Evaluating the effectiveness of macroeconomic determinants on the performance of the Dhaka Stock Exchange: A time series approach

Year 2025, Volume: 7 Issue: 1, 12 - 27

Fairuz Anjum Binte Habib

https://doi.org/10.58251/ekonomi.1550307

Abstract

The study examines the causal relationships between selected macroeconomic variables and the Dhaka Stock Exchange Broad Index (DSEX) from 2013 to 2023. The researcher employed time series economic approaches such as the Augmented Dickey-Fuller (ADF) test for stationarity, the Vector Autoregression (VAR) and Granger causality tests for short-term dynamics, and Johansen's co-integration test for long-term relationships. The findings demonstrate no co-integration between the variables, implying that there is no substantial long-term relationship between how they change over time. However, the VAR analysis shows short-term association between the chosen macroeconomic factors and the DSEX index performance. This implies that changes in any of these macroeconomic variables may have a short-term impact on the DSEX index. Additionally, causality testing reveals unidirectional relationships, indicating that the DSEX index has a considerable impact on numerous economic indicators, including GDP growth, money supply growth, unemployment, inflation and interest rates. Overall, the DSEX index plays an important role in Bangladesh's macroeconomic landscape by accurately forecasting changes in these variables. This study provides important insights into the operation of the Bangladeshi stock market and fills a gap in the literature on developing economies. The results have implications for Bangladeshi investors and policymakers aiming to increase profits, make informed decisions, and support economic stability. Future research should take into account other macroeconomic variables and market indexes to have a better understanding of stock market dynamics.

Keywords

unemployment rate, interest rate, capital market, causal, inflation, GDP growth rate, DSEX broad index

References

• Ahmad, M. et al. (2023a). Households' perception-based factors influencing biogas adoption: Innovation diffusion framework. Energy, 263, 126155.
• Ahmad, M. et al. (2023b). Is environmental sustainability transmissible? Transportation-based environmental taxation spillovers for sustainable development. Environmental Science and Pollution Research, 30(31), 77420-77435.
• Aldin, M. M., Dehnavi, H. D., & Entezari, S. (2012). Evaluating the employment of technical indicators in predicting stock price index variations using artificial neural networks (case study: Tehran Stock Exchange). International Journal of Business and Management, 7(15), 25-34. https://doi.org/10.5539/ijbm.v7n15p25
• Almansour, A. Y., & Almansour, B. Y. (2016). Macroeconomic indicators and Saudi equity market: A time series analysis. British Journal of Economics, Finance and Management Sciences, 12(2), 59-72.
• Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A., & Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326
• Al-Kandari, A. M., & Abul, S. J. (2019). The impact of macroeconomic variables on stock prices in Kuwait. International Journal of Business and Management, 14(6), 99-112. https://doi.org/10.5539/ijbm.v14n6p99
• Alvarado, R. et al. (2023). Nexuses between rent of natural resources, economic complexity, and technological innovation: The roles of GDP, human capital and civil liberties. Resources Policy, 85, 103637.
• Alvarado, R. et al. (2022a). Impact of natural resources on economic progress: evidence for trading blocs in Latin America using non-linear econometric methods. Resources Policy, 79, 102908.
• Alvarado, R. et al. (2022b). Impact of the informal economy on the ecological footprint: the role of urban concentration and globalization. Economic Analysis and Policy, 75, 750-767.
• Asekome, M. O., & Agbonkhese, A. O. (2015). Macroeconomic variables, stock market bubble, meltdown and recovery: Evidence from Nigeria. Journal of Finance and Bank Management, 3(2), 25-34. https://doi.org/10.15640/jfbm.v3n2a3
• Algieri, B., Brancaccio, E., & Buonaguidi, D. (2020). Stock market volatility, speculation and unemployment: A Granger-causality analysis. PSL Quarterly Review, 73(293), 137–160. https://doi.org/10.13133/2037-3643_73.293_3
• Abu-Libdeh, H., & Harasheh, M. (2011). Testing for correlation and causality relationships between stock prices and macroeconomic variables: The case of Palestine Securities Exchange. International Review of Business Research Papers, 7(5), 141-154.
