This article investigates monetary policy and stock market interaction across 41 developed and developing economies using GMM-Panel VAR model. The analysis is undertaken in two sub-periods—before and after the crisis of 2008 to make a comparative assessment of whether the relationship between monetary policy and stock prices altered in the aftermath of the crisis. We verify the existence of different channels of monetary transmission to stock prices. Our results point to the prevalence of discount rate channel of monetary policy in affecting stock prices after the crisis of 2008. Further, our results indicate an important role of excess liquidity in pushing stock prices upward in developed economies in the post-crisis period. In developing economies, term premia channel is the dominant channel of transmission to stock prices. Also, we find evidence of monetary authorities of developed economies responding directly to stock price movements to ensure financial stability in the post-crisis period. Central banks react primarily to inflationary pressures by tightening monetary policy both before and after the crisis in developed and developing economies. JEL Codes: C32, E44, E52, F42
This study examines price discovery and volatility linkages between USD/INR spot and futures contracts in India and between USD/INR futures contracts on National Stock Exchange of India Limited (NSE), India and on three international exchanges, namely Singapore Exchange (SGX), Dubai Gold and Commodity Exchange (DGCX) and Chicago Mercantile Exchange (CME), from 29 August 2008 to 30 March 2015. Findings show that, at domestic level, the futures dominate spot in the Indian currency market; these findings are stronger than those in an earlier study, indicating improved pricing as well as hedging efficiency in the Indian currency market. At international level, NSE is dominated by both CME and DGCX in price discovery and in short-term volatility spillovers, while NSE dominates both exchanges in long-term volatility spillovers. Further, NSE dominates SGX in the international information process. The dominance of CME and DGCX over NSE may be on account of their several advantages such as longer trading hours, operations being open even after NSE has shut business, much lower trading costs as well as lower regulatory restrictions. The study provides several significant policy suggestions for improving efficiency of the Indian currency market and is also relevant for foreign portfolio investors (FPIs), domestic investors, researchers and academicians. It contributes to literature on information transmission relating to currency markets in emerging economies.
In this study, we examine the role of fund characteristics in determining mutual fund performance in India. The data comprises of 237 open-ended Indian equity (growth) schemes during the period April 2007 to March 2013. Using daily dividend adjusted net asset values (NAVs), the risk-adjusted performance is estimated employing conditional version of Carhart (1997) four factor model in a time series regression framework. A range of fund characteristics, namely, the size of fund, growth in size of fund, expense ratio, portfolio turnover, NAV and age of fund, are examined in predictive model in a panel data regression framework that may determine the future performance of the fund. The Hausman specification test is conducted to decide if individual effects are random or fixed. The results of panel regression, based on fixed effects estimator, show that the size of fund, growth in size of fund and NAV negatively affect one period ahead risk-adjusted performance in India, while the age of fund has a positive impact. Expense and portfolio turnover ratios do not play a significant role. Identification of significant fund characteristics offer valuable insights to investors as it will allow them to make prudent selection of mutual funds and make judicious investment decisions.
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.
In this article, we focus on net stock issues which is a relatively unexplored asset pricing anomaly. We examine the relationship between net stock issues and returns in the Indian context using data for BSE 500 stocks from 1995 to 2012. The relationship between size, value and momentum attributes and stock return is confirmed, which is consistent with prior literature. We specifically find a negative relationship between net stock issues and returns after controlling for other firm characteristics, thus implying that companies with larger public offerings provide lower post-event returns. The net stock issues attribute is empirically associated with size and value characteristics. Large firms and low price to book (P/B) or relatively distressed firms tend to make bigger public offerings. While the former may do it to finance business expansion plans, the latter rely more on external financing owing to weak earnings record. Our findings are pertinent for policymakers, market practitioners and academicians. The study contributes to equity market anomaly literature for emerging markets.
In this study, we measure and analyse the time-varying nature of risk exposures for the Indian banking industry using weekly bank-level data from 23 October 2004 to 1 August 2014. We extend the literature by studying credit, equity, interest rate and exchange rate risks following a more comprehensive framework. The study finds evidence that the risk exposures are time varying in nature and differ across banks with different characteristics. Equity risk and credit risk increase post the global financial crisis (GFC) while interest rate and exchange rate risk gets reduced. The capital market has a favourable view of small-sized, well-capitalized, well-diversified private sector banks. Furthermore, the results also show that asset size and ownership structure offer relevant information for differentiating banks regarding their riskiness. Large banks have more equity risk exposure; public sector banks have higher credit risks while private sector banks have greater interest rates and exchange rate risk exposure. The study offers valuable insights for the regulators, supervisors, policymakers, banking industry, bank managers, investors and academia. The main contribution is a better understanding of sources of banks' risks and needs to enhance the supervisory process in the Basel framework.
