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  • Gen-AI

AI Algorithmic Trading Bot

An AI-driven trading assistant that ingests market data and executes or simulates trades automatically.

Overview

Historical and real-time price and volume data are fetched via APIs, LSTM and Transformer models generate Buy/Sell/Hold signals, and a LangChain reasoning agent explains each trading decision while applying risk-management logic. The bot connects to broker APIs for live or simulated execution with P&L and performance tracking.

Problem Statement

Algorithmic trading systems produce signals without justification, which makes them impossible to trust or debug when they lose money. Risk management is usually bolted on afterwards, if at all.

Proposed Solution

Pair the predictive models with a reasoning agent that states why each trade was taken and enforces risk rules before execution, and support paper trading so strategies can be validated without capital.

Key Features

  • Automated Data Ingestion

    Fetches historical and real-time price/volume data via APIs.

  • LSTM/Transformer Price Prediction

    Generates Buy/Sell/Hold trading signals.

  • LangChain Reasoning Agent

    Explains trading decisions and applies risk-management logic.

  • Live & Simulated Execution

    Connects to broker APIs with P&L and performance tracking.

Technologies Used

Deep Learning

  • LSTM
  • Transformers
  • PyTorch
  • Time series modelling

Gen-AI

  • LangChain
  • LLM reasoning agent
  • Tool calling

Trading

  • Broker APIs
  • Backtesting
  • Risk management
  • Pandas

Project Workflow

  1. 1

    Data ingestion

    Market data is fetched historically and in real time.

  2. 2

    Signal generation

    LSTM/Transformer models emit Buy/Sell/Hold calls.

  3. 3

    Reasoning & risk

    The agent explains the call and applies risk rules.

  4. 4

    Execution

    Trades are placed live or simulated via broker APIs.

  5. 5

    Tracking

    P&L and performance metrics are logged.

What You'll Receive

  • Complete, runnable source code with folder structure
  • Project report and technical documentation
  • Ready-to-present PPT content
  • Setup and installation walkthrough
  • Line-by-line project explanation session
  • Viva question bank with answers
  • Bug fixing and troubleshooting help
  • Post-delivery support after submission

Frequently Asked Questions

How much does this project cost?

Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.

Can the project be customised to my college requirements?

Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.

Will I be able to explain this project during my viva?

That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.

What if the project does not run on my laptop?

We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.

Do I get support after submission?

Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.

Want This Project?

Get complete source code, documentation, PPT, explanation, and support.

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