# Low Volatility Anomaly

_Factor Models . 2026-05-08 . By Tanmay Kurtkoti. Educational, illustrative, not advice._

Friend asked me a question last week that took me an hour to answer properly.

Why did his "boring" large cap mutual fund quietly outperform his "exciting" momentum smallcase over four years. Same starting capital. Same period. Different rides.

I pulled the NIFTY 100 split that evening. Sorted every constituent by twelve month realised volatility. Took the bottom 30, the boring side. Took the top 30, the exciting side. Looked at how each cohort actually compounded.

Bottom cohort. Mostly staples and large pharma and the predictable insurers. HUL, NESTLE, ITC, ASIANPAINT, HDFCLIFE. Median beta around 0.71. Five-year max drawdown roughly 14 pct.

Top cohort. Mostly commodities and PSU energy and cyclical metals. ADANIENT, JSWSTEEL, TATASTEEL, ONGC, VEDL. Median beta around 1.41. Five-year max drawdown roughly 33 pct. More than twice the hole.

Here is the part most retail conversations miss. A 50 pct loss does not need 50 pct to recover. It needs 100 pct. A 25 pct loss only needs 33 pct. The math is asymmetric and the asymmetry punishes variance.

Geometric return equals arithmetic return minus sigma squared over two. That sigma squared is the cost of being volatile. Two portfolios can earn the same average return year by year. The lower-variance one ends with more money. Not by being right more often. By having less of a hole to climb out of.

This is not a new finding. Haugen and Heins published the low volatility anomaly in 1975. Frazzini and Pedersen formalised it as Betting Against Beta in 2014, Journal of Financial Economics. The market still has not arbitraged it away because human investors keep paying up for the lottery ticket.

Low vol does not mean low return. It means lower variance drag.

The boring portfolio is not boring. It is the one that survives long enough to compound