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A time series analysis of the crude oil spot and futures markets

Material Information

Title:
A time series analysis of the crude oil spot and futures markets
Creator:
Quan, Jing, 1963-
Publication Date:
Language:
English
Physical Description:
vii, 147 leaves : ill. ; 29 cm.

Subjects

Subjects / Keywords:
Causality ( jstor )
Crude oil ( jstor )
Futures markets ( jstor )
Hematocrit ( jstor )
Import prices ( jstor )
Market prices ( jstor )
Mathematical variables ( jstor )
Oil prices ( jstor )
Prices ( jstor )
Supply ( jstor )
Dissertations, Academic -- Economics -- UF
Economics thesis Ph.D
Petroleum -- Marketing ( lcsh )
Petroleum industry and trade ( lcsh )

Notes

Thesis:
Thesis (Ph.D.)--University of Florida, 1990.
Bibliography:
Includes bibliographical references (leaves 143-146).
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Jing Quan.

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Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
001692912 ( ALEPH )
25215805 ( OCLC )
AJA4986 ( NOTIS )

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THE


A TIME
CRUDE OIL


SERIES
SPOT


ANALYSIS OF
AND FUTURES MARKETS


JING


QUAN


A DISSERTAT
OF
PARTIAL
FOR THI


ION PRESENTED TO THE GRADUATE S(
THE UNIVERSITY OF FLORIDA IN
FULFILLMENT OF THE REQUIREMENTS
E DEGREE OF DOCTOR OF PHILOSOPHY


UNIVERSITY


OF FLORIDA


1990


SCHOOL















dedicate


this dissertation


to the


faculty


the Department of Economics at the University of Florida.















ACKNOWLEDGEMENTS


I deeply appreciate the encouragement,


guidance,


support


and patience


from Professor G.S.


Maddala,


Professor


Toda,


Professor L.


Cheng and Professor J.S.


Shonkwiler who served as


my supervisory committee.


I am also grateful


to Mr


. R.


Duncan


and Mr.


Imran


offering me a


chance


find


this


topic


while


was


working


World


Bank.


especially thank my


parents and all


other relatives


in China


for their continuous


support


understanding.


















TABLE OF CONTENTS





Page

ACKNOWLEDGEMENTS.......................... ............. ii


ABSTRACT..................... ... .............. ........ vi


CHAPTERS


I INTRODUCTION............... ... ....... .... ..... 1


II SPOT PRICE AND FUTURES PRICES: THE........... 10
PRICE DISCOVERY OF CRUDE OIL
FUTURES PRICES


Introduction.................... .. ... ... 10
Data Analysis................. .............. 16


Using Crude Oil Futures
of the Spot Price


Predictors,......


Using Futures Prices to Update Data..
Combining Results and Futures Prices.


* t. .
* .


Relationship Tests...............
Integration Test............
Co-integration Test.........
Causality Tests..................
Garbade and Silber Approach.
Granger Causality Test.....
Error Correction Model...........
Summary.. ............ .........


....
0......
* .

......
*. C
......


......
*......
*......a


* C

......
a.....


* S .
.....
..* ..


III FUTURES PRICES AND OPEC OIL SUPPLY..........


Introduction................
Data Analysis...............
Simple Regressions..........
Specification Tests.........
Integration Test.......
Co-integration Test....
Garbade and Silber Approach.
Granger Causality Test......
Summary.. ...................


...DO..


......


......
......
......
...0..


.....B.Q.


*.*.*......


* a .
.........
....O....
...*.c..
*...*c.....
*.....ca.s












SPOT PRICES AND OPEC OIL SUPPLY.............. 108


Introduction.............
Data Analysis...........
Simple Regressions.......

Specification Tests......
Integration Test....
Co-integration Test.
The "Self-Adaptive" Model
Summary.. ................


....00"....0.0......
O..." .. .. ..........
* e a a e *at*tt Ste.* *
... O... ...." ..... ..
* t.. te... ...t e

* C S *S et t etee ** t *5*
* C S S C S S 0 C S S S S S C
.".t"... t.......*.
"....... ... .. .Q....
"te... .... C. .. ..e.
*. S ..C C


APPENDIX TO CHAPTER III........................... 140


BIBLIOGRAPHY. .. .. .. 143

BIOGRAPHICAL SKETCH............ ..... .... ... .... 147


CONCLUSIONS. ......... .. ...... .. .... 138









Abstract of


Presented


in Partial


the Degree of


the Graduate School


Fulfillment


A TIME SERIES


ANALYSIS


THE CRUDE OIL SPOT


AND


FUTURES MARKETS


Jing Quan


December,


1990


Chairman:


Major


. G.


Department


Maddala


: Economics


This


dissertation


studies


spot


futures


markets


for crude oil.


Its main objective is to study the relationship


between


these


futures


two m

market


contribution


markets,


this


particular


working


dissertation


the


role


crude


market.


better


understanding


crude


markets.


order


investigate


relationship


between


the


two markets,


two-


stage testing procedure


is proposed in this study.


First


, the


existence


long-run


relationship


tested


using


cointegration


Garbade


tests.


Silber


Second,


approach


Granger


are


causality


tests


determine


direction


of causality.


The


first


relationship


investigated


this


study


between


crude oil


spot and


futures


prices.


This


known


"price


discovery"


role


futures


prices.


Different


assumptions


about


the


futures


market


lead


different


Dissertation


University


Requirements of


of Florida


Doctor of


Philosophy


spot


provide


applied







that

price.


future

The


prices


market


not


efficiency


provide


information


hypothesis,


the


other


spot

hand,


assumes


opposite


conclusion.


These


two


hypotheses


are


tested in this


dissertation.


It is found that spot price leads


futures


prices


instead


the


futures


price


providing


information on the


spot price.


Therefore,


the hypothesis that


futures


prices


have a


price discovery role


is rejected.


Two


additional


relationships


studied


are


those


between


OPEC


supply


and


futures


prices


that


between


there


same supply


are co-integration


and spot prices.


relationships


The hypotheses


between


that


the variables


are


rejected


both


cases.


case


of OPEC


supply


spot prices, a

dummy variables


found that prices


"self-adaptive" model


with supply interruption


is introduced to study the price behavior


follow an adaptive process,


. It


that


previous


price


information


offers


powerful


influence


current


price.













CHAPTER I
INTRODUCTION


The


dramatic


developments


the


world


markets


over


past


two


decades


have


had


far-reaching


effects


world


economy


. Two


price


shocks


and


one


price


collapse


exert


powerful


influence


the


global


economy


and


international


relations.


Ramifications


can


seen


world


recessions


, in


the


third


world


debt


problems,


attempts


to resolve Arab


-Israeli


differences


in the expansion


the


U.S


. military


role


Persian


Gulf


, and


virulent


boom


bust


cycles


producing


country


the major


producing


regions


in the


Unit


ed States.


The


relationship


between


and


a country


s economy


has


proved


very


significant.


Needl


ess


say,


the


most


significant


event


story


the


market


over


last


twenty


years


was


emerge


nce of


the Organization of Petroleum Exporting


Country


(OPEC),


which


has


become


the


major


force


in determining


the


price


of crude


and


the production


policies


of its


members.


addition


, it


revolutionized


the


contractual


relationship


with


the


international


companies.









companies


petroleum


sole


market


force


(exploration,


activities


production,


world


transportation,


refining,


and marketing)


has changed.


The domestic pricing and


energy


resource


development


policies


oil-importing


countries


also


as well


changed.


their


Massive


energy


transfers


consumption


wealth


patterns


from


have


major


industrial


countries


OPEC


member


countries


have


occurred.


Concern


over


balance-of-payment


deficits


recycling of oil money back to the economies of the industrial


countries

emerging


has ix

between


itensified.


New


developed


economic relationships

industrial countries,


are

OPEC


member


countries,


other


less


developed


countries.


These


new


relationships


have


been


accompanied


new


era


international


diplomacy


Obviously


, energy


civilization rests,


is one of the foundations on which our


and one for which


there is no substitute.


connection


between


consumption


primary


energy


carriers and economic development is unmistakable.


At present


petroleum


world's


main


energy


carrier.


Forecasts


future


crude


prices,


crude


availability,


OPEC's


stability


, and its price and production strategies all affect


decisions


developing


oil-importing


alternative


countries


costlier


with


energy


respect


resources.


appreciate


the relationship between oil


and


the economy,









and


world


economy


energy


a good


economic

place to


value


begin.


and


volatility


At today


s prices,


the

the


value


primary


energy


production


amounts


about


percent


of the


world


economic


output


with


accounting


almost

worth


half

three


the


times


total

the


value.


That


value


makes

food


energy

grain


production

production


(rice


, wheat,


and


coarse grains).


similar picture emerges


world


trade.


total


world


exporters


exports


alone

are a


account


most


five


about


times


6 percent


large


value


food


grain


exports.


Even


more


important


volatility


value.


1970,


when


was


still


comparatively


cheap


and


consumption


growing


rapidly,


primary


energy


output


was


equal


percent


world


GNP


less


than


percent.


In 1981,


when


price


of oil


reached


peak,


energy


production


constituted


10 percent,


and


percent,


space


world

decade


output.


Swings


necessarily


set


this

motion


magnitude

Svast st


ructural


changes


throughout


the


world


economy.


A second


macroeconomic


variable


associated


with


inflation.


inflation


course,


rate--the


there


are many


monetary


policy


factors


and


in determining


willingness


trade


inflation


against unemployment


However,


one


also has


admit


that


the


increase


in oil


price


one


the


most


important


factors.


Since


an input


in most


industrial


processes,









heating,


would


difficult


argue


that


850-


percent increase in the price of


oil between October


1973 and


January


1981


was


maj or


factor


raising


general


price level.


It was not only major,


but crucial.


Prior to the


first oil


shock,


world


prices were


increasing


at a


rate of


percent annually


, and this was regarded as an aberration that


would


soon


brought


under


control.


Today


double-digit


inflation is common in many countries


, and it is not expected


to be brought down to rates below the


1973


levels


in the near


future.


Take


1979


1974,


United States'


example.


prices


Followin


United


economy

a the c


States


during the


)il-price


increased


period


1973-


shock


enough


restore


quasi-rents


capital


goods


their


1972-1973


levels.


With only marginal increase in money wages,


real wages


fell


enough


pay


increased


bill.


