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[Quantradin] - type a trading rule in plain english, it tests it without flattering you

built this because every backtest i ran on other tools flattered me and i couldnt tell how much. you type a rule in plain english. "buy spy when the 20 day crosses the 50, stop at -8%, hold 10 days". it turns that into a real strategy, runs it on actual us market prices, and tells you what it would have done. then if you want, it runs on a paper desk against live data so you can watch it trade tomorrow morning. the whole point is the fills. it buys at the ask and sells at the bid, never t

五维评分

付费意愿
42
需求真实度
50
个人可落地
72
竞争空间
33
新鲜度
62

AI 分析

痛点:现有回测工具用中间价、事后数据和止盈参数美化结果,散户无法知道策略真实会亏多少;同时缺少能用自然语言定义规则、并能被 AI agent 调用的诚实回测引擎。

目标用户:零售量化交易者、独立策略开发者、用 AI agent 做交易研究/选股的个人开发者

证据:built this because every backtest i ran on other tools flattered me and i couldnt tell how much / the whole point is the fills. it buys at the ask and sells at the bid, never the middle. it can't read a price that didnt exist yet when the signal fired. / your ai agent can drive the whole thing too if you connect it, which is honestly the part i built it for.

变现:免费纸张交易引流,付费解锁:真实(非模型化)期权 bid/ask 历史数据、分钟级/tick 数据、多策略组合与资金曲线管理、面向 AI agent 的 MCP/API 调用额度订阅($9–29/月)。

MVP:2 周内做一个「诚实回测对比器」:用户用自然语言描述规则 → LLM 转成策略 DSL(均线交叉/止损/持有期)→ 用日线 bid/ask 成交价(买入按 ask、卖出按 bid、信号后下一 bar 成交)跑回测 → 输出「理想回测 vs 诚实回测」收益差对比报告,并把差异最大的几笔交易列出来。数据先用免费的 yfinance/Stooq 日线,避免期权数据成本。

竞品:QuantConnect、TradingView、Backtrader、VectorBT、Composer、QuantRocket

摘要:一位开发者在 r/SideProject 发布 Quantradin:用自然语言输入交易规则,转成真实策略并在真实美股价格上回测,强调按 ask 买入、bid 卖出、不使用未来数据、不把止盈算进评分,以暴露被其他工具「美化」的回测结果。产品目前完全免费、仅纸张交易、不接券商,并支持 AI agent 驱动。发帖人自述痛点是「其他工具的回测都在讨好我,我无法判断差距有多大」,但帖中没有任何付费意愿或收入数据,且回测赛道竞品众多。