Impact of Oil Prices on the Stock Market

8/2/2019 Impact of Oil Prices on the Stock Market

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IMPACT OF OIL PRICES ON THE STOCK

MARKET

Submitted By:

Dhruv Aghi

Section-A, BBA LLB

Roll no. 9

OF

Symbiosis Law School, NOIDA

Symbiosis International University, PUNE

26th March 2012

Under The Guidance of: Dr. Pushpa Negi


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C E R T I F I C A T E

The project entitled IMPACT OF OIL PRICES ON THE STOCK

MARKETsubmitted to the Symbiosis Law School, NOIDA for

quantitative techniques as part of internal assessment is based on my

original work carried out under the guidance of Dr. Pushpa Negi on

26/03/12. The research work has not been submitted elsewhere for

award of any degree. The material borrowed from other sources and

incorporated in the thesis has been duly acknowledged. I understand

that I myself could be held responsible and accountable for

plagiarism, if any, detected later on.

Signature of the candidate

Date: 26/03/12


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ACKNOWLEDGEMENT

It is a great pleasure for us to put on records our appreciation and gratitude

towards Dr. Pushpa Negi for his immense support and encouragement all

through the preparation of this report and for his valuable support and

suggestions for the improvement and editing of this project report. Last but not

the least, we would like to thank the college staff, friends and others who

directly or indirectly helped us in completing this project report.


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INDEX

COVER PAGE 1

CERTIFICATE 2

ACKNOWLEDGMENT 3

INDEX 4

BIBLIOGRAPHY 5

INTRODUCTION 6

REVIEW OF LITERATURE 8

CONCLUSION

REFERENCES 15
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BIBILOGRAPHY

1. http://www.oilprice.com

2. http://www.wikipedia.com

3. htttp://papers.ssrn.com/

4. Http://www.reuters.com/
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Introduction

Stock market commentators like to draw parallels between the behavior

of oil prices and stock prices on any given day. After all, who hasnt seena headline like this: Oil Spike PummelsStock Market? But evidenceshows that a change in oil prices does not necessarily affect the stockmarket in any predictable and meaningful way.

Before we explain why, lets look at the traditional wisdom, which holdsthat when oil prices rise, stocks fall, and vice versa. When oil prices rise,gasoline prices follow. Higher gas prices hurt consumers, who then haveless money to spend on other goods and services. A decline in consumerspending causes businesses to see decreasing sales. At the same time,businesses are also hurt by higher oil prices because they use oil for gasand other goods as well, and must pay higher prices for it. As a result,high oil prices can create a drag on corporate earningsand businessesoften end up passing those costs onto already-strapped consumers. Its avicious cycle, and it seems obvious that it would cause stocks to decline.The opposite is true when oil prices fall.

That seems reasonable enough. So why do we say the traditional wisdomisnt always true? Because higher oil prices dont always result in a dragon corporate earnings. There a number of reasons for this. For example,the U.S. economy is less dependent on oil than it used to be: Each dollar

of U.S. gross domestic product produced today takes about half the oil itdid 30 years ago. Additionally, much of the oil used by Americanbusinesses at any given time has been purchased under fixed-pricescontracts that were negotiated when oil prices were much lower.

So, we have two ways of looking at the same situation. The traditionalwisdom holds that higher oil prices hurt stocks. But when we look a littledeeper, we can see that isnt always the case. Thats quite a muddle, andit piqued the interest of economiststwo of whom set out to find outwhich is the case: Do higher oil prices hurt stocks, or dont they?

These economists, based at the Federal Reserve Bank of Cleveland,looked at both oil prices and the S&P 500 Index, which is widelyconsidered a broad indicator of stock market performance. Theeconomists found, that over the past 10 years, oil prices and stock priceshave mostly risen but there has been little correlation between them.That was the case even during periods of peak oil prices, when we mightexpect stocks to really suffer.

The economists did find, however, that certain segments of the stock

market were correlated with oil prices. For example, the Dow JonesTransportation Index rose when oil process rose, and fell when oil prices
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fellpresumably because changes in oil prices have a significant effect ontransportation companies. On the other hand, the Dow Jones FinancialsIndex rose when oil prices fell, and fell when oil prices rosepresumablybecause the financial industry is not directly affected by oil prices.

