How to Track a Rules-Based Momentum Strategy with an API

Pull a transparent monthly momentum basket from Alphanume and reconstruct its history without rebuilding the selection logic.

Tracking a momentum strategy by hand means re-deriving the universe, the ranking, and the rebalance every month, then storing it carefully so you do not contaminate your history. The Alphanume Quant Galore Momentum Index hands you the finished basket through an API instead.

The endpoint

GET https://api.alphanume.com/v1/quant-galore-momentum-index

Authenticate with ?api_key=alp_your_key or an X-API-Key header. Each row is one constituent on one rebalance date, with a rank from 1 to 10.

Get the current basket

import requests

r = requests.get(
    "https://api.alphanume.com/v1/quant-galore-momentum-index",
    params={"api_key": "alp_your_key"},
)
basket = sorted(r.json()["data"], key=lambda x: x["rank"])
for row in basket:
    print(row["rank"], row["ticker"])

Reconstruct the rebalance history

Because the data is point-in-time, you can pull every past rebalance and walk the basket forward through time. Use date range filters to grab a window:

GET https://api.alphanume.com/v1/quant-galore-momentum-index?date_gte=2026-01-01&api_key=alp_your_key

Group the rows by date and you have the exact 10-name basket for each monthly rebalance since the start of the window. From there you can compute turnover (how many names changed between rebalances), persistence (how often a top-ranked name stays top-ranked), and forward returns per rank.

Ideas to build

• An equal-weight tracker that rebalances on the same monthly cadence.
• A rank-weighted variant that overweights the strongest momentum names.
• An options overlay that sells premium against the basket using volatility data.
• A turnover monitor that alerts when the basket churns more than usual.

Access and limits

The index is on the free tier as a rolling 30-day delayed window. Pro raises the rate limit to 600 requests per minute. Start with a free Alphanume API key and the API documentation, or explore it on Alphanume.

Turning the basket into analysis

Once you have the constituents, the interesting work is in how the basket evolves. Grouping rows by rebalance date gives you each monthly 10-name selection; comparing consecutive baskets gives you turnover; tracking how often a top-ranked name stays top-ranked gives you persistence. These are the diagnostics that tell you whether a momentum strategy is stable or churning.

Because the data is point-in-time and the universe is restricted to deeply liquid, option-friendly names, the basket is also a clean foundation for overlays. You can size an equal-weight or rank-weighted tracker, or sell premium against the constituents using Alphanume's volatility datasets, which share the same universe and join on ticker and date.

Frequently asked questions

What endpoint returns the momentum basket?

GET https://api.alphanume.com/v1/quant-galore-momentum-index. Authenticate with ?api_key=alp_your_key or an X-API-Key header. Each row is one constituent on one rebalance date with a rank from 1 to 10.

How do I reconstruct historical baskets?

Pull a window with date_gte and date_lte, then group the rows by date. Each group is the exact basket for that monthly rebalance, which you can walk forward through time.

How do I measure turnover?

Compare consecutive monthly baskets and count how many tickers changed. The point-in-time data makes this exact rather than an approximation.

Can I build an options overlay on it?

Yes. Because you have a defined basket, you can layer premium-selling or hedging structures on the constituents using Alphanume's volatility datasets, which share the same universe.

Is rank 1 the strongest or weakest name?

Rank 1 is the strongest, the highest-momentum name in the basket. Sort ascending by rank to read the basket from strongest to weakest.