Moreover,


imports


increased


very


large


amount,


which


removed


barriers


expansion


production


that


might


have


resulted


happened


from the


that


physical


inflation


unavailability


the


energy.


depreciation


It also


dollar


prevented


real


price


from


rising


face


some


minor


upward


adjustments


the


money


price


of oil.


1977


, the


United


States


had


more


less


recovered


from


first


oil-price


shock.


Both


employment


and


output


were









1972-1973


was


that


prices moved


faster after


1973.


The


latest


example


United


States


can


also


confirm


relationship


between


price and


inflation.


Consumer price


index in the United States rose 0.4


percent in December


1989,


for the year,


it reached 4.6 percent,


the highest since


1981.


The


Federal


Reserve


seems


much


concerned


about


fighting


upcoming inflation.


One of the biggest reasons behind the rise


in the consumer price


index was


higher


fuel


prices


resulting


from December's


freeze.


The impact for January


1990 should be


even more


evident.


The fear of inflation strongly influences the performance


of the stock market.


For instance,


The biggest selloff


in the


New York stock market since the October


1989


"mini-crash"


stock


market


Friday,


January


1990.


The


Jones


average of 30 industrial


tumbled 71.46 points to 2,689.21,


largest


loss since it plunged 190.58


in October 1989.


One


major


causes


were


new


inflation


worries.


Department of Labor reported that the producer price


finished goods rose 0.7 percent in December


index of


exceeding advance


estimates


that


measure


inflationary


pressures.


index


finished


1989


with


increase


percent,


biggest


in eight


years.


Finally


, it should be mentioned that the oil-price shock


initiated by OPEC helps some industrial countries--those which









uranium reserves


and has contributed


to England's


ability to


generate


foreign exchange.


From the above discussion,


one can easily appreciate the


importance of


the world oil


market.


However


since


there are


kinds


markets


oil,


namely


, the


spot


market


futures market,


in order to understand the oil markets,


it is


necessary to


study


both


these markets,


the


relationships


between


them.


The


spot,


cash


, market


need


not


market


institutional


sense


word,


simply


arrangement


between


buyers


and


sellers


that


calls


delivery--though


perhaps


consumption--of


commodity


the


immediate


future.


case


oil,


Rotterdam


Spot


Market


literally


become


household


term;


but


although


true


that


this


district


Holland


blessed


with


extensive


brokerage and oil-storage


facilities,


it bears only a passing


resemblance to the conventional image of a market,


since there


physical


locale,


trading


takes


place


means


telecommunications.


Similarly,


the spot or cash price pertains


immediate


transfer of


ownership


of a commodity.


assess


course


spot


market


helpful


during the


1981,


review

1970s,


declined


its

the


steadily


recent

price of


history.


After


rising


peaked at


thereafter


sharply


a barrel


barrel


1985,









early


1980s.


Indeed,


after adjustment


inflation,


October 1987 price was below the price reached after the first


shock


1973-74.


The futures market is an arrangement that features paper


transactions.


Physical


delivery


the


commodity


occurs


only


a small


minority


cases.


Strictly


speaking,


futures


contract is a forward contract


in that these contracts almost


always


refer


particular month


delivery;


same


time,


however


, a futures market is so organized that sales or


purchases can be


offset,


the deliveries are


unnecessary.


In addition,


futures contracts are bought and sold through an


exchange,


impersonally,


with


validity


contracts


guaranteed by the exchange.


function smoothly,


In order


large numbers


for this


traders


type of

are re


market


quired


--in


particular


speculators,


play


major


role


generating


flow


contracts


that


permit


other


types


market


actors


(such


sellers


purchasers


physical


commodities


like oil)


to avoid


price


risk.


It should


be made


clear


that


these


speculators,


who


are


uninterested


physical commodity,


but have distinct ideas about the price of


the


future,


are


buying


or selling


contracts


with


intention of making an offsetting sale or purchase later


for example,


the offsetting purchase price


less than that


the original


sale,


the speculators will make


a profit.


. If,









demand,


weather


influence,


on.


this


thesis,


three


important


relationships


will


studied:


that


between


futures prices and spot prices--to test the role of crude oil

futures prices in price discovery; that between futures prices


OPEC


supply--to


test


role


OPEC


supply


formation


expectation


price


the


futures;


finally,


that between the spot prices and OPEC supply--to test


influences


sudden


supply


shocks


the


prices.


The relationship between the futures price and spot price


deliverable


good


maturity


futures


contract is one of the long-standing research issues.


It is an


important


question,


since


resolution


important


implications


futures


market


speculation,


efficiency


futures


market


, and


effective


implementation


futures


market


hedges.


The


relationship


between


futures


price


supply


been


paid


much


attention


before.


However,


important.


Undoubtedly,


futures markets


, traders speculate on the supply available in


the near future and determine how much they are willing-to-pay


commodity.


The


market


has


long


been


sellers'


market.


Traders


' expectation of


future prices depends heavily


on the their expectations of future production.


It is observed


that


once


after


annual


meeting


of OPEC member


countries


the


new


quota,


crude


futures


prices


will









applied


the


market.


All


"oil


crises"


the


past


were


due


supply


shocks.


The


spot


pri


ces


respond


almost


immediately


the


supply


. The


opposite


direction


true.


When


price


drops


below


certain


point,


OPEC


will


interrupt


the


price


slide


reducing


supply


and


attempt


to make


the


price


rebounce.


The


res


t of


the


thesi


is organized


follows


. Chapter


II studies


the


relationship


between


the


futures


price


spot


price.


The


relationship


between


the


futures


price


OPEC


supply


is investigated


Chapter


. Chapter


examines


relationship


between


spot


price


and


OPEC


supply.


And


finally


the


conclusions


are


summarized


in Chapter













CHAPTER II


SPOT


PRICES


AND


FUTURES


PRICES:


THE PRICE


DISCOVERY


OF CRUDE OIL FUTURES


PRICES


Introduction


Futures


prices


reflect


opinions


producers,


consumers


speculators


about


prices


different


commodities


the markets at a


later date.


To be of value to


hedgers,


the futures price must respond quickly and accurately


relevant


new


information.


ability


futures


market


process


information


been


investigated


many


researchers.


following two hypotheses have been the focus


their


study:


random walk and market


efficiency.


The random walk hypothesis states that the most accurate


forecast


next


period


price


today's


price.


There


then


correlation


between


price


changes


different


days,


information


past


prices


useful


forecasting


future


prices.


Working


(1934)


and Kendall


(1953)


recognized


that


behavior


prices


very


similar


random


walk.


This


suggests


that


speculators


cannot


use


information


present


past


prices


trade


profitably.


This


conclusion


leads


one


definitions


efficient


market


hypothesis


(Jensen,


1978).


The


so-called


linear process has been assumed in nearly all


the tests.


Many


r









early


1970s papers


by Stevenson and Bear


(1970)


Leuthold


(1972)


Cargill


Rausser


(1975),


however


claimed


that


futures


prices


did


exactly


follow


random


walk,


which


implied


that some


information


took more than one


day


be absorbed


correctly


into


the


prices.


The


efficient


market hypothesis can be true when the random walk hypothesis


invalid,


provided


that


trading


costs


prevent


complete


exploitation of the information reflected relatively


slowly in


the prices.


An efficient market processes


information fairly,


which


means


that


information


can


equally


easily


accessed by different users.


Efficiency ensures that a trader


paying commission should consider the present prices to be the


only relevant


information


in the history


prices.


Hence,


corresponding to these two different assumptions,


there are controversial results discussed in the literature in


terms of


the role of


the futures markets.


Of course,


there


little


dispute


about


role


the


futures


markets


providing


mechanism


risk


sharing.


However,


many


conflicting views


remain about


their role as


a mechanism


predicting


spot


prices,


price


discovery,


other


words,


studied


efficiency


the


futures


performance of the


markets.


live cattle


Helmuth


futures


(1981)


contracts


and drew some rather strong conclusions:


"Based on the theory


efficient


markets,


existence


the


phenomenon









predictable downward bias.


Such a conclusion means that...the


futures


market


fulfilling


economic


purpose


providing


hedging


vehicle


producers.


(page


356)


Helmuth' s


conclusion


methodology


used


study


have


been


criticized


later


many


researchers.


their


studies


, Kolb and Gay


(1983)


wrote:.


"the conclusion supported


by this new methodology strongly opposes Helmuth'


conclusion.


In fact,


it appears that


futures contracts have exhibited


exemplary price work behavior over the period examined.


" (page


Since


issues


market


efficiency


hedging


effectiveness,


and


price


discovery


are


interrelated


sense


that


they


are


tested


similar


identical


statistical


techniques,


this


study


designed


distinguish


one


from


other


. Rather,


puts


the emphasis


adequacy


futures


prices


role


price


discovery.


Price


discovery


process


which


new


information affecting asset values becomes reflected in market


prices.


refers


use


futures


prices


pricing


cash


market


transaction.


There


are


three


points


associated


with


term


"price


discovery.


" First,


order


"efficient" price predicting mechanism,


futures markets do not


have to be always right;


it is


enough that they are just right


on average.


That


one of the


definitions of efficiency is


, in









earn


any


more


than


fair


competitive


premium.


Spectacular


short-term losses and gains,


while surely allowed,


would tend


cancel


each


other


over


the


long


run.


Second,


other


predictors could also be right on average,


which brings up an


interesting point.


two predictors are both


unbiased,


then


usual


way


to decide


which


one


more


"efficient"


choose the one with the smaller variance.


However,


in choosing


between price


forecasts,


a better rule might be to choose the


one


whose


variance


closer


that


price


being


predicted.


one


predictors


futures


market


(whose efficiency


is generally not questioned)


the other


econometric


model


with


similar


variance


spot


price


series,


then


question


arises


whether


forecast


from one method,


, using the


futures price,


could


significantly


improve the performance of the other predictor.


Third


based not


, hedgers


only


(or speculators)


on what


are entering a


they think will happen,


futures market

but also based


what


they


fear


will


happen.


hedger


may


think


that


prices will


fall,


but will


fear such an event to the point of


buying


"insurance"


1.e.,


hedging


futures


contracts.


they


always


did


this,


then


enough


speculator


activity would


push


price


"efficiently


forecasted"


level.


interim


short-term


bias


reflecting


this


insurance


premium would


exist.









stable


long-run


relationship


between


crude


spot


futures


DOE/EIA


prices


(1986)


issued a


direction


causality


report about using


(lead-lag).


Petroleum futures


prices


as the


predictors of


cash


prices.


The


product studied


the


report


distillate


heating


oil.


