My journey in economic research began in my undergraduate years at the University of Rajshahi, where I studied potato production and conducted correlation analysis using Python. For my Master’s, I explored the Dhaka Stock Exchange, analyzing macroeconomic influences on stock performance and applying GARCH models to study market volatility.

This page outlines the description (such as titles and abstracts) of my research.

Focus

Financial economics, volatility analysis, stock exchange, agricultural production, development economics.

Projects

Title: Macroeconomic Variables, Stock Returns, and Market Volatility: An Econometric Study of the Dhaka Stock Exchange

Purpose: Master’s Thesis

Year: 2023-2024

Datasets: DS30 monthly performance data, along with monthly inflation, interest rate, and exchange rate data from January 2013 to December 2023 for relationship analysis. In addition, the DSEX index’s daily volatility data from October 2012 to February 2024 was used for volatility analysis.

Analysis Tools used: Python (pandas, statsmodels, arch, matplotlib)

Abstract: This study investigates the relationship between key macroeconomic variables and stock market performance, as well as volatility patterns, in the Dhaka Stock Exchange (DSE) from January 2013 to December 2023. Using monthly data, we assess the influence of inflation rate, interest rate, and foreign exchange rate on the monthly returns of the DS30 index through correlation analysis, simple linear regression, and multiple linear regression models. The findings reveal weak and statistically insignificant relationships between macroeconomic indicators and stock returns, with only 1.5% of the variation in returns explained by the combined factors. In addition, the GARCH (1,1) model, EGARCH, and TGARCH models were employed to capture the volatility dynamics in the DSE using DSEX daily return (data from October 2012 to February 2024). The results suggest that volatility in the DSE is persistent, with both recent shocks and past volatility playing significant roles. Furthermore, the TGARCH model identifies an asymmetric effect, where negative shocks have a larger impact on volatility than positive shocks of the same magnitude. These findings show the complex interplay between macroeconomic variables and stock market performance, providing important implications for investors and policymakers. Effective risk management strategies are crucial, especially during periods of heightened volatility.

Title: Benefit-Cost Analysis of Potato Production in Aria Union of Shajahanpur Upazila in Bogura

Purpose: Undergraduate field study

Year: 2023

Datasets: Samples from 31 households from the study area

Analysis Tools used: MS Excel and Python

Abstract: This study aims to analyse the profitability of rural farmers who produce potatoes. The study was conducted in the Aria Union of Shajahanpur Upazila in Bogura, Bangladesh. The objective of the research was to identify the costs of inputs used in potato production, to determine the revenue farmers earn from potato sales and to analyse factors affecting the potato production. The study found an average benefit of Tk 12543.01. Additionally, the research found a moderate negative correlation between the quantity of pesticides used and the quantity of potatoes produced (-.52), a strong positive correlation between monthly income and non-agricultural income (.77), a strong positive correlation between the amount of land and agricultural income (.86), and a moderate negative correlation between the number of dependent members and the costs of final labour (-.51). These findings provide valuable information for farmers in the area to make informed decisions about their potato production operations.