scholarly journals Is the Alternative Energy Sector COVID-19 Resistant? Comparison with the Conventional Energy Sector: Markov-Switching Model Analysis of Stock Market Indices of Energy Companies

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 988
Author(s):  
Katarzyna Czech ◽  
Michał Wielechowski
Keyword(s):  
Stock Market ◽  
Alternative Energy ◽  
Markov Switching ◽  
Energy Sector ◽  
Energy Index ◽  
Markov Switching Model ◽  
Switching Model ◽  
The Government ◽  
Novel Coronavirus ◽  
The Impact

The outbreak and rapid spread of the COVID-19 pandemic has hit the global financial markets, including the energy sector. Alternative energy belongs to the economy’s key sectors concerning environmental issues and seems to be a full-fledged alternative for fossil-based conventional energy. This paper aims to assess the impact of COVID-19 on the stock market indices related to the alternative and conventional energy sector. We use daily data on the Morgan Stanley Capital International (MSCI) Global Alternative Energy Index, the MSCI All Country World Index (ACWI) Energy Index, and self-developed Average-49 COVID-19 New Cases Index and Average-49 Stringency Index. The research covers the period January–October 2020. The average level of the MSCI Global Alternative Energy Index in COVID-19 year was more than a quarter higher than in 2019 while the MSCI ACWI Energy fell almost one-third in the same period. Based on the Markov-switching model, we show that both the MSCI Global Alternative Energy and the MSCI ACWI Energy are not significantly affected by the epidemic status. The analysed indices decline as the government anti-COVID-19 policy becomes more stringent, but the relationship is statistically significant only in the high-volatility regime. In comparison to the conventional energy index, we reveal that the alternative energy index stays most of its time in the low-volatility regime without being adversely and significantly affected by the COVID-19 related indicators. Our study shows that the alternative energy sector, represented by the MSCI Global Alternative Energy Index, seems to be more resistant to COVID-19 than the conventional energy sector. It might imply that the novel coronavirus pandemic has not depreciated but emphasised the growing concern about climate change and environmental pollution.

Stock Market Volatility and Terrorism: New Evidence from the Markov Switching Model

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Faheem Aslam ◽  
Hyoung-Goo Kang ◽  
Khurrum Shahzad Mughal ◽  
Tahir Mumtaz Awan ◽  
Yasir Tariq Mohmand
Keyword(s):  
Stock Market ◽  
Significant Risk ◽  
Market Volatility ◽  
Terrorist Attacks ◽  
Stock Market Volatility ◽  
Markov Switching Model ◽  
Physical Damage ◽  
Stock Market Returns ◽  
Switching Model ◽  
The Impact

AbstractTerrorism in Pakistan poses a significant risk towards the lives of people by violent destruction and physical damage. In addition to human loss, such catastrophic activities also affect the financial markets. The purpose of this study is to examine the impact of terrorism on the volatility of the Pakistan stock market. The financial impact of 339 terrorist attacks for a period of 18 years (2000–2018) is estimated w.r.t. target type, days of the week, and surprise factor. Three important macroeconomic variables namely exchange rate, gold, and oil were also considered. The findings of the EGARCH (1, 1) model revealed that the terrorist attacks targeting the security forces and commercial facilities significantly increased the stock market volatility. The significant impact of terrorist attacks on Monday, Tuesday, and Thursday confirms the overreaction of investors to terrorist news. Furthermore, the results confirmed the negative linkage between the surprise factor and stock market returns. The findings of this study have significant implications for investors and policymakers.

scholarly journals Estimating the Peace Dividend: The Impact of Violence on House Prices in Northern Ireland

2012 ◽  
Vol 102 (2) ◽  
pp. 810-833 ◽  
Author(s):  
Timothy Besley ◽  
Hannes Mueller
Keyword(s):  
Northern Ireland ◽  
Negative Correlation ◽  
House Prices ◽  
Markov Switching ◽  
House Price ◽  
Markov Switching Model ◽  
Switching Model ◽  
Peace Dividend ◽  
The Impact ◽  
Over Time

