---
license: mit
title: Synthetic Stock Data Generator & Visualizer
emoji: 🧠
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.0
app_file: app/app.py
pinned: false
---
# 🧠 Synthetic Stock Data Generator & Visualizer

This project builds a **synthetic stock market data generator** using a combination of **Autoencoders (AE)** and **Generative Adversarial Networks (GANs)**.  
The goal is to create realistic synthetic financial time-series data and compare model performance between **real** and **synthetic** datasets.

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## 🚀 **Project Overview**

### 🔹 Workflow
1. **Autoencoder (AE):**
   - Encodes stock price data into a compressed **latent space**.
   - Captures temporal and feature-based dependencies between Open, High, Low, Close, and Volume.

2. **GAN (Generator + Discriminator):**
   - Learns to generate **synthetic latent vectors** that mimic the AE latent representations.
   - Generator produces fake latent vectors.
   - Discriminator learns to distinguish between real (from AE encoder) and fake (from Generator).

3. **Synthetic Data Reconstruction:**
   - The **synthetic latent vectors** are passed through the **AE Decoder**.
   - This recreates **synthetic stock market data** at the feature level (Open, High, Low, Close, Volume).

4. **Model Evaluation:**
   - A downstream **neural network classifier** is trained on:
     - Real data
     - Synthetic data
   - Performance metrics and comparison charts are saved in the `/charts` folder.

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## 📊 **Visualization App**

The project includes a **Gradio-powered dashboard** to visualize stock time series for real and synthetic data.

### 🖥️ Try it on Hugging Face
If you’re viewing this on Hugging Face, launch the app directly below 👇

[![Hugging Face Space](https://img.shields.io/badge/Gradio_App-Open_in_Space-blue?logo=gradio)](https://huggingface.co/spaces/Raheel31/Synthetic_Stock_Data)

### 🔍 App Features
- Select any stock ticker and feature (Open, High, Low, Close, Volume)
- View **5-year time series** comparisons of **original vs synthetic data**
- Interactive plots rendered with `matplotlib`

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## 📂 **Repository Structure**