Are gold,USD, and Bitcoin hedge or safe haven against stock? The implication for risk management

This study investigates whether gold, USD, and Bitcoin are hedge and safe haven assets against stock and if they are useful in diversifying downside risk for international stock markets. We propose a combined GO-GARCH-EVT-copula approach to examine the hedge and safe haven properties of gold, USD, and Bitcoin. We then examine the attractiveness of these assets in reducing stock portfolio risk by using downside risk measures estimated by the proposed approach and other competing models. We also evaluate the relative performance of the proposed model in reducing downside risk with the competing models. The findings of the study indicate that the USD is the most valuable hedge and safe haven asset closely followed by gold, while Bitcoin is the least valuable. It is also observed that the proposed combined approach performs best in reducing the portfolio downside risk. The findings of this study are of significance for portfolio managers and individual investors who wish to protect the portfolio value during market turmoil.     

Estimation of tail‐related risk measures in the Indian stock market: An extreme value approach

The purpose of the study is to estimate tail-related risk measures using extreme value theory (EVT) in the Indian stock market. The study employs a two stage approach of conditional EVT originally proposed by McNeil and Frey (2000) to estimate dynamic Value at Risk (VaR) and expected shortfall (ES). The dynamic risk measures have been estimated for different percentiles for negative and positive returns. The estimates of risk measures computed under different quantile levels exhibit strong stability across a range of the selected thresholds, implying the accuracy and reliability of the estimated quantile based risk measures.     

Spatial Integration of Wheat Markets in India: Evidence from Cointegration Tests

Using the maximum likelihood method of cointegration, this paper empirically evaluates intra-state and inter-state spatial integration of wheat markets in India. The cointegration tests provide strong evidence in favour of spatial integration of the regional wheat markets. Even though the regional markets are geographically dispersed, the prices across different market centres within and across the selected states have exhibited long-run spatial linkages, suggesting that all the exchange locations are integrated and the prices provide relevant market signals. There are several implications of these results for agricultural price policy and food market liberalization programmes.     

Regional Economic Growth and Inequality in India during the Pre- and Post-reform Periods

Abstract

This paper evaluates the economic performance of 15 major states in India, and examines whether initially disparate states displayed any tendency towards convergence in real per capita income during the period 1960/61–2006/07. Though the growth performance of the states has improved in the post-reform period, since 1991 the states have diverged in per capita income. The states following different steady-state paths are classified into three clubs—one convergent and two non-convergent. The regional divergence and club convergence are explained in terms of interstate variations in physical and social infrastructures, state-level policy reforms, foreign direct investment flows and economic structure. The poorly performing states could improve their relative economic position by undertaking investments in physical and social infrastructures, and speeding up the reform process by liberalizing investment and infrastructure policies. As industry and services are the major sources of regional divergence, any effort to reduce regional imbalance must focus primarily on these two sectors.     

Information share and its predictability in the Indian stock market

The study investigates price discovery in the Indian stock market and finds that spot market plays a dominating role in price discovery when it is estimated for the entire period as a whole. However, periodic measures of price discovery suggest that it does not remain the same throughout the period, but varies with time. Panel data analysis also indicates that spot market is more efficient in price discovery for majority of size and sector panels. Finally, while market state-related variables are found to impact information shares in a majority of the cases, macroeconomic announcements rarely predict the price discovery.     

Information transmission between small and large stocks in the National Stock Exchange in India: An empirical study

The study investigates return and volatility spillover effects between large and small stocks in the national stock exchange in India using daily index data on S&P CNX Nifty, CNX Nifty Junior and CNX Midcap. The VAR model together with the variance decomposition (VDC) and the impulse response function (IRF) analysis have been employed to uncover both casual and dynamic relationship between the large stocks and small stocks. The results show that there are very significant return spillovers from the market portfolio of large stocks to the portfolio of small stocks. To investigate the volatility spillover the study has used standard BEKK model and asymmetric BEKK model. Although, based on the standard BEKK model we have observed unidirectional volatility spillovers from the portfolio of large stocks to the portfolio of small stocks, the finding was less reliable. The more reliable finding, which is based on asymmetric BEKK model, is that there is bidirectional volatility spillover between the portfolio of large stocks and the portfolio of small stocks.