• Alzyadat, J. A., & Asfoura, E. (2021). The effect of the COVID-19 pandemic on the stock market: An empirical study in Saudi Arabia. Journal of Asian Finance, Economics and Business, 8(5), 913–921. https://doi.org/10.13106/jafeb.2021.vol8.no5.0913
• Anas, M. et al. (2023). Moving towards sustainable environment development in emerging economies: The role of green finance, green tech‐innovation, natural resource depletion, and forested area in assessing the load capacity factor. Sustainable Development.
• Bhuiyan, E. M., & Chowdhury, M. (2020). Macroeconomic variables and stock market indices: Asymmetric dynamics in the US and Canada. The Quarterly Review of Economics and Finance, 77(C), 62-74. https://doi.org/10.1016/j.qref.2019.10.005
• Bora, D., & Basistha, D. (2021). The outbreak of the COVID-19 pandemic and its impact on stock market volatility: Evidence from a worst-affected economy. Journal of Public Affairs, 21(4), 1-10. https://doi.org/10.1002/pa.2623
• Bintara, R. (2020). The effect of working capital, liquidity, and leverage on profitability. Saudi Journal of Economics and Finance, 4(1), 28-35. https://doi.org/10.36348/sjef.2020.v04i01.005
• Beck, K., & Stanek, P. (2019). Globalization or regionalization of stock markets? The case of Central and Eastern European countries. Eastern European Economics, 57(4), 317-330. https://doi.org/10.1080/00128775.2019.1610895
• Braun, P. A., & Mittnik, S. (1993). Misspecifications in vector autoregressions and their effects on impulse responses and variance decompositions. Journal of Econometrics, 59(3), 319-341. https://doi.org/10.1016/0304-4076(93)90029-5
• Bahloul, S., Mroua, M., & Naifar, N. (2017). The impact of macroeconomic and conventional stock market variables on Islamic index returns under regime switching. Borsa Istanbul Review, 17(1), 62-74. https://doi.org/10.1016/j.bir.2016.09.003
• Barakat, M. R., Elgazzar, S. H., & Hanafy, K. M. (2016). Impact of macroeconomic variables on stock markets: Evidence from emerging markets. International Journal of Economics and Finance, 8(1), 195-207. https://doi.org/10.5539/ijef.v8n1p195
• Bulut, U. et al. (2023). The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA. Environmental Science and Pollution Research, 30(36), 86138-86154.
• Camilleri, S. J., Scicluna, N., & Bai, Y. (2019). Do stock markets lead or lag macroeconomic variables? Evidence from select European countries. The North American Journal of Economics and Finance, 48, 170-186. https://doi.org/10.1016/j.najef.2019.01.019
• Cetin, M. et al. (2023). The impact of natural resources, economic growth, savings, and current account balance on financial sector development: Theory and empirical evidence. Resources Policy, 81, 103300.
• Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208
• Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 59, 383-403. https://doi.org/10.1086/296344
• Cook, T., & Hahn, T. (1989). The effect of changes in the federal funds rate target on market interest rates in the 1970s. Journal of Monetary Economics, 24(3), 331-351. https://doi.org/10.1016/0304-3932(89)90025-1
• Das, N. et al. (2023). Do volatilities in tourism arrivals and foreign aids matter for GDP volatility in Cambodia? Partial and vector coherence wavelet models. Tourism Economics, 13548166231208471.