Like


many


other


studies on the theory of price discovery of futures prices


, it


employed


standard


econometric


methods.


Moreover,


use


any


tests


investigate


long-run


relationships


between


spot


prices


futures


prices.


However,


relationship


is critical


in such studies.


Before


we get


into


practice


test


whether


the


futures


prices


can


provide


information


forming


spot


prices


, we


should


first


make


sure


that


a long-run


relationship


exists


between


two price


series.


If there


is no


long-run relationship at


all between them,


that


the two price series do not


follow


same


moving pattern


over time,


there


then


no point


talking


about how the


futures


prices


can


provide


information


about


the


formation


spot


prices.


Ignoring


first


step


can lead to spurious results.


If futures price series and spot


price


series


share


same


intertemporal


characteristics,


other words,


they


are


not


integrated


same


order,


procedure


that


runs


the


regressions


between these two series


are incorrect due to the violation of


the assumptions underlying the simple regression.


Therefore it









stable


long-run


relationship


between


the


spot


and


futures


prices.


The second part hinges


on the


results


from the


first


one.


there


no strong


statistical


evidence


to show


existence of


such a


relationship,


the


investigation comes to


an end.


If the results from the first part ascertain that such


relationship


well


established,


then


the


direction


causality


role


(lead-lag)


futures


will


prices.


tested


this


examine


dissertation


the discovery


examine


price


discovery


role


futures


prices


the


crude


futures market.by


following these


For the first part,


steps.


several different methods,


including


the conventional


methods


used


DOE/EIA report and some


new


techniques,


exists


stable


will


implemented


long-run


relationship


test

betwe


whether

en crude


there

oil


futures


prices


spot


price.


Provided


that


relationship between them is ascertained,


then I shall attempt


to determine


whether


spot


price


leads


futures


prices


vice versa.


From the results presented,


two points will become


clear.


First,


there


exists


stable


long-run


relationship


between


one-month-ahead


crude oil


futures


price and


the spot


price.


However


, no stable long-run relationships can be found


between


the


spot


price


and


futures


prices


for more


than


one month ahead. Second,


though a stable long-run relationship


exists


between


spot


price


and


one-month-ahead


futures









The remainder of this chapter is organized as follows.


first provide a brief overview of the data used in this study,

indicating a relationship between the futures and cash markets


"raw


data"


basis.


Second


present


the


conventional


methods


used


DOE/EIA


report


(1986),


namely,


simple


regression and combined regression or


simulation.


Even though


results


obtained


from


them


are


only


suggestive


can


still


get


some


intuitive


perspective


the


movement


price series.


Third,


the methods used to test the relationship


between


prices


are


described.


Among


them


are


integration test and


the cointegration test.


In order to test


direction


causality,


the


Garbade


and


Silber


approach


and the Granger causality test are implemented in the next two


sections.


Following


this,


we apply


an error correction model


investigate


the


dynamics


long


run


relationship


between


spot


price


futures


price.


The


chapter


concludes


with


assessment


usefulness


futures


prices


forecasting


the spot


price.


Data Analysis


Futures trading has exploded


since 1970


. Both the number


of futures markets and the participation has increased rapidly


since


then.


energy


futures


market,


contracts


petroleum products


for delivery


to 12


months


in the


future









since March 1983.


In less than ten years,


this futures market


has become the keystone of a new international pricing system


that,


time


being


least,


has


ended


the


price


domination of the Organization of Petroleum Exchange Countries


cartel.


Due to many uncertain factors,


such as the instability


prices


due


to political


influence


, natural


disasters


accidents,


wars,


and


intensified


competition


from


other


forms


ideal


substitutable


tool


energy


risk-sharing.


crude


Based


futures


provide


this,


thus


reasonable to say that the


futures prices can be also serving


as good


predictors


for the


spot


prices.


The following preliminary figures and tables suggest that


there


close


relationship


between


the


spot


and


futures


prices.

prices


Figure

series


2-1

since


shows

1984.


the

Two


monthly

things


values


are


apparent


the

from


spot

it.


First,


crude oil


prices


have been declining


since


late-1985;


Second,


this


decline


has


been


irregular.


The


fact


that


spot


prices


followed


negative


trend


over


this


period


important because


it helps


to explain


why the


futures


prices


follow a negative trend as well.


The longer the length of the


futures contracts,


time


smaller the


futures prices were


t+1+n-month-ahead


futures


(that


price


generally


less than the t+1-month-ahead price) which indicates


that


over


time


futures


market


has


been more


pessimistic

























































J0-


Figure


. Crude


r .-
*0t I*


Oil Spot


Prices


-iC c


, ^^









futures prices would exceed spot prices by a small amount.


reason is that,


in order for the speculators to participate in


futures market


, they will


expect to receive a premium for


bearing


a portion


market


risk


due


the


fluctuation


prices.


Also,


since


these


are


nominal


prices,


would


expected


that


futures


prices


should


experience


some


upward


pressure because of the inflation rate


However,


both of these


upward


biases


can


overstated


because


they


could


offset


least


other


factors.


First,


cost


storage,


upper


together


bound


with


futures


current


price,


spot


since


price,


there


acts


would


incentive to buy futures contracts which exceed the sum of the


spot price


the storage cost.


Second,


there may


be strong


expectations in the marketplace that prices are going to fall.


This was


case


from 1984


through 1989.


The spot pri


ces


are


plotted


against


, 3-


, 6-


, and


9-month-ahead


futures


prices


Figure


through


2-5,


respectively.


One


problem concerning the


futures prices


is the choice


of the daily futures prices in a month which should be used to


represent the future price


for that month.


If futures markets


are efficient


, then


it should be


true


that all


the contracts


prices


(1-month-ahead,


2-month-ahead,


etc.)


on any given day


contain


information


known


about


the


market


that


time.


Averaging


prices


throughout


the


month









which


contains


time


series


futures


prices


independent variable,


he needs only to choose the most recent


price


current


observation.


Following


this


argument,


only


the


futures


prices


available


one


reporting


per


month need


to be used


to represent a monthly value


in a


time


series.


For most of this study,


the price reported on the 15th


each


month


will


used


the


15th


day


is a


trading


not,


then


the


closest


adjacent


day


from


15th


which


is a trading day will be used.


Picking mid-month values


less


prone


to bias


than


first-


or end-of-month


ones


since


large


institutional


investors


often


use


computer


trading


programs


close


their


position


certain


months,


giving


rise


to extreme


fluctuations


prices of


futures contracts


on these days.


Table 2-1 provides the mean, standard deviation, maximum,


and minimum


for the


following prices:


spot


price and


futures


prices


, 6-


, and


9-month-ahead


contracts.


month-ahead contracted is not used because it is very closely


correlated with the 1-month and 3-month-ahead ones.


The 4-


, 5-


, and


8- month


contracts


are


examined


either because


they


are


found


to be


closely


correlated


with


month contracts.


In this analysis,


the actual series used are


lagged


number


months


futures


contracts.


instance,


December


1985 1-mo


nth


futures


price


that


. If


, 6-









contract observed in November is used for predicting


(or being


correlated


with)


cash


prices


one


month


later.


Cross


correlations


for these


series are shown in Table


2-2.


As shown,


the mean of


crude oil


spot price


from January


1984


through July


1989


$19.33


barrel,


while


mean


futures


prices


, 3-


, 6- and 9-month ahead are slightly


larger


than


mean


spot


price,


expected.


The


table


also shows that the correlation between these series falls off


from


0.95


1-month ahead


, progressively declining to 0


9-month


clearly


that


ahead.

the ]


Figures


1-month-ahead


through

futures


2.5 a

price


Ilso


demonstrate


closely


mimics


actual


spot


price,


while


correlation


diminishes


gradually


9-month


graphs.


graphs


also


show


more.


First


late-1985,


futures


prices


falsely


months


signaled a large drop


ahead


in the spot price,


futures prices are,


and the more


larger the gap


between


futures


spot


ces.


Second,


futures


prices


repeated


this


false


signal


late


1988


, though


smaller


degree.


Third


, the


futures


prices


did


correct


such


wrong


signals


after


certain


period


time,


although


the


more months


ahead


futures prices took


longer time


to adjust.


Another preliminary way to view the futures markets is to


calculate


ratio of


futures


prices divided by spot prices


the


same


month.


Under


ideal


conditions,

























r. )


I
1 -:
.-- -I.


i .39 14
I


~1


A\

7
A


193a


I-'.ont h-Out


Figure


Oil Spot


Futures


Prices


S.-


I.-.


---SCot


1i87


';aa



























4 7 9


I
-
i










.7'^
^ */I


7


- 7


3-.ontn-Out Futures


---- oot


Figure


Oil Spot


Futures


Prices


1994


19i8


1997


1988


1985


































32 -T--





30 4--


E
;

*
?
^
f
I


N ~


7


'


-V
3


1S87


rfutures


Figure


Oil Spot


Futures


rices


22




20


1s --
^ I



144


12


13T


a -*^ "TTf-- r- i


1984


1995


---- :oot


I 92






































N-
-.4,


1,


'1
*
*\ ~ -
'7
'i <7!


1987


-- Soot


Futures


Figure


Oil Spot


Futures


Prices


1984


1985


19g6


?^si


7


9-*.tantr.-Out









standard deviations for these calculations.


Not surprisingly,


ratios


1-month-ahead


and 3-month-ahead are closest


, and as expected,


ratio of


1-month-ahead


futures


small


est standard


deviation.


Figures 2-6 through 2-9 show the ratios of futures prices


spot


prices


corresponding


time


periods.


obvious that the more months ahead the futures prices are,


larger the fluctuation is.


There is a slightly downward shift


in the graphs indicating that over time the futures market has


been


pessimistic


about


crude


prices


than


actually


warranted.


Spot


prices


were


falling,


the


futures


prices


expected


them


fall


even more during this


period.


Usinq


Crude Oil


Futures


Prices


Predictors of The


Spot


Price


this


section,


results of


a number


of alternative


methods


test


relationship


between


crude oil


futures


prices


spot


price


are


presented


analyzed.


The


specifications


include


simple


regression


update


current


data series,


and a simulation which uses formulas to "combine"


regression results and known futures prices.


These two methods


are


used


EIA/DOE


report


(1986).


The


advantage


these


methods


simplicity


, even


though


usefulness


results


limited.


