Bigdata Thematic Research

作者 Bigdata-com2a52a0013662無授權條款2 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫昨天更新

Research a macro investment theme using Bigdata.com data — scope and sub-themes, investment implications, sector impact, named beneficiaries and vulnerable losers with tearsheet fundamentals, the policy and regulatory dimension, geographic impact, and concrete implementation ideas. Covers themes such as AI, energy transition, inflation and rates, deglobalization and reshoring, demographics, geopolitical risk, and fiscal policy. Triggers: "research the X theme", "X investment implications", "who benefits from X", "how do I play X", "AI / energy transition / deglobalization theme", "thematic view on X".

AI 產生的概覽

使用 Bigdata.com 資料研究跨產業宏觀投資主題,產出附引用的主題報告與可執行想法。

功能
引導代理依結構化流程進行主題研究:界定主題範圍與子主題,執行 5 至 10 次檢索,透過公司資料表基本面找出受益者與受損者,評估地理與政策影響,並將分析轉化為可執行想法。最後依固定範本產出 Markdown 報告,包含行內引用、編號來源表、Bigdata.com 署名行與免責聲明。交付後可能詢問是否將分析轉為 Word 文件或簡報。
適用情境
適用於跨產業或跨境的宏觀主題,例如人工智慧、能源轉型、通膨與利率、去全球化與回流、人口結構、地緣政治風險或財政政策。不適用於單一產業、單一國家或單一公司的分析。
執行需求
需要存取 Bigdata.com 外掛工具:bigdata_search、find_securities、bigdata_company_tearsheet 與 bigdata_country_tearsheet,且除 search 與 fetch 外每次呼叫都需將 plugin_slug 設為該技能名稱。不附帶指令碼,僅依賴報告範本資源與說明文件。

Bigdata Thematic Research

Cross-sector research on one macro theme, ending in implementable ideas. Use Bigdata.com plugin tools for every fact.

Use this skill when the subject is a theme that cuts across sectors or borders. Not this skill when:

RequestUse instead
One sector's performance and outlookSector analysis
Sectors ranked against each otherCross-sector comparison
One country's economyCountry analysis
One company exposed to the themeCompany brief / investment memo

Common themes: AI and technology transformation, energy transition and clean tech, inflation and interest rates, deglobalization and reshoring, demographic shifts, geopolitical risk, fiscal policy and government spending.

Data foundation (plugin tools)

ToolPurposePrerequisite
bigdata_searchTheme coverage, implications, policy, market impactNone
find_securitiesEntity ids for the most exposed companiesNone
bigdata_company_tearsheetFundamentals and exposure of beneficiaries and losersfind_securities
bigdata_country_tearsheetGeographic impact where availableNone

Required on every call: pass plugin_slug: "bigdata-thematic-research" in the request parameters of every Bigdata.com plugin tool call made while running this skill. The value is always the skill name, bigdata-thematic-research, regardless of the company or query.

Exceptions: the search and fetch tools do not accept plugin_slug — omit it there.

Workflow

Step 1 — Define the theme scope

State the boundaries and the sub-themes explicitly before searching. An unbounded theme produces an unbounded report — this step is what keeps the deliverable usable.

Step 2 — Search the theme (5–10 queries)

  • "[Theme] investment implications outlook"
  • "[Theme] winners beneficiaries stocks"
  • "[Theme] risks losers vulnerable"
  • "[Theme] policy government regulation"
  • "[Theme] market impact analysis"
  • "[Theme] sector exposure"

Step 3 — Beneficiaries and casualties

Use find_securities and bigdata_company_tearsheet for the most exposed companies on both sides. A theme note that names only winners is a pitch, not research — quantify the exposure where the data allows (revenue share, capex tied to the theme, contract backlog).

Step 4 — Geographic impact

Use bigdata_country_tearsheet (or search) for the countries most affected, positively and negatively.

Step 5 — Implementation

Turn the analysis into concrete ways to express the theme: direct beneficiaries, second-order plays, avoided exposures, and what would invalidate the theme.

Output

Follow assets/report-template.md exactly — section order, tables, sources, and footer.

  • Inline citations [1], [2] after every claim from a source, hyperlinked to the document URL.
  • End with the numbered Sources table (source, date, URL), then the Powered by Bigdata.com line and Disclaimer, verbatim.
  • Default format is Markdown. After delivering, you may ask: "Would you like me to create a Word document or presentation with this analysis?"

Quality bar

Non-negotiables:

  • Theme scope and sub-themes stated up front and held to
  • Both beneficiaries and losers named, with exposure quantified where possible
  • Policy dimension addressed — most macro themes are policy-driven
  • Implementation section present: how to express the theme, and what would invalidate it
  • Every claim from a source carries an inline citation and appears in the Sources table

來源與署名

來源:Bigdata-com/bigdata-plugins-marketplace位於plugins/bigdata-com/skills/bigdata-thematic-research提交2a52a00

授權條款: 無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架

更多來自 Bigdata-com/bigdata-plugins-marketplace 的技能

Bigdata Sector Playbook

Bigdata-com

為某個產業建立投資操作手冊,涵蓋關鍵指標、估值方法、爭論焦點、篩選標準與可執行配置。

Business & Finance2昨天更新

Bigdata Sector Analysis

Bigdata-com

使用 Bigdata.com 資料分析單一市場類股,涵蓋表現、估值、週期定位、催化因素並給出配置結論。

Business & Finance2昨天更新

Bigdata Regional Comparison

Bigdata-com

使用 Bigdata.com 資料比較各地區或經濟體集團,並產出跨資產配置建議。

Business & Finance2昨天更新

Bigdata Quick Take

Bigdata-com

以 Bigdata.com 資料產出一頁式 PM 風格個股速評,包含觀點、驅動因素、風險與下一個催化劑。

Business & Finance2昨天更新

Bigdata Pre Ipo Analysis

Bigdata-com

依據 S-1/F-1 文件與 Bigdata.com 資料,為即將上市的公司產出一份平衡的 IPO 前研究報告。

Business & Finance2昨天更新

Bigdata Post Ipo Day365

Bigdata-com

Write a day-365 post-IPO note on the 366-day founder and significant-investor lock-up expiry and float expansion toward 15-20%, using Bigdata.com data plus filings and market data. Covers the staggered lock-up structure from the prospectus, float expansion math and days-to-trade, the offsetting float-adjusted index reweight demand netted against new supply, a realistic read on whether founders actually sell, the dual-class governance angle, and a two-sided setup. Balanced, no buy/avoid call. Triggers: "366-day lock-up for X", "founder lock-up expiry", "float expansion for X", "post-IPO one year lockup", "index reweight after float increase", "founder selling after IPO".

待分類2昨天更新