Low volatility · top 20 · Top 1000 · long/short

by finzdata-research · published 2026-10-13 · expr · top1000 · 0 forks · 2 views

The low-volatility anomaly: less volatile stocks have historically earned similar or better returns than volatile ones because leverage-constrained investors overpay for risky names. Falsified if the strategy fails to match the benchmark's Sharpe ratio out of sample.

Forward tracking started 2026-10-13. Results appear after 21 trading days.

Backtest

Metric	Strategy	Benchmark
CAGR	-2.29%	6.17%
Volatility	17.96%	21.13%
Sharpe	-0.04	0.39
Max drawdown	-78.35%	-62.44%
Turnover (per year)	3.12

Deflated Sharpe: 0.03 (n trials: 54) — the probability the Sharpe ratio is real after the number of variants tried.

Run id 0d4f20224aeed712 · snapshot v2026-10-12

Spec

{
  "costs_bps": 10,
  "end": "2025-12-31",
  "rebalance": "M",
  "side": "long_short",
  "signal": {
    "expr": "rank(-vol(60))",
    "type": "expr"
  },
  "start": "2005-01-01",
  "top_n": 20,
  "universe": "top1000"
}

Fork this strategy

Re-run it with your own changes. The fork is computed on the server and linked back here.

curl -X POST https://api.finzdata.com/v1/hub/s/low-volatility-top-20-top-1000-long-short-cb099c/fork \
  -H 'Authorization: Bearer YOUR_KEY' -H 'Content-Type: application/json' \
  -d '{"changes": {"signal": {"lookback": 126}}}'

Or ask your AI assistant (Claude, ChatGPT, Cursor with the FinzData connector):

Fork the FinzData strategy low-volatility-top-20-top-1000-long-short-cb099c and test it with a 126-day lookback and 20 bps costs, then compare both runs.

Historical simulation, not investment advice.

Community

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