Petroleum prices and equity sector returns in petroleum exporting and importing countries: an analysis of volatility transmissions and hedging

This study scrutinizes the day-of-the-week effect anomaly in the context of market and industry analysis of the Pakistan stock exchange. For this purpose, daily closing prices of KSE-100, KSE-30, and KSE-All Share Index from January 01, 2009 to December 31, 2018, have been used. Similarly, sector returns are also calculated, taking average log-returns of selected sample firms. To analyze the data ordinary least squares (OLS) regression, general generalized autoregressive conditional heteroscedasticity (GARCH) (1,1) as well as asymmetric threshold GARCH (TGARCH) and exponential GARCH (EGARCH) models have been employed to model the leverage effect of good and bad news on market volatility. The results indicate the evidence of daily seasonality, with significant Monday and Wednesday effect in PSX indices returns as well as in most of the industry returns. Monday is found to be the day with the highest average returns with the highest return volatility. The findings of the study reveal that there exists a weak form of inefficiency in the Pakistan Stock Market, which implies the possibility of earning abnormal returns by investors using timing strategies. In terms of return predictability, this study is essential for international and domestic investors and it may affect their investment strategy and return management. The results might be interesting to the financial experts as they ponder the available conditions in the capital market for financial decision-making. This study is one of its first kind that includes both indices as well as industry returns for analysis of manufacturing industries in Pakistan stock exchange.

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Do Country Risks Matter for Tourism Development? International Evidence

Journal of Travel Research ◽

10.1177/0047287520954539 ◽

2020 ◽

pp. 004728752095453 ◽

Cited By ~ 1

Author(s):

Chien-Chiang Lee ◽

Mei-Ping Chen

Keyword(s):

Financial Stability ◽

Tourism Development ◽

Country Risk ◽

Global Perspective ◽

International Tourism ◽

Method Of Moment ◽

Policy Makers ◽

International Evidence ◽

International Tourist ◽

Sector Returns

This research fills the gap in the tourism literature on the impacts of country stability—including political, financial, and economic—on tourism development (i.e., international tourist arrivals, international tourism revenues, and travel and leisure sector returns). To account for possible asymmetric and nonlinear relationships among variables, we apply a new method of moment quantile regression, by using panel data from 106 countries spanning the period 2006–2017. From a global perspective, the empirical results indicate that higher country stability generally leads to higher tourism development, while there is no salient influence of financial stability on travel and leisure sector returns. This suggests that the effects of country risk ratings are mostly nonlinear across different tourism development quantiles. Additionally, different components of risk rating scores have diverse impacts on tourism development. The findings mean that policy makers should consider their tourism condition when setting country stability strategies.

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What Affects the Relationships between Oil and Industrial Sector? Case of Eurozone

International Journal of Economics and Finance ◽

10.5539/ijef.v9n9p52 ◽

2017 ◽

Vol 9 (9) ◽

pp. 52

Author(s):

Melik Kamisli ◽

Serap Kamisli ◽

Fatih Temizel ◽

Ethem Esen

Keyword(s):

Structural Breaks ◽

Credit Rating ◽

Debt Crisis ◽

Strong Relationship ◽

Industrial Sector ◽

Oil Price ◽

Production Costs ◽

Cost Item ◽

Economic Developments ◽

Sector Returns

Oil, which is one of the fundamental energy sources, is an important cost item especially for industrial sector. Increases in oil prices decrease the profits of the firms by causing increase in the production costs. For this reason, it is claimed that there is a strong relationship between oil price and industrial sector profitability. On the other hand, oil is an alternative investment vehicle that can be included to the portfolio. Therefore, in this study the relationships between oil price and industrial sector returns of European countries are analyzed with Maki (2012) cointegration test under multiple structural breaks, on the basis of European Debt Crisis. The results show that announcements of credit rating agencies, elections, resignations, announcements of European Central Bank and IMF, recovery packages and economic developments cause structural breaks in relationships. Results also indicate that there is no cointegration between oil price and industrial sector returns of Austria, Belgium and Holland.

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Long-term prior return patterns in stock and sector returns in India

Journal of Advances in Management Research ◽

10.1108/jamr-02-2012-0002 ◽

2014 ◽

Vol 11 (2) ◽

pp. 192-210

Author(s):

Sanjay Sehgal ◽

Sakshi Jain

Keyword(s):

