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Smart War on COVID-19 and Global Pandemics
Published in Chhabi Rani Panigrahi, Bibudhendu Pati, Mamata Rath, Rajkumar Buyya, Computational Modeling and Data Analysis in COVID-19 Research, 2021
Anil D. Pathak, Debasis Saran, Sibani Mishra, Madapathi Hitesh, Sivaiah Bathula, Kisor K. Sahu
With the outbreak of COVID-19 and the consequent lockdown of billions of people around the world, the economies of many countries are going into recession. Due to the lack of demand and various supply chain constraints, this outbreak has spiraled into cascading economic disruptions across different continents. S&P, a major global rating agency, predicted a sharp contraction of 3.8% in the global growth for the year 2020 (Gruenwald 2020). In the United States, the unemployment rate as of July 2020 was at a multi-decade high of 10.2%, surpassing the previous record observations during the global financial crisis (GFC) with a shocking Q2 GDP contraction of 32.9% (Dock David Treece 2020; Duffin 2020). The GDP growth in India contracted to a multi-decade low of 23.9% in the first quarter of fiscal year 20–21 (Reuters 2020). India’s unemployment rate also touched more than 20% during the peak of the pandemic in April 2020 (CMIE Database 2020). China had reported severe contractions across different economic indicators such as Purchasing Managers’ Index (PMI) industrial output, fixed investment, and retail sales. VIX volatility index, a gauge for fear in US stock markets, reached its highest value since the global financial crisis during the crash and ultimately destabilized the global financial markets for a certain period of time. However, massive monetary interventions by central banks around the world and a historical low in ten-year US bond yields have contributed to a spectacular V shape recovery across major global stock indices, with S&P 500 so far witnessing a 53% rise from March lows.
System Dynamics and Synthetic Worlds
Published in C.A.P. Smith, Kenneth W. Kisiel, Jeffrey G. Morrison, Working Through Synthetic Worlds, 2009
Currently, we appear to be in the middle of economic turmoil after reaching a tipping-point in the global financial and banking system. According to Grynbaum (2008), the Volatility Index, VIX, illustrates the tipping point. The Volatility Index, VIX, is a popular measure of the implied volatility of McGraw-Hill Inc’s S&P 500® (also known as the Standard & Poor’s 500). As an indicator of collapse, the Standard & Poor’s 500 has extended its 2008 retreat to 39 percent and stands poised for its worst performance since 1931 (Stanton 2008).
Developing an early warning system for the shipping industry in Korea using two approaches
Published in Maritime Policy & Management, 2022
Sunghwa Park, Janghan Kwon, Taeil Kim
In the finance sector, the LIBOR interest rates, the VIX, the Dow Jones Industrial Average, and the Korean shipping stock index are included. The LIBOR interest rate is used to reflect the capital-intensive nature of the shipping industry as interest rates could affect cash-flow and liquidity problems for individual companies (Alexandridis et al. 2018). The VIX represents the volatility of the listed S&P 500 Index Options and is forward projected for 30 days. The VIX is used as a proxy variable for macroeconomic uncertainty in many studies (Bloom 2009; Baker, Bloom, and Davis 2016). During periods in which economic uncertainty increases, economic agents postpone decisions and tend to wait until the uncertainty is resolved (Bloom 2009). This ‘wait-and-see’ behavior can be found in the shipping market by observing the impact of an uncertainty shock. In a situation of heightened uncertainty, shipowners tend to postpone their newbuilding orders, since increased uncertainty can delay investment, especially when the capital stock is more irreversible (Fuss and Vermeulen 2008). Further, an uncertainty shock may reduce GDP growth, which is related to the demand of the shipping market.
An automated financial indices-processing scheme for classifying market liquidity regimes
Published in International Journal of Control, 2021
Xing Gu, Rogemar Mamon, Matt Davison, Hao Yu
The second key variable that we investigate is the volatility index (VIX). The Chicago Board Options Exchange (CBOE), defines it as an up-to-the-minute market estimate of expected volatility that is calculated based on real-time S&P 500 index option bid-ask quotes. More specifically, the VIX provides an instantaneous measure of the future degree of volatility and market uncertainty. The VIX has been utilised to gauge the level of investors' risk aversion or market sentiment; see Brunnermeier, Nagel, and Pedersen (2008) and Bekaert, Hoerova, and Duca (2013), and it has also a negative relation with stock returns as documented by Giot (2005) and Whaley (2009).