• Dinh, D. V. (2020a). Impulse response of inflation to economic growth dynamics: VAR model analysis. The Journal of Asian Finance, Economics and Business, 7(9), 219-228. https://doi.org/10.13106/jafeb.2020.vol7.no9.219
• Dinh, D. V. (2020b). Optimal inflation threshold and economic growth: Ordinal regression model analysis. Journal of Asian Finance, Economics and Business, 7(5), 91-102. https://doi.org/10.13106/jafeb.2020.vol7.no5.09
• Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431. https://doi.org/10.1080/01621459.1979.10525042
• Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. https://doi.org/10.2307/1912517
• Demir, C. (2019). Macroeconomic determinants of stock market fluctuations: The case of BIST-100. Economies, 7(1), 8-21. https://doi.org/10.3390/economies7010008
• Dogru, T. et al. (2024). The impact of business models and state regulations on the accommodation sector: theory and empirical evidence from the recent pandemic. International Journal of Contemporary Hospitality Management, 36(6), 1713-1743.
• Dogru, T. et al. (2023). Employee turnover dynamics in the hospitality industry vs. the overall economy. Tourism Management, 99, 104783.
• Dogru, T. et al. (2019). The balance of trade and exchange rates: Theory and contemporary evidence from tourism. Tourism Management, 74, 12-23.
• Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236
• Elalaoui, O., Fadlaoui, A., Maatala, N., & Ibrahimy, A. (2021). Agriculture and GDP causality nexus in Morocco: Empirical evidence from a VAR approach. International Journal of Agricultural Economics, 6(4), 198-207. https://doi.org/10.11648/j.ijae.20210604.17
• Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417. https://doi.org/10.2307/2325486
• Forson, J. A., & Janrattanagul, J. (2014). Selected macroeconomic variables and stock market movements: Empirical evidence from Thailand. Contemporary Economics, 8(2), 154-174. https://doi.org/10.5709/ce.1897-9254.138
• Gunay, S., & Can, G. (2022). The source of financial contagion and spillovers: An evaluation of the COVID-19 pandemic and the global financial crisis. PLOS ONE, 17(1), e0261835. https://doi.org/10.1371/journal.pone.0261835
• Granger, C. W. J. (1986). Developments in the study of cointegrated economic variables. Oxford Bulletin of Economics & Statistics, 48(3). https://doi.org/10.1111/j.1468-0084.1986.mp48003002.x
• Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791
• Gazi, Md. A. I., Islam, H., Islam, Md. A., Karim, R., Momo, S. M., & Senathirajah, A. R. B. S. (2024). Unlocking sustainable development in East Asia Pacific and South Asia: An econometric exploration of ESG initiatives. Sustainable Environment, 10(1). https://doi.org/10.1080/27658511.2024.2366558
• Han, J. et al. (2024). Sustainable development pathways: Exploring the impact of green finance on urban metabolic efficiency. Sustainable Development. https://doi.org/10.1002/sd.3081
• Han, J. et al. (2023). The construction of green finance and high-quality economic development under China’s SDGs target. Environmental Science and Pollution Research, 30(52), 111891-111902.