Asset Pricing ◽

Stock Returns ◽

Risk Model ◽

Factor Model ◽

Size Factor ◽

Content Type ◽

Long Run ◽

Portfolio Managers ◽

Sector Returns

Purpose – The purpose of this paper is to analyze long-term prior return patterns in stock returns for India. Design/methodology/approach – The methodology involves portfolio generation based on company characteristics and long-term prior return (24-60 months). The characteristic sorted portfolios are then regressed on risk factors using one factor (capital asset pricing model (CAPM)) and multi-factor model (Fama-French (FF) model and four factor model involving three FF factors and an additional sectoral momentum factor). Findings – After controlling for short-term momentum (up to 12 months) as documented by Sehgal and Jain (2011), the authors observe that weak reversals emerge for the sample stocks. The risk model CAPM fails to account for these long-run prior return patterns. FF three-factor model is able to explain long-term prior return patterns in stock returns with the exception of 36-12-12 strategy. The value factor plays an important role while the size factor does not explain cross-section of average returns. Momentum patterns exist in long-term sector returns, which are stronger for long-term portfolio formation periods. Further, the authors construct sector factor and observe that prior returns patterns in stock returns are partially absorbed by this factor. Research limitations/implications – The findings are relevant for investment analysts and portfolio managers who are continuously tracking global markets, including India, in pursuit of extra normal returns. Originality/value – The study contributes to the asset pricing and behavioral literature from emerging markets.

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NYSE Sector Returns and Political Cycles

Journal of Business Ethics ◽

10.1023/b:busi.0000020873.62435.f5 ◽

2004 ◽

Vol 49 (4) ◽

pp. 387-395 ◽

Cited By ~ 3

Author(s):

R. Bruce Swensen ◽

Jayen B. Patel

Keyword(s):

Political Cycles ◽

Sector Returns

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Does the BEYR help predict UK sector returns?

Journal of Asset Management ◽

10.1057/jam.2011.3 ◽

2011 ◽

Vol 12 (2) ◽

pp. 146-156 ◽

Cited By ~ 1

Author(s):

David G McMillan

Keyword(s):

Sector Returns

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Market fear, investor mood, sentiment, economic uncertainty and tourism sector in the United States amid COVID-19 pandemic: A spillover analysis

Tourism Economics ◽

10.1177/13548166211052803 ◽

2021 ◽

pp. 135481662110528

Author(s):

Faisal Nazir Zargar ◽

Dilip Kumar

Keyword(s):

Media Coverage ◽

Spillover Effects ◽

The United States ◽

Equity Market ◽

Market Volatility ◽

Economic Uncertainty ◽

Tourism Sector ◽

The Us ◽

Media Hype ◽

Sector Returns

The study investigates and confirms the spillover effects from investor fear, mood, sentiment and uncertainty to the US tourism sector returns. The findings indicate that market fear, investor mood and sentiment are net transmitter of shocks and economic uncertainty and the tourism sector is net receiver of shocks. We also provide evidence that media-hype, infodemic, media-coverage related to COVID-19 and infectious disease equity market volatility impacts the total and directional spillover of information from fear, mood, sentiment and uncertainty to the tourism sector.

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Cross-Sector Style Analysis Of Global Equities Based On The Fama And French Three-Factor Model

International Business & Economics Research Journal (IBER) ◽

10.19030/iber.v11i2.7156 ◽

2012 ◽

Vol 11 (2) ◽

pp. 161

Author(s):

Heng-Hsing Hsieh ◽

Kathleen Hodnett

Keyword(s):

Portfolio Management ◽

Risk Premium ◽

Factor Model ◽

Statistical Significance ◽

Abnormal Returns ◽

Risk Premiums ◽

Portfolio Returns ◽

Fama And French ◽

Resource Sector ◽

Sector Returns

Although the ability of the Fama and French (1993) 3-factor model in explaining style-based portfolio returns have been widely tested, no such test has been conducted on sector-based portfolios. The study conducted by Hsieh and Hodnett (2011) indicate that the resource sector yields significant abnormal returns under the capital asset pricing model (CAPM) over the period from 1999 to 2009. In addition, the book value-to-market ratio and market capitalization are found to have pervasive effects on the pricing of sector returns for global equities. Motivated by this insight, we undertake to test the ability of the Fama and French (1993) 3-factor model in explaining the variations in the global sector returns. Our test results indicate that the market risk premium is the most significant factor that drives the returns in all sectors under review. Although the positive abnormal returns of the resource sector dissipates under the 3-factor model, the industrial sector and the information technology (I.T.) sector yield abnormal returns under the 3-factor model. Unlike the empirical findings on the style portfolios, the signs and statistical significance of the exposures to the value and size risk premiums are not consistent across all sectors. This finding suggests that sector exposures are more unique and distinctive compared to the style portfolios. It could be argued that since most of the style portfolios are directly related to the value and size anomalies, any factor model that incorporates risk premiums on these anomalies would significantly explain the style portfolio returns. However, the ability of such factor model in explaining returns on portfolios formed using methodologies other than style anomalies, such as sector portfolio returns, would be questionable. Taking into account the rising global integration, sector allocation might be more effective in terms of global active portfolio management or international diversification than style allocation and country allocation.

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