Access Risk Management for Arabian IT Company for Investing Based on Prediction of Supervised Learning

Bhupinder Singh, Santosh Kumar Henge
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引用次数: 2

Abstract

The study focuses on chances of profit from Saudi IT company to increase with few losing trade and a less margin winning investing decisions. Fear and greed are two psychological points that dominates the investing decisions. The main objective of the research to study the risk management related to Al Moammar Information Systems that is listing on Saudi Share market. Previous Research relied on limited methods for prediction of accurate price for investing in the current bullish Markets. The research also emphasizes on predicting the right price for investing on the basis of Supervised Learning methods involving Support Vector Machine, Random Forest Regression, XGBoost, Auto Arima and Quasi Poisson Regression. Research has found that the right price to investing in this company comes out to be 106.945 on the prediction of previous 6 months period data. Data is sourced though Yahoo Finance api in form of Date, Open, High, Low, Close, Volume, Dividends and Stock Splits. This solution can be fruitful for newly trained investors who are willing to invest for long term basis.
基于监督学习预测的阿拉伯IT企业投资准入风险管理
该研究的重点是沙特IT公司的利润增加的机会,几乎没有损失的贸易和更少的利润赢得投资决策。恐惧和贪婪是支配投资决策的两个心理点。本研究的主要目的是研究在沙特股票市场上市的Al Moammar信息系统公司的风险管理。以前的研究依赖于有限的方法来预测当前看涨市场的准确价格。该研究还强调了基于监督学习方法(包括支持向量机、随机森林回归、XGBoost、Auto Arima和Quasi Poisson回归)来预测正确的投资价格。研究发现,根据前6个月的数据预测,投资该公司的合适价格为106.945。数据来源通过雅虎财经api的形式,日期,开盘,高,低,收盘,成交量,股息和股票分割。这种解决方案对于愿意长期投资的新培训投资者来说是富有成效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.70
自引率
0.00%
发文量
24
审稿时长
12 weeks
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