• Herranz, E. (2017). Unit root tests. Wiley Interdisciplinary Reviews: Computational Statistics, 9(3), e1396.https://doi.org/10.1002/wics.1396
• Hendry, D. F. (1986). Econometric modelling with cointegrated variables: An overview. Oxford Bulletin of Economics & Statistics, 48(3). https://doi.org/10.1111/j.1468-0084.1986.mp48003001.x
• Hussain, A., Rafique, M., Khalil, A., & Nawaz, M. (2013). Macroeconomic determinants of stock price variations: An economic analysis of KSE-100 index. Pakistan Journal of Humanities and Social Sciences, 1(1), 28-46. https://doi.org/10.52131/pjhss.2013.0101.0003
• Haque, S., & Chowdhury, T. A. (2020). Impact of COVID-19 on Bangladesh stock market. Asian Finance & Banking Review, 4(2), 1-9. https://doi.org/10.46281/asfbr.v4i2.896
• Hasan, M. B., Kabir, M. A. R., Amin, M. R., & Mahi, M. (2022). Effect of macroeconomic variables on Islamic and conventional stock indices: Fresh evidence from Bangladesh. The Journal of Developing Areas, 56(2), 197-220. https://doi.org/10.1353/jda.2022.0024
• Ho, S. Y. (2019). Macroeconomic determinants of stock market development in South Africa. International Journal of Emerging Markets, 14(2), 322-342. https://doi.org/10.1108/IJoEM-09-2017-0341
• Islam, H., Islam, M. S., Saha, S., Tarin, T. I., et al. (2024a). Unveiling the nexus of macroeconomic factors on bank performance in Bangladesh. Journal of Ekonomi, 6(2), 64-74. https://doi.org/10.58251/ekonomi.1467784
• Islam, H., Soumia, L., Rana, M., Madavarapu, J. B., & Saha, S. (2024b). Nexus between perception, purpose of use, technical challenges, and satisfaction for mobile financial services: Theory and empirical evidence from Bangladesh. Technological Sustainability, 3(2), 147-170. https://doi.org/10.1108/TECHS-10-2023-0040
• Islam, H., Rahman, J., Tanchangya, T., & Islam, M. A. (2023a). Impact of firms’ size, leverage, and net profit margin on firms’ profitability in the manufacturing sector of Bangladesh: An empirical analysis using GMM estimation. Journal of Ekonomi, 5(1), 1-9. https://doi.org/10.58251/ekonomi.1275742
• Islam, H., Rana, M., Saha, S., Khatun, T., Ritu, M. R., & Islam, M. R. (2023b). Factors influencing the adoption of cryptocurrency in Bangladesh: An investigation using the technology acceptance model (TAM). Technological Sustainability, 2(4), 423-443. https://doi.org/10.1108/TECHS-07-2023-0025
• Işık, C., Ongan, S., & Islam, H. (2024a). A new pathway to sustainability: Integrating economic dimension (ECON) into ESG factors as (ECON-ESG) and aligned with sustainable development goals (SDGs). Journal of Ekonomi, 6(1), 34-39. https://doi.org/10.58251/ekonomi.1450860
• Işık, C., Ongan, S., Islam, H., & Menegaki, A. N. (2024b). A roadmap for sustainable global supply chain distribution: Exploring the interplay of ECON-ESG factors, technological advancement and SDGs on natural resources. Resources Policy, 95, 105114. https://doi.org/10.1016/j.resourpol.2024.105114
• Işık, C., Ongan, S., Islam, H., Sharif, A., & Balsalobre-Lorente, D. (2024c). Evaluating the effects of ECON-ESG on load capacity factor in G7 countries. Journal of Environmental Management, 360, 121177. https://doi.org/10.1016/j.jenvman.2024.121177
• Işık, C., Ongan, S., Islam, H., Jabeen, G., & Pinzon, S. (2024d). Is economic growth in East Asia Pacific and South Asia ESG factors based and aligned growth? Sustainable Development. https://doi.org/10.1002/sd.2910
• Işık, C., Ongan, S., Islam, H., Pinzon, S., & Jabeen, G. (2024e). Navigating sustainability: Unveiling the interconnected dynamics of ESG factors and SDGs in BRICS‐11. Sustainable Development. https://doi.org/10.1002/sd.2977
• Işık, C., Bulut, U., Ongan, S., Islam, H., & Irfan, M. (2024f). Exploring how economic growth, renewable energy, internet usage, and mineral rents influence CO2 emissions: A panel quantile regression analysis for 27 OECD countries. Resources Policy, 92, 105025. https://doi.org/10.1016/j.resourpol.2024.105025
• Işık, C., Ongan, S., Islam, H., Balsalobre-Lorente, D., & Sharif, A. (2024g). ECON-ESG factors on energy efficiency: Fostering sustainable development in ECON-growth-paradox countries. Gondwana Research, 135, 103-115. https://doi.org/10.1016/j.gr.2024.07.020
• Işık, C. et al., (2024h). Renewable energy, climate policy uncertainty, industrial production, domestic exports/re-exports, and CO2 emissions in the USA: a SVAR approach. Gondwana Res. https://doi.org/10.1016/j.gr.2023.08.019
• Işık, C., Ongan, S., Ozdemir, D., Yan, J., & Demir, O. (2024i). The sustainable development goals: Theory and a holistic evidence from the USA. Gondwana Research. https://doi.org/10.1016/j.gr.2024.04.014
• Işık, C. et al. (2021). The nexus between team culture, innovative work behaviour and tacit knowledge sharing: Theory and evidence. Sustainability, 13(8), 4333.
