#backtesting
Live, measured metrics for the hashtag #backtesting from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #backtesting
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-10-14 01:06 UTC6 uses by 3 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-10-14 01:06 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-14 01:06 UTCEverything below is measured over the latest 40 public posts (spanning ~3984 hours).
Posting hours (UTC) — busiest: 06:00
Languages: English (35) · Portuguese (3) · Vietnamese (1) · Norwegian (1)
Avg boosts / post: 0
Top of the latest posts
Free backtesting lets you test a trading strategy on historical data before risking capital in live markets; it does not predict future performance. Choose a tool that fits how you want to test. #Backtesting #Trading #RiskManagement https:/
I ported TradingView's SuperTrend strategy to Python and ran it on 6.7 years of real ticks with spread and commission: PF 1.97 on gold H4, 0.81 on NZDUSD. https://hackernoon.com/the-truth-about-tradingviews-supertrend-strategy-after-67-year
0xMarioNawfal (@RoundtableSpace) Jane Street가 트레이딩 리서치에서 LLM과 AI 에이전트를 활용하는 방식을 공유했다. 특히 사후 정정된 데이터를 반영해 과거 데이터를 덮어쓰면 당시에는 알 수 없던 정보를 사용한 가짜 트레이딩 신호가 생길 수 있으므로, 부정확했던 과거 데이터도 보존한다는 점이 핵심이다. 시계열 데이터·백테스트의 데이터 누수 방지에 유용한 원칙이다. https://x.com/R
What “backtesting” means
WikipediaBacktesting is a term used in modeling to refer to testing a predictive model on historical data. Backtesting is a type of retrodiction, and a special type of cross-validation applied to previous time period(s). In quantitative finance, backtesting is an important step before deploying algorithmic strategies in live markets.
“Backtesting” on Wikipedia (CC BY-SA) →#backtesting across platforms
every network with a public tag surfaceFollow #backtesting straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/backtesting