Backwards to the Future: A Test of Three Futures Markets

8/9/2019 Backwards to the Future: A Test of Three Futures Markets

1/26

BACKWARD TO THE FUTURE: A TESTOF THREE FUTURES MARKETS

by:

D.E.Allen 1

School of Finance and Business EconomicsEdith Cowan University

S. Cruickshank School of Finance and Business Economics

Edith Cowan University

N. Morkel-KingsburySchool of Accounting and Finance

Monash University

and

N. SounessW.A. Treasury

AbstractNormal backwardation, first discussed by Keynes (1923), (1930) and Hicks (1946), is

a fee paid by a seller of a security to the buyer for the privilege of deferring delivery. Itimplies that a risk premium exists so that the futures price falls short of the expectedfuture spot price. The reverse case, contango, implies that the futures price exceedsthe expected future spot price. This paper applies tests for the existence of normalbackwardation to daily closing prices on the Sydney Futures Exchange (SFE), LondonInternational Financial Futures and Options Exchange (LIFFE) and the SingaporeInternational Monetary Exchange (SIMEX). By applying a series of tests after Kolbs(1992) study of US commodities, it is found that few of the contracts studiedconsistently exhibit normal backwardation while many show evidence of contango.

Keywords: Futures Prices; Normal Backwardation.JEL classification: G13.

1 D.E. AllenProfessor of FinanceEdith Cowan UniversitySchool of Finance and Business EconomicsJoondalup CampusJOONDALUP WA 6027Ph. 61-8-9400 5471Fax. 61-8-94005271Email: [email protected]


2/26

2

1. Introduction

The following paper presents the findings of an investigation into normal

backwardation on the Sydney Futures Exchange (SFE), London International

Financial Futures and Options Exchange (LIFFE) and Singapore International

Monetary Exchange (SIMEX) using a method of analysis which parallels the methods

used by Kolb (1992) in his US study.

Under the theory of normal backwardation developed by Keynes and Hicks, futures

prices tend to rise over the life of a futures contract because hedgers tend to be short in

the futures market. That is, hedgers hold short positions as insurance against their

cash position and must pay speculators a return to hold long positions in order to

offset their risk. Markets are therefore considered to be in normal backwardation

when the futures price is less than expected future spot price. In other words, Keynes

and Hicks saw normal backwardation to be the equivalent of a positive risk premium.

Keynes (1930, p.144), therefore suggested that The quoted forward price, though

above the present spot price, must fall below the anticipated future spot price by at

least the amount of the normal backwardation. This theory follows essentially from

the view that hedgers as a group take a short futures position whilst speculators

collectively adopt a long position.

Hicks suggested that this leads to a constitutional weakness in the market. Keynes

and Hicks explained this in terms of technical conditions in production and

consumption. Producers have to look further to the future than consumers, the former

are committed to maintaining production whilst the latter have a more liberal choice


3/26

3

about their consumption. This leads to a stronger demand to cover planned production

(supplies) than to cover planned consumption (demand). Thus, producers are net short

in futures and speculators have to be induced to go net long. A positive risk premium,

or normal backwardation, emerges to induce them to do this. This explanation applies

to commodity markets but does not necessarily fit the case of financial futures.

Kawai (1987) provides the following explanation. Consider the following equilibrium

conditions in spot and futures markets at time 0.

Q0,0 + Z -1 = C 0,0 + K 0 (Spot Market Equilibrium)

Q0,1 + K 0 - C 0,1 = Z 0 (Futures Market Equilibrium)

The variables Q, C, K, and Z refer to output supply, consumption, storage and futures

speculation and their subscripts represent time. For example, Q t,s is output planned at

time t and delivered at time s. K 0 is the amount carried from time 0 to time 1, whilst

Z0 is the amount of speculative futures contracts purchased if Z 0 > 0 or sold if Z 0 < 0

at time 0 for delivery at time 1 (Kawai ignores storage from the previous period).

The market clearing conditions yield:

Z0 = Q 0,1 + K 0 - C 0,1 = C 1,1 + K 1 - Q 1,1

The arguments suggested by Keynes and Hicks posit that production is mostly

planned and consumption is more flexible, therefore Q 0,1 > C 0,1 and C 1,1 > Q 1,1 . The


4/26

4

above implies that Z 0 > 0 follows and there exists a positive risk premium or normal

backwardation.

