Pr 33 Berk Istemi

7/31/2019 Pr 33 Berk Istemi

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IMPACTS OF FINANCIAL

DERIVATIVES MARKET ON

OIL PRICE VOLATILITY

Istemi Berk

Department of Economics

Izmir University of Economics


2/27

OUTLINE

MOTIVATION

CRUDE OIL MARKET FUNDAMENTALS

LITERATURE & CONTRIBUTION OF THIS

PAPER DATA

METHODOLOGY

EMPIRICAL RESULTS

CONCLUSION


3/27

MOTIVATION

Does Futures Trading Increase the

Efficiency of Crude Oil Market?

If not;

What is the impact of this to Risk

Management in Crude Oil Market?


4/27

MOTIVATION (contd)

This paper examines the impacts of crude

oil futures on spot market volatility.

The main aim of this paper is to analyzewhether it is possible for industrial agents

to handle volatility risk with using crude oil

futures contracts.


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Source: BP Statistical Review of World Energy 2009

Real Prices of Crude Oil since 1940 and Market Domination


6/27


(contd)Volume of Transactions Held in Spot Crude Oil Market and Futures

Exchanges

(Representative: Nymex WTI Crude Oil Nearest Month Contract)

Source: NYMEX & BP Statistical Review of World Energy 2008

0

100000

200000

300000

400000

500000

600000

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

Thousand Barrels Daily

futures trading volume crude oil production


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LITERATURE

Sadorsky (2006) & Agnolucci (2009);

GARCH models fit well for crude oil

volatility modeling

Several studies on commodities and

indices;


8/27

LITERATURE (contd)

Introduction of futures

exchange hasdecreased the spot

market volatility

ISE 100 spot and

futures returns

Kasman & Kasman

(2008)

Volatility has increased

in the short-run but

does not carried in

long-run

SP500 spot and futures

returns

Edwards (1988)

Darrat et. al. (2002)

Variance has

decreased after the

introduction of futures

exchange

Pork Belly and Beef

Spot and Futures Price

Powers (1970)

FindingsData SetResearcher


9/27

LITERATURE (contd)

Studies on Crude Oil;

Bidirectional Causality

between spot and

futures market

WTI Crude Oil futures

and spot prices from

1991 to 1999

Bekiros and Dicks

(2008)

Unidirectional Causality

from spot to futuresmarket


and spot prices from1985 to 1996

Silvapulle and Moosa

(1998)

Futures trading has

increased spot market

volatility


and spot prices from

1983 to 1997

Flemming and Ostdiek

(1999)

Futures contract has

decreased the volatility

of spot market

Brent Crude Oil Futures

and Spot Prices from

1986 to 1990

Antoniou and Foster

(1992)

FindingsData SetResearcher


10/27

CONTRIBUTION

This paper would contribute to the

literature with modeling crude oil spot and

futures market volatilities and causality

analysis on volatility series from 1986 to2009 (post-futures period).


11/27

DATA

Two analysis with two sample periods

1) From October 1973 to December 2008

monthly data

(US F.O.B. Cushing Oklahoma monthly)

2) From January 3, 1986 to February 27, 2009

weekly data (post-futures period)

(WTI nearest month futures and spot weekly)


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DATA (contd)

Summary Statistics of Series

12081208422# of observations

610.75**591.84**546.98**J-B Stat

6.466.378.53Kurtosis

-0.17-0.29-0.36Skewness

0.0460.0440.077Std. Dev.

-0.192-0.191-0.373Minimum

0.2510.2550.380Maximum

0.0020.0020.005Median

0.0010.0010.005Mean

rs

rf

rfob

Varible

**denotes significance at 1% confidence level


13/27

DATA (contd)

The Ljung-Box Test for Standardized Residuals of MeanEquations

50.038-0.041-0.05254.390-0.039-0.054117.890.0610.09220

33.9700.010-0.00134.6750.0120.00272.2970.1800.18310

25.508-0.0070.00526.857-0.0130.00362.9300.003-0.0345

25.4810.0630.07426.8470.0670.07662.426-0.066-0.0464

18.7780.0480.03619.7900.0410.03561.508-0.0170.0403

17.212-0.055-0.04218.298-0.030-0.01560.8230.0190.1402

15.0470.1110.11118.0310.1220.12252.4630.3510.3511

Q-statPACFACQ-statPACFACQ-statPACFACLag

rsrfrfob


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METHODOLOGY

1) Modeling F.O.B. Cushing Oklahoma spotprice volatility

where,

; log return of F.O.B. price

We have used EGARCH(1,1) model withdummy to capture asymmetries and

overcome non-negativity conditions

tfobr

ttfobtfobrr !"# +$+=

%100


15/27

METHODOLOGY (contd)

where;

2t ; conditional variance

2t-1 ; lag of variance

; asymmetric term

; size of asymmetry

Dfut ; post-futures dummy

fut

t

t

t

ttt D12

1

112

1

11

2

110

2 )ln()ln( !"

#$

"

#%"&'" +(+(+(+=

)

)

)

)

)

2

jt

jt

!

!

"

#

2

jt

jt

!

!

"

#


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METHODOLOGY (contd)

2) Modeling crude oil futures and spot

market volatility for post-futures period.

Log return series for both spot and futuresprices;

ttff rr 1)1(11 !"# +$+= %

ttss rr 2)1(22 !"# +$+= %

where; rs and rfare spot and futures return

series respectively


17/27

METHODOLOGY (contd)

EGARCH(1,1) model is conducted for bothspot and futures market volatilities.

2

)1(1

12

)1(1

1

2

11

2

11

1)ln()ln(

!!

!

!!

"+"+"+=

tt

tt

f

t

f

t

ff

#

$%

#

$'(#

where;; variance of futures market

; variance of spot market

2

tf!

2

ts

!


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METHODOLOGY (contd)

Moreover, Granger Causality test will be

conducted on volatility series;

where; zt-1s are error correction terms

tttttf

j

js

i

is z 1112

1

2

1

1

2

11

!"#$#% +'+'+'+= (==

(( ))

tttttf

j

js

i

if z 2122

1

2

1

2

2

11

!"#$#% +'+'+'+= (==

(( ))


19/27

METHODOLOGY (contd)

Cointegration test is conducted on price

series;

where; pfand p

sare futures and spot prices

respectively. 1t and 2t are residuals to be

tested for unit root

tsf tt pp 111 !"#+$+=

tfs ttpp

222!"# +$+=


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EMPIRICAL RESULTS


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EMPIRICAL RESULTS (contd)

1: statistically significant and negative; asymmetric effect1: statistically significant and positive: introduction of

futures contract has increased spot market volatility


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23/27


Bidirectional causality exists between futures and spot

crude oil market; decreases efficiency


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25/27

CONCLUSION

Introduction of Crude Oil Futures Contracts has

increased the volatility

decreased the efficiency of spot market

Asymmetric structure of crude oil price volatility detersprecise forecasting

consistent Value At Risk Measurement

Bidirectional causality/feedback and long-runcointegration between markets would beexplained by market depth of futurestransactions


26/27

CONCLUSION (contd)

What does it mean for Industrial Agents?

Handling volatility risk with futures contract would notbe possible

Market is under influence of Large Investor Groups and Traders more than Industrial

Agents

Non-commercial and speculative Trading rather thanHedging

Forecasting & VAR measurements would not beconsistent


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QUESTIONS?

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Pr 33 Berk Istemi