• Işık, C. et al. (2019). Turizm ve girişimcilik alanında yapılmış çalışmaların bibliyometrik analizi. Güncel Turizm Araştırmaları Dergisi, 3(1), 119-149.
• Işık, C., & Türkmendağ, T. (2016). Atatürk Üniversitesi turizm fakültesi öğrencilerinin bireysel yenilikçilik algılarının belirlenmesi. Gazi Üniversitesi Turizm Fakültesi Dergisi, (1), 70-99.
• Işık, C. (2015). Foreign direct investment in tourism: Panel data analysis of D7 countries. Athens Journal of Tourism, 2(2), 93-103.
• Işık, C. (2014). Patent harcamaları ve iktisadi büyüme arasındaki ilişki: Türkiye örneği. Sosyoekonomi, 21(21). Jabeen, G. et al. (2024a). Role of energy utilization intensity, technical development, economic openness, and foreign tourism in environmental sustainability. Gondwana Research, 127, 100-115.
• Jabeen, G. et al. (2024b). Promoting green taxation and sustainable energy transition for low-carbon development. Geoscience Frontiers, 101928.
• Jabeen, G. et al. (2024c). Transitioning to sustainable energy: Multidimensional factors guiding solar power technology adoption. Energy, 133468.
• Jo, C., Kim, D. H., & Lee, J. W. (2023). Forecasting unemployment and employment: A system dynamics approach. Technological Forecasting and Social Change, 194, 122715. https://doi.org/10.1016/j.techfore.2023.122715
• Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
• Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica, 59(6), 1551–1580. https://doi.org/10.2307/2938278
• Jareño, F., & Negrut, L. (2016). US stock market and macroeconomic factors. Journal of Applied Business Research, 32(1), 325-340. http://dx.doi.org/10.19030/jabr.v32i1.9541
• Jalil, A., & Rao, N. H. (2019). Time series analysis (stationarity, cointegration, and causality). In Environmental Kuznets Curve (pp. 85–99). https://doi.org/10.1016/b978-0-12-816797-7.00008-4
• Islam, K. M. Z., & Ahmed, S. F. (2015). Stock market crash and stock return volatility: Empirical evidence from Dhaka Stock Exchange. The Bangladesh Development Studies, 38(3), 25–34. https://www.jstor.org/stable/26538811
• Ibrahim, M., & Musah, A. (2014). An econometric analysis of the impact of macroeconomic fundamentals on stock market returns in Ghana. Research in Applied Economics, 6(2), 47-72. http://dx.doi.org/10.5296/rae.v6i2.5146
• Keele, L., Stevenson, R. T., & Elwert, F. (2020). The causal interpretation of estimated associations in regression models. Political Science Research and Methods, 8(1), 1–13. https://doi.org/10.1017/psrm.2019.31
• Karanasos, M., Yfanti, S., & Hunter, J. (2022). Emerging stock market volatility and economic fundamentals: The importance of US uncertainty spillovers, financial and health crises. Annals of Operations Research, 313(2), 1077–1116. https://doi.org/10.1007/s10479-021-04042-y
• Keswani, S., & Wadhwa, B. (2022). Association among the selected macroeconomic factors and Indian stock returns. Materials Today: Proceedings. http://dx.doi.org/10.1016/j.matpr.2021.01.841
• Kwofie, C., & Ansah, R. K. (2018). A study of the effect of inflation and exchange rate on stock market returns in Ghana. International Journal of Mathematics and Mathematical Sciences, 2018, 1-8. http://dx.doi.org/10.1155/2018/7016792
• Ligocká, M. (2023). The relationship between macroeconomic variables and stock market indices: Evidence from Central and Eastern European countries. Eastern Journal of European Studies, 14(2), 76-107. https://doi.org/10.47743/ejes-2023-0204
• Liu, H. Y., Manzoor, A., Wang, C. Y., Zhang, L., & Manzoor, Z. (2020). The COVID-19 outbreak and affected countries' stock markets response. International Journal of Environmental Research and Public Health, 17(8), 1-19. https://doi.org/10.3390/ijerph17082800
• Lee, J. W. (2020). An exploration of dynamic relationships between macroeconomic variables and stock prices in Korea revisited. Journal of Asian Finance, Economics and Business, 7(10), 23-34. https://doi.org/10.13106/jafeb.2020.vol7.no10.023
• Li, M. et al. (2024). The nexus between clean energy market risk and US business environment: evidence from wavelet coherence and variance analysis. Stochastic Environmental Research and Risk Assessment, 1-16.
