window is closest to SIP simply because it reacts faster and spends less time misallocating based on a stale volatility reading.

The logic behind the strategy is intuitive — deploy more when markets are calm, pull back when they are turbulent. The problem is that Nifty's volatility regimes and its return regimes do not align cleanly enough for the scaling to help. High-volatility periods include both crashes and sharp recoveries. Reducing deployment during high-vol months means missing some of the fastest recovery days. Low-vol periods include late-stage bull runs where valuations are stretched. Deploying more during those months means buying near peaks.

The result is that the scaling fraction oscillates without generating consistent timing advantage. 361 trades executed out of 367 months across most variants, with only ₹14,000 to ₹28,000 left idle. The strategy is almost always invested — the drag comes from fractional deployment, not from sitting in cash.

Reading both together

Strategy 15 works marginally. Strategy 19 does not work at all. The difference is instructive.

Strategy 15 makes no forecast. It does not predict whether this month is a good or bad time to invest. It simply shifts the execution date within the month and relies on a documented structural pattern around F&O expiry. The result is a small, real edge with no implementation risk beyond remembering the expiry date.

Strategy 19 makes a forecast — that current volatility predicts near-term returns well enough to justify varying deployment. That forecast is wrong often enough that the scaling destroys the edge it is trying to create. The more parameters added to the scaling function, the more ways the forecast can be wrong.

Verdict

Seven buy-day rules tested. Four outperform SIP, led by F&O expiry at +0.025% alpha and ₹93,673 of additional wealth over 30 years. Thirty-six volatility-scaling variants tested. Zero outperform, with the best result trailing SIP by ₹1.95 lakh and the worst by ₹3.90 lakh. Changing when you invest within the month produces a small, real edge. Changing how much you invest based on volatility does not. The execution change that requires no forecast outperforms the one that does.**