Market Intelligence v1 Charts + News + Sentiment → Structured Suggestions
Fresh Start · v1 Concept + Mock API

A website that analyzes any ticker using charts, news, and sentiment

This is the first-principles direction: a decision-support system for crypto and stocks. Enter a ticker, let the system evaluate technical structure, gather relevant news, estimate sentiment, and return a structured trade or investment suggestion.

Analyzer

Interactive mock analyzer

Market Intelligence Enter a ticker and request a structured analysis

Examples: BTC, SOL, AAPL, TSLA, NVDA

This form now targets https://api.trading.sofianavarro.cloud/analyze.

Live Demo Area

Generated analysis result will appear here

Right now this section is wired and waiting for the backend route. Once /api/analyze is reachable from the site, submitting the form above will render the result here.

Flow

How one analysis request moves through the system

Ticker Input
Market Data
Technical Engine
News + Sentiment
Recommendation Engine
Structured Report
Schema

Analyzer result JSON contract

Top-level sections

  • request
  • asset
  • technical
  • news
  • sentiment
  • recommendation
  • meta

Why this matters

This is the contract between frontend and backend. If we keep this stable, the UI, analysis modules, and future API can evolve without turning into soup.

Example analyzer result

{
  "request": {
    "ticker": "BTC",
    "asset_class": "crypto",
    "timeframe": "4H",
    "horizon": "swing"
  },
  "asset": {
    "name": "Bitcoin",
    "ticker": "BTC",
    "asset_class": "crypto",
    "exchange": "Binance",
    "currency": "USD",
    "price": 84250.5,
    "change_percent_24h": 2.1,
    "volume_24h": 34800000000,
    "market_cap": 1670000000000
  },
  "technical": {
    "trend": "bullish",
    "momentum": "positive",
    "volatility": "moderate",
    "structure": "pullback_continuation",
    "support": 82900,
    "resistance": 85500,
    "score": 68,
    "confidence": 74,
    "summary": "Price remains above major trend structure with constructive momentum."
  },
  "news": {
    "score": 22,
    "confidence": 61,
    "summary": "Recent headline flow is mildly supportive.",
    "headlines": []
  },
  "sentiment": {
    "label": "moderately_bullish",
    "score": 18,
    "confidence": 55,
    "summary": "Overall sentiment appears constructive.",
    "sources": {
      "news_sentiment": 21,
      "social_sentiment": 8,
      "market_context_sentiment": 16
    }
  },
  "recommendation": {
    "direction": "bullish",
    "action": "trade_candidate",
    "confidence": 71,
    "time_horizon": "swing",
    "weighted_score": 46.4,
    "summary": "Technicals, news, and sentiment are aligned enough for a constructive swing-trade bias.",
    "thesis": [],
    "risks": [],
    "invalidation": "A sustained move below support would weaken the thesis."
  },
  "meta": {
    "generated_at": "2026-03-26T22:07:00Z",
    "version": "v1",
    "data_freshness": {},
    "notes": []
  }
}
Roadmap

What comes next

01

Expose mock API

Run the FastAPI service and route it behind the site as /api or a subdomain.

02

Live demo flow

Let the website submit real requests to the mock backend and render results dynamically.

03

Replace mock technicals

Start feeding real chart data and computed indicator logic.

04

Replace mock news

Pull relevant headlines and classify them by impact.

05

Replace mock sentiment

Compute real sentiment scores and confidence.

06

Refine recommendation engine

Turn the output into a more disciplined, evidence-weighted suggestion model.