However, in some markets such as those for foreign exchange and financial

instruments the technological distinction between production (Q) and consumption

(C) is not pronounced and storage could be negative (K


5/26

5

zero returns. Bodies and Rosansky (1980), Carter, Rausser and Schmidt (1983), and

Fama and French (1987) all reported evidence in support of backwardation.

The notion of a convenience yield as suggested by Kaldor (1939) and Working

(1948) is often used as an explanation for backwardation in futures prices of storable

commodities. Litzenburger and Rabinowitz (1995) analyse backwardation in the oil

futures markets where it is prevalent and find that it is linked to oil price volatility.

The most comprehensive recent study of backwardation in US markets is by Kolb

(1992). He studied 29 commodities for the period 1957-1988. Only four contracts,

feeder cattle, live beef, live hogs and orange juice conform well to normal

backwardation. Another five, copper, cotton, soy beans, soy meal, and soy oil partially

conform to it. The remaining 20 commodities did not display evidence of

backwardation and three of these (crude oil, heating oil and lumber) appear to be in

contango.

This work was followed by Deaves and Krinsky (1995) who reassessed the contracts

that Kolb (1992) found to exhibit evidence of normal backwardation, but with 5

additional years of data. They found that fewer of the contracts then produced

evidence of increasing futures prices over time and concluded that market participants

would be better off viewing futures prices as reflective of market expectations of

future spot prices.

The current paper, however, re-applies Kolbs (1992) tests to commodity futures listed

on the Sydney Futures Exchange (SFE), London International Financial Futures and


6/26

6

Options Exchange (LIFFE) and the Singapore International Monetary Exchange

(SIMEX).

3. Testing Methodology and Data.

No arbitrage conditions between cash and futures markets mean that the futures price

must converge to the cash price as expiration approaches. Black (1976) sets out these

conditions very clearly. If we follow Kolb (1992) and let F i,t represent the price of a

futures contract i with t days remaining until expiration. Similarly P i,t stands for the

cash price t days before the expiry of contract i. We know that at expiry the two

prices must be equal to one another to prevent arbitrage. It follows that:

P i,0 = F i,0 for all i (1)

Given this identity, this study uses the price of the futures contract at expiry, F i,0 as a

proxy for the cash price at the expiration of the contract.

It is further assumed that the market forms unbiased expectations of the spot price

expected to hold at expiry and that the observed spot price is a proxy for the expected

spot price. Thus, F i,0 is regarded as the spot price expected to hold when contract i

expires.

If backwardation holds, then futures prices should rise over the life of the contract to

the expected spot price at expiry. Kolb (1992) demonstrates that this implies:


7/26

7

E[ln(F i,t / F i,t+1 )] > 0 and E[F i,t / F i,t+1 - 1] > 0 (2)

This suggests a straightforward test involving the computation of simple and

logarithmic returns across all contract maturities (I) and across all days from inception

until expiry T.

The mean return on any given contract is given by the equation below:

T I

RET T

t

I

i

t i

== =1 1

,

(3)

In (3) above RET i t , = F i,t / F i,t+1 - 1. In effect, the existence of normal backwardation

suggests that the daily returns on futures contracts must be positive. All contracts

are examined to see whether the daily mean return is positive.

Kolb (1992) further demonstrates that futures prices before expiration should lie

below the expected future spot price at expiration.

E(F i,t - F i,0) < 0 (4)

This can be examined by analysing the relative differences between all futures prices

at time t, and all futures prices ultimately observed at expiry. Kolb (1992)

recommends the examination of the relative price differential D i,t, defined in (5)

below, on the grounds that this metric will not be affected by the units in which the

contracts are denominated or by absolute level of all prices examined.


8/26

8

D i,t = (F i,t / F i,0) - 1 (5)

The expected value of D i,t should be negative for any day prior to expiration of the

contract if normal backwardation holds.

E(D i,t) < 0 for t > 0 (6)

The following metric is compared across all contracts.

t M = I

D I

i

t i=1

,

(7)

Given normal backwardation M t should be negative for all days prior to expiry. In

effect

E(M t+k ) < ..... < E(M t) .... < E(M o) (8)

The expression in (8) can be tested by running the following regression.

D i,t = i + i t + t (9)

To avoid serial correlation Kolb randomly selects contracts i and time to maturity t.

We follow suit. The hypothesis is that if normal backwardation holds, i < 0.