That information may offer investors some insight when it comes tobuying and selling stocks during periods of high and low oil prices. Whenoil prices are high, you might want to sell (or short) airline stocks. Whenoil prices are low, you might want to buy energy stocks. Savvy stockpickers could potentially benefit in this way.
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Review of Literature

1. Gogineni (2006) investigated the impact of daily oil price changes onthe stock returns of a wide array of industries. In addition tothe stock returns of industries that depend heavily on oil, stockreturns ofsome industries that use little oil also are sensitive to oil prices perhapsbecause their main customers are impacted by oil price changes. Inaddition, he presented robust estimates of industries cost-side anddemand-side dependence on oil. These measures can serve as reliablebenchmarks when classifying industries into oil-intensive and non-oil intensive groups, a distinction widely used in studies and mediawithout any quantitative justification so far. Further, the sensitivity ofindustries returns to oil price changes depends on both the cost-side anddemand-side dependence on oil and that the relative effects of thesefactors vary across industries.

2. Thornton and Welker (1999) in their study explored associationsbetween U.S. firms' 10-K disclosures of market risk exposure, which werenewly mandated by a 1997 SEC Release, and stock price sensitivity tounderlying risk factors. Firms whose stock prices were more sensitiveto oil and gas prices tended to have open year-end positions incommodity derivatives and disclose the value-at-risk or the sensitivity oftheir derivative contracts to commodity price changes. Firmswhose stock prices were less sensitive to oil and gas prices tended not tohave open year-end positions in commodity derivatives or, if they did, to

give simple tabular disclosures of derivative contracts. On their SEC filingdates, firms that disclosed value-at-risk or sensitivity experienced moresignificant shifts than other firms did in stock-price sensitivity to oil andgas price changes. Firms disclosing that their material derivative contractshad zero net sensitivity to commodity price changes, given an assumedshift in commodity prices, experienced the most significant shifts instock-price sensitivity to those same price changes. Preliminary tests on an oil-intensive sub-sample suggest a tentative economic interpretation of theseresults that is both intuitively appealing and consistent with the SEC'sperceptions. Producers with naturally long oil exposure that disclosed the

value-at-risk or sensitivity of their derivative contracts experienced areduction in the sensitivity of their stock prices to oil price changesbecause such disclosures signaled to the market that they hadimplemented effective risk management strategies.

3. Sawyer and Nandha (2006) concluded that the important questionin asset markets is whether oil prices are a global factor in asset returns.In this paper, we propose a hierarchical model of stock returns whichassumes that markets are integrated conditional on a set of factors,including oil. The hierarchical model is a variant of the Jorion and Schwarz


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model of market integration and permits significance testing of factors atthree levels; global, country and sector. In an application to threecountries across nine common sectors, we found the pattern ofsignificance of oil was different than for six other commodities. Whilethere is no evidence that oilis a global or country factor, there is evidence

that oil is more significant at the sector level than other commodities. Theaverage P-values for oil are less than for other commodities and, in Waldtests across sectors, oil behaves like a global market factor and acountry market factor. The effect of oil is therefore both disaggregatedand heterogeneous. There are two important implications of this study.First, in the aggregate, stock prices appear remarkably insensitiveto oil prices, suggesting that the correlation between stock prices andoil prices is less certain than usually perceived. While an oil shock maycause a real economy recession, it does not necessarily cause an asseteconomy recession. A second implication relates to the testing of linear

factor models. If factors affect asset prices in a hierarchy rather thanlinearly, tests of factor models must adjust for the hierarchical structure.

4. Davis and Diaz (2008) quantifed the time-varying effects of oil-priceshocks on the U.S. economy, Federal Reserve policy, and global equitymarkets. While the first-round impact of oil-price shocks on U.S.economic growth has not changed materially over time, their formerly-negative second-round effects are notably absent over the past 25 yearsgiven oil's near-zero impact on long-term inflation expectations. Since oil-

price shocks now represent a less-stagflationary policy tradeoff, theyshowed why the Federal Reserve should lower short-term interest rates inresponse to anoil-price shock under certain (but not all) macro scenarios.For domestic and international stocks, simple regressions reveal theanticipated inverse relationship, with a 10% increasein oilprices associated with a statistically significant 1.5% lower totalreturn. However, the stock market's reaction varies dramaticallydepending on the source of the oil-price shock, with global stocks - inparticular the industrial and materials sectors - responding quite favorablyto oil-price increases attributed to global-demand shocks. A keyimplication is that oil-price increases do not uniformly lead tolower stock returns. Interestingly, our oil-price decomposition suggeststhat oil's recent surge cannot be explained by supply disruptions, globaldemand fundamentals, or the depreciation of the U.S. dollar.