Despite


their


shortcomings,


these


1 4 *i- 4 7


methods


halo


travel 1


t-ho


potential


Orosoective


A.. A L Lt t&1- L-. .1 V t~. JLt t- L^. A. I-/^- t A. A .. __ h t.. V .. t' ..f La .*_ .5.. hJ ._ -A V


F -- %.F I.. .JL y


























1- Ltrnth-Cut Futtres


2-

1.9 -

1.9 -

1.7 -

1.6 -

1.5 -

1,4 -

1.3 -
1,2

1 1

1 -

0 9

0.8 -

07.1

0.6 -1

03 4


1984


1985


198e6


1987


r- \ \,
V
f / 1


1is8


Figure


Price Ratio:


Futures/Spot


939























3-AtMot n-Out Futures


t12 -


1 -
o09-
0 a -


1984


1985 1986 1987 1988 '=


Figure


Price


Ratio


Futures/Spot






















6-MLcntn-Out ;utures


1985 1988 6987 1988 1989


Figure


Price


Ratio:


Futures/Spot


1984


0.9 -

0,8 -

0.4 -









































Figure


Ratio


Futures/Spot









negative,


suggesting intuitively that these two variables are


related at all,


then there


is no


need to go any


further.


Usina


Futures


Prices


to Update Current Data


The


first method


that the


futures data


could be used


to update


data


series


those


cases


when


official


data


current


calendar month


few months.


To determine


futures prices could be used


this manner


four


estimations


are


attempted.


The crude oil


prices


reported by


IECCM of


World


Bank are


regressed


the New


York Mercantile Exchange


futures


prices


for crude oil


using


1-month,


3-month,


6-month


and 9-month ahead contract price.


Thus to fill in missing data


points


the


following


equations are estimated:


= a + 3 FPt-


2-1)


FP,6


83 FPt9


(2-4)


where


= crude oil


FPt,J


price at time t;


= j-month-ahead futures prices for delivery at time


= regression coefficients.









futures


price


delivery


the


current


month.


Tabli


gives


the


results


of the


estimation


. When


equations


are


estimated


and


corrected


expected


autocorrelation


, the


6- month


ahead


futures


crude


prices


are


seen


significant


predictors


spot


price


prices


. Thus


can


appears


used


that


the


fill


1- and


the


6- month


missing


data


ahead


contract


values;


When


the


step


ahead


pri


ces


are


used,


the


estimates


are


statistically


significant


. Two


interesting points here are


worth mentioning.


Firs


, while


the 3


-month


-ahead


futures price


no significant


effect


on the spot


price


6-month


ahead


futures


price


does


. One


possible


explanation


is that


there are


coincidentally


period.


two


Inflationary


competing


forces


expectations


work


and


risk


over


time


premium


would


both


tend


increase


distant


futures


ces


, while


long-


run


negative


trend


spot


pri


ces


would


work


ress


futures


prices


. If there


been


a strong


upward


trend,


then


the 3-month


-ahead


futures


price


might


have


had


a significant


role.


Second,


while


both


6-month


ahead


futures


prices


are


Thi


significant,


the coeffi


may


the


cents


have opposite


timing


people


signs however


expectation


formation.


is obvious


that


takes


a while


before


people


absorb


new


information.


When


crude


price


ses


unexpe


ctedly


month,


people


may


expect


to drop


late.









Combining


Model


Results


and


Futures


Prices


the


above


discussion


futures


prices


were


viewed


potential


inputs


energy


models.


Along


with


other


energy


related


data


, decision


makers


would


also


have


knowledge


about


futures


prices


when


they


make


price


forecast


. Now,


however,


futures


markets


will


viewed


competing


forecasting


mechanism


. The


question


we are


asking


whether


the


futures


prices


obtained


from


regression


model


add


anything


to the


prices


combined


attempt


forecast


answer


based


the


question


estimated


studying


results


futures


prices.


Two


estimated


and


. In


crude


both


ces


cases


are


reported


used here:


below,


those


1-month


from


-ahead


futures


prices


make a


significant contribution


to the


combined


forecast,


but


the results


with more


-than-


1-month ahead


futures


prices


are


ambiguous.


Simulations


from


are


used


to generate


estimation


results


. First,


two


equations


are


estimated,


each


form:


t = a + f


SMPt


where


the


price


estimated


from


one


the


model


and


2-3).







34

associated forecast adds anything to the combined forecast in


a statistically


significant manner.


The


test of


significance


for the


coefficient


combined


is also


forecasts.


a test

the e


the


unbiasedness


estimate


statistically different from zero,


then no bias


is indicated.


In contrast,


it is statistically different


from zero,


then


either


an upward


or a downward


bias


is present.


The


results


are given


in Table


2-5.


From


tables,


we can


see


that


1-month-ahead


futures


prices


consistently


make


statistically


significant


contributions


the


combined


process


(Case


Case


However,


the 1-month-ahead futures prices generate a bias when


they


are


combined


with


(2-3)


(Case


The


bias


combinations


would


have


been


serious


problem


there


had not been

be slightly


"risk


consistent trend,


higher than


premium"


since


futures


spot prices due


Interestingly,


the


prices should


presence of


3-month-ahead


futures


prices turn out to be significant in Case


which combines


Strangely


enough


9-month-ahead


futures


prices


are


also significant in the model


which combines with


(2-3)


(Case


However,


since


sign


bias


not


consistent


across


two


models


when


more


distant


futures


prices


were


used.


Therefore,


again


that


the


general


weakness


predictive ability of


futures prices more than 1 month out is









Relationship Tests


The


results


the previous


section assume stationarity


spot


futures


prices.


Even


though


we may


get


some


intuitive idea of the price performance,


the basic assumptions


underlying the simple regression are no longer valid,


prices are nonstationary


when the


. The results obtained in the sections


above are


useful


only


if both spot


prices


and


futures


prices


are


stationary


levels.


However,


this


not


case,


the results of the of the simple regression would be spurious


misleading.


Therefore,


necessary


test


stationarity and the nature of the stochastic movement of the


prices.


Hence,


will


employ


the


integration


cointegration tests below to take these aspects into account.



Integration Test


Many


macroeconomic


variables


are


often


found


nonstationary


levels.


empirical


fact


that


these


variables


appear


integrated


order


(stationary


the first differences),


or to possess unit roots.


Integration


tests


are


designed


help


evaluate


the


nature


nonstationarity of economic variables.


In other words,


whether


they are stationary in levels or in differences of some order.


Suppose


there


are


two


economic


variables


which


are


nonstationary


question


ask


whether


they


move









of two economic variables.


In the example here,


we try to link


the crude oil spot price Pt


and the futures price and test the


relationship


between


them.


stable


relationship


exists,


then it may be possible to make quantitative inferences about


crude


price


from


the


observations


futures


prices.


will


implement


integration


test


examine


stationarity of the crude oil spot price and futures price.


form


must


long-run


share


equilibrium


same


relationship,


intertemporal


the


characteristics.


variables


That


they


must


integrated


same


order.


The


dynamic


property


single


series


can be described by how often


needs


difference


achieve


time-invariant


linear


properties and provide a stationary process. A series that has

at least invariant mean and variance and whose autocorrelation


"short


memory"


called


I(0) ,


"integrated


order


zero"


. If,


on the other hand,


a series needs to be difference


times


to become


I(0),


said


to be


integrated of


order


denoted


I(A)


The order of


integration is


inferred by testing for unit


roots.


The most widely


applied


unit root tests


are:


CRDW:


Durbin-Watson Test of


Sargan and Bhagrava


(1983);


Dickey-Fuller test;









these


tests


the


null


hypothesis


that


series


are 1(1) ,


that


- I(1).


The three statistics


used


in this


analysis are as


follows


CRDW:


I(1),


CRDW


.532


at 99%


level;


pet.


+ vt


I(1) ,


negative


statistic lower than


and

(95%)


or -4.07


(99%) ;


ADF


+ Sl=1YiAet-


~ I(1)


negative


and


statistic lower than -3


or -3.37


(99%) ;


where et


are


the


residuals


from X


regression


(CRDW)


and n is


selected


to be


large


enough


ensure


that


the


residuals


are white noise


. A statistically significant and negative sign


coefficients


3 signifies


that changes can be


reversed


over time,


and


level


is stable.


The


Sargan-Bhagrava


(CRDW),


Dickey-Fuller


(DF)


Augmented Dickey-Fuller


(ADF)


test statistics are reported in


Table 2-6 and


2-7.


The results


in table 2-6 show that all


series


are


nonstationary


level


significance.


Therefore,


the rates of change of all


the variables are tested


: Xt


= a + et


= -- +









same


level


integrated


significance.


first


order,


Thus,


that


the


I(1)


prices


This


are


implies


that


the


levels of


crude oil


spot price and each


four


futures


prices


show


similar


temporal


properties.


Therefore,


the level of the spot price and futures prices are expected to


be statistically


linked over the long-run,


and that the ratios


of spot


price and


futures


prices are expected


to be constant


over time


the


long-term.


Cointecration


Test


After establishing that crude oil spot price and futures


prices are


integrated


, both of the first order


, the next step


is to examine whether they are also co-integrated.


The idea of


this


test


that


individual


economic


time


series


can


integrated of order one,


1(1), but certain linear combinations


of the series may be stationary,


i.e.,


I(0).


That implies that


linear


combination


individually


nonstationary


economic variables may be stationary


. Formally,


two variables


are


said


co-integrated


there


exists


constant


such


that


C Q,


integrated


order


zero


I(0).


then


stationary


with


positive,


finite


spectrum


zero


frequency.


This


rather


special


condition,


because


implies


that


both


series


individually


have


extremely


important


long-run


components.


However,









similar


the


one


applied


test


for


integration


followed


. In


first stage


, the coefficient C


is estimated


by OLS;


the


second stage,


the


resulting


series


FPt.


tested


I(0)


rather


than


I(1).


The


same


procedure


employed in


the section above,


is used here to test Zt.


Table


2-8 gives


results of


the test.


It is clear


, from the table below,


that the only futures


price


variable


with


statistics


CRDW,


ADF


being


significant


percent


confidence


level


the


1-month-


ahead


futures


prices.


None


the


other


futures


price


variables


have


significant ADF values


. Therefore,


can be


concluded


that


only


1-month-ahead


futures


price


cointegrated


with


the spot price;


the hypotheses


about


other


futures prices,


however


, cannot be accepted at the 95 percent


significance


level.


