Intraday Volatility Spillovers among European Financial Markets during COVID-19

During crises, stock market volatility generally rises sharply, and as consequence, spillovers are identified across markets. This study estimates the volatility spillover among twelve European stock markets representing all four regions of Europe. The data consists of 10,990 intraday observations from 2 December 2019 to 29 May 2020. Using the methodology of Diebold and Yilmaz, we use static and rolling windows to characterize five-minute volatility spillovers. Our results show that 77.80% of intraday volatility forecast error variance in twelve European markets comes from spillovers. Furthermore, the highest gross directional volatility spillovers are found in Sweden and the Netherlands, while the minimum spillovers to other stock markets are observed in the stock markets of Poland and Ireland. However, German and Dutch markets transmit the highest net directional volatility spillovers. Splitting the whole sample in pre- and post-pandemic declaration (11 March 2020) we find more stable spillovers in the latter. The findings reveal important information about European stock market interdependence during COVID-19, which will be beneficial to both policy-makers and practitioners.

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Monetary Policy And Stock Returns: The Case Of Turkey

Journal of Applied Business Research (JABR) ◽

10.19030/jabr.v19i4.2188 ◽

2011 ◽

Vol 19 (4) ◽

Author(s):

Ramazan Sari ◽

Farooq Malik

Keyword(s):

Monetary Policy ◽

Stock Market ◽

Stock Returns ◽

Forecast Error ◽

Error Variance ◽

Forecast Errors ◽

Stock Market Volatility ◽

Font Size ◽

Significant Information ◽

Forecast Error Variance

This paper investigates how much of the variance in stock returns can be explained by monetary policy for the case of Turkey. We extend the work of Ewing (2001a) for the case of Turkey by using the newly developed generalized forecast error variance decomposition technique [Koop et al. (1996), Pesaran and Shin (1998)]. Results suggest that the growth rate of money supply contain significant information for predicting variance of future forecast errors of stock returns. The results provide information which is important for building accurate asset pricing models, forecasting future stock market volatility and furthers our understanding of stock market behavior in Turkey.

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Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

Journal of Risk and Financial Management ◽

10.3390/jrfm14030112 ◽

2021 ◽

Vol 14 (3) ◽

pp. 112

Author(s):

Kai Shi

Keyword(s):

Stock Market ◽

Frequency Band ◽

Stock Markets ◽

Emerging Market ◽

Low Frequency ◽

Systematic Risk ◽

Error Variance ◽

Frequency Bands ◽

Volatility Spillovers ◽

Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

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Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers

Financial Innovation ◽

10.1186/s40854-021-00228-2 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Syed Jawad Hussain Shahzad ◽

Elie Bouri ◽

Ladislav Kristoufek ◽

Tareq Saeed

Keyword(s):

Stock Market ◽

Network Structure ◽

Forecast Error ◽

Common Factor ◽

Error Variance ◽

Stock Market Index ◽

Vector Autoregressive ◽

The Us ◽

Market State ◽

Forecast Error Variance

AbstractThe aim of this study is to examine the extreme return spillovers among the US stock market sectors in the light of the COVID-19 outbreak. To this end, we extend the now-traditional Diebold-Yilmaz spillover index to the quantiles domain by building networks of generalized forecast error variance decomposition of a quantile vector autoregressive model specifically for extreme returns. Notably, we control for common movements by using the overall stock market index as a common factor for all sectors and uncover the effect of the COVID-19 outbreak on the dynamics of the network. The results show that the network structure and spillovers differ considerably with respect to the market state. During stable times, the network shows a nice sectoral clustering structure which, however, changes dramatically for both adverse and beneficial market conditions constituting a highly connected network structure. The pandemic period itself shows an interesting restructuring of the network as the dominant clusters become more tightly connected while the rest of the network remains well separated. The sectoral topology thus has not collapsed into a unified market during the pandemic.

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

Mathematics ◽

10.3390/math9111212 ◽

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.

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

Vision The Journal of Business Perspective ◽

10.1177/0972262921990981 ◽

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.

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The influence of economic policy uncertainty and geopolitical risk on US citizens overseas air passenger travel by regional destination

Tourism Economics ◽

10.1177/1354816620981199 ◽

2020 ◽

pp. 135481662098119

Author(s):

James E Payne ◽

Nicholas Apergis

Keyword(s):

Economic Policy ◽

Forecast Error ◽

Error Variance ◽

Variance Decomposition ◽

Air Travel ◽

Policy Uncertainty ◽

Economic Policy Uncertainty ◽

Passenger Travel ◽

Forecast Error Variance

This research note extends the literature on the role of economic policy uncertainty and geopolitical risk on US citizens overseas air travel through the examination of the forecast error variance decomposition of total overseas air travel and by regional destination. Our empirical findings indicate that across regional destinations, US economic policy uncertainty explains more of the forecast error variance of US overseas air travel, followed by geopolitical risk with global economic policy uncertainty explaining a much smaller percentage of the forecast error variance.

