scholarly journals Market Volatility and Causal Relationship among BRICS Stock Markets

2021 ◽  
Vol 42 (3) ◽  
pp. 1-14
Author(s):  
Soumya Ganguly ◽  
Amalendu Bhunia
Keyword(s):  
Causal Relationship ◽  
Stock Markets ◽  
Market Volatility

scholarly journals Volatility Modeling: An Overview of Equity Markets in the Euro Area during COVID-19 Pandemic

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1212
Author(s):  
Pierdomenico Duttilo ◽  
Stefano Antonio Gattone ◽  
Tonio Di Di Battista
Keyword(s):  
Stock Market ◽  
Euro Area ◽  
Risk Premium ◽  
Stock Markets ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Volatility Modeling ◽  
The Impact ◽  
Second Wave ◽  
Daily Returns

Volatility is the most widespread measure of risk. Volatility modeling allows investors to capture potential losses and investment opportunities. This work aims to examine the impact of the two waves of COVID-19 infections on the return and volatility of the stock market indices of the euro area countries. The study also focuses on other important aspects such as time-varying risk premium and leverage effect. This investigation employed the Threshold GARCH(1,1)-in-Mean model with exogenous dummy variables. Daily returns of the euro area stock markets indices from 4th January 2016 to 31st December 2020 has been used for the analysis. The results reveal that euro area stock markets respond differently to the COVID-19 pandemic. Specifically, the first wave of COVID-19 infections had a notable impact on stock market volatility of euro area countries with middle-large financial centres while the second wave had a significant impact only on stock market volatility of Belgium.

Do Lower Foreign Flows and Higher Domestic Flows Reduce Indian Equity Market Volatility?

2021 ◽  
pp. 097226292199098
Author(s):  
Vaibhav Aggarwal ◽  
Adesh Doifode ◽  
Mrityunjay Kumar Tiwary
Keyword(s):  
Stock Market ◽  
Mutual Fund ◽  
Stock Markets ◽  
Large Scale ◽  
Structural Changes ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Equity Investments ◽  
Net Equity ◽  
Indian Stock Market

This study examines the relationship that both domestic and foreign institutional net equity flows have with the India stock markets. The motivation behind is the study to examine whether increased net equity investments from domestic institutional investors has reduced the influence of foreign equity flows on the Indian stock market volatility. Our results indicate that only during periods in which domestic equity inflows surpass foreign flows by a significant margin, as seen during 2015–2018, is the Indian stock market volatility not significantly influenced by foreign equity investments. However, during periods of re-emergence of strong foreign net inflows, the Indian market volatility is still being impacted significantly, as has been observed since 2019. Furthermore, we find that both large-scale net buying and net selling by domestic funds increased the stock market volatility as observed during 2015–2018 and COVID-impacted year 2020 respectively. The implications of this study are multi-fold. First, the regulators should discuss with industry bodies before enforcing major structural changes like reconstituting of mutual fund investment mandate in 2017 which forced domestic funds to quickly change portfolio allocation amongst large-cap, mid-cap and small-cap stocks resulting in higher stock market volatility. Second, adequate investor educational and awareness programmes need to be conducted regularly for retail investors to minimize herd behaviour of investing during market rise and heavy redemptions at times of fall. Third, the economic policies should be stable and forward-looking to ensure foreign investors remain attracted to the Indian stock markets at all times.

scholarly journals Agricultural Commodity Trading: Is it Destabilizing Spot Markets?

2018 ◽  
Vol 43 (1) ◽  
pp. 47-57 ◽  
Author(s):  
C. P. Gupta ◽  
Sanjay Sehgal ◽  
Sahaj Wadhwa
Keyword(s):  
Causal Relationship ◽  
Trading Volume ◽  
Spot Market ◽  
Market Volatility ◽  
Future Market ◽  
Soy Oil ◽  
Open Interest ◽  
Future Trading ◽  
The Future ◽  
Spot Volatility

Executive Summary The future trading has been held responsible by certain political and interest groups of enhancing speculative trading activities and causing volatility in the spot market, thereby further spiralling up inflation. This study examines the effect of future of trading activity on spot market volatility. The study first determined the Granger causal relationship between unexpected future trading volume and spot market volatility. It then examined the Granger causal relationship between unexpected open interest and spot market volatility. The spot volatility and liquidity was modelled using EGARCH and unexpected trading volume. The expected trading volume and open interest was calculated by using the 21-day moving average, and the difference between actual and expected component was treated as the unexpected trading volume and unexpected open interest. Empirical results confirm that for chickpeas ( channa), cluster bean ( guar seed), pepper, refined soy oil, and wheat, the future (unexpected) liquidity leads spot market volatility. The causal relationship implies that trading volume, which is a proxy for speculators and day traders, is dominant in the future market and leads volatility in the spot market. The results are in conformity with earlier empirical findings — Yang, Balyeat and Leathan (2005) and Nath and Lingareddy (2008) —that future trading destabilizes the spot market for agricultural commodities. Results show that there is no causal relationship between future open interest and spot volatility for all commodities except refined soy oil and wheat. The findings imply that open interest, which is a proxy of hedging activity, is leading to volatility in spot market for refined soy oil and wheat. The results are in conformity to earlier empirical studies that there is a weak causal feedback between future unexpected open interest and volatility in spot market ( Yang et al., 2005 ). For chickpeas (channa), the increase in volatility in the spot market increases trading activity in the future market. The findings are contrary to earlier empirical evidence ( Chatrath, Ramchander, & Song, 1996 ; Yang et al., 2005 ) that increase in spot volatility reduces future trading activity. However, they are in conformity to Chen, Cuny and Haugen (1995) that increase in spot volatility increases future open interest. The results reveal that the future market has been unable to engage sufficient hedging activity. Thereby, a causal relationship exists only for future trading volume and spot volatility, and not for future open interest and spot volatility. The results have major implications for policymakers, investment managers, and for researchers as well. The study contributes to literature on price discovery, spillovers, and price destabilization for Indian commodity markets.