The


findings


that


the


spot


price


and


1-month-ahead


futures


price


crude


are


I(1)


and


certain


liner


combination of them is I(0)


have clearly demonstrated a long-


run


relationship


between


the


spot


and


futures


prices


remaining


question now


is what


direction of


"causation"


this


relationship


follows,


that


which


price


leads,


which


price


follows.


attempt


to answer this question


in the next


section.


= p









Causality Tests


been


ascertained


above


that


stable


long-run


relationship exists


between the spot


price and


month ahead


futures prices.


The next problem is to determine the direction


of causation between the spot price and the futures price.


this


section


the Garbade and Silber approach and


the Granger


causality test


procedure


will


be employed


investigate the


direction of


causality.


Since a long-run relationship


is only


found between the spot price and 1-month-ahead


futures price,


denote


1-month-ahead


futures


price


later


on in


this chapter


, unless


otherwise


indicated.


The Garbade and Silber


ADDroach


essence


the


price


discovery


function


futures


markets


hinges


changed


on whether new


futures


prices


information


changed


reflected


cash


first


prices.


Garbade and Silber approach provides a framework for analyzing


whether


one market


is dominant


in terms of


information


flows


and price discovery


. The model can be applied to the crude oil


markets,


with


one


minor


modification.


The


prices,


both


spot


and futures,


are often reported on a monthly basis while this


only


lengthens


the


transaction


period,


the


fundamental


characters of the monthly data are identical


to those of daily


reported price.












,t-1


(2-6)


where St is the logarithm of the spot price for month t and Ft


the


logarithm


the


1-month-ahead


futures


price


for the


same month.


The constant


terms,


and af,


have been added to


equation


(2-6)


to capture any secular price trends in the data


and any persistent differences between spot price and futures


price


attributable


different


quotation


conventions.


coefficient fs


and f3 reflect the influence of the lagged price


from


one


market


the


current


price


the


other


market.


Since


spot


futures


market


prices


are


same


commodity,


one


would


anticipate


that


both


and


f are


non-


negative.


The


ratio


ps/(p


can


used


examine


price


discovery


relationship between


the


two markets.


ratio equals


unity


that 40f


= 0),


convergence


of spot


futures


prices


occurs


because


spot


price


always


moves


towards the futures prices.


This


is an extreme case where the


spot


market


"pure


satellite"


the


futures


market.


ratio


s/


+ Pf)


equals


zero


that fs


= 0),


then


futures prices always adjust


towards


spot


prices and


futures


market


pure


satellite.


Intermediate


values


between


Zero


- -.


one


imply


mutual


adjustments


and


feedback









Equation


(2-6)


can be


solved


function


- St-1


to yield:


t St


where a


- as'


- Ps'


and et


= ut


- Vt


. As can be


observed


convergence


equation


between


2-7)


spot


reflects


futures


the


prices.


speed


small,


relatively


little difference between


futures


and spot prices


month


persi


month


Prices


will


therefore


converge quickly.


We rearrange equations


(2-6) algebraically


as follows,


that


they


can be estimated via


ordinary


-S -] +


least


squares:


The estimates 6 obtained with ordinary


least squares are


summarized in Table


(2-9) .


p /(Cps


+ ,f)


represents the relative


contribution


futures


market


price


discovery


process,


and 6 measures the rate of the convergence of futures


and spot prices.


Two results have emerged.


First,


the estimate


of 3, is


significantly positive.


This


finding


shows


that


of Ft.


6 (Ft1


- St-1)


= (,f


t-S,


+ et


F -F
* t c-1


wa v









positive nor significant,


suggesting that little


feedback of


pricing information occurs from the futures market to the spot


market.


The derived estimate of the parameter 6


indicates that


less


than


half


differential


between


futures


spot


prices


month


arbitrage


persists


undertaken


rather


month


quickly


This


to bring


implies


about


that


price


convergence between


two markets.


Granqer Causality Test


The


lead-lag


relationship


can


also


examined


through


Granger's


causality


test,


which


states


that


the


stationary


linear combination of


levels must Granger-cause the change in


at least


one of


the cointegrated variables.


is well known


that


causality


sense of


Granger


from a


variable


1 to


variable


2 can


arise


two


reasons.


The


variable


may


cause


in the common-language sense,


or instead the variable


may


anticipate


forecast


former


case


intervention which changes the stochastic process for


z2 will


change


while


latter


case


intervention


which


changes the stochastic process for


will change the behavior


The Granger's test is designed to examine whether two time


series


are generated separately from each other


. When they are


generated separately,


one time series provides no information


characterizing the other.









Following


Granger


(1969),


the


simple


causal


model


liPt-i
1 1 t -i1


l JF


, (2-10)


where


denotes


crude


spot


price


and


1-month-


ahead


futures


price,


and


are


taken


uncorrelated


white-noise


series.


some


of $


are


zero


, then


said


cause


. Similarly


some


are


zero


, then


said


cause


events


there


feedback


both


relationship


occur,


between


then


said


t and


. The


that


usual


F-test


can


be applied


to test


the


null


hypothesis


that


does


cause


.e. ,


= 0 for


, or F


t does


cause


, izJ


= 0


Equation


2-10)


are


estimated


least


squares


method


under


restrictions


. = 0
J


respectively.


Table


summarizes


the


results.


From


table,


clear


that


the


restrictions


imposed


equation


2-9)


are statistically


significant at 81


confidence


level.


contrast


those


equation


(2-10)


are


statistically


significant


According


definition


Granger


causality


, thi


suggests


that


spot


price


causing the


future


price,


but


the


futures


price


is not


causing


il n ( i t-i


.e.


= s


= 2









futures


prices


not


play


important


role


price


discovery and the spot market always leads the futures market.


The


Error Correction Model


Now


that


long


run


relationship


between


crude


spot


price


1--nonth-ahead


futures


price


and


direction of the causality have been established,


we are


in a


position


to study the dynamics of


the stochastic movement


prices.


Since


the crude oil


spot


price and


1-month-ahead


futures price are cointegrated.


An error correction model can


be used to examine more closely the relationship between these


variables.


The


error


correction


model


(ECM)


cointegrated


variables


commonly


interpreted


reflecting


partial


adjustment


one


variable


another.


Campbell


Shiller


(1988)


show


error


correction


models


may


also ari


when


one variable forecasts another


. The concepts of cointegration


and error correction are closely related.


Indeed,


It has been


proven that two variables which are cointegrated have an error

correction model representation. An error correction model for


two variables


relates


the changes


in the variables to


lagged


changes and a lagged linear combination of levels.


The linear


combination of levels which enters the error correction model


just


that


combination


which is


stationary


levels.


__









correction


model


can


thought


description


stochastic process by which the variables eliminate or correct

the equilibrium error.


Let us consider the crude oil spot price Pt


and 1-month-


ahead


futures


price


FPt


know


that


both


them


are


integrated of


order


one and


therefore


they


are cointegrated,


their


linear


combination


integrated


order


zero.


Therefore


residuals


they


from


are


the


said


cointegrated


cointegrated.


regression


Define


- C FPt


the equilibrium error


which enters the error correction model


below:


-- -YZt-1


+ y=1" 6 APt
'~ =1 T"i t-i


+ s.n l AFPt.J
i j + jS lAFPt-
S+sE-s 0 AFP
t ]j=1 2J t


(2-11)


(2-12)


where Y '


6i and 8. are coefficients,


et and et are assumed


to be white noi


ses.


equations


have


been


estimated


descending


order


of generality.


The


results are given


the Table 2-11


below.


model.


Two main


First,


conclusions


error


follow


correction


from


the error correction


term


statistically


very significant in equation


(2-11),


but neither the value of


its coefficient nor the t-statistics of the equation


significant.


(2-12)


equilibrium.


suggests


that


disequilibrium


distance


.e.


AFPt


-Y2Zt-


Since the value of Zt measures the deviation from


ir =6


1 + s


iAP.









fluctuation


of the


crude


spot


price


in the


real


world


. In


contrast,


futures


market


deviates


ess


away


from


equilibrium


"risk

equatic


and


sharing"


role


much


thus


more


futures


better thai


stable.


Thi


markets.

n equation


justifies


Second,


-11) ,


overall,


terms


the


stati


(unadjusted


stical


and


adjusted),


significance


the


the


model.


standard


Thi


error


throws


, and


light


lead


-lag


questi


on.


The


changes


futures


price


are


well


explained


changes


the


lagged


spot


prices


futures


pri


ces


Moreover


, while


the


lagged


spot prices


play


important


role


equations


-12)


, the


changes


lagged


futures


prices


are


significant


equation


-11)


Therefore


spot


as in the


market


previous


dominates


section


the


, we have


futures


found


market,


again


but


that


vice


versa.


Having


analyzed


dynamics


the


price


movement,


next


estion


about


forecast


stability


illustration,


both


equation


-11)


and


-12)


are estimated by


using


the


monthly


data


from


1984


to 1988,


excluding


first


seven


months


1989


. The


results


, provided


Table


-13),


are


identi


to those


obtained


when


the


whole


sample


used


The forecast


values


of changes


in both


spot


futures


prices


are summarized


in Table


-13)


. The variance of


the difference


between


actual


predicted


values


from


equation


-12)









equation


(2-12)


doing


much


better


than


the


other


one


erms


of prediction


. Above


all,


we conclude


that


equation


should


be used


to capture


dynamic


interaction between


these


prices.


Summary


Thi


chapter


been


divided


into


two


related


parts.


First


, it has


investigated


whether there


exists


a stable


long-


run


relationship


between


crude


spot


price


futures


prices


. 1-


, 3-


9-month


ahead


futures


prices


have


been


used


carry


out


test.


Both


conventional


cointegration


test methods


have


been


performed


. We


find


that


while


there


exists


a stable


long


run


relationship


between


spot


price


-month-ahead


futures


price


, no


such


relationships


exists


between


spot


price


other


futures


pric


es.


Second,


a dynamic


regression


testing


scheme


Granger


causality


test


have


been


applied


further


investigate


price


lead


-lag


relationships


between


the


spot


1-month-


ahead


futures


price.


The


results


from


both


tests


leads


us to


conclude


that


crude


spot


price


generally


leads


futures


price


incorporating


new


pricing


information,


that


crude


spot


market


always


dominates


futures


markets


These


results


suggest


that


the


crude


futures









Table

Selected Statistics


2-1

for Crude Oil


Spot


and Futures


Price


Price Series Mean S.D. Max. Min.


