Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets

2022 ◽  
Vol 59 ◽  
pp. 101543
Author(s):  
Shangrong Jiang ◽  
Yuze Li ◽  
Quanying Lu ◽  
Shouyang Wang ◽  
Yunjie Wei
Keyword(s):  
Financial Markets ◽  
Volatility Spillover

‘Indian Stock Market Volatility’: A Study of Inter-linkages and Spillover Effects

2019 ◽  
Vol 18 (2_suppl) ◽  
pp. S183-S212 ◽  
Author(s):  
Suparna Nandy (Pal) ◽  
Arup Kr. Chattopadhyay
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Volatility Spillover ◽  
Exchange Market ◽  
Causality Test ◽  
Asymmetric Volatility ◽  
Indian Stock Market ◽  
Domestic Stock

The article attempts to examine interdependence between Indian stock market and other domestic financial markets, namely, foreign exchange market, bullion market, money market, and also Foreign Institutional Investor (FII) trade and foreign stock markets comprising one regional stock market represented by Nikkei of Japan and other stock market for the rest of the world represented by Standard & Poor’s (S&P) 500 of the USA. Attempts are also made to examine asymmetric volatility spillover, first, between the Indian stock market and other domestic financial markets and second, between the Indian stock market and global stock markets (represented by Nikkei and S&P 500) along with the foreign exchange market. To measure linear interdependence among multiple time series of financial markets multivariate Vector Autoregression (VAR) analysis, Granger causality test, impulse response function and variance decomposition techniques are used. For estima-ting the volatility spillover among the aforesaid markets Dynamic Conditional Correlation-Multivriate-Threshold Autoregressive Condi-tional Heteroscedastic (DCC-MV-TARCH) (1, 1) model is applied on daily data for a quite long period of time from 01 April 1996 to 31 March 2012. The results of multi­variate VAR analysis, Granger causality test, variance decomposition analysis and impulse response function estimation establish significant interdependence between domestic stock market and different other financial markets in India and abroad. The results of DCC-MV-TARCH (1, 1) model estimation further show signi- ficant asymmetric volatility spillover between the domestic stock market and the foreign exchange market and also from the domestic stock market to bullion market and changes in gross volume of FII trade. We also find (a) both way asymmetric volatility spillover between the domestic stock market and the Asian stock market and (b) its unidirectional movement from the world stock market to the domestic stock market. The results of the study may help market regulators in setting regulatory policies considering the inter-linkages and pattern of volatility spillovers across different financial markets. JEL Classification: G15, G17

VOLATILITY SPILLOVER EFFECT OF FEDERAL RESERVE’S BALANCE SHEET ON THE FINANCIAL AND GOODS MARKETS OF INDO-PAK REGION

2019 ◽  
Vol 14 (03) ◽  
pp. 1950015
Author(s):  
QASIM RAZA SYED ◽  
WASEEM SHAHID MALIK ◽  
BISHARAT HUSSAIN CHANG
Keyword(s):  
Financial Markets ◽  
Federal Reserve ◽  
Balance Sheet ◽  
Spillover Effect ◽  
Spillover Effects ◽  
The Other ◽  
Volatility Spillover ◽  
Monthly Basis ◽  
Volatility Spillovers ◽  
Volatility Spillover Effect

This paper examines the volatility spillover effect of the balance sheet of Federal Reserve (Fed) on the financial and goods markets of Pakistan, India and Bangladesh (collectively known as the Indo-Pak region). Diagonal BEKK-GARCH methodology is used to capture the volatility spillover effects on Indo-Pak economies. This study took data from the year 2004 to year 2019 on a monthly basis. The findings of the paper describe that there are volatility spillovers from Fed’s balance sheet to the financial markets of Pakistan, India and Bangladesh economies. On the other hand, there is also evidence of volatility spillovers from the balance sheet of Fed to the goods markets of these economies.

scholarly journals Watch Your Neighbor: A Volatility Spillover in ASEAN-5 Stock Exchange

2019 ◽  
Vol 10 (1) ◽  
pp. 59-65
Author(s):  
Sumani Sumani ◽  
Siti Saadah
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Return ◽  
Stock Exchange ◽  
Selection Process ◽  
Asset Price ◽  
Price Volatility ◽  
The Philippines ◽  
Volatility Spillover ◽  
Asean Countries

In the process of financial markets integration, this research was conducted to investigate the phenomenon of the transmission of stock return volatility among stock market in five ASEAN countries. Those were Indonesia, Singapore, Malaysia, Philippines, and Thailand. The research was important because when the interdependence of financial markets had increased, changes in asset prices in the market were not only influenced by the shock in the market but also by its response to asset price volatility that occurred in other countries. Information about the volatility spillover between markets was important for investors to the portfolio selection process. Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) method was used on a daily time series stock return data obtained by accessing www.bloomberg.com. The result indicates that the shock in Singapore, Malaysia, Thailand, and the Philippines stock market will be transmitted to the Indonesia Stock Market with an asymmetric pattern. It has increased intensity after the implementation of the ASEAN Economic Community in December 2015.

scholarly journals INTER-MARKETS VOLATILITY SPILLOVER IN U.S. BITCOIN AND FINANCIAL MARKETS

2019 ◽  
Vol 20 (4) ◽  
pp. 694-714 ◽  
Author(s):  
Muhammad Owais Qarni ◽  
Saqib Gulzar ◽  
Syeda Tamkeen Fatima ◽  
Majid Jamal Khan ◽  
Khurram Shafi
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
Significant Risk ◽  
Time Varying ◽  
Volatility Spillover ◽  
Foreign Investors ◽  
Risk Hedging ◽  
Insignificant Effect ◽  
Asymmetry Measure ◽  
The U.S

