Oil, Oil Volatility and Airline Stocks: A Global Analysis

Nandha, Mohan; Brooks, Robert; Faff, Robert Article Oil, Oil Volatility and Airline Stocks: A Global Analysis Journal of Accounting and Management Information Systems (JAMIS) Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Nandha, Mohan; Brooks, Robert; Faff, Robert (2013) : Oil, Oil Volatility and Airline Stocks: A Global Analysis, Journal of Accounting and Management Information Systems (JAMIS), ISSN 2559-6004, Bucharest University of Economic Studies, Bucharest, Vol. 12, Iss. 2, pp. 302-318 This Version is available at: https://hdl.handle.net/10419/310527 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Accounting and Management Information Systems Vol. 12, No. 2, pp. 302–318, 2013 OIL, OIL VOLATILITY AND AIRLINE STOCKS: A GLOBAL ANALYSIS Mohan NANDHA 1 and Robert BROOKS Monash University, Australia Robert FAFF University of Queensland, Australia ABSTRACT By selecting a globally representative dataset of airline indices, this study demonstrates that oil price or oil price regimes (delineated by the first gulf war and the 9/11 terror attacks) alone do not have any significant implications for airline stock prices. Overall, these findings are contrary to the general perception that higher oil prices or oil volatility are bad news for the airlines industry. Perhaps airlines are in a better position to estimate their oil risk and take hedging positions as appropriate. However, airlines stocks appear to be significantly prone to the combined effects of oil volatility and oil regimes determined by the globally significant events/ shocks. Oil price, oil volatility, airlines, gulf war, 9/11 attacks JEL codes: G15, Q43 INTRODUCTION There is a widely held belief in the financial media that higher oil prices have an adverse impact on equity markets, and particularly on airline profitability and shares. For instance, news headlines such as ‘NWA stock sinks on oil-price surge’ 1 , ‘Airline industry optimism sapped by surging oil prices’ 2 , and ‘Airline shares surge as oil slips’ 3 , are indicative of this belief. Singapore Airlines 4 reported quarter (July-September, 2008) profit being 36 percent lower blaming fuel costs for increased expenditures. Dubai-based airline Emirates 5 reported an 88 percent fall in net profit compared in the same period and blamed steep fuel prices for dragging its profit down sharply in the six months through September, 2008. Emirate’s Chairman and Chief Executive (Sheik Ahmed bin Saeed al-Maktoum) said, "The first half of the year has been very tough for the airline industry, with record fuel 1 Correspondence address: Accounting and Finance, Monash University; PO Box 527, Frankston VIC Australia 3199; Phone: +613 9904 4610; Fax: +613 9904 4145; Email address: [email protected]  Oil, oil volatility and airline stocks: a global analysis Vol. 12, No. 2 303 prices forcing many carriers to shut shop or consolidate." In fact, the adverse impact of rising fuel price on airlines profitability and service demand is widespread and such views are supported by the International Air Transport Association (IATA) sources. In the words of Giovanni Bisignani, IATA’s Director General and CEO: ‘The situation remains bleak. The toxic combination of high oil prices and falling demand continues to poison the industry’s profitability’ (see IATA press release No. 41, 2008). Oil price fluctuations over recent years have attracted the attention of many scholars and a number of studies have explored the linkage between oil prices and equity returns. Collectively, these studies have covered almost every major market around the world and a representative sample, particularly of more recent times, include: Hammoudeh & Aleisa, 2004; Basher & Sadorsky, 2006; Park & Ratti, 2008; Miller & Ratti, 2009; Masih et al., 2013; Wang et al., 2013; Tsai, 2013; and Kumar & Maheswaran, 2013. 