9/26

9

As previously mentioned, in contrast to Kolb's (1992) study of commodity futures

markets in the United States, this paper examines those in Australia, Singapore and

the United Kingdom. Table 1 summarises the data used in the analysis. We recovered

daily settlement price data from the Datastream International database for 5 contracts

listed on the LIFFE, 6 listed on the SFE and the single SIMEX commodity contract.

In total, 454 contracts with 138,278 daily observations are analysed. Although

substantially less than the sample used by Kolb, this is still sufficient to draw

confident conclusions. The largest data series was provided by LIFFE cocoa futures

which began in 1979 and involved a total of 103 contracts. The smallest data sets

were those of the broad wool and fine wool contracts on the SFE. Having only

commenced trading in 1998, data for each of these commodities was available on only

6 contracts.


10/26

10

4. Results

The first procedure is a complete test of mean daily futures returns, both simple and

logarithmic 2. Results are displayed in Table 2 which includes the first four moments

of the distributions, a significance test for the returns and a Bera & Jarque (1981) test

for normality 3.

Interestingly, of the 12 contracts included in the study, mean returns are negative in 8

contracts and positive for the remaining 4. Negative returns, consistent with

contango, are evident in each of the SFEs wool contracts, LIFFE barley and cocoa

futures, wheat contracts on both the SFE and LIFFE and SIMEX crude oil futures.

Consequently, evidence of normal backwardation in the form of positive mean returns

exists only in LIFFE coffee and sugar contacts as well as both of the SFEs electricity

futures.

The mean returns for all contracts are not significantly different from zero and non-

normal. Contrary to Kolb, there is no discrepancy between the results for simple and

logarithmic returns.

The results in Table 3 measure daily price observations before expiry relative to the

terminal futures price, this time producing weaker evidence of normal backwardation.

In fact less than 45% of the total sample observations are below the terminal price.

The results show that futures prices tend to be below the expiry price for LIFFE sugar

2

As in Kolb (1992), return refers to the percentage change in settlement price or logarithmic pricedifferences from one day to the next.3 These tests were repeated after the removing the outliers, however the results did not altersignificantly.


11/26

11

futures and both SFE electricity contracts, thus strengthening the previous findings for

these commodities. LIFFE wheat contracts also show evidence of normal

backwardation, although somewhat more marginal than that of the other three

contracts.

These findings are reinforced by the z-scores 4 displayed in Table 3 which provide

another test for the proportion of observations below the expiry price. Again we see

evidence of backwardation in the contracts outlined above, with the p-values shown to

be significant for all but the LIFFE wheat contract.

We complement Kolb's analysis by also presenting the results for the number of

individual contracts that are in normal backwardation/contango. The criteria for

classification as normal (contango) is a minimum of 60% of futures prices below

(above) the terminal futures price. Contracts with between 40% and 60% of prices of

each type were classified as mixed. Using this method, the evidence for normal

backwardation in all but one case (SFE wheat) is reduced. While the LIFFE sugar

contract now shows signs of being in contango, the SFE electricity contracts continue

to produce evidence of normal backwardation.

Table 4 presents an analysis of whether the relative price differentials D it are

significantly different from zero across contracts on given days to expiry. The results

here are shown for the 90 days prior to expiry and are much weaker than those of

Kolb. There is not one daily return for any contract that is significantly different to

zero as per a t-test of / . However, notwithstanding the lack of significance, a very

4 Z-score statistics are calculated as (2x-(N-1))/ n.


12/26

12

high proportion of daily futures returns relative to the terminal futures price are

positive, strongly supporting contango. Only the barley and sugar futures on the

London exchange produce evidence of normal backwardation with 78% and 84% of

prices, respectively, being below the terminal price.

The results of the regression specified in (9) are presented in Table 5. For each of the

contracts we selected 5,000 observations (or used the full sample when fewer than this

number of observations were available) on which this regression was estimated. We

avoided serial correlation by randomly selecting these observations and used Whites

(1980) procedure to take account of possible heteroskedasticity. The results reinforce

our earlier findings with negative betas for the electricity futures, again an indication

of normal backwardation. The LIFFEs coffee contract is the only other commodity

that exhibits a negative coefficient, strengthening the possibility of normal

backwardation in this particular commodity first evidenced in Table 2.

