Research background: The rapid development of digital economy has set off a new wave of enterprise reform. Developing the digital economy is not only an urgent requirement of the current situation, but also an important way to meet the people's better life. Purpose of the article: This paper attempts to reveal the important role of the development of digital technology on the debt financing cost of micro enterprises, and provide micro evidence for the integration of digital economy and real economy. At the same time, this paper wants to provide relevant guidance for formulating digital related policies and reducing the financing cost of the real economy. Methods: Taking China?s A-share listed companies from 2007 to 2020 as a sample, this paper empirically tests the impact of enterprise digital transformation on debt financing cost and its mechanism. In the robustness test, this paper uses the measures of changing independent variables and dependent variables, instrumental variable method and quantile regression method. In the mechanism test, this paper uses the intermediary effect model. In the further study, this paper uses the method of group regression. Findings & value added: The study finds that the digital transformation of enterprises significantly reduces the cost of debt financing. Mechanism tests show that the role of enterprise digital transformation in reducing debt financing costs is mainly realized by reducing information asymmetry and alleviating agency problems. Further tests show that the relationship between enterprise digital transformation and debt financing cost is affected by the degree of market competition, whether it is a high-tech enterprise and audit quality. When the degree of market competition is high, the enterprise is a high-tech one, or it is audited by the four major international accounting firms, the effect of enterprise digital transformation on the reduction of debt financing cost is more significant. The method used in this paper is also applicable to the study of other economic management problems. This paper proves a positive significance of digital transformation, which is conducive to promoting the digital transformation of enterprises. Especially for those enterprises in non-high-tech industries, they should speed up the pace. At the same time, this paper has a certain guiding role for the introduction and implementation of policies to encourage digital transformation.

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Research background: Covid-19 has affected the global economy and has had an inevitable impact on capital markets. In the week of February 24?28, 2020, stock markets crashed. The index FTSE 100 decreased 13%, while the indices DJIA and S&P 500 fell 11?12%, the biggest drop since the 2007?2008 financial and economic crisis. It is therefore of interest to test the random walk hypothesis in developed capital markets, European and also non-European, in order to understand the different predictabilities between them. Purpose of the article: The aim is to analyze capital market efficiency, in its weak form, through the stock market indices of Belgium (index BEL 20), France (index CAC 40), Germany (index DAX 30), USA (index DOW JONES), Greece (index FTSE Athex 20), Spain (index IBEX 35), Ireland (index ISEQ), Portugal (index PSI 20) and China (index SSE) for the period from December 2019 to May 2020. Methods: Panel unit root tests of Breitung (2000), Levin et al. (2002) and Hadri (2002) were used to assess the time series stationarity. The test of Clemente et al. (1998) is used to detect structural breaks. The tests for the random walk hypothesis follows the variance ratio methodology proposed by Lo and MacKinlay (1988). Findings & Value added: In general, we found mixed confirmation about the EMH (efficient market hypothesis). Taking into account the conclusions of the rank variance test, the random walk hypothesis was rejected in the case of stock indices: Dow Jones, SSE and PSI 20, partially rejected in the case indices: BEL 20, CAC 40, FTSTE Athex 20 and DEX 30, but accepted for indices: IBEX 35 and ISEQ. The results also show that prices do not fully reflect the information available and that changes in prices are not independent and identically distributed. This situation has consequences for investors, since some returns can be expected, creating opportunities for arbitrage and for abnormal returns, contrary to the assumptions of random walk and information efficiency.