6 Hammoudeh and Aleisa (2004) discuss dynamic links among five (of six) oil rich GCC (Gulf Cooperation Council) markets and the NYMEX oil futures. Their findings suggest that the Saudi market has the most causal linkages with other GCC markets except Oman. Basher and Sadorsky (2006) examine stock returns in 21 emerging stock markets and their evidence indicates that oil price has an impact on stock price returns in emerging markets. Park and Ratti (2008) estimate the effects of oil price shocks and oil price volatility on the real stock returns of the US and 13 European countries and report that oil price shocks have a statistically significant impact on real stock returns. Findings of Miller and Ratti (2009) are supportive of a long-run relationship between the crude oil price and six OECD stock markets. Masih et al. (2013) explore the linkage between oil price volatility and stock returns in South Korea. Using a structural VAR analysis, Wang et al. (2013) examine the impact of oil price shocks on stock market returns, differentiating oil-importing vs. oil-exporting countries. Tsai (2013) investigates the asymmetric impact of monetary shocks on stock returns conditioned on high vs. non-high oil price events. In a framework combining GARCH and VAR, Kumar and Maheswaran (2013) examine return, volatility, upside/downside risk spillovers from crude oil prices to the major Indian industrial sectors. There appears to be a limited amount of literature specifically relating to the effects of oil prices on transportation shares, let alone airline shares. Some examples of studies which have at least a partial focus on transportation are: Faff & Brailsford, 1999; Hammoudeh & Li, 2005; and Nandha & Faff, 2008. Faff and Brailsford (1999) look at an Australian setting, identifying the impact of oil prices on various industry sectors including transport; Hammoudeh and Li (2005) consider the US transportation industry and Nandha and Faff (2008) visit the global scene as represented by the global transportation industry index. All these studies report a Accounting and Management Information Systems Vol. 12, No. 2 304 negative linkage between the oil price and transport sector stock returns. More recently, Nandha and Brooks (2009) show that oil prices play some role in determining the transport sector returns for the countries falling within the ‘Developed’, ‘Europe’ and ‘G7’ groupings. Surprisingly, studies covering airlines stocks appear to be non-existent. Perhaps this situation may be partly explained by the difficulty in isolating the oil price factor when there are a variety of factors affecting airline share prices. For instance, other factors might include: the effect of unforeseen events, such as the 9/11 attacks (Kim & Gu, 2004; and Drakos, 2004); changes in government regulations, such as deregulation (Hanna et al., 2005); increased use of jet fuel hedging to increase firm value (Carter et al., 2006); consumer experiences, both positive and negative (Luo, 2007); changed operational arrangements, such as code-sharing (Song et al., 2007); use of different business models (Flouris & Walker, 2007); and the amount of performance information available in inter-firm rivalry (Gong et al., 2008). According to Edelstein and Kilian (2007: 32): “It is widely believed that higher energy prices are associated with reduced consumer demand for airline travel between cities. Private (as opposed to business) airline travel often is a luxury which consumers are likely to forego when their purchasing power falls.” Further, Drakos (2004) suggests that the systematic risk of airline stocks has significantly increased since the terrorist incident of 9/11, and their evidence has wide implications for portfolio diversification. Our study contributes to the literature in the following ways. First, it aims to examine the linkages between the oil price and the airlines stocks which have been rarely covered in any previous study. Second, the impact of oil regimes described by the first Gulf War and 9/11 terror attacks is tested. Third, the selected dataset is of global nature including all the airlines for which data are available in the market. Fourth, this study is the first one which applies the GARCH-M approach to explore the linkage between oil price and stock markets. The remainder of this study is organized as follows: Section 1 provides a brief overview of the airline industry. The research method and hypotheses are outlined in Section 2. Empirical results are discussed in Section 3 and the last section provides some concluding comments. 