32 lines
1.0 KiB
Markdown
32 lines
1.0 KiB
Markdown
# Augor
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> Drilling beneath surface sentiment to extract trading signals from financial news.
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## What is this?
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Augor uses Large Language Models to interpret business events and generate trading signals. Instead of just counting positive/negative words, it understands what events *mean* for markets.
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Traditional sentiment analysis: "This news mentions 'partnership' → positive"
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Augor: "This partnership expands market access but dilutes margins → mixed signal"
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## Why?
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Traditional NLP methods are limited:
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- Can't understand context or nuance
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- Miss complex implications of business events
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- Struggle with negation and sarcasm
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LLMs can reason about *why* news matters, not just classify it as positive/negative.
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## What it does
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1. Aggregates news from multiple sources
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2. Interprets business events (mergers, partnerships, product launches)
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3. Generates trading signals based on reasoned analysis
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4. Backtests performance against traditional approaches
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## Author
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Benjamin Watt
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Supervisor: Panagiotis Kanellopoulos
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University of Essex |