# Ashwin Badrinath (@AshwinBadri2) on x

- id: koinon:creator:x_ashwinbadri2
- url: https://koinonlink.com/kol/x/AshwinBadri2
- schema_version: 1.4

## Identity
- platform: x
- handle: AshwinBadri2
- platform_url: https://twitter.com/AshwinBadri2
- country: India
- entity_type: creator
- person_id: Cross-platform identity not resolved for this creator.

## Reach
- followers: 4462
- following: 747
- posts_total: 3949
- posts_observed: 1
- posts_per_day: 1.116
- account_age_days: 3537
- verified: true
- size_tier: nano

## Engagement
- status: peak_post_only
- peak_post_engagement_rate: 0.01591
- best_post_interactions: 71
- 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: Closing auction mechanics on NSE, Expiry settlement and price discovery issues, Options premium volatility and mean reversion, Market structure changes as alpha source
- bio: Tracking the narratives, signals and risk shifts that move markets before consensus catches

https://t.co/uoyA3xa8Gv

## Audience (inferred)
- status: present
- description: Indian derivatives traders and market microstructure analysts focused on NSE expiries, closing auctions and options premiums
- roles: data
- seniority: practitioner
- pain_points: Closing auctions moving indices 150+ points after 3:15 PM and distorting expiry settlements, Wild swings in premiums (e.g. +20L to -19L) that break normal price discovery, Inconsistent mean reversion in PnL that is hard to time reliably, Regulatory/market structure changes that suddenly alter alpha opportunities
- posts_analysed: 4
- 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: 78
- authenticity_basis: engagement_observed
- credibility_score: 78
- 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_ashwinbadri2#7c77fa71] Serious question for @SEBI_India and @NSEIndia Why should expiry settlements depend on a closing auction that can move the index 150+ points after 3:15 PM, when continuous spot trading has already ended? Today’s data showed: 1. HHI: 0.646 (93rd percentile) 2. 80% of dealer gamma  (https://twitter.com/AshwinBadri2/status/2070472401574568047)
- [x_ashwinbadri2#cba1c0cd] +20L to -19L to +18L to -9L to +6L to -15L. If this is healthy price discovery, then I’m the Queen of England. 2 PM onwards, premiums suddenly discover steroids while liquidity disappears. @NSEIndia & @SEBI_India seem determined to finish off what’s left of India’s options ecosys
- [x_ashwinbadri2#b67133af] +20L to -6L. Mean reversion came in Pnl. Mean reversion works
- [x_ashwinbadri2#a7ca47f1] Sometimes a market structure change creates more alpha than a new indicator. Closing Auction Mech

## 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=78, 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=78, 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=78, 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: 78
- audience_updated_days_ago: 76

## AI retrieval
- indexing_requests: 10
- 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_ashwinbadri2
- Request removal: https://koinonlink.com/claim?k=x_ashwinbadri2
- Terms: https://koinonlink.com/for-ai