5. Manera, Lanza, Grasso and Giovannini (2003) conclude that theidentification of the forces that drive oil stock prices is extremelyimportant given the size of the Oil&Gas industry and its links with theenergy sector and the environment. In the next decade oil companies willhave to deal with international policies to contrast climate change. Thisissue is likely to affect companies' shareholder values. In this paper wefocus on the long-run financial determinants of the stock prices of sixmajor oil companies (Bp, Chevron-Texaco, Eni, Exxon-Mobil, Royal Dutch
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Shell, Total-Fina-Elf) using multivariate cointegration techniques andvector error correction models. Weekly oil stock prices are analyzedtogether with the relevant stock market indexes, exchange rates, spotand future oil prices over the period January 1998 - April 2003. Theempirical results confirm the statistical significance of the major financial

variables in explaining the long-run dynamicsof oil companies' stockvalues.

6. Fodor and Stowe (2010) studied that the BP Deepwater Horizondrilling rig exploded on April 20, 2010, leading to an unprecedentedenvironmental and financial disaster. This paper details responses in thefinancial markets for BP securities, including stock, bonds, options, andcredit default swaps. Following the disaster BP shares dropped more than50 percent in value, with high volatility. BP share trading volumeincreased thirteen-fold, and option trading volume increased twenty-fold.

The implied volatility of BP shares also jumped, ranging between two andfour times its earlier levels. Interest rate spreads on BP bonds widenedand the prices of credit default swaps exploded. Finally, on June 16, thecompany announced that cash dividends were suspended. We provideevidence from options markets that this dividend suspension wasanticipated. From late June through September, there was a partialreversion to pre-explosion levels in all markets. We detail the degree ofintegration across markets, as wide swings in BPs outlook weresimultaneously absorbed in the various markets.

7. Oseni (2009) parallel Brav & Heaton (2003) alleges marketindeterminacy (a situation where it is impossible to determine whether anasset is efficiently or inefficiently priced) in the stock market. Kang (2008)argue that empirical tests of linear asset pricing models show presence ofmispricing in asset pricing. Asset pricing is considered efficient if the assetprice reflects all available market information to the extent no informedtrader can outperform the market and/or the uninformed trader. Thisstudy examined the extent to which some information factorsor market indices affect the stock price. A model defined by Al-Tamimi(2007) was used to regress the variables (stockprices, earnings per

share, gross domestic product, lending interest rate and foreign exchangerate) after testing for multicollinarity among the independent variables.The multicollinarity test revealed very strong correlation between grossdomestic product and crude oil price, gross domestic product and foreignexchange rate, lending interest rate and inflation rate. All the variableshave positive correlation to stock prices with the exception of lendinginterest rate and foreign exchange rate. The outcomes of the study agreewith earlier studies by Udegbunam and Eriki (2001); Ibrahim (2003) andChaudhuri and Smiles (2004). This study has enriched the existingliterature while it would help policy makers who are interested indeploying instruments of monetary policy and other economic indices forthe growth of the capital market.


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8. Cifarelli , Paladino (2008) assessed empirically whether speculationaffects oil price dynamics. The growing presence of financial operators in

the oil markets has led to the diffusion of trading techniques based onextrapolative expectations. Strategies of this kind foster feedback tradingthat may cause large departures of prices from their fundamental values.We investigate this hypothesis using a modified CAPM that follows Shiller(1984) and Sentana and Wadhwani (1992). At first, a univariateGARCH(1,1)-M is estimated assuming that the risk premium is a functionof the conditional oil price volatility. The single factor model, however, isoutperformed by the multifactor ICAPM (Merton, 1973) which takes intoaccount a larger investment opportunity set. The analysis is then carriedout using a trivariate CCC GARCH-M model with complex nonlinear

conditional mean equations where oil price dynamics are associated withboth stock market and exchange rate behavior. We find strong evidencethat oil price shifts are negatively related to stock price and exchange ratechanges and that a complex web of time varying first and second orderconditional moment interactions affect both the CAPM and feedbacktrading components of the model. Despite the difficulties, we identify asignificant role of speculation in the oil market which is consistent withthe observed large daily upward and downward shifts in prices. A clearevidence that it is not a fundamentals-driven market. Thus, from a policypoint of view - given the impact of volatile oil prices on global inflation

and growth - actions that monitor more effectively speculative activitieson commodity markets are to be welcomed.