By applying Whites procedure we were able to obtain heteroskedastic-consistent

standard errors and consequently estimate more accurate t-statistics. It is vital to use

such standard errors since this is the one consistently incongruent property of the data.

It does not appear that Kolb did so and it has an important impact on the results. In

our case beta is highly significant for all but the sugar and SIMEX crude oil futures.


13/26

13

5. Conclusion

It appears quite clear that normal backwardation does not prevail for a majority of the

contracts examined. The SFEs electricity and LIFFE sugar contracts produced the

strongest evidence of normal backwardation, satisfying three of the four testing

criteria. While the former display significantly negative betas in the regression of

relative price differentials on time and the latter negative price differentials, both show

evidence of positive mean returns and more observations below than above the expiry

price (even on an individual contract basis). Overall, for these commodities it can be

concluded that futures price do indeed increase over time, that is, a positive risk

premium does exist.

The LIFFE coffee contracts also showed signs of normal backwardation, satisfying

two of the test procedures. However as the other two criteria cannot be met, we can at

best describe the evidence in favour of backwardation in this commodity as mixed.

The remaining contracts can however clearly be classified as being in contango.

While the LIFFE barley contract satisfies only one of the four tests for normal

backwardation, not one of the other 7 contracts satisfies even one of these criteria but

rather satisfy all the criteria in favour of contango.

Therefore, while examining alternative markets with a smaller sample period, we are

able to conclude in the same manner as Kolb: normal backwardation does not appear

to be a feature of these commodity futures markets normal backwardation is not


14/26

14

normal. In other words, it does not appear that a positive risk premium exists in a

majority of the markets studied.


15/26

15

Table 1DATA DESCRIPTION

Commodity Expiration First year Contracts Number of Months Of Expiration Analysed Observations

LIFFE Barley 1,3,5,9,12 1989 50 13,696LIFFE Cocoa 3,5,7,9,12 1979 103 40,858LIFFE Coffee 1,3,5,7,9,11 1991 52 14,768LIFFE Sugar 3,5,8,10,12 1989 49 17,600LIFFE Wheat 1,3,5,7,9,11 1989 56 15,240SFE Greasy Wool 2,4,6,8,10,12 1995 24 8,324SFE Broad Wool 2,4,6,8,10,12 1998 6 1,348SFE Fine Wool 2,4,6,8,10,12 1998 6 1,348SFE NSW Electricity All 1997 21 4,059SFE Victoria Electric. All 1997 21 4,062SFE Wheat 1,3,5,7,9,11 1996 18 5,814SIMEX Crude Oil All 1995 48 11,161Total 454 138,278


16/26

Table 2MEAN FUTURES RETURNS AND OTHER STATISTICS

Obs. Mean. (%) Stdev (%) t-Stat Skewness KurtosisSimple 13,646 -0.002278 0.604924 -0.0038 0.1653 83.10

LIFFE-Barley Log 13,646 -0.001785 0.262975 -0.0068 -0.6261 87.6Simple 40,755 -0.030141 1.287712 -0.0234 0.3448 5.5

LIFFE-Cocoa Log 40,755 -0.016687 0.558515 -0.0299 0.2050 5.2Simple 14,716 0.044834 2.082358 0.0215 1.7183 26.3

LIFFE-Coffee Log 14,716 0.010232 0.892185 0.0115 1.0319 19.4Simple 17,551 0.013090 1.080705 0.0121 0.1068 8.8

LIFFE-SugarLog 17,551 0.003150 0.469301 0.0067 -0.0683 8.8Simple 15,184 -0.001816 0.669963 -0.0027 -1.7992 69.40

LIFFE-WheatLog 15,184 -0.001773 0.293196 -0.0060 -2.5745 88.0Simple 4,038 0.106823 4.074665 0.0262 0.9854 21.5

SFE-NSW ElectricityLog 4,038 0.010676 1.762770 0.0061 -0.3560 20.2Simple 4,041 0.096001 4.332543 0.0222 5.7935 141.1

SFE-Vic Electricity Log 4,041 0.004530 1.771706 0.0026 1.4498 55.3Simple 8,300 -0.065033 1.270583 -0.0512 -0.0601 3.0

SFE-Greasy Wool Log 8,300 -0.031766 0.552616 -0.0575 -0.1573 3.1Simple 1,342 -0.096804 1.708213 -0.0567 -0.1787 7.9

