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  • Whitepaper
    • Abstract
    • C-Mizar
      • Problem
      • Solution
      • Opportunity
      • Product
        • Marketplace
        • DCA Bots
        • API Bots
        • Smart Trading
        • Paper Trading
        • Portfolio Manager
    • D-Mizar
      • Problem
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      • Product
        • Contract Sniffer
        • Sniper Bot
    • $MZR Token
      • Use Cases
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      • Vesting Schedule and Release
      • FAQ
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      • Supersonic Phase (C-Phase)
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    • Team
  • SDK
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      • DCA Bot SDK
      • DCA Bot - TradingView
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  • Mizar AI (on hold)
    • Mizar AI (on hold)
    • Data Sources
    • Model
      • Downsampling with CUSUM Filter
      • Average Uniqueness
      • Sample Weights
      • Sequentially Bootstrapped Bagging Classifier
      • Metalabeling
      • Bet Sizing
      • Combinatorial Purged Cross Validation
    • Structural Breaks
    • Transformations
      • Labeling Methods
      • Technical Analysis Features
      • Microstructural Features
    • Strategy Backtesting
    • Strategy Deployment
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  1. Mizar AI (on hold)

Model

A set of tools to support users developing better models.

Developing the model is arguably one of the most important parts of the development process of a trading strategy, however when a user is developing machine learning models in a time series context, one should be wary that traditional methods can lead to results that are too optimistic when used incorrectly. The following set of modules assist the user in multiple aspects of building a machine learning model.

The following subsections are technical by nature and it is assumed the reader has familiarity with modeling financial time series.

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Last updated 4 years ago

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