Wasim Ahmad

The Eurozone crisis and its contagion effects on the European stock markets

Purpose - – This paper aims to examine the contagion effects of Greece, Ireland, Portugal, Spain and Italy (GIPSI) and US stock markets on seven Eurozone and six non-Eurozone stock markets. Design/methodology/approach - – In this paper, a dynamic conditional correlation (DCC) model popularly known as DCC-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model given by Engle (2002) is applied to estimate the DCCs across sample markets. Findings - – Analyzing the Eurozone crisis period, the empirical results suggest that among GIPSI stock markets, Spain, Italy, Portugal and Ireland appear to be most contagious for Eurozone and non-Eurozone markets. The study finds that France, Belgium, Austria and Germany in Eurozone and UK, Sweden and Denmark in non-Eurozone are strongly hit by the contagion shock. Practical implications - – The findings of the study have significant implications for the concerned regulatory authorities, as it may provide an important direction for further policy research with regard to financial integration in the European Union (EU). From global investors’ perspective, the EU-based diversification strategies seem to be inefficient especially during Eurozone crisis. Originality/value - – To the best of the authors’ knowledge, this is the first study that examines the issue of financial contagion of Eurozone crisis for a large basket of stock markets of European countries comprising seven Eurozone and six non-Eurozone markets for the period 2009-2012. The study uses the Markov regime switching model to identify crisis period and utilizes the DCC estimates of DCC-GARCH to examine the patterns of financial contagion. The finding of this study is quite interesting and is different in several ways than existing studies in the literature.

Economic growth, energy consumption and CO2 emissions in India: a disaggregated causal analysis

ABSTRACT This study examines the long-run and short-run causal relationships among energy consumption, real gross domestic product (GDP) and CO2 emissions using aggregate and disaggregate (sectoral) energy consumption measures utilising annual data from 1971 to 2011. The autoregressive distributed lag bounds test reveals that there is a long-run relationship among the variables concerned at both aggregate and disaggregate levels. The Toda–Yamamoto causality tests, however, reveal that the long-run as well short-run causal relationship among the variables is not uniform across sectors. The weight of evidences of the study indicates that there is short-run causality from electricity consumption to economic growth, and to CO2 emissions. The results suggest that India should take appropriate cautious steps to sustain high growth rate and at the same time to control emissions of CO2. Further, energy and environmental policies should acknowledge the sectoral differences in the relationship between energy consumption and real gross domestic product.

On the Role of the Trend and Cyclical Components in Electricity Consumption and India's Economic Growth: A Cointegration and Cofeature Approach

In this paper, the relationship between electricity consumption (LEC) and economic growth (LGDP) using Autoregressive Distributed Lag (ARDL) model and Granger causality within error correction framework in India over the period 1970–1971 to 2009–2010 are analysed. The results of these tests exhibit the existence of long-run equilibrium relationship and bilateral causality in case of India. Then, Hodrick–Prescott filter is used to decompose the data into trend and cyclical (fluctuation) components of electricity consumption and economic growth. The results of decomposed series revealed that both series are cointegrated with the strong evidence of bidirectional causality, implying that trend and cyclical components are strongly correlated with business cycles in India. From these findings, we conclude that the feedback hypothesis is applicable in case of India. Therefore, government should undertake necessary policy measures to augment the investment in power sector from existing level and more importantly the emphasis should also be given on the efficient use of electricity.

Time-Varying Spillover and the Portfolio Diversification Implications of Clean Energy Equity with Commodities and Financial Assets

ABSTRACT This article examines the time-varying spillover and its implications on hedging and portfolio diversification for clean energy equities (WilderHill New Energy Global Innovation Index (NEX)) with technology stocks (PSE), four energy sub-indices of Standard & Poor Goldman Sachs Commodity Index (S&P-GSCI) viz., Crude oil, Brent crude oil, Gasoline and Heating oil and three major global equities indices represented by the USA, Europe, World, Dow-Jones Islamic Market Index (DJIMI) along with USD-Euro exchange rate. We find that in a mixed portfolio set-up, the inclusion of NEX in energy portfolio provides better diversification and risk reduction benefits for hedgers and portfolio managers.

An Analysis of Dynamic Spillover in India’s Forex Derivatives Markets

This chapter uses multivariate GARCH models to study volatility spillovers in foreign exchange markets. The study is based on daily data of futures and spot of four exchange rates viz., EURO/INR, GBP/INR, USD/INR and JPY/INR, traded on NSE and MCX-SX for the period February 2010 to November 2014. The main objective is to examine the dynamic spillover in India’s forex derivatives markets. The study suggests that the static spillover analysis explicitly categorizes the sample exchange rates into net transmitters and net receivers. The dynamic spillover analysis shows periods wherein the roles of emitters and recipients of return and volatility spillovers can be interrupted or even reversed. Thus, even if some commonalities appear in each identified category of exchange rates, such commonalities are event specific and time dependent.

The investigation of destabilization effect in India’s agriculture commodity futures market: An alternative viewpoint

Purpose - – This paper aims to examine the destabilization effect in the case of India’s agricultural commodity market for the sample period of 01 January 2009 to 31 May 2013. Design/methodology/approach - – The daily data of eight agricultural commodities traded on the National Commodity & Derivatives Exchange, viz., barley, castor seed, chana (chickpea), chilli, potato, pepper, refined soya and soybean, have been used in this study. At the first stage of the empirical analysis, the study estimates the time-varying spot market volatility by using the exponential generalized autoregressive conditional heteroscedasticity model and applies three different high and band-pass filters, viz., the two-sided linear band-pass filter by Hodrick and Prescott (1997), the fixed-length symmetric band-pass filter by Baxter and King (1999) and the asymmetric band-pass filter by Christiano and Fitzgerald (2003), to calculate the unexpected liquidity of sample commodities. At the second stage of the empirical analysis, the study applies linear Granger causality and recently developed non-linear causality given by Diks and Panchenko (2006) to examine the cause and effect between time-varying volatility of spot market and futures market liquidity of sample commodities. Findings - – The linear and non-linear causality results suggest the destabilizing effect of commodity futures on the underlying spot market for chana, chilli and pepper. The empirical findings are in contrast with the recommendations of Abhijit Sen’s committee and provide important direction for further policy research. Research limitations/implications - – The study has a limitation in that it is based on the daily data. The use of intra-day data would have been more suitable for such type of analysis. Practical implications - – The study has strong policy implications from a financial policy perspective, as there is already disagreement among researchers and policy makers with regard to the functioning of commodity derivatives markets in India. There have been many occasions when commodity market regulators have to undertake decisions of suspension of trading of many commodities. The study also provides new directions of policy research with regards to the restructuring of the commodity derivatives market in India. Social implications - – The findings of this study may further help the regulators and policy makers to undertake decisions about how to provide an alternative platform for farmers to sell their agricultural produce more efficiently. This will certainly have some impact on the socioeconomic set-up of the country, as India is primarily an agriculture-dominated country. Originality/value - – So far not many studies have investigated the destabilization hypothesis in the case of emerging markets. This study is a novel attempt to fill the gap. In the case of emerging markets and especially in the case of India’s commodity derivatives market, this is the first study that examines the destabilization hypothesis in the case of India by applying new methods of high and band-pass filters and non-linear causality.