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Purpose: This paper aims to investigate the association of COVID-19 confirmed cases and deaths with mental health, unemployment and financial markets-related search terms for the USA, the UK, India and worldwide using Google Trends. Design/methodology/approach: The authors use Spearman's rank correlation coefficients to assess the relationship between relative search volumes (RSVs) and mental health, unemployment and financial markets-related search terms, with the total confirmed COVID-19 cases as well as deaths in the USA, UK, India and worldwide. The sample period starts from the day 100 cases were reported for the first time, which is 7 March 2020, 13 March 2020, 23 March 2020 and 28 January 2020 for the US, the UK, India and worldwide, respectively, and ends on 25 June 2020. Findings: The results indicate a significant increase in anxiety, depression and stress leading to sleeping disorders or insomnia, further deteriorating mental health. The RSVs of employment are negatively significant, implying that people are hesitant to search for new jobs due to being susceptible to exposure, imposed lockdown and social distancing measures and changing employment patterns. The RSVs for financial terms exhibit the varying associations of COVID-19 cases and deaths with the stock market, loans, rent, etc. Research limitations/implications: This study has implications for the policymakers, health experts and the government. The state governments must provide proper medical facilities and holistic care to the affected population. It may be noted that the findings of this study only lead us to conclude about the relationship between COVID-19 cases and deaths and Google Trends searches, and do not as such indicate the effect on actual behaviour. Originality/value: To the best of the authors' knowledge, this is the first attempt to investigate the relationship between the number of COVID-19 cases and deaths in the USA, UK and India and at the global level and RSVs for mental health-related, job-related and financial keywords. [ABSTRACT FROM AUTHOR]

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC. [ABSTRACT FROM AUTHOR]

This paper explores the importance of central banking policies in financial market performance, using the case of India. For this purpose, the paper comparatively analyzes the performance of financial markets during the regimes of last three governors of the Reserve Bank of India—Y V Reddy, D Subbarao, and Raghuram Rajan. The paper discusses the central banking policies in these periods with respect to monetary stability, inflation, and growth challenges. The paper presents an analysis of returns and volatility in stock markets and currency markets in their tenures in comparison with those from other selected emerging markets (Brazil, Russia, China, South Africa) and developed markets (USA and UK). The paper also brings out the leverage effect by applying the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model in addition to comparatively analyzing the performance of financial markets. Further, the paper assesses the impact of central banking policies on financial markets by using the fixed effect model on the reference countries for the period under reference. [ABSTRACT FROM AUTHOR]

This paper examines if the Indian stock market moves with other markets in Asia and the United States in an era of capital market reforms and the sustained interest of foreign investors in that market. By using techniques of cointegration, vector autoregression, vector error-correction models, and Granger causality, we find that, though there is definite information leadership from the U.S. market to all Asian markets, the U.S. indexes do not uniquely influence the integration of Asian markets, while Japan is found to play a unique role in the integration of Asian markets. The U.S. market is seen not only to influence, but also to be influenced by information from most of the major Asian markets. The Indian stock return in recent times is definitely led by major stock index returns in the United States, Japan, as well as other Asian markets, such as Hong Kong, South Korea, and Singapore. More important, returns on the Indian market are also seen to exert considerable influence on stock returns in major Asian markets. [ABSTRACT FROM AUTHOR]