Stock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is ...

An automatic stock market categorization system would be invaluable to individual investors and financial experts, providing them with the opportunity to predict the stock price changes of a company with respect to other companies. In recent years, clustering all companies in the stock markets based on their similarities in the shape of the stock market has increasingly become a common scheme. ...

This research paper was an endeavor to make a model, to find out the connection involving stock market and interest rate (Pakistani market) and to run certain tests related to statistical analysis. These tests run with the help of month end closing stock prices of Karachi Stock Exchange and interest rates of previous ten years i.e. Jan 2004 to Dec 2013. Correlation, Regression analysis and desc...

The increasing use of Twitter as a medium for sharing news related to various topics, facilitates methods for automatic news creation or event detection and prediction. However, these methods are hindered by users posting and propagating incorrect or irrelevant content. Choosing the right users is crucial in order to sample down the tweets to be analyzed, and preserve the quality of the predict...

market crash is a phenomenon which occurs in stock markets occasionally and leads to loss of the investors’ wealth and assets in a relatively short period of time. therefore, attempts for prediction of this phenomenon are of much importance for the investors, financial institutions and government. to this date, numerous and varied studies have been carried out for predicting and modeling  stock...

In this paper, we propose a Hybrid Kansei-SOM model, using Kansei Evaluation integrated with Self-Organizing Map (SOM) for stock market investment strategies. The proposed approach, using a group Decision Support System (DSS), aims to aggregate experts’ preferences with the selection of the most suitable stocks, matching with investing strategies to achieve investment returns by dealing with co...

The presence of stock market efficiency is a distinctive characteristic of the effectively functioning market economy. Investigation of the market efficiency of seven emerging East-European stock exchanges is carried out as their major stock indices (BELEX15, BET, CROBEX, ISE100, PFTS, RTSI, SOFIX) are studied in respect of long-range dependence (LRD), persistency, and forecasting possibili...

The present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, explanatory variables were aligned with petroleum products index mostly due to application of dollar data. Subsequently, to check va...

The stock evaluation process plays an important role in portfolio selection because it is the prerequisite for investment and directly influences on the stock allocation. This paper presents a methodology based on Data Envelopment Analysis for portfolio selection, decision making units which can be stocks or other financial assets. First, DMUs efficiencies are computed based on input/output com...