9. Tansuchat, Chang and McAleer (2010) investigated the conditionalcorrelations and volatility spillovers between crude oil returnsand stock index returns. Daily returns from 2 January 1998 to 4November 2009 of the crude oil spot, forward and futures prices from theWTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500index returns, are analysed using the CCC model of Bollerslev (1990),VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model

of McAleer, Hoti and Chan (2008), and DCC model of Engle (2002). Basedon the CCC model, the estimates of conditional correlations for returnsacross markets are very low, and some are not statistically significant,which means the conditional shocks are correlated only in thesamemarket and not across markets. However, the DCC estimates of theconditional correlations are always significant. This result makes it clearthat the assumption of constant conditional correlations is not supportedempirically. Surprisingly, the empirical results from the VARMA-GARCHand VARMA-AGARCH models provide little evidence of volatility spilloversbetween the crude oil and financial markets. The evidence of asymmetriceffects of negative and positive shocks of equal magnitude on the
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conditional variances suggests that VARMA-AGARCH is superior toVARMA-GARCH and CCC.

10. Alpanda and Alva (2008) concluded that the market value of U.S.corporations was nearly halved following the oil crisis of October 1973.

Real energy prices more than doubled by the end of the decade,increasing energy costs and spurring innovation in energy-savingtechnologies by corporations. This paper uses a neo-classical growthmodel to quantify the impact of the increase in energy prices onthe marketvalue of U.S. corporations. In the model, corporations adoptenergy-saving technologies as a response to the energy price shock andthe price of installed capital falls due to investment irreversibility. Themodel calibrated to match the subsequent decline in energy consumptionin the U.S. generates a 24% decline in market valuation - accounting fornearly half of what is observed in the data.

11. Khan (2010) investigated the short-run and long-run relationshipbetween the crude oil prices and the stock market of BRIC countries byusing Structural Vector Error Correction technique. By imposing short-runand long-run restrictions, the results indicate that the real stock returnsof Russia, India and China follows Efficient Market Hypothesis (EMH) inresponse to crude oil shock. Brazils real stock returns do not follow EMHdue to its transformed status as crude oil exporter. The industrialproduction of BRIC countries behaves almost in a similar fashion. The

output increase in short-run and decrease over short to long-run period.This behavior is attributed to short-run commercial oil future contractswith physical delivery. This reduces the impact of initial oil shock to theoutput. The short-term interest rate behavior varies to some extentamong BRIC countries. In case of Brazil and Russia which can becategorized as net crude oil exporters, the interest rates increase overshort-run and then decline from short to long-run (negative change). Onthe contrary, the Indian and Chinese interest rates increase over short-run and decline over long-run (positive change). The increase in interestrates is attributed to contain the inflationary pressure while the decline in

interest rates is associated with increase in the output.

12. Yang, Fok and Chang (2007) examined the valuation effects ofcorporate name changes involved oil related terms during recent oil pricesurges. Using data from the U.S. and Canadian stock markets, we showthat there is a tendency for companies in both markets to add oil orpetroleum to their corporate names when oil prices are high. Results showthat U.S. investors react more positively for firms that add oil-relatedterms to their names. Name changes trigger short-term positive and long-term negative returns in the Canadian market. Our results add supportsof the literature that investors are potentially influenced by corporatename changes associated with market wide sentiments.
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13. Driesprong, Jacobsen and Maat (2007) studied that changesin oil prices predict stock market returns worldwide. In our thirty yearsample of monthly returns for developed stock markets, we findstatistically significant predictability for twelve out of eighteen countries

as well as for the world market index. Results are similar for our shortertime series of emerging markets. We find no evidence that our results canbe explained by time varying risk premia. Even though oil price shocksincrease risk, investors seem to underreact to information in the priceof oil: a rise in oil prices does not lead to higherstock market returns, butdrastically lowers returns. For instance, an oil price shock of one standarddeviation (around 10 percent) predictably lowers world market returns byone percent.Oil price changes also significantly predict negative excessreturns. Our findings are consistent with the hypothesis of a delayedreaction by investors to oil price changes. In line with this hypothesis the

relation between monthly stock returns and lagged monthly oil pricechanges becomes substantially stronger once we introduce lags of severaltrading days between monthly stock returns and lagged monthly oil pricechanges.

14. Hayo and Kutan (2009) analyzed the impact of news, oil prices,and international financial market developments on daily returns onRussian bond and stock markets. First, there is some persistence in bothbond and stock market returns. Second, we find thatU.S. stock market returns Granger-cause Russian financial markets.

