Enhancing Technical Trading Strategy on the Bitcoin Market using News Headlines and Large Language Models
سال انتشار: 1402
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 49
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شناسه ملی سند علمی:
TCCONF07_063
تاریخ نمایه سازی: 3 اردیبهشت 1403
چکیده مقاله:
We present a technical trading strategy that leverages the FinBERT language model and financial newsanalysis with a focus on news related to a subset of Nasdaq ۱۰۰ stocks. Our approach surpasses the baselineRange Break-out strategy in the Bitcoin market, yielding a remarkable ۲۴.۸\% increase in the win ratio forall Friday trades and an impressive ۴۸.۹% surge in short trades specifically on Fridays. Moreover, weconduct rigorous hypothesis testing to establish the statistical significance of these improvements. Ourfindings underscore considerable potential of our NLP-driven approach in enhancing trading strategies andachieving greater profitability within financial markets.
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نویسندگان
Mohammad Hosein Panahi
Graduate Student at dept. Electrical and Computer Engineering, University of Tehran
Naser Yazdani
Professor at dept. Electrical and Computer Engineering, University of Tehran