1. OIL PRICE AND THE AIRLINE INDUSTRY In its International Energy Outlook report for the year 2008, the Energy Information Administration (EIA, 2008) identifies the transportation sector as being the major user of liquid energy (mainly oil and petroleum) between 2005 and 2030. The two primary contributing factors to this growth will be the continued demand for personal travel and the increase in freight transport, especially in the Oil, oil volatility and airline stocks: a global analysis Vol. 12, No. 2 305 non-OECD countries. While it is acknowledged that improvements in fuel efficiency will occur, it is still estimated that fuel use in this sector will grow by an overall average of 1.85 percent per year (EIA, 2008). The Report notes that air transport forms a significant part of this growth. The International Air Transport Association’s 2008 Annual Report (IATA, 2008) depicts a gloomy outlook for airlines and has predicted a significant decline in profitability and in many cases losses by the end of the year. This prediction was supported during the year in the US when at least three airlines, namely Skybus, Aloha and ATA, filed for bankruptcy. While each of these airlines had a different combination of factors leading to a bankruptcy situation, the fuel price was a common factor (Compart, 2008). No doubt, fuel cost is not the only factor impacting the airlines industry, it appears to be the foremost driver underlying the demise of various airlines. In 2000, the fuel bill constituted only 14.47% of total operating costs when the oil price was $30.33 (average for 2000) but this proportion jumped to more than double (31.70%) as the oil price crossed the $90 barrier in 2008. 7 It is worth mentioning that there are various types of jet fuel (airline fuel) and crude oil prices. These prices are closely linked and highly correlated. In a way they are inseparable and, thus, crude oil price is a true proxy for the airlines fuel cost. This study is based on West Texas Intermediate (WTI, also known as Texas Light Sweet) spot price as this is a type of oil used as a benchmark in oil pricing and most commonly mentioned in the media. Furthermore, WTI is also an underlying commodity for the New York Mercantile Exchange oil futures contracts. Historically, WTI oil price has nearly perfect correlation with other types of oil and jet fuel prices. 2. RESEARCH METHOD AND HYPOTHESIS DEVELOPMENT 2.1. Data Seeking to present global evidence of the oil price impact on airline stocks, we select all the major airlines from across the world. On the one hand, we wish to include as many airlines as possible, while on the other hand we wish to cover as lengthy a period as possible. To achieve both of these conflicting objectives, this study is based on two alternative samples of weekly data. Sample 1 covers a longer period (July 1989 to September 2008) but fails to include some important airline countries (e.g. Australia, China, Russia) as they are have a relatively short market history. Sample 2 covers a shorter period (October 1997 to September 2008). Airline stock returns are based on the total (i.e. inclusive of dividends) return country and regional airline indices sourced from the Datastream and expressed in US dollar terms. The market is represented by the world market index and oil price Accounting and Management Information Systems Vol. 12, No. 2 306 by the West Texas Intermediate spot in US dollar terms. Oil price returns and other return series are generated by taking log differences of consecutive index/price values. Oil volatility (OILVOL) is defined as conditional variance of oil price returns generated by a GARCH (1,1) process. Figure 1 presents a visual view of the oil price, oil volatility, oil price returns and the world airlines industry index. Figure 1. Oil price, oil volatility, oil price returns and the airlines