• Lütkepohl, H. (2013). Introduction to multiple time series analysis. Springer Science & Business Media.
• Lütkepohl, H., Meitz, M., Netšunajev, A., & Saikkonen, P. (2021). Testing identification via heteroskedasticity in structural vector autoregressive models. The Econometrics Journal, 24(1), 1-22. https://doi.org/10.1111/1368-423X.12176
• Mazur, M., Dang, M., & Vega, M. (2020). COVID-19 and the March 2020 stock market crash: Evidence from S&P 1500. Finance Research Letters, 38, 101690. https://doi.org/10.1016/j.frl.2020.101690
• Megaravalli, A. V., & Sampagnaro, G. (2018). Macroeconomic indicators and their impact on stock markets in ASIAN 3: A pooled mean group approach. Cogent Economics & Finance, 6(1), 1432450. http://dx.doi.org/10.1080/23322039.2018.1432450
• Mostafa, A. L. I. (2020). Dynamic relation between economic growth, stock market depth, and macroeconomic variables of Bangladesh. Eurasian Journal of Business and Economics, 13(26), 45-63. https://doi.org/10.17015/ejbe.2020.026.03
• Mishra, S., & Debasish, S. S. (2018). Analysis of interaction between global crude oil price, exchange rate, inflation, and the stock market in India: Vector autoregression approach. Parikalpana: KIIT Journal of Management, 14(1), 120-133. https://doi.org/10.23862/kiit-parikalpana/2018/v14/i1/173252
• Mukhlis, I., Simanjuntak, T. H., & Prasetyo, T. (2018). The analysis of the bank interest influence and exchange rate towards composite stock price index in Indonesia using vector error correction model approach. International Research Conference on Economics and Business, 3(3), 127–139. https://doi.org/10.18502/kss.v3i3.1879
• Miah, M. D., & Banik, S. L. (2013). Measuring weak-form of market efficiency: The case of Dhaka Stock Exchange. International Journal of Financial Services Management, 6(3), 219-235. https://doi.org/10.1504/IJFSM.2013.058069
• Mahzabeen, S. (2016). Impact of money, interest rate, and inflation on the Dhaka Stock Exchange (DSE) of Bangladesh. Journal of Business and Technology, 41-54.
