The impact of cash flow statement components on stock volatility: Evidence from Qatar

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The published financial statements are considered one of the most important sources of information that investors rely on in forecasting stock performance or even judging the organization’s ability to cover short-run liabilities. Cash flows play a core role in maintaining a high market value for its shares. Hence, this study came to analyze the explanatory value of the cash flow statement in explaining stock volatility (SV) in the Qatar financial market. Study data were collected using published financial statements from a sample of 44 Qatari-listed companies throughout 2013–2019. A panel cross-sectional data technique using the E-views program was used to analyze the data. The study results show there is a positive and significant impact of cash flows from operating CFO activities on SV, indicating that the higher change in CFO increases stock volatility. This means that operating cash flows give significant information to investors, and it is reflected in the stock price movements directly. Also, the cash flow from CFF financing activities has a positive and significant effect on SV. This means that CFF affects stock prices, causing greater changes and fluctuation in stock returns. This is because one of the major components of CFF is dividends, which affect directly stock prices and stock returns. In contrast, there is an insignificant effect of CFI on SV, which may indicate that investors do not build their investment decisions based on CFI. Accordingly, the cash flow from investing activities failed to explain the stock volatility of the listed Qatari companies.

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    • Figure 1. Stock volatility (SV) (2013–2019)
    • Figure 2. Cash flows from operations (CFO) (2013–2019)
    • Figure 3. Cash flows from investment (CFI) (2013–2019)
    • Figure 4. Cash flows from financing (CFF) (2013–2019)
    • Figure 5. Net income (NI) (2013–2019)
    • Table 1. Study variables and measurement
    • Table 2. Descriptive statistics of the study variables
    • Table 3. Pearson correlation matrix
    • Table 4. Regression analysis results of the study model
    • Conceptualization
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Data curation
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Formal Analysis
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Funding acquisition
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Methodology
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Software
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Supervision
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Validation
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Writing – original draft
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh
    • Writing – review & editing
      Mo’taz Kamel Al Zobi, Othman Hel Al-Dhaimesh