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BroStock AI

Python FastAPI Chart.js Status

AI-powered stock analytics dashboard built with FastAPI, JavaScript, and Chart.js.
It provides technical analysis indicators, multi-panel financial charts, and short-term AI price forecasting in a modern trading-terminal style web interface.

Live Demo

https://brostock-ai-demo.onrender.com

Technical Analysis Dashboard

Technical Dashboard

AI Forecast Mode

AI Forecast

Example Trading Interface

The dashboard provides two main analysis modes:

Technical Analysis Mode

Displays price action with indicators and trade signal markers.

AI Forecast Mode

Displays short-term price projection along with an aggregated AI trading signal.

Overview

BroStock AI is a full-stack financial analytics dashboard that combines:

  • real-time market data
  • technical indicators
  • machine learning forecasting

into a single interactive web application. The system fetches stock market data using Yahoo Finance, processes the data in a FastAPI backend, and visualizes the indicators through synchronized multi-panel charts built with Chart.js. This project demonstrates how financial analytics pipelines and machine learning models can be integrated into a modern web application architecture.

Features

Price & Trend Analysis

  • Live stock price fetching via Yahoo Finance (yfinance)
  • Interactive price charts built with Chart.js
  • 7-day and 21-day Moving Averages (MA7, MA21)
  • Integrated volume bars inside the main price chart
  • Toggle controls for indicators

Trade Signal Markers

The technical chart includes visual trade signal markers generated from indicator conditions. Markers displayed on the chart:

  • ▲ Buy Signal
  • ▼ Sell Signal
  • ★ Strong Buy
  • ✖ Strong Sell

Signals are derived from combinations of:

  • Moving Average crossovers
  • RSI momentum conditions
  • MACD trend confirmation

These markers help highlight potential entry and exit points directly on the price chart.

Volume Analysis

  • Integrated volume bars within the price chart
  • Dual-axis scaling for accurate price/volume comparison
  • Helps confirm price movement strength

RSI (Relative Strength Index – 14)

Momentum indicator displayed in a dedicated analysis panel. Features include:

  • RSI(14) calculation
  • Overbought level at 70
  • Oversold level at 30
  • Rolling averages computed in the backend
  • Defensive handling of NaN / infinite values

MACD (Moving Average Convergence Divergence)

Trend-following momentum indicator with its own chart panel. Includes:

  • EMA(12) and EMA(26) MACD calculation
  • 9-period Signal line
  • Histogram visualization
  • Dynamic momentum bars (green/red)
  • Synchronized time axis with the price chart

AI Forecasting

BroStock AI includes an AI-powered forecasting module that predicts short-term price movement using linear regression trend modeling.

AI Forecast Panel

  • Separate AI Forecast chart mode
  • Historical price vs predicted future prices
  • Forecast displayed as a dashed projection line

Forecast Horizon Controls

Users can dynamically select forecast length:

  • 7 Days
  • 14 Days
  • 30 Days

The chart updates automatically without reloading the page.

AI Signal Engine

In addition to price forecasting, BroStock AI generates a trade signal summary using multiple technical indicators. The AI Signal panel evaluates:

  • Trend direction
  • RSI momentum
  • MACD momentum
  • Forecasted price movement

The system then produces an aggregated signal:

  • Strong Buy
  • Buy
  • Neutral
  • Sell
  • Strong Sell

Example signal output:

  • AI SIGNAL
  • STRONG BUY
  • Confidence: 66%
  • Trend: Bullish
  • RSI: 50.56
  • MACD: Bullish Momentum

This provides a quick high-level interpretation of the current market conditions.

Forecast Model

The backend trains a Linear Regression model on historical price data to estimate short-term price trajectory. While intentionally simple, it demonstrates the integration of machine learning workflows inside a real-time analytics dashboard.

Dashboard Controls

The interface provides several interactive controls:

  • Technical Mode / AI Forecast Mode toggle
  • Forecast horizon selection (7D / 14D / 30D)
  • Indicator visibility toggles (MA7 / MA21)
  • AI signal summary panel
  • Smooth chart redraws when switching modes
  • Trading-terminal inspired dark interface

Data Integrity & Stability

Financial data can contain missing or unstable values.
The backend includes defensive engineering to ensure stable visualization.

  • Safe float sanitization before JSON serialization
  • NaN / infinite value handling
  • Pandas multi-index normalization
  • Stable backend-frontend data contracts

Tech Stack

Backend

  • Python
  • FastAPI
  • yfinance
  • pandas
  • NumPy
  • scikit-learn (Linear Regression)

Frontend

  • HTML
  • CSS (custom dark UI)
  • JavaScript (ES Modules)
  • Chart.js

Architecture Overview

User Input
→ JavaScript fetch request
→ FastAPI backend
→ Yahoo Finance data (yfinance)
→ Backend computes indicators (MA, RSI, MACD)
→ Linear Regression model generates forecast
→ Safe JSON serialization
→ Chart.js renders interactive dashboard

All financial calculations and forecasting are performed in the backend to ensure numerical stability and clean architecture.

Indicators Explained

Moving Averages (MA7 / MA21)

Moving averages smooth price data and help identify short-term versus medium-term trends.

Volume

Volume confirms the strength behind price movement.
High volume during breakouts often signals stronger market conviction.

RSI (14)

Momentum oscillator:

  • Above 70 → Overbought
  • Below 30 → Oversold

MACD

Trend-following momentum indicator:

  • MACD crossing above signal → Bullish shift
  • MACD crossing below signal → Bearish shift
  • Histogram visualizes momentum acceleration

Project Structure

backend/ ├── main.py └── stock_analyzer.py

frontend/ ├── index.html ├── style.css └── js/ ├── app.js ├── charts.js ├── ui.js └── api.js

The application follows a clear separation of concerns:

Backend

  • Data fetching
  • Indicator calculations
  • AI forecasting

Frontend

  • Data visualization
  • Chart rendering
  • User interface controls

Running Locally

Clone the repository: git clone https://github.com/RDC4321/BroStock-AI.git cd BroStock-AI

Install dependencies: pip install -r requirements.txt

Run the server: uvicorn main:app --reload

Open in browser: http://127.0.0.1:8000

Roadmap

Future improvements planned for BroStock AI:

  • AI confidence interval bands
  • Portfolio backtesting tool
  • Candlestick chart mode
  • Time-range selector (1W, 1M, 3M, 1Y)
  • Crosshair synchronization across charts
  • News sentiment integration
  • Cloud deployment

Why This Project?

This project demonstrates practical skills in:

  • Full-stack system design
  • Financial indicator implementation
  • Machine learning integration
  • API design and structured JSON contracts
  • Defensive data engineering
  • Chart.js multi-panel visualization
  • Interactive UI state management The system demonstrates how traditional technical analysis and machine learning models can be combined into a unified trading dashboard.

Disclaimer

This project is for educational and portfolio purposes only. It does not provide financial advice or trading recommendations.