Stock drawdown8/18/2023 ![]() ![]() A paper presented at International Conference Science Index, LOS Angeles USA. Downside risk analysis of the Nigerian Stock Market: A value at risk approach. Implementing and testing the maximum drawdown at risk. ![]() ![]() Pattern-Based method for reducing drawdowns in stock index investment (MPhil thesis, Chinese University of Hong Kong, China). The Journal of Applied Business Research, 34(2), 217-222. Are value at risk and maximum drawdown different from volatility in stock market? South Korea. Value and momentum drawdowns (Master’s dissertation, Ghent University, Ghent, Belgium). A note on Covid-19 instigated maximum drawdown in Islamic markets versus conventional counterparts. Hassan, M., K., Chowdhury, M., I., H., Balli, F., & Hasan, R. Central and Eastern European Journal of Management and Economics, 4(2), 105-123. A theoretical approach to quantitative downside risk measurement methods. Research in International Business and Finance, 47, 264-278. Empirical analysis of intertemporal relations between downside risks and expected returns – Evidence from Asian markets. European Financial Management, 22 (5), 749-796. Empirical analysis of intertemporal relationship between downside risk and expected return: Evidence from time-varying transition probability models. Management Science and Engineering, 12(1), 58-61. A strategy considering both magnitude and duration of drawdown in China. The downside risk and stock return the case of Amman Stock Exchange (Master’s dissertation, Yarmouk University, Irbid, Jordan). Drawdown measure and market timing skills: An International empirical Study (Doctoral thesis, Western Sydney University, Australia). Volatility forecasting: Downside risk, jumps and leverage effect. Jordan Journal of Business Administration, 18(2), 189-201. Downside risk and stock returns: The case of Amman stock exchange. Expert Systems with Applications, 87, 267–279. An adaptive portfolio trading system: A risk-return portfolio optimisation using recurrent reinforcement learning with expected maximum drawdown. ![]()
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