IMPACTS OF FINANCIAL DERIVATIVES MARKET ON OIL PRICE VOLATILITY. Istemi Berk Department of Economics Izmir University of Economics

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1 IMPACTS OF FINANCIAL DERIVATIVES MARKET ON OIL PRICE VOLATILITY Isemi Berk Deparmen of Economics Izmir Universiy of Economics

2 OUTLINE MOTIVATION CRUDE OIL MARKET FUNDAMENTALS LITERATURE & CONTRIBUTION OF THIS PAPER DATA METHODOLOGY EMPIRICAL RESULTS CONCLUSION

3 MOTIVATION Does Fuures Trading Increase he Efficiency of Crude Oil Marke? If no; Wha is he impac of his o Risk Managemen in Crude Oil Marke?

4 MOTIVATION (con d) This paper examines he impacs of crude oil fuures on spo marke volailiy. The main aim of his paper is o analyze wheher i is possible for indusrial agens o handle volailiy risk wih using crude oil fuures conracs.

5 CRUDE OIL MARKET FUNDAMENTALS Real Prices of Crude Oil since 940 and Marke Dominaion Source: BP Saisical Review of World Energy 009

6 CRUDE OIL MARKET FUNDAMENTALS (con d) Volume of Transacions Held in Spo Crude Oil Marke and Fuures Exchanges (Represenaive: Nymex WTI Crude Oil Neares Monh Conrac) Thousand Barrels Daily Year fuures rading volume crude oil producion Source: NYMEX & BP Saisical Review of World Energy 008

7 LITERATURE Sadorsky (006) & Agnolucci (009); GARCH models fi well for crude oil volailiy modeling Several sudies on commodiies and indices;

8 LITERATURE (con d) Researcher Daa Se Findings Powers (970) Edwards (988) Darra e. al. (00) Kasman & Kasman (008) Pork Belly and Beef Spo and Fuures Price SP500 spo and fuures reurns ISE 00 spo and fuures reurns Variance has decreased afer he inroducion of fuures exchange Volailiy has increased in he shor-run bu does no carried in long-run Inroducion of fuures exchange has decreased he spo marke volailiy

9 LITERATURE (con d) Sudies on Crude Oil; Researcher Anoniou and Foser (99) Flemming and Osdiek (999) Silvapulle and Moosa (998) Bekiros and Dicks (008) Daa Se Bren Crude Oil Fuures and Spo Prices from 986 o 990 WTI Crude Oil fuures and spo prices from 983 o 997 WTI Crude Oil fuures and spo prices from 985 o 996 WTI Crude Oil fuures and spo prices from 99 o 999 Findings Fuures conrac has decreased he volailiy of spo marke Fuures rading has increased spo marke volailiy Unidirecional Causaliy from spo o fuures marke Bidirecional Causaliy beween spo and fuures marke

10 CONTRIBUTION This paper would conribue o he lieraure wih modeling crude oil spo and fuures marke volailiies and causaliy analysis on volailiy series from 986 o 009 (pos-fuures period).

11 DATA Two analysis wih wo sample periods ) From Ocober 973 o December 008 monhly daa (US F.O.B. Cushing Oklahoma monhly) ) From January 3, 986 o February 7, 009 weekly daa (pos-fuures period) (WTI neares monh fuures and spo weekly)

12 DATA (con d) Summary Saisics of Series Varible r fob r f r s Mean Median Maximum Minimum Sd. Dev Skewness Kurosis J-B Sa ** ** ** # of observaions ** denoes significance a % confidence level

13 DATA (con d) The Ljung-Box Tes for Sandardized Residuals of Mean Equaions ε rfob ε rf ε rs Lag AC PACF Q-sa AC PACF Q-sa AC PACF Q-sa

14 METHODOLOGY ) Modeling F.O.B. Cushing Oklahoma spo price volailiy where, ; log reurn of F.O.B. price r fob r = # + " $ r +! fob 0 0 fob % We have used EGARCH(,) model wih dummy o capure asymmeries and overcome non-negaiviy condiions

15 METHODOLOGY (con d) where; σ ; condiional variance σ - ; lag of variance ; asymmeric erm ; size of asymmery D fu ; pos-fuures dummy fu D 0 ) ln( ) ln(! " # $ " # % " & ' " + ( + ( + ( + = ) ) ) ) ) j j!! " # j j!! " #

16 METHODOLOGY (con d) ) Modeling crude oil fuures and spo marke volailiy for pos-fuures period. Log reurn series for boh spo and fuures prices; rf = # + " $ r f ( % ) +! rs = # + " $ r s +! ( % ) where; r s and r f are spo and fuures reurn series respecively

17 METHODOLOGY (con d) EGARCH(,) model is conduced for boh spo and fuures marke volailiies. ln( # f ) = ( + ' " ln( # f )! + & " $ (! ) # f! + % " $ (! ) # f! where;! f! s ; variance of fuures marke ; variance of spo marke

18 METHODOLOGY (con d) Moreover, Granger Causaliy es will be conduced on volailiy series; where; z - s are error correcion erms f j j s i i s z! " # $ # % & # + ' + ' + ' + = ( = = ( ( ) ) f j j s i i f z! " # $ # % & # + ' + ' + ' + = ( = = ( ( ) )

19 METHODOLOGY (con d) Coinegraion es is conduced on price series; p f = # + " $ ps +! ps = # + " $ p f +! where; p f and p s are fuures and spo prices respecively. ε and ε are residuals o be esed for uni roo

20 EMPIRICAL RESULTS

21 EMPIRICAL RESULTS (con d) β : saisically significan and negaive; asymmeric effec θ : saisically significan and posiive: inroducion of fuures conrac has increased spo marke volailiy

22 EMPIRICAL RESULTS (con d)

23 EMPIRICAL RESULTS (con d) Bidirecional causaliy exiss beween fuures and spo crude oil marke; decreases efficiency

24 EMPIRICAL RESULTS (con d)

25 CONCLUSION Inroducion of Crude Oil Fuures Conracs has increased he volailiy decreased he efficiency of spo marke Asymmeric srucure of crude oil price volailiy deers precise forecasing consisen Value A Risk Measuremen Bidirecional causaliy/feedback and long-run coinegraion beween markes would be explained by marke deph of fuures ransacions

26 CONCLUSION (con d) Wha does i mean for Indusrial Agens? Handling volailiy risk wih fuures conrac would no be possible Marke is under influence of Large Invesor Groups and Traders more han Indusrial Agens Non-commercial and speculaive Trading raher han Hedging Forecasing & VAR measuremens would no be consisen

27 THANK YOU QUESTIONS?