Spot
Futures


19.33


6.24


8.72


1-Month-ahead
3-Month-ahead
6-Month-ahead
9-Month-ahead


21.39
21.04
20.93
21.05


5.98
5.96
5.95
5.85


31.35
30.73
30.73
30.62


11.04
10.58
10.86
10.92















Table


Cross-Correlations
Spot and Futures


for Crude Oj
Price Series


Spot 1-Month 3-Month 6-Month 9-Month

Spot 1.00 0.95 0.85 0.69 0.62
1-Month-ahead 1.00 0.87 0.70 0.70
3-Month-ahead 1.00 0.85 0.73
6-Month-ahead 1.00 0.89
9-Month-ahead 1.00















Table


Selected Statistics
Futures


2-3


for Crude Oil Spot and
Price Ratios


Ratio


to Spot


Price of:


Mean


S.D.


Max.


Min.


Futures:


1-Month-ahead
3-Month-ahead
6-Month-ahead
9-Month-ahead


0.43


0.91
0.37
0.63
0.63


2.53
2.94















Table


Regression
Oil


Coefficients


Futures


Prices


6- and


as Predictors


9-Month Ahead


Crude


of Spot Prices


Variables Equations

(2.1) (2.2) (2.3) (2.4)

Constant 10.16* 13.23* 18.18* 15.06*
(3.09) (4.07) (5.12) (4.16)

FPi 0.31*
(3.49)
FP,3 0.11
(0.98)
FP,6 -0.29*
(-2.32)
FP9 -0.02
(-0.17)
1st-Order
Autocorrelation 0.94 0.95 0.96 0.94

R 0.96 0.95 0.94 0.93

R2 0.96 0.95 0.94 0.93

D-W 1.73 1.15 1.03 1.13

Std. Error 1.28 1.40 1.38 1.47

Estimation Technique Cochrane-Orcutt


Notes:


: t-Statistic


in parentheses.


* denotes


that


coefficients


the 95 percent or higher
: The notations are for all


are


confidence


tables


significant
level.


this


dissertation,


not otherwise


indicated.














Table

Regression Coefficients


2-5

for Equations Combining


Crude Oil


Price with Futures


Prices


Regression Coefficients
Case a p, 1

1 -0.62 0.55* 0.43*
(-0.80) (4.20) (3.08)

2 -0.03 0.89* 0.10*
(-0.04) (26.10) (3.23)

3 0.42 0.94* 0.03
(0.57) (30.11) (1.30)

4 0.71 0.95* 0.01
(0,90) (30.25) (0.44)

5 -1.63 0.49* 0.54*
(-2.13) (4.12) (4.54)

6 -0.38 0.92* 0.09
(-0.45) (10.35) (1.09)

7 -0.09 1.00* 0.01
(-0.11) (15.89) (0.16)

8 1.19 1.06* -0.11*
(1.50) (26.44) (-3.64)

Key:
Case 1: (2-1) and 1-month-ahead futures prices
Case 2: (2-1) and 3-month-ahead futures prices
Case 3 (2-1) and 6-month-ahead futures prices
Case 4: (2-1) and 9-month-ahead futures prices
Case 5 (2-3) and 1-month-ahead futures prices
Case 6 (2-3) and 3-month-ahead futures prices
Case 7: (2-3) and 6-month-ahead futures prices
Case 8: (2-3) and 9-month-ahead futures prices















Table


Results of Integration Tests for
Crude Oil Spot and Futures Prices


Series CRDW DF ADF
(crit. value (crit. value (crit. value
99%: 0.532) 99%: -4.07) 99%: -3.77)

P 0.050 -1.37 -1.44
FP1 0.094 -1.62 -1.72
FP3 0.077 -1.52 -1.72
FP6 0.060 -1.36 -1.69
FP9 0.564 -1.03 -1.49















Table


Results of
Differenced


Integration Tests


Crude Oil


Spot and


First Order


Futures


Prices.


Series


CRDW


ADF


(crit


. value


(crit.


value


(crit


. value


99%:


0.532)


99%:


-4.07)


: -3.77)


-4.99
-6.61
-6.69
-6.55
-6.67


-4.64
-4.90
-4.80
-4.24
-4.03















Table


Results of


Cointegration Tests


for Crude Oil


Spot and Futures


Prices.


Series CRDW DF ADF
(crit. value (crit. value (crit. value
99%: 0.532) 99%: -4.07) 95%: -3.17)

Case 1 1.507 -9.59 -3.45
Case 2 1.173 -5.32 -2.84
Case 3 0.964 -4.47 -2.87
Case 4 0.119 -4.70 -2.80

Key:
Case 1: Spot Price vs 1-Month-Ahead Futures Price
Case 2: Spot Price vs 3-Month-Ahead Futures Price
Case 3: Spot Price vs 6-Month-Ahead Futures Price
Case 4: Spot Price vs 9-Month-Ahead Futures Price















Table 2-9


Estimated


Coefficients


Futures and Spot Prices


Garbade and Silber's Approach


Parameter Period
1984M1 1989M7

Ps -0.033
(-0.29)

f 0.684
(7.92)

os!(oof) 0.oo**
6 0.40


Notes:
Silber


the


s procedure


calculated


value


requires both f3ps


0.05,


but


and Pf are


Garbade


positive.
















Table


2-10


Causality On


Crude Oil


and Futures


Prices


Dependent Variable
Independent
Pt F
il-lltl -illlillli


Constant


0.41


.44)


.11
.80)

.15


.82)


-1.13)


.05)

.10


-0.72)

.38


0.88

0.88


S.E.


likelihood


-143.70


-164.49


Significance
of restriction















Table 2-11

Error Correction Model


Equation (2.6.1) (Sample 1984M1


1989M7).


= -1.243Zt.i + 1.688APt i


(-1.93)


(2.71)


- 0.074APt.2

(-0.31)


- 0.300APt3

(1.22)


-0. 456AFPt.,1


- 0.123AP.2, + 0.035APt.3


(-1.73)


(-0.69)


(0.34)


= 0.30 R2


= 0.20 S.E.


= 1.30


D.W.


1.93


Equation (2.6.2) (Sample 1984M1


1989M7)


AFPtI


= -0.078Z.1 + 1.198AP + 0.382AP_2 + 0.138AP.3
t-1 .-1 X-2 t-3


(-0.15)


(2.42)


(2.03)


(0.70)


-0.433AFPt.,1

(-2.06)


0.129APt2,i

(-0.92)


- 0.153APt_3

(-1.88)


= 0.74 R2


= 0.70 S.E.


= 1.03


D.W.


=- 2.05















Table 2-12

Error Correction Models and Forecasting Stability


Equation (2.6.1)


(Sample 1984M1


1988M12)


= -0.243ZtI + 0.729APt.1


- 0.108APt_2 + 0.534APt3


(-1.29)


(3.33)


(-0.38)


(1.74)


-0.160AFPt ,

(-0.69)


0.299APt.2,1

(-1.42)


0.002APt3

(-0.22)


= 0.28 R2


0.18 S.E.


1.34


D.W.


1.91


Equation (2.6.2)


(Sample 1984M1


1988M12)


AFPtl1


= 0.143Zti + 1.012APt1 + 0.340APt2


0.024APt3


(1.00)


(6.10)


(1.57)


(-0.102)


-0.292AFPt.,I

(-1.66)


- 0.030APt_,i

(-0.19)


- 0.143APt3

(-1.66)


= 0.75 R2


= 0.72 S.E.


= 1.03


D.W.


= 2.10















Table


2-13


ECM Predicted Values of


Changes


in Spot And Future Prices


Spot


Price


Futures


Price


Time


Actual


Pred.


diff.


Actual


Pred.


diff.













CHAPTER III


FUTURES


PRICES


AND OPEC CRUDE OIL SUPPLY


Introduction


The


relationship


between


futures


prices


OPEC


crude


supply


is not


as clear


as the one between


futures


prices


and crude oil spot price.


And little research has been done in


this


field yet.


Naturally,


different assumptions will


lead to


different


conclusions.


instance,


crude


futures


prices


follow


random walk,


there will be no relationship at all between OPEC


supply and futures prices.


As a result,


nothing can be used to


predict


the


futures


prices.


contrary,


traders


are


assumed to have rational expectations then there is


a definite


relationship


between


futures


prices


OPEC


crude


supply.


can


argued


that


speculators


their


futures


prices


based


on their


expectations of


the market


near


future.


demand


crucial


factors


undoubtedly play


very


markets


important


like


role


supply


process


trader's


expectations.


The


purpose


this


chapter


investigate


relationship between OPEC supply


and


futures prices.


It will


become


clear


that


even


though


some


relationship


between









elementary


methods


, these


variabi


are


not


expected


stationary


. Thi


suggests


that


the


results


obtained


elementary


methods


can


wrong.


the


last


Chapter


, we


shall


first


try


to det


ermine


a stable


relationship


exists.


Unfortunately


most


of the researchers on price discovery


have


ignored


this


step


went


to the


test


of causality


directly


However,


results


stabi


obtained


relationship


Garbade


does


and


exist,


Silber


then


approach


Granger


causality


test


nay


incorrect


conclusions


The rest


this


chapter


is organic


zed


as follows


. First,


study


some


prior


information


about


data


using


some


preliminary


methods


such


stati


stical


analy


S1S


, graphic


illustrations and


simple


regressions


Second


, the


results


from


simple


regression


are


presented


next


. The


character


stics


time


series


under


consideration


will


tested


following


section


with


integration


cointegration


tests


. Even


though


futures


prices


and


OPEC


supply


are


found


cointegrated,


which


suggests


that


there


long


-run


stable


relationship


between


them


the


Garbade


Silber


approach


Granger


causality


test


are


used


anyway


the next two


sections


tc show


one


can


get


leading


results


finally


, the conclu


sons


are


ese


nted


bri


efly


Data


Analysis









analysis


simple


include


regressions.


graphs,


basic


Figure


statistical


shows


the


analysis,


monthly values


OPEC


crude


production


series


since


1984.


Several


things


are


apparent


from


First


, the


OPEC


crude


production has had an upward trend.


This may explain that the


crude


price


been


declining


from


peak


so-


called


"oil


crisis"


and has


recovered


that


level.


It also


helps


to explain why,


over time,


futures market has


been


pessimistic


about


crude


prices


that


the


crude


futures prices follow a negative trend as well.


Traders in the


market


expect


that


the


upward


trend


OPEC


production


will


continue.


Secondly,


decline has been irregular


there is


no recognizable


pattern


follow.


