Autotrader – paper trading AI agent for Indian equities
A paper trading AI agent named Autotrader has been tested on Indian equities, specifically the Nifty 500 index. The experiment, which ran for two weeks, concluded with an 8.05% gain on the initial capital of Rs 100,000. The project is paused, but the repository is available for others to fork and continue the work.
- ▪The Autotrader experiment utilized real transaction costs and a live price feed without using real money.
- ▪The trading agent was designed to edit its own strategy based on performance during the trading loop.
- ▪The project included detailed documentation and setup instructions for users interested in replicating the experiment.
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Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/analyticalmonk/autotrader |
| Publication time | Sun, 24 May 2026 11:55:38 +0000 |
| Retrieval time | 2026-05-24T12:07:32.400Z |
| Last seen | 2026-05-24T12:07:32.400Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | al9NwpNwD9-U |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
autotrade A paper-trading experiment on Indian equities (Nifty 500). Claude itself runs the trading loop on a free GCP VM and edits its own strategy between polls. Real Indian transaction costs (STT, GST, stamp duty, brokerage), real Kite Connect price feed, no real money. Status: paused. Two-week run ended May 8 2026 at Rs 108,049 (+8.05% on Rs 1,00,000 starting capital). The repo is left in a state forkable for anyone who wants to continue or reuse the harness. The full writeup (sessions, incidents, what the experiment actually taught) is at https://www.akashtandon.in/autotrader/. What's in here live.py - single-shot polling loop. Fetches prices, runs strategy, executes paper trades, persists state. strategy.py - trading signals + position sizing.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.