One of the important sectors of the economy of any country is their capital market and this sector, as one of the subsets of economy in the event of crisis and external shocks and instability in the economy is affected, which makes evident the need to pay attention to the stability of this sector and, more importantly, to increase its resilience. The 2008 global financial crisis affected all asset classes, making diversity in crisis and recession an inefficient mechanism for risk management. Applying the timing approach in investment, it is possible to have a favorable encounter with high-risk assets such as stocks. By developing Exponential Moving Average (EMA) timing strategies, this study commits to take an effective step in protecting the investment portfolio against significant declines in turbulent times and financial crises and reducing stock investment by creating a cash position. It therefore seeks to test the effectiveness of K-Means clustering in the development of a market timing strategy (i.e. EMA) that intends to provide early signals to protect securities in turbulent times. The specified timing strategies were tested on the total index of the stock exchange during the period 2013-2019. The results indicate that the optimal EMA strategy will have a better performance using the K-Mean clustering when the trend (the time series of the index) has structural breaks and the results from the predictions obtained from this tool can be closer to the reality. Also using the clustering method, the sensitivity of this market timing tool in a situation where the market trend is experiencing severe economic fluctuations and shocks has improved and enjoyed more resistance.