• Mishra, P. K., & Mishra, S. K. (2020). Corona pandemic and stock market behaviour: Empirical insights from selected Asian countries. Millennial Asia, 11(3), 341-365. https://doi.org/10.1177/0976399620952354
• Ma, Y., Wang, Z., & He, F. (2022). How do economic policy uncertainties affect stock market volatility? Evidence from G7 countries. International Journal of Finance & Economics, 27(2), 2303-2325. https://doi.org/10.1002/ijfe.2274
• Mohnot, R., Banerjee, A., Ballaj, H., & Sarker, T. (2024). Re-examining asymmetric dynamics in the relationship between macroeconomic variables and stock market indices: Empirical evidence from Malaysia. The Journal of Risk Finance, 25(1), 19-34. https://doi.org/10.1108/JRF-09-2023-0216
• Nisha, N. (2016). Macroeconomic determinants of the behaviour of Dhaka Stock Exchange (DSE). International Journal of Asian Business and Information Management, 7(1), 1-17. https://doi.org/10.4018/IJABIM.2016010101
• Nielsen, B. (2006). Order determination in general vector autoregressions. Lecture Notes-Monograph Series, 93-112.
• Nicholson, W. B., Wilms, I., Bien, J., & Matteson, D. S. (2020). High dimensional forecasting via interpretable vector autoregression. Journal of Machine Learning Research, 21(166), 1-52.
• Olokoyo, F. O., Ibhagui, O. W., & Babajide, A. (2020). Macroeconomic indicators and capital market performance: Are the links sustainable? Cogent Business & Management, 7(1), 1792258. https://doi.org/10.1080/23311975.2020.1792258
• Ongan, S. et al. (2023). Are economic growth and environmental pollution a dilemma?. Environmental science and pollution research, 30(17), 49591-49604.
• Ongan, S. et al. (2022). Retesting the EKC hypothesis through transmission of the ARMEY curve model: an alternative composite model approach with theory and policy implications for NAFTA countries. Environmental Science and Pollution Research, 29(31), 46587-46599.
• Paulsen, J. (1984). Order determination of multivariate autoregressive time series with unit roots. Journal of Time Series Analysis, 5(2), 115-127. https://doi.org/10.1111/j.1467-9892.1984.tb00381.x
• Plíhal, T. (2016). Stock market informational efficiency in Germany: Granger causality between DAX and selected macroeconomic indicators. Procedia-Social and Behavioral Sciences, 220, 321-329. https://doi.org/10.1016/j.sbspro.2016.05.505
• Peiró, A. (2016). Stock prices and macroeconomic factors: Some European evidence. International Review of Economics & Finance, 41, 287-294. https://doi.org/10.1016/j.iref.2015.08.004
• Pan, W. F. (2018). Does the stock market cause unemployment? A cross-country analysis. The North American Journal of Economics and Finance, 44, 34-43. https://doi.org/10.1016/j.najef.2017.11.002
• Pradhan, R. P., Arvin, M. B., Hall, J. H., & Bahmani, S. (2014). Causal nexus between economic growth, banking sector development, stock market development, and other macroeconomic variables: The case of ASEAN countries. Review of Financial Economics, 23(4), 155-173.
• Pokou, F., Sadefo Kamdem, J., & Benhmad, F. (2024). Hybridization of ARIMA with learning models for forecasting of stock market time series. Computational Economics, 63(4), 1349-1399. https://doi.org/10.1007/s10614-023-10499-9
• Pradhan, R. P., Arvin, M. B., & Ghoshray, A. (2015a). The dynamics of economic growth, oil prices, stock market depth, and other macroeconomic variables: Evidence from the G-20 countries. International Review of Financial Analysis, 39, 84-95. https://doi.org/10.1016/j.irfa.2015.03.006
• Pradhan, R. P., Arvin, M. B., & Bahmani, S. (2015b). Causal nexus between economic growth, inflation, and stock market development: The case of OECD countries. Global Finance Journal, 27, 98-111. https://doi.org/10.1016/j.gfj.2015.04.006
• Pal, K., & Mittal, R. (2011). The impact of macroeconomic indicators on Indian capital markets. Journal of Risk Finance, 12(2), 84-97. https://doi.org/10.1108/15265941111112811
• Rezina, S., Jahan, N., & Mustafi, M. A. A. (2017). Contribution of the stock market towards economic growth: An empirical study on Bangladesh economy. European Scientific Journal, ESJ, 13(4).