Third, growth in oil prices has a positive effect onRussianstock market returns. Fourth, there is a significant economic andstatistical influence of a specific type of news on the Russianbond market: Positive (negative) news related to the energy sector raise(lower) daily returns by one percentage point. News from the war inChechnya, on the other hand, do not appear to have a significantinfluence on financial markets.

15. Rault and Arouri (2009) investigated that in the empiricalliterature, only few studies have focused on the relationship

between oil prices and stock markets in net oil-importing countries. Innet oil-exporting countries this relationship has not been widelyresearched. This paper implements the panel-data approach of Knya(2006), which is based on SUR systems and Wald tests with country-specific bootstrap critical values to study the sensitivity of stock marketsto oil prices in GCC (Gulf Corporation Council) countries. Using twodifferent (weekly and monthly) datasets covering respectively the periodsfrom 7 June 2005 to 21 October 2008, and from January 1996 toDecember 2007, we show strong statistical evidence that the causalrelationship is consistently bi-directional for SaudiArabia. Stock market price changes in the other GCC member countriesdo not Granger cause oil price changes, whereas oil price shocks Granger


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cause stock price changes. Therefore, investors in GCC stock marketsshould look at the changes in oil prices, whereas investors in oil marketsshould look at changes in the Saudi stock market.
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Conclusion

Market commentators and journalists like to draw direct lines between thebehavior of crude oil prices and market behavior on a given day, with

such headlines as Oil Spike Pummels Stock Market (Wall Street Journal)or U.S. Stocks Rally as Oil Prices Fall(Financial Times). But does achange in oil prices affect the overall stock market in any predictable,meaningful way? Might a hike in crude foretell a weak day on the Street?

It seems logical to assume that oil prices and stock market performancemight be negatively correlated. More expensive fuel translates into highertransportation, production, and heating costs, which can put a drag oncorporate earnings. Rising fuel prices can also stir up concerns aboutinflation and curtail consumers discretionary spending. But it is alsopossible to associate expensive crude with a booming economy. Higherprices could reflect stronger business performance and increased demandfor fuel.

Which is it? A look at oil prices and the S&P 500 index suggests neither.Both oil prices and the S&P 500 index have mostly climbed over the past10 years, but they have frequently moved in opposite directions.Sometimes they rise and fall together, but the relationship between oiland stocks does not appear to be very strong. The following scatter plotrelates the weekly behavior of crude prices with S&P 500 performancesince the beginning of 1998. If a clear negative relationship between oil

prices and the S&P 500 index existed, we would expect to see the pointsaligned along somewhat of a downward-sloping line, indicating poorerstock performance when oil prices pick up. No such relationship isevident, at least not in the time period sampled. Furthermore, thecorrelation between weekly averages of the spot oil price and the S&P 500index is a weak and statistically insignificant 0.021 for the past 10 years(with a confidence level of 95 percent). It is possible that a strongercorrelation might exist for data at different frequencies (daily, weekly,monthly) or with different stock indexes. The S&P 500 index is widelyused as a broad market indicator because it contains the stocks of 500

leading U.S. companies that trade on the two largest U.S. stock markets,the New York Stock Exchange and the Nasdaq. We can expand theindustries covered by including other indexes: S&P Financial, S&PIndustrial, Dow Jones Industrial, Dow Jones Transportation, the NasdaqComposite, and the NYSE Composite, and we can look at data at all threefrequencies to see if either of these factors affect the correlation.

It is also possible that the relationship between oil and the stock marketchanges over time, say when oil prices are at a trough versus when theyare at a peak. To investigate this possibility, we designate the 18-month

period surrounding December 1998 as an oil price trough (from March1998 to September 1999) and the most recent 18-month period
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beginning February 2007 as a price peak, and compare the correlations.As it turns out, correlations between oil prices and all of these stockindexes at the daily, weekly, and monthly levels for the two time periodsalso reveal very few relationships of statistical significance.
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REFERENCES

1. Gogineni, Sridhar, Oil and the Stock Market: An Industry Level Analysis(February 19, 2010). The Financial Review, Forthcoming . Available at

SSRN:http://ssrn.com/abstract=947568

2. Thornton, Daniel B. and Welker, Michael, Impact of Market RiskDisclosures on Stock Price Sensitivity to Oil and Gas Prices (April 1999).Available at SSRN: http://ssrn.com/abstract=160788 orhttp://dx.doi.org/10.2139/ssrn.160788

