Neutrosophic soft set decision making for stock trending analysis

In this paper, we point out a major issue of stock market regarding trending scenario of trades where data exactness, accuracy of expressing data and uncertainty of values (closing point of the day) are lacked. We use neutrosophic soft sets (NSS) consisting of three factors (True, Uncertainty and Fa...

Full description

Saved in:
Bibliographic Details
Published in:Evolving systems 2019-12, Vol.10 (4), p.621-627
Main Authors: Jha, Sudan, Kumar, Raghvendra, Son, Le Hoang, Chatterjee, Jyotir Moy, Khari, Manju, Yadav, Navneet, Smarandache, Florentin
Format: Article
Language:English
Subjects:
Artificial Intelligence
Complex Systems
Complexity
Engineering
Original Paper
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we point out a major issue of stock market regarding trending scenario of trades where data exactness, accuracy of expressing data and uncertainty of values (closing point of the day) are lacked. We use neutrosophic soft sets (NSS) consisting of three factors (True, Uncertainty and False) to deal with exact state of data in several directions. A new approach based on NSS is proposed for stock value prediction based on real data from last 7 years. It calculates the stock price based on the factors like “open”, “high”, “low” and “adjacent close”. The highest score value retrieved from the score function is used to determine which opening price and high price decide the closing price from the above mentioned four factors.
ISSN:1868-6478
1868-6486
DOI:10.1007/s12530-018-9247-7