开发者工具1 week ago
Ticker Line — Market sparklines through a URL
为股票、加密货币和指数生成可嵌入的市场迷你图表。
Open source
kahtaf · HN
Ticker-line.com – embeddable market sparkline SVGs
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为股票、加密货币和指数生成可嵌入的市场迷你图表。
kahtaf · HN
Ticker-line.com – embeddable market sparkline SVGs
AI代理24/7监控投资组合，提供漂移监控、收益提示和基准跟踪。
@SigVestAI · X
通过交互式分析工具和实践学习掌握股票市场基础知识。
@ak_stan001 · X
Built making stock market education practical with real analysis tools and hands-on learning.
使用历史股票数据回测交易策略。
@basisfinnce · X
Taking the hype out of short term stock trading using a backtest engine running off decades of data 📊 👉
DeepStock每日AI股票评分榜，1-10分
@zway_ai · X
最近用 codex 多余的算力， 把我之前的这个域名 又拿出来炼了一下 做了一个 AI 股票打分榜，简单直接~ 每天找一只高分股来研究一下📈 #earnings
追踪并浏览 f(x) Protocol 和 fxUSD 的 on-chain data
@0xDrVV
粘贴预测市场网址获得AI分析，含赔率、情绪和交易建议。
@pillarlabai · X
发布股票、ETF和加密货币预测，在排行榜上跟踪结果，证明你的判断。
kkjh0723 · HN
I ran 12 AI bots predicting stocks for two months, every call public
SeeBet.ai：查看NFL博彩赔率、盘口变动和十年回测数据的分析工具。
u/sebriz · Reddit
I built an institutional NFL data terminal that audits 44 situational factors against 10 years of market data [Open Beta] Hey everyone, I wanted to share a side project I’ve been building called SeeBet.ai . As someone who loves sports data, I got tired of generic broadcast hype, sports betting "gurus," and subjective narratives about things like "revenge games," travel fatigue, or short rest. I wanted an institutional, zero-hype terminal that simply audits physical reality against market
AI 研究代理分析公开市场，提供收益警报并总结 SEC 文件（附引用源）。
oceanplexian · HN
I Built OpenClaw for Stocks
Tradovate AI 风险管理，根据您的风险规则自动阻止订单。
@SanuCodes · X
still building-
查看 Bitcoin 底部和顶部风险信号，来自综合技术、链上和情绪指标。
@BDNcontent · X
Every post in my LinkedIn timeline is about one of two things right now: 1) Github is the new necessity for marketers, and 2) Substack integrated Pangram to "combat AI slop." The first one is kind of cool, I made my own Github this week to publish the first tool I vibe coded on my own. The second one is kind of annoying because while some people already know AI detectors are almost useless, some are also hailing Substack as being forward-thinking and righteous for bringing down the big bad AI sloppers. What Substack did boils down to a marketing ploy. The hot trend in advertising/marketing right now is being anti-AI because a lot of people are sick of AI slop, understandably. But Pangram isn't a fix for anything other than the most generic one-prompt outputs, i.e., someone goes to ChatGPT and says "write me a long-form newsletter," and they copy + paste the output. That will obviously be flagged. If someone has a custom project or GPT they trained extensively,