SFE-Broad WoolLog 1,342 -0.048429 0.744779 -0.0650 -0.4317 8.0Simple 1,342 -0.039473 1.409964 -0.0280 -0.1120 2.5

SFE-Fine WoolLog 1,342 -0.021470 0.613356 -0.0350 -0.2067 2.5Simple 5,796 -0.005838 1.985963 -0.0029 0.4599 9.1

SFE-WheatLog 5,796 -0.011067 0.860413 -0.0129 0.1382 8.7Simple 11,113 -0.002635 1.574792 -0.0017 0.3970 3.7

SIMEX-Crude OilLog 11,113 -0.006511 0.682287 -0.0095 0.2701 3.3


17/26

Table 3PRICE OBSERVATIONS ABOVE AND BELOW TERMINAL FUTURES PRICES

Commodity Observations Relative to Terminal Futures Price Overall ContrAbove Below %Below Z-Score p-value Contango Normal B.

LIFFE-Barley 6,905 6,636 49.01% -2.32 0.0102 17LIFFE-Cocoa 26,333 14,332 35.24% -59.52 0.0000 67LIFFE-Coffee 7,618 7,060 48.10% -4.61 0.0000 23LIFFE-Sugar 7,901 9,593 54.84% 12.78 0.0000 24LIFFE-Wheat 7,464 7,636 50.57% 1.39 0.0823 26SFE-Greasy Wool 5,526 2,743 33.17% -30.62 0.0000 16SFE-Broad Wool 1,139 196 14.68% -25.84 0.0000 5SFE-Fine Wool 711 624 46.74% -2.41 0.0080 3SFE-NSW Electricity 1,360 2,631 65.92% 20.10 0.0000 9SFE-Vic. Electricity 1,473 2,498 62.91% 16.25 0.0000 8SFE-Wheat 3,611 2,148 37.30% -19.29 0.0000 9SIMEX-Crude Oil 5,694 5,395 48.65% -2.85 0.0022 22Total Sample 75,735 61,492 44.62% 229 171


18/26

18

Table 4RELATIVE PRICE DIFFERENTIALS t DAYS BEFORE EXPIRY

LIFFE-Barley LIFFE-Cocoa LIFFE-Coffee LIFFE-Sugar

t Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat1 -0.0026 -0.1793 -0.0016 -0.0694 0.0064 0.1391 -0.0033 -0.16362 -0.0034 -0.2352 -0.0005 -0.0198 0.0060 0.1057 -0.0014 -0.06313 -0.0065 -0.3267 0.0027 0.0860 0.0033 0.0521 -0.0023 -0.07144 -0.0108 -0.3877 0.0048 0.1480 0.0081 0.1230 -0.0054 -0.17995 -0.0108 -0.3706 0.0049 0.1435 0.0137 0.2082 -0.0042 -0.12426 -0.0126 -0.4422 0.0048 0.1254 0.0176 0.2794 -0.0016 -0.04877 -0.0112 -0.3653 0.0035 0.0850 0.0199 0.2857 -0.0021 -0.05448 -0.0116 -0.3859 0.0033 0.0744 0.0203 0.2705 -0.0044 -0.11109 -0.0129 -0.4156 0.0019 0.0413 0.0213 0.2612 -0.0014 -0.0338

10 -0.0122 -0.3746 0.0009 0.0176 0.0205 0.2506 -0.0033 -0.077311 -0.0122 -0.3770 -0.0012 -0.0225 0.0228 0.2593 -0.0022 -0.0496