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Linkages between gold and emerging Asian stock markets: New evidence from the Chinese stock market crash

Studies of Applied Economics ◽

10.25115/eea.v39i2.3016 ◽

2021 ◽

Vol 39 (2) ◽

Author(s):

Imran Yousaf ◽

Shoaib Ali

Keyword(s):

Financial Crisis ◽

Stock Market ◽

Stock Markets ◽

Global Financial Crisis ◽

Chinese Stock Market ◽

Stock Market Crash ◽

Volatility Spillovers ◽

Hedge Ratios ◽

The Global Financial Crisis ◽

New Evidence

This study examines the return and volatility transmission between gold and nine emerging Asian Stock Markets during the global financial crisis and the Chinese stock market crash. We use the VAR-AGARCH model to estimate return and volatility spillovers over the period from January 2000 through June 30, 2018. The results reveal the substantial return and volatility spillovers between the gold and emerging Asian stock markets during the global financial crisis and the Chinese stock market crash. However, these return and volatility transmissions vary across the pairs of stock markets and the financial crises. Besides, we analyze the optimal portfolios and hedge ratios between gold and emerging Asian stock markets during all sample periods. Our findings have important implications for effective hedging and diversification strategies, asset pricing and risk management.

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Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM

Climate ◽

10.3390/cli9090144 ◽

2021 ◽

Vol 9 (9) ◽

pp. 144

Author(s):

Harleen Kaur ◽

Mohammad Afshar Alam ◽

Saleha Mariyam ◽

Bhavya Alankar ◽

Ritu Chauhan ◽

...

Keyword(s):

Water Management ◽

Short Term Memory ◽

Forecast Error ◽

Error Variance ◽

Water Levels ◽

Water Bodies ◽

Economic Activities ◽

Management Actions ◽

Forecast Error Variance ◽

Water Treatments

Recently, awareness about the significance of water management has risen as population growth and global warming increase, and economic activities and land use continue to stress our water resources. In addition, global water sustenance efforts are crippled by capital-intensive water treatments and water reclamation projects. In this paper, a study of water bodies to predict the amount of water in each water body using identifiable unique features and to assess the behavior of these features on others in the event of shock was undertaken. A comparative study, using a parametric model, was conducted among Vector Autoregression (VAR), the Vector Error Correction Model (VECM), and the Long Short-Term Memory (LSTM) model for determining the change in water level and water flow of water bodies. Besides, orthogonalized impulse responses (OIR) and forecast error variance decompositions (FEVD) explaining the evolution of water levels and flow rates, the study shows the significance of VAR/VECM models over LSTM. It was found that on some water bodies, the VAR model gave reliable results. In contrast, water bodies such as water springs gave mixed results of VAR/VECM.

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Oil Prices and the U.S. Dollar Exchange Rate: Evidence from the Monetary Model

Research in Applied Economics ◽

10.5296/rae.v10i4.14076 ◽

2018 ◽

Vol 10 (4) ◽

pp. 17

Author(s):

Moayad H. Al Rasasi

Keyword(s):

Exchange Rate ◽

Forecast Error ◽

Negative Relationship ◽

Impulse Response Function ◽

Decomposition Analysis ◽

Oil Prices ◽

Error Variance ◽

Monetary Model ◽

Forecast Error Variance ◽

Positive Shock

This paper analyzes how changes in global oil prices affect the US dollar (USD) exchange rate based on the monetary model of exchange rate. We find evidence indicating a negative relationship between oil prices and the USD exchange rate against 12 currencies. Specifically, the analysis of the impulse response function shows that the depreciation rate of the USD exchange rate ranges between 0.002 and 0.018 percentage points as a result of a one-standard deviation positive shock to the real price of crude oil. In the same vein, the forecast error variance decomposition analysis reveals that variation in the USD exchange rate is largely attributable to changes in the price of oil rather than monetary fundamentals. In last, the out-of-sample forecast exercise indicates that oil prices enhance the predictability power of the monetary model of exchange rate.

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KAJIAN AKTIVITAS EKONOMI LUAR NEGERI INDONESIA TERHADAP PERTUMBUHAN EKONOMI INDONESIA PERIODE 1998-2014

MEDIA STATISTIKA ◽

10.14710/medstat.9.2.119-132 ◽

2017 ◽

Vol 9 (2) ◽

pp. 119

Author(s):

Ryan Hawari ◽

Fitri Kartiasih

Keyword(s):

Economic Growth ◽

Foreign Direct Investment ◽

Exchange Rate ◽

Direct Investment ◽

Forecast Error ◽

Foreign Debt ◽

Trade Openness ◽

Impulse Response Function ◽

Error Variance ◽

Forecast Error Variance

Indonesia is a developing country which adopts an “open economic”. That caused Indonesia economic is strongly influenced by factors that come from outside of Indonesia. External factors in this research is referred to foreign debt, foreign direct investment, trade openness and exchange rate of rupiah with USD. The analytical method in this research used Vector Error Correction Model (VECM) which will focused on Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD). Based on result of IRF, exchange rate had a positive effect to economic growth, while foreign debt, foreign direct investment and trade openness had a negative effect to economic growth. Based on result of FEVD, shock on economic growth in Indonesia affected by economic growth itself (43.21%), followed by foreign debt (26.30%), trade openness (14.16%), foreign direct investment (8.29%) and exchange rate (8.04%) Keywords: economic growth, trade openness, VECM, IRF, FEVD

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