ML-QuantSubscribe

SSRNDerivatives & Volatility

Bi-objective Cost-sensitive Machine Learning: Predicting Stock Return Direction Using Option Prices

The research investigates the use of cost-sensitive loss functions in machine learning models to predict equity market index movement, using option prices as a measure of error costs.

Featured in No. 13 on 24 Aug 2023 · 3 days after release · 0 citations today

Released
21 Aug 2023
First featured
No. 13 · 24 Aug 2023
Citations (Semantic Scholar)
0
Influential citations
0
Published in
Not yet, as far as Semantic Scholar knows
Shares when featured
2
Identifier
SSRN 4546402

Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).

    Type to search. Try rough volatility, LLM agents or FinGPT.

    ↑↓ move↵ openesc closeFull search page