Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for improved trend tracking and risk adjustment

Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for improved trend tracking and risk adjustment

Abstract Commodity Trading Advisor (CTA) strategies traditionally rely on fixed technical indicators for trend tracking, which often yield significant errors in volatile markets. This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machin...

Full description

Saved in:
Bibliographic Details
Main Authors: Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu
Format: Article
Language:English
Published: Springer 2025-05-01
Series:Discover Applied Sciences
Subjects:
Adaptive moving average (AMA)
Support vector machine (SVM)
Sparrow search algorithm (ISSA)
Hybrid strategy
CTA
Securities investment
Online Access:https://doi.org/10.1007/s42452-025-07016-y
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1007/s42452-025-07016-y

Similar Items