Md. Ashraful Islam Khan

University of Rajshahi | RU · Department of Population Science and Human Resource Development

https://intjappscengineering.com/Journal/abstract/id/NDc3Nw==/?year=2021&month=June&volume=Volume%209&issue=Issue%201

Aim: The continuous innovation of information technologies accelerates the global economic development. The recent development of artificial intelligence and machine learning theory are not only through a big challenge to the graduates to enter to the job market but also all the stakeholders of entire knowledge economy to stay in the right track fo...

Global Access to Research Software: The Forgotten Pillar of Open Science Implementation.

The objective of this study is to model volatility (conditional variance) in the daily returns of the principal stock exchange of Bangladesh namely, Dhaka Stock Exchange (DSE) over the period from 27th November 2001 to 31st July 2013 for DSE general index. Based on AIC, BIC and LL the empirical results shows that the PGARCH model is the best fitted...

Engle and Patton (2000) point out that a volatility model must have the forecasting ability, this is the central requirement. They explore the stylized factors of volatility and observe the ability of GARCH type models to capture those features. In this paper, we aim to evaluate the ability of GARCH type models to capture the stylized factors of Dh...

The growing attention has been given for rural development during past two decades in most of the developing countries over the world. This is because of majority peoples live in rural areas where problems of poverty, inequality, unemployment etc. are increasing rapidly. Like other developing countries, Government of Bangladesh has given priority t...

Stock market plays the crucial role to move funds from the surplus units to the deficit units, therefore, it accelerate the economic development of a country. Noise trading is one of the important issues that influence the stock market volatility dynamics. Noise traders are very sensitive in having well or bad news rather use standard data/stock in...

Support vector machines (SVMs) are new semi-parametric tool for regression estimation. This paper introduced a new class of hybrid models, the nonlinear support vector machines heterogeneous autoregressive (SVM-HAR) models and aimed to compare the forecasting performance with the classical heterogeneous autoregressive (HAR) models to forecast finan...

The aim of this paper is to compare the performance of the daily nonlinear support vector machines, the new semi-parametric tool for regression estimation, heterogeneous autoregressive (SVM-HAR)-ARCH type models based on the daily realized volatility (which uses intraday returns) with the performance of the classical HAR-ARCH type models by using d...