Table 3-1 provides the mean, standard deviation, maximum,


and minimum


for the


following variables:


OPEC oil


production


futures


prices


9 month-ahead


contracts.


Again,


futures prices picked are the same as those stated


in the last chapter


, that is the 2-month-ahead is very closely


correlated with the 1-month and 3-month-ahead ones and the 4-


8-month-ahead


correlated


with


contracts

and 9-


are


-month


found


be closely


contracts.


Cross


correlations


for these


series are given


Table


3-2.


shown


table


, the


mean


OPEC


crude


production


from


January


1984


through


July


1989


17.83




































o 18


- 17


16


15


1-I


1984


!


1985


199S


1987


nA

r


1988


Figure


OPEC


Crude


Oil


Production


1929









coefficients


between


OPEC


crude


supply


and


futures


price


series


are


negative.


This


result,


which


surprising,


tells


that


the


OPEC


supply


has


negative


effect


futures


production


prices,


lower are


the


that


more


futures prices.


This can be


easily explained by the fact that when there is


excess


supply


price


will


tend


decline.


Second,


unlike


relationship


between


spot


price


and


futures


prices


shown


the Table


2-2,


which shows that the correlation between spot


futures


prices


falls


from


0.95


1-month


ahead,


progressively declining to 0.62


for 9-month ahead,


cross-


correlations


increase


from


0.465


(in absolute


value)


for the


1-month-ahead to 0.531 for the 3-month-ahead and 6-month-ahead


then drop to 0


.528


for 9-month-ahead futures.


The correlation


between OPEC supply


, 9-month-ahead


futures prices


larger


than


that


between


1-month-ahead


futures


price.


The 1-


, 6- and 9-month-ahead crude oil futures prices


are plotted against OPEC production in Figure 3-2 through 3-5,


respectively


. They


demonstrate some


interesting movements of


futures prices and the OPEC production since 1984.


crude oil


First,


futures prices move oppositely to that of the OPEC


production.


Generally


speaking,


when


there


is an


increase


the production,


there is a drop in the futures prices.


Second,


, 6-























K!>


IN


N


x


1984


195S


1986


1987


1988


-- OPEC Of


SucoD t y


.-utures


Figure


Oil


Supply


Futures


ces


m9a


*-Month-uut









production are very big.


The


futures


prices


falsely


signaled


trend

oil c


crisis,


supply

people


. This

were e


is due


expecting


the


the


fact


that


prices


after

in the


futures to


increase.


From Figure 3-1.


we can


see


clearly that


during this mid-1984 and late 1985 periods,


the OPEC crude oil


production


such


kept


negative


declining,


trend


too.

the


Therefore

production


traders


expected


continue


anti


cipated


another


shortage


supply


. Second,


after


mid


1986,


futures


prices


have


been


following


OPEC


production


much


more


closely.


This


because


during


this


time,


investors realized the mistake in their expectation


adjusted


according


the


new


information.


There


another


reason


that


the


futures


markets


are


getting more mature and the new technology has been adopted so


that


people


the market can


receive and


respond


the new


information more quickly


prices declined


. Third,


a great deal.


after mid-1985,


This was due


futures


the continuous


increase in the OPEC crude oil production.


Since mid-1985,


OPEC


faced


strong


competition


from


non-member


countries.


order to


maintain


the market


share,


OPEC has


been


increasing


its production steadily.


This


exerted a


downward


pressure on


the futures markets.


Observing this fact


the traders became


pessimistic about the market.


Fourth,


from the figures,


it can


seen


easily


that


the


6-month-ahead


futures


prices



































7YA-- I-


11 v< '- r
/'^
( \ 7.
\ r,
,-- 4


19B5 1986 9g7 198a


--- OPEC 01


Stcoty


3-Moflnt-Out


Figure


Oil


Supply


Futures


Prices


1984






































7 -^
' 7'

NflN


197


7
w/-
7


C/
^


19g8


1989


-- OPEC O05 5uooly


6-Month-Out Futures


Figure


Supply


Futures


ces


1995


198s





















,Tr\


r j '
A <7 t

^H


1985


19865


1987


1988


1989


- CPEC O0


Suc ly


tuturs


Figure


Oil


Supply


Futures


Prices


1984


9-'onth-uut









Another


calculate


preliminary


ratio of


review


futures


the


prices


relationship


OPEC production of


crude


same


month.


Table


3-3


presents


mean


ratios and standard deviations for these calculations.


Again,


the lagged response effects of supply


is verified.


The ratios


of 3-


, 6- and 9-month-ahead futures prices to the OPEC supply


have values closest to unity


. This suggests that 3-


, 6- and 9-


month-ahead


futures


prices


move


more


closely


along with


OPEC


However


production


, by


looking


than


1-month-ahead


standard


futures


deviations,


prices


one can also


notice


that


relationship


between


the OPEC


production


9-month


ahead


futures


prices


have


higher


variance


than


ones


between


the


supply


and


1-month-ahead


futures


prices,


price


because


OPEC


ratio


production


1-month-ahead


has


smallest


futures


standard


deviation.


This


time


span


during


which


people


adjust their expectations.


The longer the


time span,


the more


likely


some


new


events are


to happen during this


period


, and


more


likely


that


investors


readjust


their


expectations.


Figure


3-6 through


show the ratios of the OPEC crude


production


futures


prices


the


corresponding


time


periods.


There


is a


slightly upward


shift


the graphs


indicating


that


over


time


the


futures


market


been


pessimistic about crude oil


prices.


obvious


that prior


, 6-









reached


OPEC


production.


The


futures


prices


over-


adjusted to the


increase in the OPEC production.


These "over-


shoots"


have had an


impact on


the


futures markets.


They were


the turning points when the futures market switched from being


optimistic


pessimistic.


The


market


never


returned


level before 1986. After the over-reaction, both investors and


the market adjusted.


The market was becoming more mature and


traders


could


information


using


respond


modern


more


instantaneously


technology.


futures


new


prices


then followed the OPEC production more closely


much closer to unity


. The ratios are


, even though there are some fluctuations.


Simple Recressions


this


section,


simple


regressions


are


used


investigate


relationship


between


OPEC


crude


production and futures prices are presented and analyzed.


Thus


following


equations


are estimated:


FPt,l


(3-1


p St


(3-2)


= a + 3 St


(3-3)


FPt.9


8 St


(3-4)


where


= the OPEC crude oil


production at


time


= a +


= a +
























l-Month-Out Futures


A

S'N


\


A.
A1


i .T ..r t I .. .. I T I I i 1rtl + -f. a a ... 1- ..T--. ." "


1985


1986


19ia


1988


1989


Figure 3.6 Oil Supply /Futures Prices


1984



















3-Montnh-Out Futtraes


1985ga 198 987 1988 1989


Figure


Supply


/Futures


Prices


1984





















6-Month-Out Puttures


A
/V
2!


1997 1989 1989


Figure


3.8


Supply


/Futures


Prices


1.7


t 1


1984


1985


1986


/
























9-mrontn-out futtres prices


1. 1


0.6 -
0.5 -
0.4-
0.3-
0.2 -
0. 1 -


1984


1985


Figure


OPEC


Oil


Supply


/Futures


1986


1987


1988


1989









Table 3-4 gives the results of this estimation.


From this


preliminary


table,


can


obtain


following


conclusions.


First,


the supply variables are statistically very significant


in all


four


equations


the corresponding


coefficients


are


negative


standard


expected.


errors,


Second,


we can conclude


in terms


that


of R-squared


the equations with


, 6- and 9-month-ahead futures prices performed better than


the one with 1-month-ahead futures prices.


This again verifies


the lagged response effects of supply on people's expectations


futures


prices.


Basically,


however,


four


equations


may


perform


poorly.


This is because of the fact that the time series


consideration


nonstatinary.


under


basic


assumptions of simple regression are violated


. Therefore,


results


from this method can be "spurious"


the following sections of this


chapter,


and misleading.


the nonstationarity of


time


series variables


will


tested.


Specification Tests


Integration


Test


Many


macroeconomic


variables


such


price,


supply,


demand


Furthermore


exhibit


these variables


nonstatinonarity


often appear to


levels.


integrated of


order one


(stationary in the first differences)


, or to possess









other


words,


whether


they


are


stationary


levels


differences


some


order.


The


co-integration


test


aims


detecting whether there exists a


stable


relationship


between


the level


of two economic variables.


In the example here,


link


the


OPEC


crude


production


and


futures


prices and test the relationship between them.


a relationship,


If there exists


then it may be possible that some quantitative


effect of the futures prices on the OPEC crude oil production


can


made.


The


theory


integration


test


method


was


discussed


Chapter


Two,


hence


details


will


repeated here.


Table


report


Sargan-Bhagrava


(CRDW)


Dickey-Fuller


(DF)


Augmented


Dickey-Fuller


(ADF)


test


statist


iCS.


Table


3-5


shows


that


for all


the series


their


level


unit


root hypothesis


rejected


at 99%


level


of significance.


This


suggests


that


even though some


results


are


obtained


previous


section,


they


are


not


valid.


order to get these variables to satisfy the normal


conditions


of simple


regression,


we need to difference all


the variables


see


whether


the


difference


series


has


a unit


root.


From


Table 3-6


it is apparent that all of the difference variables


reject


hypothesis


unit


root


same


level


significance.


Thus


, all the variables in level


are 1(1) .


This


implies


that


levels of


the OPEC crude oil


production and









prices are expected to be statistically


run,


linked over the long-


and that the ratios of spot price and futures prices will


be constant over time


in the


long-term.


Cointeoration Test


After investigating the fact that both the OPEC crude oil


production


futures


prices


are


integrated


first


order


the next


step


is to examine whether they


are also co-


integrated.


The


idea


behind


the


co-integration


test


follows.


Suppose


two economic variables


show nonstationarity


they


share


same


character


the


nonstationary


stochastic movement? More precisely


while individual economic


time


series


can


integrated


order


one,


I(1)


, certain


linear


combinations of the series can be stationary or


I(0)


clear


from


table


below,


that


statistics


CRDW


ADF


is significant


at 95 percent confidence


level.


This implies that no linear combination of the I(1)


OPEC crude


production and


futures prices


is possibly


stationary


and they do not share the same character of the nonstationary


stochastic


movement.


Therefore,


can


conclude


that


futures


prices are


co-integrated with


the OPEC crude


production


level.


From


above


analysis,


conclude


that


there


stable


long-run


relationship


between


the


OPEC


Crude









researchers


make


mistakes


here.