This paper investigates the volatility spillover dynamics between U.S. Bitcoin and financial markets from July 19, 2010 to December 29, 2017. Diebold and Yilmaz (2012) volatility spillover index, Barunik, Kocenda, and Vacha (2017) Spillover Asymmetry Measure, and Barunik and Krehlik (2018) frequency connectedness methodologies are applied to investigate the time varying dynamics of volatility spillover among U.S. Bitcoin and financial markets. The findings of the study indicate the presence of low level of integration and contagion between U.S. Bitcoin and financial markets. Asymmetric nature of volatility spillover is also detected. The connectedness among the U.S. Bitcoin and financial markets is found to be concentrated at high frequency, suggesting that markets process information rapidly. Moreover, the turbulence in Bitcoin market will have insignificant effect on U.S. financial markets. This non-contagion nature of Bitcoin markets provides significant risk hedging and diversification benefits for domestic and foreign investors in the U.S.

scholarly journals Volatility Connectedness between Clean Energy Firms and Crude Oil in the COVID-19 Era

2020 ◽  
Vol 12 (23) ◽  
pp. 9863
Author(s):  
Matteo Foglia ◽  
Eliana Angelini
Keyword(s):  
Financial Markets ◽  
Portfolio Management ◽  
Spillover Effect ◽  
Clean Energy ◽  
Financial Contagion ◽  
Volatility Spillover ◽  
Portfolio Decisions ◽  
Volatility Spillovers ◽  
Global Pandemic ◽  
Active Portfolio Management

The work investigates the volatility connectedness between oil price and clean energy firms over the period 2011–2020 (including the COVID-19 outbreak). Using the volatility spillover models, and dynamic conditional correlation, we are able to identify the volatility spillover effect between these financial markets and its implications for portfolio diversification. The results indicate a significant change in both static and dynamic volatility connectedness around the COVID-19 outbreak. For instance, total connectedness index changes from 21.36% (pre-COVID-19) to 61.23% (COVID-19). This finding shows the strong effect of the COVID-19 pandemic on these financial markets. Furthermore, we show how the WTI oil from the volatility transmitter (before the outbreak of the pandemic) becomes a risk receiver after the start of the global pandemic COVID-19. Our findings indicate that recent pandemic intensified volatility spillovers, supporting the financial contagion effects. Finally, we determine the optimal hedge ratios and portfolio weights. The estimates provided suggest the need for active portfolio management, taking into account the distinct characteristics of each sector and thus, the firm. For example, the optimal weight analysis shows how the clean sector has become important in optimal diversification strategies. Our results can be used for portfolio decisions and regulatory policymaking, particularly in the current context of high uncertainty.

scholarly journals RMB Exchange Rates and Volatility Spillover across Financial Markets in China and Japan

Risks ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 120 ◽  
Author(s):  
Fengming Qin ◽  
Junru Zhang ◽  
Zhaoyong Zhang
Keyword(s):  
Financial Markets ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Stock Markets ◽  
Spillover Effects ◽  
Policy Implications ◽  
Foreign Exchange Markets ◽  
Volatility Spillover ◽  
Exchange Markets ◽  
China And Japan

This study examines empirically the volatility spillover effects between the RMB foreign exchange markets and the stock markets by employing daily returns of the Chinese RMB exchange rates and the stock markets in China and Japan during the period in 1998–2018. We find evidence that there exist co-volatility effects among the financial markets in China and Japan, and the volatility of RMB exchange rates contribute to the co-volatility spillovers across the financial markets. Reversely, the return shock from the stock markets can also generate co-volatility spillover to the foreign exchange markets. The bidirectional relationship reveals that both the fundamental hypothesis and the investor-induced hypothesis are valid. Our estimates also show that the spillover effects led by the stock market in Japan are stronger than that from the foreign exchange markets and the Chinese stock markets, implying that market with higher accessibility has greater spillover effects onto other markets. We also found that the average co-volatility spillover effects among the RMB exchange markets and the stock markets in Japan and China are generally negative. These findings have important policy implications for risk management and hedging strategies.

scholarly journals Spillovers de Volatilidades Cambiais e de Mercados Financeiros Internacionais no Mercado Acionário Brasileiro

2018 ◽  
Vol 15 (4) ◽  
pp. 569
Author(s):  
Wendy Sidon Meira de Oliveira ◽  
André Nunes Maranhão
Keyword(s):  
Exchange Rate ◽  
Financial Markets ◽  
Financial Market ◽  
Temporal Dynamics ◽  
Granger Causality Test ◽  
Volatility Spillover ◽  
Causality Test ◽  
Conditional Correlations ◽  
Exchange Rate Shocks ◽  
Market Shocks

We present in this study the results of volatility spillover in the Brazilian stock market, measured by conditional correlations. Using GARCH multivariate conditional correlations were estimated at 3 different models combining the Ibovespa index of the three types of exchange rate shocks and a shock of international financial markets. The existence and direction of spillovers of volatility of forward exchange shocks, international financial market shocks and the Ibovespa were tested by Granger causality test of second order. The results show the existence of spillovers from exchange rate shocks and financial markets for the Ibovespa index, and these correlations have temporal dynamics, with spillovers always in the direction of the shocks to the Ibovespa index.

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