Quant Workers

Detailed Explanation for Quant Worker Role at TickLab.IO

Overview

A Quant Worker at TickLab.IO is responsible for developing, testing, and deploying algorithmic trading strategies. The role involves utilizing the TickLab SDK, engaging with E.D.I.T.H., and ensuring strategies meet performance criteria before going live. The process is highly structured to ensure the reliability and profitability of trading strategies.

Workflow for Quant Worker

  1. Application Process

    • Join Worker Form: Interested individuals apply by filling out a form.

    • Application Accepted: If accepted by E.D.I.T.H , they proceed to the next step.

  2. Setup

    • Accepted as Quant Worker Engineer: Officially becomes a Quant Worker at TickLab.IO.

    • Open IDE (VS Code): Sets up the development environment, primarily using VS Code.

  3. Strategy Development

    • Develop Strategy: The core phase where the Quant Worker uses the TickLab SDK to:

      • Pull Market Data: Retrieve necessary market data for analysis.

      • Build Trading System: Develop the algorithmic trading system.

      • Write and Test Code: Implement and refine the trading strategy.

  4. Backtesting and Live Evaluation

    • Perform Backtesting: Test the strategy against historical data to validate its performance and E.D.I.T.H will confirm to pass to Evaluation step or not.

    • Submit for Evaluation: Submit the strategy for formal evaluation.

    • Evaluation Step: The strategy undergoes a rigorous evaluation process.

  5. Deployment and Live Testing

    • Host Strategy: The strategy is hosted on the TickLab platform.

    • Use API for Live Testing: Conduct live tests using API connections to trading platforms.

    • Successful Evaluation: Upon passing live tests and evaluations, the strategy is funded and goes live.

Data Pipeline for Quant Worker

  1. Data Sources

    • Real-time & Historical Data: Collect both real-time and historical market data and some type of TickLab indicators with edith SDK.

    • Data Ingestion Pipeline: Process data through an ingestion pipeline for analysis.

  2. Data Processing

    • Clean & Normalize: Clean and normalize the data for consistency use the help of edith SDK.

    • Data Storage: Store processed data for easy access and retrieval using Storj.io .

    • Stream: Stream real-time data for immediate analysis using Pyth Network.

    • Backtester: Use historical data for backtesting strategies using TickLab SDK.

  3. Strategy Development and Optimization

    • Quant Worker: The central role in developing and optimizing trading strategies.

    • Strategy Development: Create new strategies based on data insights.

    • Optimization with E.D.I.T.H.: Use E.D.I.T.H. to optimize and refine strategies.

    • Deployment: Deploy strategies for live trading.

    • Execution Engine: Execute trades based on the deployed strategy.

    • Risk Management: Implement risk management protocols to minimize losses.

    • Performance Monitoring: Continuously monitor the performance of strategies and make necessary adjustments.

    quant worker digram

Components and Tools Used

Component
Description

TickLab SDK

A toolkit for building and testing algorithmic trading strategies.

E.D.I.T.H.

AI-powered financial intelligence system for optimization and risk management.

Backtester API

Tool for validating trading strategies against historical data.

IDE (VS Code)

Integrated Development Environment used for coding and testing strategies.

API Trading

Interface for connecting trading accounts and automating trades.

Data Storage

Central repository for cleaned and normalized market data.

Execution Engine

Platform for executing trades based on the deployed strategy.

Risk Management

System for managing and mitigating risks associated with trading.

Performance Monitoring

Tools for tracking and evaluating the performance of live strategies.

Storj.io

To store the data

Pyth Network

Stream real-time data

Key Performance Criteria

  • Maximum Daily Drawdown: 5% - 10% (not final decision)

  • Maximum Loss: 10% (not final decision)

  • Take Profit: 10% (not final decision)

Evaluation Process

  1. Backtesting Results: Initial validation using historical data.

  2. Real-time Performance Evaluation: Testing the strategy in a live environment.

  3. Funding: Successful strategies receive funding from TickLab.IO.

Interaction with E.D.I.T.H.

  • Market Analysis: Provides real-time insights and predictions.

  • Strategy Optimization: Offers suggestions for improving strategy performance.

  • Risk Assessments: Conducts detailed risk evaluations for strategies.

Summary

A Quant Worker at TickLab.IO plays a pivotal role in creating and maintaining profitable trading strategies. By leveraging the tools and resources provided by TickLab.IO, including the TickLab SDK and E.D.I.T.H., Quant Workers can develop, test, and optimize their strategies efficiently. The structured workflow ensures that only the most robust and effective strategies go live, thereby maximizing returns and minimizing risks for investors.


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