12 -0.0127 -0.3993 -0.0007 -0.0114 0.0210 0.2330 -0.0006 -0.014413 -0.0128 -0.3980 -0.0030 -0.0475 0.0216 0.2324 -0.0004 -0.010214 -0.0124 -0.3589 -0.0031 -0.0480 0.0211 0.2213 -0.0020 -0.042615 -0.0129 -0.3838 -0.0034 -0.0548 0.0132 0.1370 -0.0045 -0.092016 -0.0141 -0.4927 -0.0025 -0.0386 0.0127 0.1301 -0.0037 -0.075617 -0.0145 -0.5129 -0.0029 -0.0428 0.0083 0.0816 -0.0056 -0.114118 -0.0154 -0.5435 -0.0015 -0.0215 0.0051 0.0494 -0.0043 -0.083819 -0.0168 -0.5853 -0.0003 -0.0048 0.0025 0.0234 -0.0050 -0.095020 -0.0173 -0.5900 -0.0010 -0.0126 -0.0019 -0.0178 -0.0044 -0.082721 -0.0178 -0.6042 -0.0006 -0.0080 -0.0032 -0.0292 -0.0046 -0.082822 -0.0164 -0.5610 0.0020 0.0236 0.0009 0.0083 -0.0065 -0.110123 -0.0157 -0.5492 0.0041 0.0462 0.0020 0.0169 -0.0063 -0.103024 -0.0150 -0.5303 0.0075 0.0851 0.0002 0.0015 -0.0080 -0.127825 -0.0145 -0.4971 0.0070 0.0773 -0.0021 -0.0168 -0.0076 -0.118526 -0.0150 -0.5231 0.0035 0.0388 -0.0007 -0.0052 -0.0066 -0.101227 -0.0147 -0.5051 0.0053 0.0563 0.0013 0.0104 -0.0079 -0.121128 -0.0137 -0.4632 0.0081 0.0850 0.0047 0.0373 -0.0065 -0.095529 -0.0131 -0.4578 0.0081 0.0832 0.0006 0.0049 -0.0097 -0.138530 -0.0137 -0.4710 0.0079 0.0789 0.0007 0.0055 -0.0108 -0.152031 -0.0131 -0.4419 0.0091 0.0887 0.0014 0.0110 -0.0092 -0.131132 -0.0123 -0.4148 0.0116 0.1118 0.0007 0.0059 -0.0124 -0.171033 -0.0128 -0.4224 0.0143 0.1349 -0.0014 -0.0109 -0.0130 -0.177834 -0.0122 -0.3871 0.0155 0.1452 0.0006 0.0048 -0.0142 -0.182435 -0.0113 -0.3344 0.0168 0.1548 -0.0006 -0.0045 -0.0139 -0.166636 -0.0117 -0.3377 0.0164 0.1517 -0.0020 -0.0156 -0.0158 -0.191437 -0.0102 -0.2948 0.0180 0.1626 -0.0008 -0.0063 -0.0141 -0.168938 -0.0085 -0.2414 0.0185 0.1619 -0.0004 -0.0030 -0.0157 -0.180139 -0.0082 -0.2343 0.0193 0.1691 -0.0019 -0.0132 -0.0159 -0.182640 -0.0086 -0.2368 0.0217 0.1913 0.0047 0.0334 -0.0109 -0.126741 -0.0092 -0.2441 0.0225 0.2005 0.0064 0.0444 -0.0102 -0.118342 -0.0077 -0.1763 0.0257 0.2244 0.0060 0.0410 -0.0134 -0.153143 -0.0109 -0.2830 0.0252 0.2164 0.0038 0.0262 -0.0123 -0.140644 -0.0096 -0.2426 0.0289 0.2435 0.0075 0.0468 -0.0104 -0.115545 -0.0099 -0.2434 0.0285 0.2385 0.0114 0.0679 -0.0110 -0.120146 -0.0085 -0.2051 0.0302 0.2483 0.0063 0.0404 -0.0118 -0.127447 -0.0082 -0.1954 0.0351 0.2817 0.0028 0.0183 -0.0132 -0.146848 -0.0082 -0.1928 0.0363 0.2892 0.0014 0.0098 -0.0117 -0.131649 -0.0084 -0.1970 0.0352 0.2831 0.0041 0.0271 -0.0119 -0.134150 -0.0086 -0.2088 0.0351 0.2717 0.0089 0.0574 -0.0114 -0.1247


19/26

19

LIFFE-Barley LIFFE-Cocoa LIFFE-Coffee LIFFE-Sugart Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat

51 -0.0075 -0.1805 0.0342 0.2644 0.0094 0.0598 -0.0097 -0.107152 -0.0075 -0.1823 0.0343 0.2624 0.0129 0.0806 -0.0095 -0.100453 -0.0057 -0.1389 0.0357 0.2752 0.0144 0.0919 -0.0083 -0.0863

