Performance evaluation metric for statistical learning trading strategies
We analyze how the sentiment of financial news can be used to predict stock returns and build profitable trading strategies. Combining the textual analysis of financial news headlines and statistical methods, we build multi-class classification models to predict the stock return. The main contributi...
Saved in:
Main Authors: | Jiawei He, Roman N. Makarov, Jake Tuero, Zilin Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
AIMS Press
2024-12-01
|
Series: | Data Science in Finance and Economics |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/DSFE.2024024 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Impact of using time-averaged exposure metrics on binary endpoints in exposure-response analyses
by: Yu-Wei Lin, et al.
Published: (2025-01-01) -
Investor sentiment networks: mapping connectedness in DJIA stocks
by: Kingstone Nyakurukwa, et al.
Published: (2025-01-01) -
The introduction of the metric system of weights and measures in the Omsk district in the 1920s
by: I. V. Makarov
Published: (2024-05-01) -
Selection of geometrical features of nuclei оn fluorescent images of cancer cells
by: Ya. U. Lisitsa, et al.
Published: (2019-06-01) -
Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models
by: Filipe Augusto Felix de Queiroz, et al.
Published: (2024-12-01)