The novel Covid-19 virus has changed the dynamics of 'flight to safety' investment for various economies. Thus, the hedging ability of the stocks must be revisited in the scenario of this pandemic. For this purpose, specifically understanding the importance of a semi-strong form of an efficient market hypothesis is important. This was to observe the speed at which the markets react to the news announcement, and how rapidly they absorb new information to regain thier position in the market. Hence, this study conducts an event study analysis on Pakistan's emerging market to detect the financial and non-financial stock price reactions towards the lockdown announcement, following the spread of Covid-19 in Pakistan. The daily data on the KSE-100 index for thirty different industries, comprising of ninety firms, spanning from December 12, 2019, till June 7, 2020, was collected and analyzed. The abnormal returns were recorded to be at around 21 [À10. þ10] and 41 days [À20, þ20] event window, around the day of the lockdown announcement. These abnormal returns were obtained through the market model regression. The data collected implied that most of the industries were stable and behaved well before the event day, while the affected sectors recovered fairly quickly. Therefore, it has been affirmed that Pakistan's equity portfolios are informationally efficient, and can benefit the investors during a pandemic.

Given the alarming deterioration of the environment, the present analysis investigates the role of eco-innovation, natural resources and financial development in influencing the environmental degradation of China. Applying the novel method of Quantile-ARDL, the current research is beneficial in portraying the dependence patterns of the variables with special emphasis on the nexus of eco-innovation and ecological footprint across numerous quantiles of the distribution which has not been examined so far in the literature. The empirical findings reveal that in the long run, eco-innovation reduces the level of ecological deterioration in China across all quantiles. On the other hand, the results suggest that the increase in credit to the private sector and natural resource rents augment environmental degradation. The outcomes imply that the over-dependence on natural resources and financial development can worsen the goals of sustainable development in China if the strategies of conservation and management are ignored. Moreover, witnessing the favourable role of eco-innovation, competent policies and regulations can be made towards sustainable efficient technologies and eco-friendly energy sources to halt global warming.

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The purpose of this study is to investigate the bank specific determinants related to the performance of public and private sector banks in Pakistan. Using strongly balanced panel yearly data from 2010 to 2017, Pooled OLS, fixed effect, Random effect and Random Effect Mundlak Transformation (REMT) have been utilized to provide the empirical evidences in credit risk management in Pakistan. The identification of suitable explanatory variable that explains the banking profitability wisely is made possible by using the panel data techniques. In this study, impact of bank specific variables are: Return On Assets, Capital Ratio, Credit Risk, Credit deposit ratio, Liquidity Ratio, Interest expended to interest earned, bank size and ownership on the profitability of banks in Pakistan has been assessed using four different panel data techniques. Out of the four estimation strategies Random Effect with Mundlak (1978) transformation raises the overall variation of the baseline model to 63% that is explained by banking profitability. Ignoring the time-invariant characteristics in the model, credit deposit ratio and interest expanded to interest earned possess negative relationship with return on assets of banks. Size of the bank is positive and significant when with-in and between banks information is augmented in Radom effect method of estimation. However the size of banks may not affect the banking profitability by allowing correlation between unobservable heterogeneity using Random Effect with Mundlak (1978) transformation.