LOW-FREQUENCY VOLATILITY AND MACROECONOMIC DYNAMICS: CONVENTIONAL VERSUS ISLAMIC STOCK MARKETS

2020 ◽  
pp. 1-28 ◽  
Author(s):  
HONG-BAE KIM ◽  
A.S.M. SOHEL AZAD
Keyword(s):  
Interest Rates ◽  
Stock Markets ◽  
Low Frequency ◽  
Frequency Component ◽  
Market Volatility ◽  
Macroeconomic Dynamics ◽  
Macroeconomic Factors ◽  
Macroeconomic Risk ◽  
Islamic Countries ◽  
The Relationship

This study investigates the relationship between macroeconomic risk and low-frequency volatility of conventional and Islamic stock markets from around the world. Using a panel of 36 countries, representing developed, emerging and Islamic countries for the period from 2000 to 2016, the study finds that low-frequency market volatility is lower for Islamic countries and, markets with more number of listed companies, higher market capitalization relative to GDP and larger variability in industrial production. The study also finds that low-frequency component of volatility is greater when the macroeconomic factors of GDP, unemployment, short-term interest rates, inflation, money supply and foreign exchange rates are more volatile. The empirical results are robust to various alternative specifications and split sample analyses. The findings imply that religiosity has an influence on the correction of market volatility and investors may consider the Islamic stocks to diversify their risks.

scholarly journals Opportunity or Crisis? Volatility and Leverage Effect in the World’s Largest Economies

2019 ◽  
Vol 9 (4) ◽  
pp. 1
Author(s):  
Amalendu Bhunia ◽  
Devrim Yaman
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Market Volatility ◽  
Future Market ◽  
Market Returns ◽  
Stock Market Returns ◽  
The Us ◽  
The World ◽  
The Impact ◽  
The Relationship

This paper examines the relationship between asset volatility and leverage for the three largest economies (based on purchasing power parity) in the world; US, China, and India. Collectively, these economies represent Int$56,269 billion of economic power, making it important to understand the relationship among these economies that provide valuable investment opportunities for investors. We focus on a volatile period in economic history starting in 1997 when the Asian financial crisis began. Using autoregressive models, we find that Chinese stock markets have the highest volatility among the three stock markets while the US stock market has the highest average returns. The Chinese market is less efficient than the US and Indian stock markets since the impact of new information takes longer to be reflected in stock prices. Our results show that the unconditional correlation among these stock markets is significant and positive although the correlation values are low in magnitude. We also find that past market volatility is a good indicator of future market volatility in our sample. The results show that positive stock market returns result in lower volatility compared to negative stock market returns. These results demonstrate that the largest economies of the world are highly integrated and investors should consider volatility and leverage besides returns when investing in these countries.

scholarly journals Impact of news-based equity market volatility on international stock markets

2020 ◽  
Vol 23 (1) ◽  
pp. 224-234
Author(s):  
Abdullah Alqahtani ◽  
Michael J. Wither ◽  
Zhankui Dong ◽  
Kimberly R. Goodwin
Keyword(s):  
Stock Markets ◽  
Equity Market ◽  
Market Volatility ◽  
International Stock Markets

Forecasting Stock Market Volatility: Evidence from Six Emerging Markets

2013 ◽  
Vol 14 (2) ◽  
pp. 68-93
Author(s):  
Naliniprava Tripathy ◽  
Ashish Garg
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Stock Price ◽  
Market Volatility ◽  
Future Market ◽  
Investment Strategies ◽  
Stock Market Volatility ◽  
Efficient Management ◽  
Asymmetric Garch

This paper forecasts the stock market volatility of six emerging countries by using daily observations of indices over the period of January 1999 to May 2010 by using ARCH, GARCH, GARCH-M, EGARCH and TGARCH models. The study reveals the positive relationship between stock return and risk only in Brazilian stock market. The analysis exhibits that the volatility shocks are quite persistent in all country’s stock market. Further the asymmetric GARCH models find a significant evidence of asymmetry in stock returns in all six country’s stock markets. This study confirms the presence of leverage effect in the returns series and indicates that bad news generate more impact on the volatility of the stock price in the market. The study concludes that volatility increases disproportionately with negative shocks in stock returns. Hence investors are advised to use investment strategies by analyzing recent and historical news and forecast the future market movement while selecting portfolio for efficient management of financial risks to reap benefits in the stock markets.

CAUSAL LINKAGES AMONG SHANGHAI, SHENZHEN, AND HONG KONG STOCK MARKETS

2004 ◽  
Vol 07 (02) ◽  
pp. 135-149 ◽  
Author(s):  
HONGQUAN ZHU ◽  
ZUDI LU ◽  
SHOUYANG WANG ◽  
ABDOL S. SOOFI
Keyword(s):  
Hong Kong ◽  
Error Correction ◽  
Causal Relationship ◽  
Positive Feedback ◽  
Stock Markets ◽  
Composite Index ◽  
Stock Index ◽  
Error Correction Models

In this paper, we test for causal relationship between China's stock markets by using returns and a measure of volatility for the Shanghai Composite index, the Shenzhen Composite Subindex, and the Hong Kong Hang Seng Index. We also show that the stock index series are nonstationary and that cointegrating vectors and error correction models do not exist for the series. Based on these tests, for the return series, we conclude that Shenzhen Granger caused Shanghai before 1994. For the volatility data, we find that there exists a positive feedback relationship between Shanghai and Shenzhen stock markets, and that Hong Kong volatility Granger causes Shanghai volatility, but not vice versa.

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