The


next


sections


are


designed


illuminate


these


mistakes


. It


known


that


OPEC


crude


production


and


futures


prices


are


co-


integrated


, which


suggests


that


there


long


-run


relationship


between


them.


disregard


this


fact


purpose


, and


ahead


to implement


the


popular methods


used by


many


researchers,


Garbade


and


Silber


approach,


and


Granger


causality t


As it will


become clear


, controversial


results


are


obtained


: one


method


suggests


that


futures


prices


res


pond


the


OPEC


crude


production;


other


, on the


other


hand


, suggests


that


futu


res


ces


Granger


cause


OPEC


production


The Garbade


Silber


s Approach


We present


Garbade


Silber


approach


which


leads


following


model


time


sern


behavior


t-1.IJ


where


tIS


logarithm


the OPEC


crude


production


month


t and


the logarithm


of the j-month


-ahead


futures


prices


deliv


in the


same


month.


The


constant


terms


indicate


trends


data


and


persistent


' as


I -


i









other variable.


The


ratio Pf/(


+ 3)


can be


used


to examine


relationship


between


variables.


ratio


equals


unity


that


s = 0),


then


implies


that


futures prices always moves


in response to the OPEC crude oil


production.


ratio


/ f/(s


P f)


equals


zero


that


= 0),


then the OPEC oil production always adjusts


to the futures pr


ices.


in response


An intermediate value between zero and


imply


ies


mutual


interaction between the


two variables.


Equation


can


be solved


t as


function


- St1
t-1


- St


- St-1)


where a


- a


= 1


- P


= ut


- s'


As can be


observed


equation


(3-6) ,


reflects


the


speed


convergence between two variables.


If 6


is small


, only a small


fraction


the


difference


between


month


persists


month


this


case,


will


converge


quickly.


rearrange


equation


(3-5)


algebraically


following way


, so that it can be estimated via ordinary


least


squares:


F -1,


cS-S
^C -1


fl


/-*











The


estimates


obtained


from


this


equation


using


ordinary


least squares


are summarized


in Table


(3-8)


through


Table


(3-11)


. Also given in


these tables are


the ratio f#/({s


+ 9Pf)


which show the relative contribution of the OPEC crude


production


formation


futures


prices,


which measures the rate of the convergence of these two kinds


of variables.


These tables reveal the following points.


First,


cases,


estimates


/3's


are


significantly


positive


. This


finding


leads


conclude


that


OPEC


crude oil production leads the futures prices in incorporating


new


information.


Second,


the


estimates


are


also


significantly


positive,


though


much


smaller


than


Pf's,,


which


suggests


smaller


feedback


from


the


futures


market


OPEC crude oil production.


Third,


The derived estimates of 6's


shown


in the


tables


indicate


that only


a small


amount of


difference


between


futures


prices


and


the


OPEC


production in month t-1 persists to month t.


This can also be


explained by the lagged response effect of production.


In this


month,


the traders are unable to absorb the difference


in the


relationship between


the OPEC oil


production and the


futures


prices


which


happened


last


month.


Little


the


difference


persists


from last month


to this month.


However,


it may


have


to be taken into account several months later.


Fourth









expectations


futures


prices.


This


last


point


strengthens


the


first


point


that


not


only


does


OPEC


crude


production


lead


futures


prices


, but


also


influence


on the


futures


prices


significant.


Granger


Causality


Test


Ignoring


the


finding


that


there


long


-run


relationship


between


the


OPEC


crude


production


futures


prices


which


was


based


on the


co-integration


test


previous


sections


, let


implement


Granger


test


to oil


supply


futures


prices


anyway


According


to Granger


(1969)


, the


simple


causal


mod


t =


= z
t


i =1 1 t-


+ =1 i2Ft-


where


denotes


OPEC


crude


production


futures


prices,


, 3-


and


9-month-ahead


. 1it


are


taken


uncorrelated


white


-noise


series.


t is


said


cause


t if


some


are


zero.


Similarly


t is said


cause


some


s are


zero.


both


these


events


occur


, there


feedback


relationship


between


hypothesis


and


The


that


usual


t does


not


F-test


cause


applied


to test


corresponding


null


to 81


J = 0


+-









use


restricted


least


squares


method


estimate


equation


and


imposing


the


restrictions


respectively


. Table


-12)


through


Table


-15)


summarize


estimation


results.


The


following


results


emerge.


First,


unclear what kind


of relationships exists


between


the


OPEC


crude


production


and


the


futures


prices.


The


restrictions


imposed


on the


equations


are


stati


stically


significant for different variables


For


1-month-ahead


futures


price


, it


seems


that


the OPEC oil


production


is Granger


caused


futures


ces


. The


significance


level


about


cent.


For


, and


6-month


-ahead


futures


prices


however


, the


situation


is just


the opposite


futures


ces


are


Granger


caused


OPEC


production.


The


significance


level


about


per


cent.


For


9-month-ahead


futures


ces


, the


restrictions


on both


OPEC


production


and


the


futures


prices


are


not


states


tically


significant,


result


which


suggests


that


neither


OPEC


production


Granger


causes


the


futures


ces


nor


futures


ces


Granger


cause


OPEC


production.


Compared


with


results


presented


the


two


previous


sections


, the


outcomes


obtained


thi


section


are


obviously


different


The


results


obtained


there


with


the


Garbade


Silber

strong


approach


effect


indicate


that


futures


the

pri


OPEC

ces.


oil

The


production


outcomes


has

thi









between


1-month-ahead


futures


prices


and


that


between


the


6-month


-ahead


futures


prices


are exactly the opposite


. The


contradiction


findings


due


the


nonexis


tence


stable


long


-run


relationship


between


OPEC


production


futures


prices,


question


that


needs


answered


first


step


of the


proper


"two


-step"


testing


procedure


long


run


relationship


between


variable


. If


we ignore


ste


and


ahead


investigate


causal


relation


ships


then


is not


surprise


at all


that


conflicting


results


are


obtained.


Summarv


chapter


, we


have


studied


relation


ships


between


OPEC


crude


production


futures


prices


Different methods


simple


have


methods


been


used


such


to examine


graphic


relationship


simple


regression


suggest


that


variable


there

. The


an apparent


coefficients


relationship


regressing


between.

the


ese


futures


prices


on the


OPEC


production


is negative


which


implies


that


the


OPEC


production


has


downward


pressure


futures


prices.


can


also


be easily


seen


graphs.


With


the


exception


an unstable


period


, there


was


a drop


futures


ces


when


production


increased.


The


integration


co-integration


tests


were


then


used









the


OPEC


production


were


integrated


order


one,


suggesting


that


levels


of both


OPEC production and


futures


prices


were


unstable,


however,


their


first


order


differences


are


stable


. This


finding prompted us


to employ the


co-integration


test


examine


the hypothesis


whether such


nons


tationarity


the


same


order


was


generated


a similar


mechanism


. The


co-integration


test


rejected


thi


hypothesis.


means


that


the


nonstationarity


of the OPEC production and


that


futures


prices


are


generated


same


mechani


. There


fore


we can


conclude


that


there


no long-


run


stable


relationship


between


these


variable


es.


The


last


sections


of thi


chapter showed


the mi


stakes


that


can


arise


fact


that


there


no long


run


stable


relationship


between


two


variabi


ignored.


Most


research


ers


have


made


this


mistake


. They usually


did


test


the exi


stence


of the


long


run


relationship before


they went


estigate


nature


relationship


with


methods


such


Garbade


and


Silber


approach


or the


Granger


causality


test.


When


long-run


relationship


does


exist,


results


about


relationship


are


meaning


ess.


These


sections confirm


this argument


We showed conflicting outcomes


could


arise


about


relationship


between


the


futures


ces


the


OPEC


production


when


different


methods


were


used.


The


results


from


the


Garbade


silber


approach









causality test suggested a lack of a


consistent relationship.


For the


1-month-ahead


futures


price,


the OPEC


production


was Granger caused by futures price.


For


, and 6-month-ahead


futures


prices,


however,


situation


was


reversed:


futures prices are Granger caused by the OPEC production.















Table


Selected Statistics


OPEC Crude Oil


Supply


Futures


Price


Series Mean S.D. Max. Min.

Supply 17.83 1.82 22.46 14.46
Futures
1-Month-ahead 21.39 5.98 31.35 11.04
3-Month-ahead 21.04 5.96 30.73 10.58
6-Month-ahead 20.93 5.95 30.73 10.86
9-Month-ahead 21.05 5.85 30.62 10.92















Table


3-2


Cross-Correlations


OPEC Crude Oil


Supply and Futures


Price


Variable Supply 1-Month 3-Month 6-Month 9-Month

Supply 1.000 -0.465 -0.531 -0.531 -0.528
1-Month-ahead 1.000 0.872 0.700 0.700
3-Month-ahead 1.000 0.854 0.732
6-Month-ahead 1.000 0.889
9-Month-ahead 1.000















Table 3-3


Selected Statistics


for OPEC Crude Oil


Supply


and Futures


Price Ratios


Ratio to Supply:
Mean S.D. Max. Min.

Futures
1-Month-ahead 1.23 0.42 1.94 0.57
3-Month-ahead 1.21 0.43 1.97 0.62
6-Month-ahead 1.21 0.43 2.01 0.66
9-Month-ahead 1.21 0.43 2.04 0.66















Table


Regression Coefficients


Crude Oil


Futures


Prices


on OPEC Crude oil


9-Step Ahead
Production


Variable Dependent variable

F1 F3 F6 F9

Constant 48.91* 57.28* 50.42* 49.86*
(7.53) (8.32) (8.18) (8.02)

S -1.54* -1.67* -1.66* -1.61
(-4.24) (-4.93) (-4.81) (-4.66)

1st-Order 0.90 0.88 0.88 0.90
Autocorrelation

R2 0.22 0.28 0.28 0.28

R2 0.20 0.27 0.27 0.27

D-W 0.17 0.18 0.20 0.16

Std. Error 5.37 5.09 5.08 5.01















Table


Results of
Oil


Integration Tests
Supply and Futures


for OPEC Crude
Prices.


Series CRDW DF ADF
(crit. value (crit. value (crit. value
99%: 0.532) 99%: -4.07) 99%: -3.77)

S 0.231 -1.64 -1.76
FP1 0.094 -1.62 -1.72
FP3 0.077 -1.52 -1.72
FP6 0.060 -1. 36 -1.69
FP9 0.564 -1.03 -1.49




Full Text

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