Open AccessAccess Risk Management for Arabian IT Company for Investing Based on Prediction of Supervised Learning
Author(s) -
Bhupinder Singh,
Santosh Kumar Henge
Publication year - 2021
Publication title -
journal of risk analysis and crisis response
Language(s) - English
Resource type - Journals
eISSN - 2210-8505
pISSN - 2210-8491
DOI - 10.54560/jracr.v11i3.300
Subject(s) - autoregressive integrated moving average , dividend , share price , profit (economics) , margin (machine learning) , actuarial science , profit margin , economics , financial economics , finance , business , stock exchange , marketing , computer science , time series , microeconomics , machine learning
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.