industry index 0 20 40 60 80 100 120 140 160 90 92 94 96 9 8 00 02 0 4 06 0 8 OIL PRICE -.4 -.3 -.2 -.1 .0 .1 .2 .3 .4 90 9 2 94 9 6 98 00 02 04 06 0 8 O IL P R IC E R E T UR NS .000 .004 .008 .012 .016 .020 .024 .028 .032 90 92 94 96 9 8 00 02 0 4 06 0 8 O IL VO L A T IL IT Y 400 800 1200 1600 2000 2400 90 9 2 94 9 6 98 00 02 04 06 0 8 W O R L D A IR L INE S IND E X 9/1 1 Atta cks Gulf War Gulf War Gulf War Gulf War 9/1 1 Atta cks 9/1 1 Atta cks 9/1 1 Atta cks Notes: a. Gulf war indicates first Gulf war which started on January 17, 1991. b. 9/11 attacks indicate September 11, 2001 terror attacks in the US. c. Oil volatility is defined as conditional variance of oil price returns (log differences of oil prices) and generated by a GARCH (1,1) process. d. World airlines index represents Datastream World Airlines Industry index. 2.2. Model selection The financial literature is abundant with applications of conditional variance models which include the autoregressive conditional heteroskedastic (ARCH) model introduced by Engle (1982) and the generalised ARCH (GARCH) model developed by Bollerslev (1986). These models have been further extended and extensions like the ARCH and GARCH-in-mean (ARCH-M, GARCH-M) have been applied for studying stock markets. Relative strengths and superiority of these Oil, oil volatility and airline stocks: a global analysis Vol. 12, No. 2 307 models over basic ARCH/GARCH models are fully discussed in Engle et al. (1987). On the other hand, there are popular asset pricing theories such as the capital asset pricing model (CAPM) and arbitrage pricing theory (APT) which establishes a theoretical relationship between risk and excess return. Application of the ARCH-M/ GARCH-M methodology to the capital asset pricing framework is viewed as an improvement, particularly when the variance of asset returns is timevarying. For example, Elyasiani & Mansur (1998) and Faff et al. (2005) apply the GARCH-M method to investigate the impact of interest rate and its volatility on the banking and financial sector returns. Using a modified version of this model, the current study examines the impact of oil price and oil price volatility on airline stocks. Another important aspect is to account for oil price movements during events such as the first Gulf War and the 9/11 terrorist attacks in the US. When investigating five major oil shocks between 1973 and 2004, De Gregorio et al. (2007) find the 1991 shock (first Gulf War) to be the most transitory of them all. Events such as the 9/11 attacks also highlight the effect that an unforeseen event can have on airline stocks. Kim and Gu (2004) study the effect of these attacks on the return and risk profile of airline stocks. They find that the mean weekly return of airline stocks dropped but not to any level of statistical significance. However, the risk profiles increased thus putting pressure on airlines stocks. Airlines which managed to survive this period tended to have lower operating costs and a fuel hedging system in place. In addition, a reflection of Gulf war and 9/11 attacks on the oil markets and the airlines industry is also visible from graphs in Figure 1. The selected model allows for major shifts in oil prices due to events such as the Gulf War (January 17, 1991) and September 11, 2001 (9/11) terror attacks in the US. Formally, the model can be described by equations (1)-(5) as follows (adapted from Elyasiani & Mansur, 1998): tjtj tttttj h DoilDoiloilEMREAR ,, , )log(      1 3132121110 (1) 313 2121111 2 1 10 DOILVOL DOILVOLOILVOLhh t tttj tj tj        , , , (2) tOtt oiloil ,110    (3) 11 2 1,10   ttOt OILVOLbaaOILVOL  , (4) ),0(~ 1, tttO hN    and ),0(~ ,1, tjttj hN    ,j = 1,2, ……… n. (5) where, EARj is the excess return for airline j defined as log(Pt/ Pt-1) – WRf,t, Pt indicates price for the corresponding airline index at time t. Accounting and Management Information Systems Vol. 12, No. 2 308 WRf,t is the weekly risk free rate at time t calculated as: annualized US 3M treasury bill rate at time t x 7 / 36500; EMRt (excess market return at time t) is defined as: log(Mt / Mt-1 ) – WRf,t, Mt