# Street Alpha | Macro & Equities (@StAlphaResearch) on x

- id: koinon:creator:x_stalpharesearch
- url: https://koinonlink.com/kol/x/StAlphaResearch
- schema_version: 1.4

## Identity
- platform: x
- handle: StAlphaResearch
- platform_url: https://twitter.com/StAlphaResearch
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 2112
- following: 51
- posts_total: 1009
- posts_observed: 8
- posts_per_day: 1.006
- account_age_days: 1003
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.00142
- best_post_interactions: 3
- measurement_source: x_post_interactions
- measurement_formula: interactions on one post — likes, or likes + reposts + replies depending on the discovery path (the two are not distinguishable in the stored data)
- comparable_pool: peak_interactions
- status_note: We have only the single best observed post, so no mean exists. peak_post_engagement_rate is an UPPER BOUND, systematically higher than an average — never compare it against an average rate.
- unit_note: engagement_rate and peak_post_engagement_rate are ratios (0-1); avg_interactions_per_post and best_post_interactions are absolute counts. Read status before reading any number: a null rate has several different causes and status says which one applies here.

## Content
- category: finance
- subcategory: investing
- category_confidence: 0.95
- category_source: derived_from_recent_content
- topics: macros, equities, earnings reports, economic data, geopolitics
- bio: Former buyside analyst. I tell stories in two languages to help you understand macros, geopolitics and equities.

## Audience (inferred)
- status: present
- description: financial market professionals, investors, and traders focused on macro analysis, equity markets, and geopolitical insights
- roles: none
- seniority: practitioner
- pain_points: difficulty interpreting market triggers, challenges in assessing stock and sector correlations during earnings season, evaluating the impact of macro data like Non-Farm Payrolls on market movements
- posts_analysed: 2
- confidence: 0.4

## Commercial (inferred)
- audience_buyer_fit: 0.2
- promotion_intent: 0.1
- open_to_collaboration: false
- contact: Koinon does not publish creator contact details.

## Quality signals
- authenticity_score: 65
- authenticity_basis: engagement_observed
- credibility_score: 65
- flagged_for_review: false
- koinon_bd_grade: C — measures Koinon partner-outreach fit, not creator quality
- interpretation: Signals for triage, not verdicts. A flag means the profile is worth a manual check.

## Evidence
- [x_stalpharesearch#e27fc6ea] 大概率是世界杯期间的临时工。挺好的，非农来个小miss吧 (https://twitter.com/StAlphaResearch/status/2067040567796838824)
- [x_stalpharesearch#447e7561] 回顾一下整个7月至今。7月初下跌的触发器是Bloomberg那篇"Meta Compute"报道，市场读成超大规模云厂商已经过度建设、开始甩卖算力的信号。Lam Research单日跌10%，SanDisk跌14%，KLA跌12%，整个semicap链条按照capex ROI证伪的逻辑被踩踏。 这个财报季，亚马逊和微软交出答卷，也在电话会上明确表态收入增长已经开始超越增量capex增长，ROIC在提升而不是恶化。这从基本面上推翻了整个7月下跌的叙事前提。 昨晚我们看到的大涨（Mag 7 中五只涨幅超3%）不像超跌后的技术反弹，SPX在历史新高伴随异常机构

## Provenance
Every inferred field below carries how it was produced. Facts stay facts; inferences stay inferences.

- audience.description: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.roles: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- audience.seniority: source_type=ai_inferred, confidence=0.4, freshness_days=76, method=llm_persona_from_recent_content
- commercial.audience_buyer_fit: source_type=ai_inferred, confidence=0.6, freshness_days=80, method=llm_scorer — Relative signal within Koinon indexing, not a market-wide score.
- commercial.promotion_intent: source_type=ai_inferred, confidence=0.6, freshness_days=80, method=llm_scorer
- quality.anomaly_flags: source_type=heuristic, confidence=0.5, freshness_days=117, method=profile_snapshot_and_engagement_ratio_heuristic — Means "worth a manual check", NOT confirmed fraud. Flags can be wrong and are not a verdict about the person.
- quality.authenticity_score: source_type=heuristic, confidence=0.5, freshness_days=80, method=Profile-shape heuristic from a single snapshot (follower count, following ratio, account age, posting volume, verification), reduced for engagement red flags where post engagement was collected. Where only a follower count is available the score saturates at 58. — The input set differs by platform; do not compare this score across platforms.
- quality.koinon_bd_grade: source_type=ai_inferred, confidence=0.5, freshness_days=117, method=llm_partner_fit_classifier + fit_score >= 0.6 AND authenticity >= 60 => A; fit_score >= 0.4 AND authenticity >= 45 => B; else C. authenticity < 30 or a promotional-pattern flag => quarantine. — Koinon partner-outreach fit, not creator quality.
- reach.followers: source_type=observed, confidence=0.95, freshness_days=117, method=platform_profile

## Freshness
- profile_checked_days_ago: 117
- content_analysed_days_ago: 80
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 8
- user_triggered_requests: 0
- note: Being indexed in bulk is not the same as being retrieved to answer a question.

## This profile
- Claim or correct: https://koinonlink.com/claim?k=x_stalpharesearch
- Request removal: https://koinonlink.com/claim?k=x_stalpharesearch
- Terms: https://koinonlink.com/for-ai