3. Sawyer, Kim R. and Nandha, Mohan, How Oil Moves Stock Prices (June20, 2006). Available at SSRN: http://ssrn.com/abstract=910427 orhttp://dx.doi.org/10.2139/ssrn.910427

4. Davis, Joseph H. and Aliaga-Diaz, Roger A, Oil, the Economy, and theStock Market (April 2008). Available at SSRN:http://ssrn.com/abstract=1136524

5. Manera, Matteo, Lanza, Alessandro, Grasso, Margherita and Giovannini,Massimo, Long-run Models of Oil Stock Prices (October 2003). FEEMWorking Paper No. 96.2003. Available at SSRN:http://ssrn.com/abstract=467283 orhttp://dx.doi.org/10.2139/ssrn.467283

6. Driesprong, Gerben, Jacobsen, Ben and Maat, Benjamin, Striking Oil:Another Puzzle (July 2003, 11). ERIM Report Series Reference No. ERS-2003-082-F&A. Available at SSRN:http://ssrn.com/abstract=474424

7. Fodor, Andy and Stowe, John D., The BP Oil Disaster: Stock and OptionMarket Reactions (December 20, 2010). Available at SSRN:http://ssrn.com/abstract=1631970 orhttp://dx.doi.org/10.2139/ssrn.1631970

8. Manera, Matteo, Lanza, Alessandro, Grasso, Margherita and Giovannini,Massimo, Conditional Correlations in the Returns on Oil Companies StockPrices and Their Determinants (April 2004). FEEM Working Paper No.71.04. Available at SSRN: http://ssrn.com/abstract=546482 orhttp://dx.doi.org/10.2139/ssrn.546482

9. Oseni, Jimoh Ezekiel, Determinants of Equity Prices in the StockMarkets (January 14, 2009). Available at SSRN:http://ssrn.com/abstract=1326912 orhttp://dx.doi.org/10.2139/ssrn.1326912
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10. Simpson, John L., Evans, John P. and Husain, Tasneem, TheImportance of the Relationship between OPEC Oil Prices and GulfCooperating Economy Banking Stock Returns (September 2004).University of Wollongong in Dubai Working Paper No. 21/2004. Availableat SSRN: http://ssrn.com/abstract=585241 or

http://dx.doi.org/10.2139/ssrn.585241

11. Cifarelli, Giulio and Paladino, Giovanna, Oil Price Dynamics andSpeculation: A Multivariate Financial Approach (November 4, 2008).Available at SSRN: http://ssrn.com/abstract=1295353 orhttp://dx.doi.org/10.2139/ssrn.1295353

12. Tansuchat, Roengchai, Chang, Chia-Lin and McAleer, Michael,Conditional Correlations and Volatility Spillovers between Crude Oil andStock Index Returns (January 10, 2010). Available at SSRN:

http://ssrn.com/abstract=1534043 orhttp://dx.doi.org/10.2139/ssrn.1534043

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U.S. Stock Market: A Distinguish between the Total Market Index and theSustainability Index (February 10, 2009). Available at SSRN:http://ssrn.com/abstract=1340574 orhttp://dx.doi.org/10.2139/ssrn.1340574

15. Khan, Salman, Crude Oil Price Shocks to Emerging Markets:Evaluating the BRICs Case (April 30, 2010). Available at SSRN:http://ssrn.com/abstract=1617762 orhttp://dx.doi.org/10.2139/ssrn.1617762
http://dx.doi.org/10.2139/ssrn.585241http://dx.doi.org/10.2139/ssrn.585241http://dx.doi.org/10.2139/ssrn.1295353http://dx.doi.org/10.2139/ssrn.1295353http://dx.doi.org/10.2139/ssrn.1534043http://dx.doi.org/10.2139/ssrn.1534043http://ssrn.com/abstract=929059http://ssrn.com/abstract=929059http://dx.doi.org/10.2139/ssrn.1340574http://dx.doi.org/10.2139/ssrn.1340574http://dx.doi.org/10.2139/ssrn.1617762http://dx.doi.org/10.2139/ssrn.1617762http://dx.doi.org/10.2139/ssrn.1617762http://dx.doi.org/10.2139/ssrn.1340574http://ssrn.com/abstract=929059http://dx.doi.org/10.2139/ssrn.1534043http://dx.doi.org/10.2139/ssrn.1295353http://dx.doi.org/10.2139/ssrn.585241

Impact of Oil Prices on the Stock Market

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