indicates market price represented by world market index; t OIL = change in oil price during time t = log(Oilt) – log( Oilt-1), Oilt indicates oil price at time t. D2 and D3 are oil price dummies aimed at capturing the Gulf War and September 11, 2001 (9/11) terror attacks in the US. To avoid the ‘dummy variable trap’, the pre-Gulf War period is captured as the base case rather than by another dummy D1, and the dummies D2 and D3 are defined as: D2 = 1 if January 17, 1991 <= TIME <= September 11, 2001; and = 0 otherwise. D3 = 1 if TIME >= September 12, 2001; and = 0 otherwise. OILVOLt (Oil volatility at time t) is defined as conditional variance of oil price change (log differences of oil prices) and generated by a GARCH (1,1) process. Following the practice in literature, the variance term is included in logarithmic form. However, unlike Elyasiani & Mansur (1998) and Faff et al. (2005), our model excludes lagged excess (airline) return and replaces it with EMR (excess market return) as an independent factor. The reasons for this modification are: first, the financial literature argues that stock market returns are independent and generated by a random process. Second, our empirical estimates 8 do not support an autoregressive component in the model. As indicated in the data section, this study examines two samples. Sample 1 covers a longer period (July 1989 to September 2008) but a smaller number of airlines. Sample 2 covers October 1997 to September 2008 but enables us to include airlines with a short market history. Considering that sample 2 does not have enough data for post Gulf War and pre September 11, 2001, the dummy D2 becomes irrelevant. Accordingly, the above mentioned model needs modification with equations (1) and (2) changed as follows: tjtjttttj hDoiloilEMREAR ,,13131110, )log(    (1*) 313111,1 2 1,10, DOILVOLOILVOLhh tttjtjtj    (2*) 2.3. Key research questions and hypothesis The key research questions in this study are aimed at examining the oil price and oil price volatility effects on airline stocks. These research questions and corresponding hypotheses are detailed in Table 1. Oil, oil volatility and airline stocks: a global analysis Vol. 12, No. 2 309 Table 1. Key research questions and hypothesis for samples 1 and 2 Research Question Null Hypothesis (Sample 1) Null Hypothesis (Sample 2) Q1: Are airline returns sensitive to oil price changes? 0: 11   a H 0: 211   b H 0: 311   c H 0: 1 * 1  a H 0: 31 * 1  b H Q2: Is the oil price sensitivity of airline stock returns affected by oil regimes described by globally significant events such as the gulf war and 9/11 terrorist attacks? 0: 22   a H 0: 32   b H 0: 322   c H 0: 3 * 2  H Q3: Does oil price volatility have any effect on airline stock risk? 0: 13   a H 0: 213   b H 0: 313   c H 0: 1 * 3  a H 0: 31 * 3  b H Q4: Is the effect of oil price volatility on airline stock risk affected by oil regimes described by globally significant events such as the gulf war and 9/11 terrorist attacks? 0: 24   a H 0: 34   b H 0: 324   c H 0: 3 * 4  H Q5: Can we dismiss the total effect of oil price on airline stock risk and return – either through oil price sensitivity or through oil price volatility? 0: 115   a H 0: 21215   b H 0: 31315   c H 0: 11 * 5  a H 0: 3131 * 5  b H Notes: a. Sample 1 covers July 1989 to September 2008 period and the corresponding parameter are described in equations 1 and 2: tjtj tttttj h DoilDoiloilEMREAR ,, , )log(      1 3132121110 313 2121111 2 1 10 DOILVOL DOILVOLOILVOLhh t tttj tj tj        , , , b. Sample 2 covers October 1997 to September 2008 period and the corresponding parameter are described in equations 1* and 2*: tjtjttttj hDoiloilEMREAR ,,13131110, )log(    313111,1 2 1,10, DOILVOLOILVOLhh tttjtjtj    Accounting and Management Information Systems Vol. 12, No. 2 316 Boyer, M.M. & Filion, D. (2007) “Common and fundamental factors in stock returns of Canadian oil and gas companies”, Energy Economics, 29: 428-453 Carter, D., Rogers, D. & Simkins, B. (2006) “Does Hedging Affect Firm Value? Evidence from the US Airline Industry”, Financial Management, 35: 53-86 Chen, N.