Market efficiency and tax incentive policies during the COVID-19 pandemic: Case of Indonesia

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From an accounting perspective, taxes reduce profits and are often perceived as diminishing shareholders’ rights. Consequently, government support through tax reductions plays a crucial role in enhancing the effectiveness of corporate strategies aimed at minimizing tax burdens. From the perspective of the Efficient Market Hypothesis (EMH), government tax incentive policies serve as vital signals to investors, shaping their expectations and influencing investment decisions. This study focuses on Indonesia’s tax incentive policy introduced at the onset of the COVID-19 pandemic on April 1, 2020, and continuing until September 30, 2023. To assess market efficiency during this period, portfolios were constructed from the top 21 firms listed on the IDX Quality 30 and IDX High Dividend 20 indices, categorized by their systematic risk and cost of equity. The findings indicate that portfolios with higher systematic risk and cost of equity exhibit more optimal returns, greater volatility, and better risk-return trade-offs. Conversely, portfolios with lower systematic risk and cost of equity tend to yield suboptimal returns due to their passive investment characteristics. Overall, the returns from all portfolios during the tax incentive period align with the weak form of the EMH, albeit showing negative autocorrelation instead of a purely random walk pattern. These findings imply that information regarding tax incentives influences prices primarily among firms with higher cost of equity or systematic risk. This study contributes to the understanding of the EMH by examining the impact of tax incentives during the pandemic while controlling for both the cost of equity and systematic risk.

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    • Figure 1. Normality test
    • Figure 2. Variance ratio trends of high β
    • Figure 3. Variance ratio trends of low β
    • Figure 4. Variance ratio trends of high ER
    • Figure 5. Variance ratio trends of low ER
    • Table 1. Descriptive statistics
    • Table 2. Unit root problem test
    • Table 3. Variance ratio test
    • Table A1. Sample
    • Conceptualization
      Novi Swandari Budiarso
    • Formal Analysis
      Novi Swandari Budiarso
    • Methodology
      Novi Swandari Budiarso
    • Supervision
      Novi Swandari Budiarso
    • Writing – review & editing
      Novi Swandari Budiarso
    • Data curation
      Winston Pontoh
    • Funding acquisition
      Winston Pontoh
    • Investigation
      Winston Pontoh
    • Project administration
      Winston Pontoh
    • Resources
      Winston Pontoh
    • Software
      Winston Pontoh
    • Validation
      Winston Pontoh
    • Visualization
      Winston Pontoh
    • Writing – original draft
      Winston Pontoh