Returns, volatility and spillover – A paradigm shift in India?

Dey, Shubhasis; Sampath, Aravind

doi:10.1016/j.najef.2019.101110

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…Su [ 10 ] used the MHS-EGARCH model, finding that there are negative return and volatility spillover effects between currency and stock markets, and the stock indices in emerging markets have a higher return and a higher risk. Dey and Sampath [ 11 ] analyzed spillovers in returns and volatility among five major financial assets in India, especially the shock from the USA, by using a generalized vector autoregressive model, and they find that banking, real estate and gold matter the most for India. There are a number of similar studies such as Georgiadis [ 12 ], Yang and Zhou [ 13 ], and Miranda-Agrippino and Rey [ 14 ] that show that the US monetary policy could cause a considerable spillover impact in the global financial market.…”

Section: Literature Reviewmentioning

confidence: 99%

A Network Approach to the Study of the Dynamics of Risk Spillover in China’s Bond Market

Liao

Zhang

Guo

et al. 2021

Entropy

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Since 2018, the bond market has surpassed the stock market, becoming the biggest investment area in China’s security market, and the systemic risks of China’s bond market are of non-negligible importance. Based on daily interest rate data of representative bond categories, this study conducted a dynamic analysis based on generalized vector autoregressive volatility spillover variance decomposition, constructed a complex network, and adopted the minimum spanning tree method to clarify and analyze the risk propagation path between different bond types. It is found that the importance of each bond type is positively correlated with liquidity, transaction volume, and credit rating, and the inter-bank market is the most important market in the entire bond market, while interest rate bonds, bank bonds and urban investment bonds are important varieties with great systemic importance. In addition, the long-term trend of the dynamic spillover index of China’s bond market falls in line with the pace of the interest rate adjustments. To hold the bottom line of preventing financial systemic risks of China’s bond market, standard management, strict supervision, and timely regulation of the bond markets are required, and the structural entropy, as a useful indicator, also should be used in the risk management and monitoring.

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Section: Literature Reviewmentioning

confidence: 99%

A Network Approach to the Study of the Dynamics of Risk Spillover in China’s Bond Market

Liao

Zhang

Guo

et al. 2021

Entropy

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“…Another study by Mallikarjuna and Rao (2017) in the Indian context used BSE‘s sectoral indices and revealed volatility persistence in all the indices. Dey and Sampath (2020) studied the volatility and spillover effects in returns of five financial assets in India using Garman and Klass’s range-based volatility measure. Their study pointed out that any shock from an event in the USA affects India’s gold and forex markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Sub-prime Crisis or COVID-19: A Comparative Analysis of Volatility in Indian Banking Sectoral Indices

Bhatia

Gupta²

2020

FIIB Business Review

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Stock market volatility may be a function of company, industry, or world over information made public. The present study has investigated the volatility of Indian banking sectoral indices with the general banking index for two shocking events: the Sub-prime crisis and COVID-19. A comparative analysis of both the shocks leading to these indices’ volatility has been conducted using symmetric and asymmetric models. This study’s findings show that these indices’ volatile behaviour has been strong enough to persist in the market with the leverage effect present during the sub-prime crisis. This effect disappeared for Nifty Bank Indices and Private Sector Bank Indices as compared to Public Sector Undertaking Bank Indices during COVID-19 (probably because the pandemic is not over yet). With GARCH and EGARCH models, the study suggests that the investors may use the diversification approach, in the long run, to safeguard their portfolio values to survive from global shocks.

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“…Engle et al (1990) pioneering study examined spillover in different exchange rate markets by deploying the GARCH technique. Dey and Sampath (2020) have highlighted that mostly multivariate GARCH models or Diebold and Yilmaz’s (2012) technique has been deployed in extant literature for empirically investigating the extent of volatility linkages amongst financial markets. Understanding the volatility linkages for investors to formulate an optimum risk-adjusted portfolio is critical.…”

Section: Introductionmentioning

confidence: 99%

Stock market volatility: a systematic review

Dhingra,

Batra,

Aggarwal

et al. 2023

JM2

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Purpose The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility. Design/methodology/approach This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area. Findings The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area. Originality/value This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

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Returns, volatility and spillover – A paradigm shift in India?

Cited by 8 publications

References 29 publications

A Network Approach to the Study of the Dynamics of Risk Spillover in China’s Bond Market

A Network Approach to the Study of the Dynamics of Risk Spillover in China’s Bond Market

Sub-prime Crisis or COVID-19: A Comparative Analysis of Volatility in Indian Banking Sectoral Indices

Stock market volatility: a systematic review

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