-F., Roll, R. & Ross, S.A. (1986) “Economic forces and the stock market”, Journal of Business, 59: 383-403 Compart, A. (2008) “Free Fall”, Aviation Week & Space Technology, 168: 57-58 De Gregorio, J., Landerretche, O., Neilson, C., Broda, C. & Rigobon, R. (2007) “Another Pass-Through Bites the Dust? Oil Prices and Inflation/Comments”, Economia, 7: 155-196 Drakos, K. (2004) “Terrorism-induced structural shifts in financial risk: airline stocks in the aftermath of the September 11th terror attacks”, European Journal of Political Economy, 20: 435-446 Driesprong, G., Jacobsen, B. & Matt, B. (2008) “Striking oil: Another puzzle?”, Journal of Financial Economics, 89: 307-327 Edelstein, P. & Kilian, L. (2007) “Retail Energy Prices and Consumer Expenditures”, available online at http://sitemaker.umich.edu/pedelstein/ files/ek040707a.pdf (accessed on June 4, 2009) El-Sharif, I., Brown, D., Burton, B., Nixon, B. & Russell, A. (2005) “Evidence on the nature and extent of the relationship between oil prices and equity values in the UK”, Energy Economics, 27: 819-830 Elyasiani, E. & I. Mansur (1998) “Sensitivity of the Bank Stock Returns Distribution to Changes in the Level and Volatility of Interest Rates: A GARCH-M Model”, Journal of Banking and Finance, 22: 535–63 EIA (2008) International Energy Outlook - 2008, Energy Information Agency report DOE/EIA-0484(2008), available online at http://www.eia.doe.gov/ oiaf/ieo/pdf/0484(2008).pdf (accessed on June 4, 2009) Engle, R.F. (1982) “Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation”, Econometrica, 50: 987-1007 Engle, R.F., Lilien, D.M. & Robins, R.P. (1987) “Estimating time varying risk premia in the term structure: The ARCH-M model”, Econometrica, 55: 391-407 Faff, R. & Brailsford, T. (1999) “Oil price risk and the Australian stock market”, Journal of Energy Finance & Development, 4: 69–87 Faff, R., Hodgson, A. & Kremmer, M. (2005) “An Investigation of the Impact of Interest Rates and Interest Rate Volatility on Australian Financial Sector Stock Return Distributions”, Journal of Business Finance & Accounting, 32: 1001-1031 Flouris, T. & Walker, T. (2007) “Financial Comparisons Across Different Business Models In The Canadian Airline Industry”, Journal of Air Transportation, 12: 25-52 Gisser, M. & Goodwin, T. (1986) “Crude Oil and the Macroeconomy: Tests of Some Popular Notions”, Journal of Money, Credit, and Banking, 18: 95–103 Oil, oil volatility and airline stocks: a global analysis Vol. 12, No. 2 317 Gong, S., Firth, M. & Cullinane, K. (2008) “International oligopoly and stock market linkages: The case of global airlines”, Transportation Research. Part E, Logistics & Transportation Review, 44:621-636 Hamilton, J. (1983) “Oil and macro-economy since World War II”, Journal of Political Economy, 91: 228-248 Hamilton, J. (2009) “Understanding crude oil prices”, The Energy Journal, 30: 179-206 Hammoudeh, S. & Aleisa, E. (2004) “Dynamic Relationships among the GCC Stock Markets and NYMEX Oil Futures”, Contemporary Economic Policy, 22: 250-269 Hammoudeh, S. & Choi, K. (2007) “Characteristics of permanent and transitory returns in oil-sensitive emerging stock markets: The case of GCC countries”, Journal of International Financial Markets, Institutions and Money, 17: 231-245 Hammoudeh, S. & Li, H. (2005) “Oil sensitivity and systematic risk in oil-sensitive stock indices”, Journal of Economics and Business, 57: 1-21 Hanna, J., Kunkel, R., Kuhlemeyer, G. & Johnson, R. (2005) “The Immediate Financial Impact Of Transportation Deregulation On The Stockholders Of The Airline Industry”, Journal of Air Transportation, 10: 83-95 Huang, R. D., Masulis, R. W. & Stoll, H.R. (1996) “Energy shocks and financial markets”, Journal of Futures Markets, 16: 1-27 Huang, B-N, Hwang, M.J. & Peng, H-P. (2005) “The asymmetry of the impact of oil price shocks on economic activities: An application of the multivariate threshold model”, Energy Economics, 27: 455-476 IATA Annual Report (2008) International Air Transport Association’s Annual Report for 2008, available online at: http://www.iata.org/NR/rdonlyres/ 