Bigdata Sector Analysis

作者 Bigdata-com2a52a0013662无许可证2 个星标收录于 2026年10月8日更新于 2026年10月8日仓库昨天更新

Analyze a market sector using Bigdata.com data — performance, valuations, themes, sub-industries, and upcoming catalysts. Maps the sector to its own operating and valuation KPIs rather than generic P/E, reads cycle and profitability positioning as early, mid, or late versus history, aggregates bellwether tearsheet metrics, and closes with a positioning call plus top picks and areas to avoid. Triggers: "analyze the X sector", "what's happening in X sector", "X sector outlook", "how is the X industry doing", "X sector valuations", "is the X sector attractive", "semiconductor/energy/healthcare sector view".

AI 生成的概览

使用 Bigdata.com 数据分析单一市场板块,涵盖表现、估值、周期定位、催化剂并给出配置结论。

功能
该技能针对单一市场板块生成完整解读:交易位置、驱动因素以及后续看点。它把板块映射到其自身的经营与估值 KPI,而非通用市盈率,汇总龙头公司的指标,判断周期与盈利能力相对历史处于早期、中期还是后期,最后给出配置结论以及首选标的和应回避领域。输出遵循报告模板,包含行内引用、编号来源表和免责声明。
适用场景
当主题是单一板块时使用,例如要求分析某板块、说明该板块正在发生什么、给出板块展望,或评估板块估值与吸引力。不适用于两个及以上板块的比较、特定国家或地区的板块分析、单一公司,或跨板块的宏观主题。
运行要求
需要访问 Bigdata.com 插件工具:bigdata_search、find_securities、bigdata_company_tearsheet 和 bigdata_events_calendar,其中 tearsheet 与日历工具需先调用 find_securities。每次调用 Bigdata.com 插件工具都必须传入 plugin_slug 为 bigdata-sector-analysis,search 和 fetch 除外,这两者不传该参数。仅为指令,不附带脚本。

Bigdata Sector Analysis

Full read on one sector: where it trades, what drives it, and what is coming. Use Bigdata.com plugin tools for every fact.

Use this skill when the subject is one sector. Not this skill when:

RequestUse instead
Two or more sectors compared, or rotationCross-sector comparison
A sector inside a specific country or regionCountry-sector analysis
An actionable KPI-and-debates playbook for investing the sectorSector playbook
A macro theme that cuts across sectorsThematic research
One company in the sectorCompany brief / investment memo

Data foundation (plugin tools)

ToolPurposePrerequisite
bigdata_searchSector trends, valuations, policy, catalysts, cycle contextNone
find_securitiesEntity ids for 5–10 sector bellwethersNone
bigdata_company_tearsheetPer-company metrics, estimates, sentiment, segmentsfind_securities
bigdata_events_calendarUpcoming earnings and conferencesfind_securities

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

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

Run 5–10 targeted searches across the workflow. Include temporal context ("last 30 days", "2026 outlook").

Workflow

Step 1 — Sector context

Search:

  • "[Sector] sector outlook trends analysis"
  • "[Sector] sector earnings performance"
  • "[Sector] sector headwinds tailwinds"
  • "[Sector] sector valuations multiples"
  • "[Sector] sector regulatory policy"

Step 2 — Sector-specific KPI lens (GICS)

Do not rely only on generic P/E, P/S, and EV/EBITDA. Map the sector to its primary operating and valuation KPIs:

GICS sectorEmphasize these KPIs
Information Technology / Software-SaaSARR growth, NRR, Rule of 40, FCF margin, payback
FinancialsNIM, CET1 / capital, credit costs, ROTCE, efficiency
Health Care (incl. Pharma)Growth drivers, pipeline / patent, R&D, payer mix, regulatory
Real Estate (REITs)AFFO, NAV, cap rates vs bonds, same-store NOI
IndustrialsBacklog, book-to-bill, margin mix, OEM / capex cycle
Consumer Discretionary / StaplesSame-store sales, promo, input costs, private label
EnergyCommodity linkage, breakeven, FCF at forward curve, capital discipline
MaterialsPrice/volume, capacity, inventory, China / construction linkage
Communication ServicesSubscribers, ARPU, churn, ad market / streaming economics
UtilitiesAllowed ROE, rate case risk, weather / load growth
(Other)Default to margin trajectory, ROIC vs peers, and segment growth

Deeper playbooks: references/sector-routing.md.

Step 3 — Key companies

Use find_securities for 5–10 major sector companies, then bigdata_company_tearsheet for each: financial metrics and performance, analyst estimates and sentiment, revenue segmentation, ESG scores.

Step 4 — Aggregate sector metrics

From the tearsheets, compile sector-relevant multiples (per Step 2, not only P/E), the Step 2 KPIs where visible, revenue and earnings growth trends, the analyst rating distribution, and sentiment indicators.

Step 5 — Cycle and profitability positioning

Add brief, evidence-based cycle context:

  • Search "[Sector] sector ROIC profitability cycle outlook" and "[Sector] margin cycle vs history"
  • State whether ROIC (or a sector proxy) and margins look early / mid / late versus a normal cycle — or flag the data limits
  • Industry-economics mental model: references/porter-five-forces.md

Step 6 — Catalysts

Search:

  • "[Sector] regulatory changes policy"
  • "[Sector] technology disruption"
  • "[Sector] M&A consolidation"
  • "[Sector] earnings expectations"
  • "[Sector] supply chain tariffs"

Step 7 — Events calendar

Use bigdata_events_calendar for upcoming earnings and conferences across the bellwethers.

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 in every sector analysis:

  • Sector-specific KPIs present — a report built only on P/E has not done the job
  • Cycle positioning stated (early / mid / late) or its data limits flagged
  • Tailwinds and headwinds name which companies are exposed
  • Positioning call given: overweight / neutral / underweight, with top picks and areas to avoid
  • Every claim from a source carries an inline citation and appears in the Sources table

GICS sectors reference

Information Technology, Health Care, Financials, Consumer Discretionary, Consumer Staples, Industrials, Energy, Materials, Real Estate, Communication Services, Utilities.

来源与署名

来源:Bigdata-com/bigdata-plugins-marketplace位于plugins/bigdata-com/skills/bigdata-sector-analysis提交2a52a00

许可证: 无许可证

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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