This study tries to find the dynamic stock market linkages among 12 Asian countries over the period January 3, 2000 to June 20, 2017. We employ ADCC-GARCH model to study the conditional correlations and Diebold and Yilmaz (2012) spillover index methodology to investigate return and volatility spillovers across the sample markets [1]. Based on ADCC results, we find that Singapore exhibits highest conditional correlation with other sample markets. Dynamic conditional correlations across the markets amplify during the crisis periods, pointing to financial contagion. The findings under Diebold-Yilmaz framework corroborate with the ADCC-GARCH model results as Singapore is found to be the dominant market based on both return and volatility spillovers. Inter-temporal pattern of spillovers reveals that cross-market linkages intensify during the turmoil periods. Our results have important implications for international investors and policymakers. The study contributes to financial integration literature for Asian markets.

In this study we examine the stock price reaction around earnings announcement for India. The data are used for 469 companies and the study period spans from December 2002 to December 2011 covering 37 quarterly periods. Significant pre-event abnormal returns are observed for 32 out of 37 quarters which may be an outcome of superior analysis coupled with information asymmetry. Significant post-event abnormal returns are observed for 35 out of 37 quarters implying strong rejection of semi strong efficiency with regards to earning announcements. There are strong continuation patterns in earnings suggesting that investors are able to anticipate the informational contents of earnings. Post-event abnormal returns are higher for financial vis-à-vis non-financial closing quarters. A large part of abnormal returns is observed over an elongated event window rather than very close to event date. Lower post-event abnormal returns are reported for periods of high aggregate earnings and vice versa. The findings shall be useful for market regulator, investment managers, companies as well as researchers. The study contributes to stock market efficiency and behavioural finance literature for an emerging market.

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Purpose: The study tries to find pattern in the bilateral trade and impact of macro happenings like GFC, Chinese meltdown, Galwan conflict, COVID-19 on it over the period of 1995 to 2020. Design/Methodology/Approach: The study has two dimensions. The first one analyses the monthly export and import figures between India and China product wise (based on HS Code at two-digit level) from Jan2016 to Jan 2021 whereas second one focus on annual data of Indo-China Export and Import along with their annual GDP for 26 years starting from 1994-1995 to 2019-2020. Bilateral trades are analysed by using four tools namely- Bilateral Trade Dependence Index (BTDI); Trade Intensity Index (TII); Herfindahl Hirschmann Market Concentration Index (HHI); and Index of Export market penetration (IEMP). The study has also used Time series analysis to find the relationship between total bilateral trade and GDP of respective countries using Johansen Cointegration Test, Granger Causality Test, and VAR model. Findings: The annual growth rate of import and export for India with China suggest the short-term impact of macro happenings. Research Limitations: The study has several limitations with respect to availability of very recent data, availability of cost components of trade items in respective countries etc. Managerial Implications: Policy makers for India are suggested to work towards import substitution via various programs like Make-in-India with priority of domestic productions of HS Code 85, 84, 29 which are increasing the trade deficit continuously. Originality/Value: This study is an original effort to highlight the dynamic bilateral trade relationships between India and China in last twenty-five years.

Volatility in foreign exchange rates is an indicator of economic performance particularly for emerging market economies like India. This study tries to re-examine the relationship between exchange rates and macroeconomic variables for Indian economy. It addresses three issues, namely Volatility in exchange rates (USD/INR; EUR/INR and GBP/INR); Effect of Economic crisis represented by global financial crisis (GFC) and macroeconomic variables mainly Inflation and Yield of 10yearsGovt. Securities on above mentioned three exchange rates; and Relationship between exchange rates volatility and foreign trade (both export and import). Daily data for three exchange rates are taken for the period of January 3 rd , 2000 to March 26 th 2019, whereas for other two objectives, monthly average exchange rates are used along with monthly data for select macroeconomic variables for the period of Jan 2000 to Dec 2018. Volatility is represented by Standard Deviation and Causality is checked through Granger Causality Test. The findings suggest that volatility is highest for EUR/ INR followed by GBP/INR and USD/INR. The average annual volatility for all three exchange rates indicates the minimum value in 2001 whereas maximum value for 2013. It is also observed that volatility is higher during crisis period compared to pre and post crisis periods for all three exchange rates. Granger Causality test suggests that out of 10 pairs of testing for causality only unidirectional cause effect relationships stating GBP granger causes yield on 10 years Government securities. The study further finds that USD/ INR exchange rate granger cause imports of India. These findings will help the market players at the time of taking their strategic decisions whereas to regulators during their policy decision process. For academicians and researchers, it provides an opportunity to explore the conditions with more macroeconomic variables and with the use of advanced econometric tools.