The firm’s valuation (FV) is the key element for all stakeholders, particularly the investors, for their investment decisions. The main impetus of this research is to estimate the effects of the debt ratio (DR, i.e., leverage) on the FV (i.e., assets and market capitalisation) of the non-financial firms listed in India. The quantile panel data regression (QPDR) on the secondary data of 76 non-financial BSE-100 listed firms in India is employed. This study also checks the effect of the net profit margin (NPM) as profitability on the association between DR and FV. The QPDR estimates result in multiple quantiles and provide evidence in scenarios. The findings reveal a positive relationship of DR to assets only in higher quantiles, i.e., 90%ile), and a negative association of DR is found with a market capitalisation in all quantiles. Under the interaction effect, profitability (NPM) does not affect the association of DR with assets but negatively affects the association of debt ratio with market capitalisation in the middle (50%) quantile. The findings indicate that leverage (DR) affects a firm’s value. The study’s outcomes are helpful to all stakeholders, particularly investors, to realise the leverage (DR) as a critical indicator of FV before making any investment decisions. Managers should also consider lower debt ratios for better firm value. The present analysis is original and holds novelty in the form of the moderating role of the net profit margin, i.e., the profitability of the firm between DR and FV in the non-financial firm in India. To the best of our knowledge, no such studies have been performed to look for the association of the debt ratio with a firm’s value under the effect of profitability in different quantiles using quantile regression.

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E-learning is the learning process that continues with the help of technology. Learners and educators interact with online platforms or tools like video, audio, virtual or augmented reality, etc. The inclusion of e-learning has geared up during the COVID-19 pandemic. It also existed before where educators used to interact, discuss, teach, or guide the learners from different parts of world. Emotional intelligence is something which we can do, keeping the emotions aside and following the cognitive behaviour for a particular situation. Compassion is a feeling of being moved by someone's feelings and finding a way to help or motivate or support the individual. The sharing of the compassionate feelings becomes difficult in the case of e-learning. This chapter will provide a detailed understanding of the concept of compassion as provided by different authors and the method of practicing compassion for an improved and effective learning process. This chapter will also discuss the relationship of emotional wellbeing with compassionate behaviour.

Crude oil is an imperative energy source for the global economy. The future value of crude oil is challenging to anticipate due to its nonstationarity in nature. The focus of this research is to appraise the explosive behavior of crude oil during 2007–2022, including the most recent influential crisis COVID-19 pandemic, to forecast its prices. The crude oil price forecasts by the traditional econometric ARIMA model were compared with modern Artificial Intelligence (AI)-based Long Short-Term Memory Networks (ALSTM). Root mean square error (RMSE) and mean average percent error (MAPE) values have been used to evaluate the accuracy of such approaches. The results showed that the ALSTM model performs better than the traditional econometric ARIMA forecast model while predicting crude oil opening price on the next working day. Crude oil investors can effectively use this as an intraday trading model and more accurately predict the next working day opening price.

The focus of this article is to analyse the inter-linkages between eight leading stock markets in Asian continent from the period of July 2011 to February 2018. This period holds relevance as this was the time when Recession 2.0 set in, which adversely affected the developed economies; however, the developing economies withstood the crisis without much of an impact. Co-integration and Granger causality tests were conducted to probe the inter-linkages. Study revealed a positive impact on Asian stock market indices collectively on each of the indexes. The highest number of unidirectional causalities was to KOPSI and NIFTY from rest of the stock indices. Results confirmed that no co-integration relationship existed among the selected indices indicating favourable diversification opportunities. Thus, the study fosters global market participants and policymakers to consider the nitty-gritties of stock market integration so as to benefit from international stock market diversification in the Asian region.