This article exploits data on the pattern of violence across regions and over time to estimate the impact of the peace process in Northern Ireland on house prices. After establishing a negative correlation between killings and house prices, we estimate the parameters of a Markov switching model with conflict and peace as latent states. We use the model to estimate the size of the peace dividend as captured in house price changes. (JEL D74, R23, R31)

scholarly journals Impact of International Outsourcing on Domestic Wage of Singapore Manufacturing Sector

2017 ◽  
Vol 9 (6) ◽  
pp. 82
Author(s):  
Sandip Chakraborty ◽  
Ram Kumar Kakani ◽  
Bernadette C. Canasa
Keyword(s):  
Manufacturing Sector ◽  
Markov Switching ◽  
International Outsourcing ◽  
Markov Switching Model ◽  
Parametric Stability ◽  
Switching Model ◽  
The Impact

This study focuses on measuring the extent of international outsourcing across Singapore manufacturing sector and the impact on domestic wages of workers. Based on the framework of Feenstra and Hanson (1999), this study measured the narrow and wide outsourcing from the overseas intermediate imports. In estimating the impact of international outsourcing on wage, this study reviews the model developed by Geishecker and Görg (2008) and modifies the same by incorporating the parametric stability approach of Hamilton’s (1989) Markov Switching model. Results after incorporating the nonlinearity, indicates that outsourcing dynamics can be better understood through modified framework developed.

Impact of Central Bank Intervention during Periods of Speculative Pressure: Evidence from the European Monetary System

2007 ◽  
Vol 8 (3) ◽  
pp. 399-427 ◽  
Author(s):  
Helmut Stix
Keyword(s):  
Central Bank ◽  
Markov Switching ◽  
European Monetary System ◽  
Turbulent Regime ◽  
Markov Switching Model ◽  
European Monetary ◽  
Central Bank Intervention ◽  
Switching Model ◽  
Monetary System ◽  
The Impact

Abstract This paper studies the effects of Banco de Espanna and Banque de France interventions during the 1992-93 European Monetary System crises. In particular, a Markov Switching model is estimated where interventions influence the probabilities of transition between a calm and a turbulent regime. Furthermore, we analyze the impact of intervention on the expected rate of realignment. On balance, the results are consistent with the view that publicly known interventions but not secret interventions increased both the probability of switching to the turbulent regime as well as the expected realignment rate.

scholarly journals Mean reversion in a price-earnings ratio and under / overvaluation in the Brazilian stock market

2021 ◽  
Vol 32 (86) ◽  
pp. 301-313
Author(s):  
Daniel Penido de Lima Amorim ◽  
Marcos Antônio de Camargos
Keyword(s):  
Stock Market ◽  
Unit Root ◽  
Markov Switching ◽  
Mean Reversion ◽  
Markov Switching Model ◽  
Switching Model ◽  
Non Linear ◽  
Price Earnings Ratio ◽  
The Mean ◽  
Fourier Function

ABSTRACT The market price-earnings ratios differ from those of each share. Despite allowing for several pertinent analyses, authors have rarely addressed these valuation ratios in the Brazilian context. We can use it to evaluate whether the stock market is overvalued (undervalued). In this article, we analyze the mean reversion in a price-earnings ratio based on Ibovespa and identify periods of overvaluation (undervaluation) in the Brazilian stock market. We considered the period from December 2004 to June 2018. Until then, there are no studies that sought to identify periods of overvaluation (undervaluation) in this market. In the analyses, we used non-linear econometric methods. We analyzed the mean reversion in the price-earnings ratio using a unit root test that incorporates a Fourier function in the deterministic term. We identified the periods of market overvaluation (undervaluation) through the regime probabilities obtained from a Markov Switching model, estimated with the price-earnings ratio. The results evidenced that the price-earnings ratio based on the Ibovespa has a non-linear trend and exhibits mean reversion. Thus, this valuation ratio should provide information on the future stock market returns, mostly when it is very dispersed in relation to historical standards. We identified four periods of market overvaluation interposed with five periods of market undervaluation. Mean reversion in the price-earnings ratio contraposes the Efficient Markets Hypothesis. There are no other applications of unit root tests with a Fourier function in the Brazilian context. Furthermore, adopting a Markov Switching model to identify periods of market overvaluation (undervaluation) consists of a methodological contribution. Investors can take advantage of the identification of these periods to establish investment strategies.

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