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Earlier sources: Markets
Markets connect capital, goods, services, and labor. This region follows economic developments, public markets, venture capital, fintech, and commerce. Source attention does not constitute financial advice or forecast investment returns.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗249 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Mitigating Hallucinations in Finance-Based Multi-Agent Large Language Model Systems ↗
Large language models are increasingly used for financial question answering, while they are prone to generating hallucinated content. In this research, we propose a multi-signal framework for hallucination detection and mitigation. Our framework combines six signals (entailment, semantic similarity, claim verification, numeric consistency, token overlap and confidence calibration techniques) to identify hallucination type and severity. We evaluated our framework using multiple language models across three financial QA benchmark datasets (FinQA, FinanceQA, and FinDER). Our proposed framework c…
- Hacker News · Posted on Hacker News · First archived
Oil Slips as Iran Diplomacy Sparks Fresh Hopes for a Market Reset ↗
Hacker News discussion.
- arXiv · Published · First archived
Oracle-Parametrized Constant Function Market Makers: From Price Feeds to Pricing Rules ↗
This paper introduces oracle-parametrized automated market makers (OP-AMMs), i.e., automated market makers whose quoted price depends jointly on the pool reserves and an external oracle price. In doing so, we extend the information-agnostic AMM framework to settings, such as tokenized securities, for which price discovery occurs off-chain. Under a strict oracle-contraction condition, we show that the quoted price of any OP-AMM interpolates between the oracle price and an implicit autarkic price determined by the pool reserves. We then derive a general loss-versus-rebalancing (LVR) decompositio…
- arXiv · Published · First archived
Taming the Greeks: Option Portfolios with Inductive Biases ↗
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures. While neural networks trained to optimize risk-adjusted performance have been shown to outperform traditional rules-based strategies, such approaches remain agnostic to the sensitivities of the resulting portfolios with respect to specific underlying risk factors. We propose a general training objective that combines a performance-driven loss with a differentiable risk-sensitivity penalty, enforcing neutrality to selec…
- GitHub · Repository created · First archived
jangviktor-web/NiuCap ↗
牛来选股面板 Niucap：本地自托管的 A 股量化看盘面板，覆盖选股、择时与复盘全流程，新手也能零门槛上手。内置小白选股、25+ 策略选股、条件选股、实时行情（约3分钟自动刷新）、连板梯队、情绪周期、题材雷达、龙虎榜后验、双源快讯情绪分析、策略回测（T+1 真实约束/夏普/最大回撤/卡玛/网格防过拟合）、虚拟盘模拟交易、60+ 技术指标个股分析（资金流向/筹码分布/基本面）、市场榜单与宽度、多股对比、ETF 筛选、自选股、监控中心与命令面板 Cmd+K、沪深交易时段时钟。免 API Key，移动端响应式，数据完全私有，MIT 开源；Python/FastAPI + ECharts 构建，支持本机/云端/workbudd在线应用 一键部署，行情来自腾讯/新浪/同花顺/东财免费公开接口。
- arXiv · Published · First archived
EverMine: Dissecting the Self-Evolution of Research Capabilities in Long-Horizon Alpha Research ↗
Self-evolving agents aim to turn research feedback into reusable skills, tools, and research rules. Whether these accumulated capabilities continue to improve later research requires controlled evaluation. Long-horizon alpha discovery provides a state-dependent setting: once a new factor enters the portfolio, the predictive information already covered changes, so the value of the same candidate or experience may change over time. We introduce EverMine, an empirical framework for studying self-evolving research capabilities in long-horizon alpha discovery. EverMine decomposes the research state…
- GitHub · Repository created · First archived
pafa/Signal-Hunter ↗
信号猎手 · Local event research and human-approved paper-trading workbench for A-share, Hong Kong and US equities.
- GitHub · Repository created · First archived
ethnv/BUYIN ↗
Familiar money. New markets. BUYIN financial access layer for Robinhood Chain — product documentation and an offline reference.
- GitHub · Repository created · First archived
xiaodou-official/xiaodou-market ↗
小豆集市 · 数字商品交易平台：卡密、课程、电子书、软件、素材模板、会员权益、游戏道具都能卖；自动发货、微信/支付宝收款、持牌机构清算、次日到账；实物可当面交易。Digital-goods marketplace with auto-delivery, Alipay & WeChat Pay, licensed PSP settlement.
- arXiv · Published · First archived
LiveOption: Evaluating LLM Agents in Structured Option Trading with Nonlinear Payoffs ↗
Large language models (LLMs) and multi-agent systems (MAS) have shown promise in financial decision-making, yet existing evaluations focus on equity trading and primarily assess directional prediction, overlooking the structural complexity of derivative markets. Option trading introduces fundamentally different challenges, including nonlinear payoffs and multi-leg strategy construction, requiring structured decisions rather than simple directional bets. We introduce LiveOption, an evaluation framework for LLM-based agents in option trading. LiveOption formulates the problem as structured seque…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Markets
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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