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sentiment.ai
  • Introduction
  • More about tweets
  • Project setup
    • Installation
    • User tweets
    • Stock tweets
  • Data collection
    • Web scraping
    • Historical Stock Data
    • Generate User Features
      • Example user feature
    • Generate Stock Features
      • Example stock feature
  • Prediction
    • System Overview
    • Backtesting
      • Parameter Optimization
      • User cutoffs
      • User transformation
      • User weighting
      • Feature standardization
  • Cloud processing
    • AWS
    • MongoDB
      • Tweets
  • Future Work
    • Data Collection
    • Prediction
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  1. Prediction
  2. Backtesting

User weighting

PreviousUser transformationNextFeature standardization

Last updated 4 years ago

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List of current features being used in user weighting and their associated parameter weighting. These weights were determined based on . The strategy for generating these features and corresponding weights are all open to change.

return: 0.9

return_s: 2.8

return_w: 0.7

accuracy: 1.7

accuracy_s: 0.6

all_features: 1.5

all_features_s: 0.9

all_features = accuracy * return * num_tweets
parameter optimization