84158349-7772-4892-86AB836DE73E0A52/0/IATAAnnualReport2008.pdf IATA Press Release No. 41 (2008, Sept 3) Airlines to lose US$5.2 billion in 2008 - Slowing Demand and High Oil to Blame, available online at: http://www.iata.org/pressroom/pr/2008-09-03-01.htm Jones, C. & Kaul, G. (1996) “Oil and the stock markets”, Journal of Finance, 51: 463–491 Kim, H. & Gu, Z. (2004) “Impact of the 9/11 terrorist attacks on the return and risk of airline stocks”, Tourism & Hospitality Research, 5: 150-163 Kumar, D. & Maheswaran, S. (2013) “Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors”, The Journal of Applied Economic Research, 7: 61-91 Luo, X. (2007) “Consumer Negative Voice and Firm-Idiosyncratic Stock Returns”, Journal of Marketing, 71: 75-88 Masih, R., Peters, S. & De Mello, L. (2011) “Oil price volatility and stock price fluctuations in an emerging market: Evidence from South Korea”, Energy Economics, 33: 975-986 Accounting and Management Information Systems Vol. 12, No. 2 318 Masseron, J. (1992) “Impacts of the Gulf War and Changes in Eastern Europe”, Energy Journal, 13: 1-16 Miller, J.I. & Ratti, R.A. (2009) “Crude oil and stock markets: Stability, instability, and bubbles”, Energy Economics, 31: 559-568 Nandha, M. & Brooks, R. (2009) “Oil prices and transport sector returns: an international analysis”, Review of Quantitative Finance and Accounting, 33: 393-409 Nandha, M. & Faff, R. (2005) “Impact of oil price on stock market returns: Evidence from South Asian markets”, The ICFAI Journal of Applied Finance 2: 5-20 Nandha, M. & Faff, R. (2008) “Does oil move equity prices? A global view”, Energy Economics, 30: 986-997 Park, J. & Ratti, R.A. (2008) “Oil price shocks and stock markets in the U.S. and 13 European countries”, Energy Economics, 30: 2587–2608 Papapetrou, E. (2001) “Oil price shocks, stock markets, economic activity and employment in Greece”, Energy Economics, 23: 511-532 Sadorsky, P. (1999) “Oil price shocks and stock market activity”, Energy Economics, 21: 5,449-469 Song, Y., Woo, W. & Rao, H. (2007) “Interorganizational information sharing in the airline industry: An analysis of stock market responses to code-sharing agreements”, Information Systems Frontiers, 9(2-3): 309-324 Tsai, C. (2013) “The high-frequency asymmetric response of stock returns to monetary policy for high oil price events”, Energy Economics, 36: 166-176 Wang, Y., Wu, C. & Yang, L. (2013) “Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries”, Journal of Comparative Economics, forthcoming Yamani, A. (1991) “The Gulf crisis: Oil fundamentals, market perceptions and political realities”, Energy Journal, 12 (2): 1-7 1 Full news at: www.entrepreneur.com/localnews/1570599.html 2 Full news at: www.usatoday.com/travel/flights/2007-07-31-airline-fuel-costs_N.htm 3 Full news at: www.reuters.com/article/hotStocksNews/idUSN2365172520080123?sp=true 4 Details at: www.bloomberg.com/apps/news?pid=20601080&sid=aLqNP2E8LIQQ&refer=asia 5 Details at: www.iht.com/articles/ap/2008/11/10/business/ML-Dubai-Earns-Emirates.php 6 In addition, there are various other studies focused on the linkage between the oil price and stock markets. For example, Hamilton (1983); Chen et al. (1986); Gisser & Goodwin (1986); Al-Mudhaf and Goodwin (1993); Huang et al. (1996); Jones & Kaul (1996); Sadorsky (1999); Papapetrou (2001); El-Sharif et al. (2005); Huang et al. (2005); Nandha and Faff (2005); Boyer and Filion (2007); Hammoudeh and Choi (2007); Driesprong et al. (2008); and Hamilton (2009). These studies cover stock markets from all over the world and offer variety in their datasets, research methods and conclusions. 7 Source: icao / iata. As reported in the financial forecast (March, 2009) briefing note on the IATA website (accessed on May 29, 2009): www.iata.org/economics 8 Initially, results were estimated by including lagged EAR for all airlines, but none was found significant and all adjR2values were negative or close to zero. Accordingly, we dropped lagged EAR and replaced it by EMR (excess market return). All EMR coefficients were found to be significant at 1% level and values of adjR2are relatively much higher.