PERTANIKA JOURNAL OF TROPICAL AGRICULTURAL SCIENCE

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• Ahmed, S. F., Islam, K. M., & Khan, M. (2015). Relationship between inflation and stock market returns: Evidence from Bangladesh. DIU Journal of Business and Economics, 9(1), Article 14.

• Alanyali, M., Moat, H. S., & Preis, T. (2013). Quantifying the relationship between financial news and the stock market. Scientific Reports, 3(1), Article 3578. https://doi.org/10.1038/srep03578

• Alquraan, T., Alqisie, A., & Al Shorafa, A. (2016). Do behavioral finance factors influence stock investment decisions of individual investors? (Evidences from Saudi Stock Market). American International Journal of Contemporary Research, 6(3), 159-169.

• Bahmani-Oskooee, M., & Bohl, M. T. (2000). German monetary unification and the stability of the German M3 money demand function. Economics Letters, 66(2), 203-208. https://doi.org/10.1016/S0165-1765(99)00223-2

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• Chatzis, S. P., Siakoulis, V., Petropoulos, A., Stavroulakis, E., & Vlachogiannakis, N. (2018). Forecasting stock market crisis events using deep and statistical machine learning techniques. Expert Systems with Applications, 112, 353-371.

• Churchill, S. A., Inekwe, J., Ivanovski, K., & Smyth, R. (2019). Dynamics of oil price, precious metal prices and the exchange rate in the long-run. Energy Economics, 84, Article 104508. https://doi.org/10.1016/j.eneco.2019.104508

• Delgado, N. A. B., Delgado, E. B., & Saucedo, E. (2018). The relationship between oil prices, the stock market and the exchange rate: Evidence from Mexico. The North American Journal of Economics and Finance, 45, 266-275. https://doi.org/10.1016/j.najef.2018.03.006

• Drehmann, M., & Juselius, M. (2014). Evaluating early warning indicators of banking crises: Satisfying policy requirements. International Journal of Forecasting, 30(3), 759-780. https://doi.org/10.1016/j.ijforecast.2013.10.002

• Drucker, P. F. (1978). Managing the third sector. The Wall Street Journal, 3, 26-26.

• Elliott, G., & Timmermann, A. (2016). Forecasting in economics and finance. Annual Review of Economics, 8, 81-110. https://www.annualreviews.org/doi/abs/10.1146/annurev-economics-080315-015346

• Freund, Y., & Schapire, R. E. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1), 119-139. https://doi.org/10.1006/jcss.1997.1504

• Habiba, U. E., & Zhang, W. (2020). The dynamics of volatility spillovers between oil prices and stock market returns at the sector level and hedging strategies: Evidence from Pakistan. Environmental Science and Pollution Research, 27, 30706-30715. https://doi.org/10.1007/s11356-020-09351-6

• Hasan, M. A., & Zaman, A. (2017). Volatility nexus between stock market and macro-economic variables in Bangladesh: An extended GARCH approach. Scientific Annals of Economics and Business, 64(2), 233-243.

• Hou, Q., Bing, Z. T., Hu, C., Li, M. Y., Yang, K. H., Mo, Z., Xie, X. W., Liao, J. L., Lu, Y., Horie, S., & Lou, M. W. (2018). RankProd combined with genetic algorithm optimized artificial neural network establishes a diagnostic and prognostic prediction model that revealed C1QTNF3 as a biomarker for prostate cancer. EBioMedicine, 32, 234-244.

• Ibrahim, M. H. (2015) Oil and food prices in Malaysia: A nonlinear ARDL analysis. Agricultural and Food Economics, 3, Article 2. https://doi.org/10.1186/s40100-014-0020-3.

• Khan, M. M., & Yousuf, A. S. (2013). Macroeconomic forces and stock prices: Evidence from the Bangladesh stock market. Munich Personal RePEc Archive.

• Kolapo, F. T., & Adaramola, A. O. (2012). The impact of the Nigerian capital market on economic growth (1990-2010). International Journal of Developing Societies, 1(1), 11-19.

• Kumar, G., & Misra, A. K. (2019). Liquidity-adjusted CAPM - An empirical analysis on Indian stock market. Cogent Economics & Finance, 7(1), Article 1573471. https://doi.org/10.1080/23322039.2019.1573471

• Lacheheb, M., & Sirag, A. (2019). Oil price and inflation in Algeria: A nonlinear ARDL approach. The Quarterly Review of Economics and Finance, 73, 217-222. https://doi.org/10.1016/j.qref.2018.12.003

• Musallam, S. R. (2018). Exploring the relationship between financial ratios and market stock returns. Eurasian Journal of Business and Economics, 11(21), 101-116.

• Okere, K. I., Muoneke, O. B., & Onuoha, F. C. (2021). Symmetric and asymmetric effects of crude oil price and exchange rate on stock market performance in Nigeria: Evidence from multiple structural break and NARDL analysis. The Journal of International Trade & Economic Development, 30(6), 1-27. https://doi.org/10.1080/09638199.2021.1918223

• Pan, X., Uddin, M. K., Han, C., & Pan, X. (2019). Dynamics of financial development, trade openness, technological innovation and energy intensity: Evidence from Bangladesh. Energy, 171, 456-464. https://doi.org/10.1016/j.energy.2018.12.200

• Patel, J., Shah, S., Thakkar, P., & Kotecha, K. (2015). Predicting stock market index using fusion of machine learning techniques. Expert Systems with Applications, 42(4), 2162-2172. https://doi.org/10.1016/j.eswa.2014.10.031

• Rahman, A. S. A., Abdul-Rahman, S., & Mutalib, S. (2017, November). Mining textual terms for stock market prediction analysis using financial news. In A. Mohamed, M. Berry & B. Yap (Eds.), Soft Computing in Data Science (pp. 293-305). Springer. https://doi.org/10.1007/978-981-10-7242-0_25

• Raza, N., Shahzad, S. J. H., Tiwari, A. K., & Shahbaz, M. (2016). Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. Resources Policy, 49, 290-301. https://doi.org/10.1016/j.resourpol.2016.06.011

• Sarwar, S., & Wasim, H. (2016) Oil prices and Asian emerging stock markets: Pakistan and Bangladesh. European Journal of Economic Studies, 2(16), 353-357. https://doi.org/10.13187/es.2016.16.353

• Sheikh, U. A., Asad, M., Ahmed, Z., & Mukhtar, U. (2020). Asymmetrical relationship between oil prices, gold prices, exchange rate, and stock prices during global financial crisis 2008: Evidence from Pakistan. Cogent Economics & Finance, 8(1), Article 1757802. https://doi.org/10.1080/23322039.2020.1757802

• Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. Sickles & W. Horrace (Eds.), Festschrift in honor of Peter Schmidt (pp. 281-314). Springer. https://doi.org/10.1007/978-1-4899-8008-3_9

• Singhal, S., Choudhary, S., & Biswal, P. C. (2019). Return and volatility linkages among international crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico. Resources Policy, 60, 255-261. https://doi.org/10.1016/j.resourpol.2019.01.004

• Tuyon, J., & Ahmad, Z. (2016). Behavioural finance perspectives on Malaysian stock market efficiency. Borsa Istanbul Review, 16(1), 43-61. https://doi.org/10.1016/j.bir.2016.01.001

• Uthayakumar, J., Metawa, N., Shankar, K., & Lakshmanaprabu, S. K. (2020). Financial crisis prediction model using ant colony optimization. International Journal of Information Management, 50, 538-556. https://doi.org/10.1016/j.ijinfomgt.2018.12.001