• Rayball, R. (1994). The development, accomplishments and limitations of the theory of stock market efficiency. Managerial Finance, 20(2), 3-48. https://doi.org/10.1108/eb018462
• Ross, S. A. (1976). The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13, 341-360.
• Surakhi, O., Zaidan, M. A., Fung, P. L., Hossein Motlagh, N., Serhan, S., AlKhanafseh, M., ... & Hussein, T. (2021). Time-lag selection for time-series forecasting using neural network and heuristic algorithm. Electronics, 10(20), 2518. https://doi.org/10.3390/electronics10202518
• Sibande, X., Gupta, R., & Wohar, M. E. (2019). Time-varying causal relationship between stock market and unemployment in the United Kingdom: Historical evidence from 1855 to 2017. Journal of Multinational Financial Management, 49, 81-88. https://doi.org/10.1016/j.mulfin.2019.02.003
• Subrata, R. O. Y. (2020). Causal relationship between stock market and macroeconomic variables: Indian evidence. Euro Economica, 39(3), 211-231.
• Song, Y. et al. (2024). Crossing the willingness-behavior gap: A study of factors influencing the e-commerce selling behavior of cherry farmers. Journal of Infrastructure, Policy and Development, 8(9), 7231.
• Sukmawati, F. N., & Haryono, N. A. (2021). Cointegration of macroeconomic variables and Dow Jones Industrial Average index on the Composite Stock Price Index in 2015-2019. Journal of Business and Management Review, 2(3), 178-191.
• Sun, A. et al. (2024). Unravelling complexities: a study on geopolitical dynamics, economic complexity, R&D impact on green innovation in China. Stochastic Environmental Research and Risk Assessment, 1-16.
• Topcu, M., & Gulal, O. S. (2020). The impact of COVID-19 on emerging stock markets. Finance Research Letters, 36, 101691. https://doi.org/10.1016/j.frl.2020.101691
• Tripathi, V., & Seth, R. (2014). Stock market performance and macroeconomic factors: The study of Indian equity market. Global Business Review, 15(2), 291-316. https://doi.org/10.1177/0972150914523599
• Tiryaki, A., Erdoğan, L., & Ceylan, R. (2017). The causal relationship between selected macroeconomic variables and stock returns in Turkey. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 19, 299-326. https://doi.org/10.18092/ulikidince.309275
• Yan, J. et al. (2024a). Analysis of green total factorproductivity in China's forestry industry: Technological, organizational, and environmental framework for sustainableeconomic development. Sustainable Development, 1–14. https://doi.org/10.1002/sd.308014
• Yan, J. et al. (2024b). The nexus between natural resource development, trade policy uncertainty, financial technology and poverty in China: Contributing to the realization of SDG 1. Resources Policy, 95, 105154. https://doi.org/10.1016/j.resourpol.2024.105154
• Wold, H. (1954). Causality and econometrics. Econometrica, 22(2), 162–177. https://doi.org/10.2307/1907540
• Winful, C. E., Sarpong, D. Jnr., & Sarfo, A. K. (2016). Macroeconomic variables and stock market performance of emerging countries. Journal of Economics and International Finance, 8(7), 106-126. https://doi.org/10.5897/JEIF2016.0743
• Wickramasinghe, M. A. (2023). Macroeconomic determinants of stock market performances in Sri Lanka. London Journal of Research in Management & Business, 23(5), 1-15.
• Wooldridge, J. M. (2009). On estimating firm-level production functions using proxy variables to control for unobservables. Economics Letters, 104(3), 112-114. https://doi.org/10.1016/j.econlet.2009.04.026
• Sunjida Parven (0000-0002-4000-4589) is an assistant professor in Business Administration Department at Varendra University, Rajshahi, Bangladesh. She has completed her BBA and MBA from Department of Marketing at University of Rajshahi. Her research interest mainly addresses social media marketing, Sustainable marketing, Luxury branding and fashion marketing, Entrepreneurship, Tourism.