54 -0.0068 -0.1577 0.0358 0.2730 0.0158 0.0993 -0.0062 -0.062955 -0.0054 -0.1254 0.0368 0.2867 0.0138 0.0869 -0.0059 -0.060356 -0.0053 -0.1182 0.0346 0.2695 0.0145 0.0875 -0.0063 -0.064757 -0.0045 -0.0994 0.0361 0.2771 0.0148 0.0905 -0.0042 -0.043858 -0.0032 -0.0703 0.0370 0.2798 0.0115 0.0707 -0.0023 -0.023259 -0.0024 -0.0524 0.0343 0.2652 0.0115 0.0699 -0.0016 -0.016360 -0.0020 -0.0430 0.0328 0.2541 0.0009 0.0055 -0.0036 -0.036561 -0.0017 -0.0371 0.0328 0.2514 -0.0004 -0.0024 -0.0052 -0.053762 -0.0029 -0.0636 0.0337 0.2571 -0.0019 -0.0112 -0.0093 -0.095863 -0.0033 -0.0730 0.0356 0.2720 -0.0024 -0.0141 -0.0083 -0.082164 -0.0031 -0.0697 0.0364 0.2791 -0.0042 -0.0245 -0.0068 -0.067065 -0.0038 -0.0863 0.0358 0.2669 -0.0042 -0.0244 -0.0055 -0.0529

66 -0.0033 -0.0749 0.0370 0.2659 -0.0020 -0.0114 -0.0048 -0.046467 -0.0027 -0.0620 0.0407 0.2888 0.0031 0.0173 -0.0046 -0.043968 -0.0020 -0.0456 0.0411 0.2890 0.0005 0.0027 -0.0029 -0.026769 -0.0016 -0.0355 0.0393 0.2791 -0.0002 -0.0009 -0.0008 -0.007270 -0.0003 -0.0068 0.0383 0.2677 -0.0016 -0.0084 0.0019 0.017371 0.0006 0.0132 0.0402 0.2842 0.0014 0.0073 0.0037 0.033272 0.0005 0.0118 0.0416 0.2972 0.0006 0.0033 0.0008 0.007573 0.0011 0.0236 0.0421 0.2977 -0.0026 -0.0137 -0.0002 -0.001774 0.0009 0.0195 0.0419 0.2942 -0.0001 -0.0006 -0.0020 -0.017975 0.0012 0.0260 0.0433 0.2964 0.0014 0.0074 -0.0051 -0.046476 0.0015 0.0301 0.0446 0.3029 -0.0009 -0.0049 -0.0031 -0.027577 0.0010 0.0192 0.0448 0.3025 -0.0043 -0.0232 -0.0027 -0.0238

78 0.0022 0.0434 0.0460 0.3078 -0.0109 -0.0607 -0.0014 -0.012079 0.0034 0.0652 0.0421 0.2845 -0.0061 -0.0333 -0.0005 -0.004180 0.0033 0.0634 0.0403 0.2725 -0.0037 -0.0201 0.0006 0.004881 0.0034 0.0644 0.0420 0.2826 -0.0040 -0.0217 0.0024 0.020482 0.0035 0.0660 0.0432 0.2914 0.0007 0.0034 0.0027 0.023683 0.0045 0.0843 0.0451 0.3024 0.0018 0.0091 0.0030 0.025384 0.0043 0.0803 0.0470 0.3110 0.0038 0.0188 0.0064 0.052685 0.0047 0.0886 0.0485 0.3181 0.0045 0.0220 0.0061 0.050586 0.0039 0.0718 0.0481 0.3106 0.0061 0.0302 0.0052 0.043087 0.0037 0.0671 0.0494 0.3206 0.0052 0.0244 0.0032 0.026288 0.0040 0.0726 0.0506 0.3290 0.0070 0.0318 0.0031 0.025789 0.0041 0.0720 0.0523 0.3378 0.0025 0.0119 0.0034 0.0277

90 0.0049 0.0849 0.0547 0.3505 0.0018 0.0086 0.0028 0.0227

Avg -0.0067 0.0239 0.0049 -0.0052Std Dev 0.0066 0.0180 0.0075 0.0054

t-Stat -1.0133 1.3273 0.6442 -0.9488# Pos 20 77 64 14# Neg 70 13 26 76% Neg 77.78% 14.44% 28.89% 84.44%


20/26

20

LIFFE-Wheat SFE-Greasy Wool SFE-Broad Wool SFE-Fine Woolt Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat1 -0.0027 -0.1292 -0.0065 -0.3617 0.0057 0.2387 0.0017 0.42252 0.0015 0.1022 0.0030 0.0984 0.0052 0.1906 -0.0041 -0.37233 -0.0021 -0.2042 0.0029 0.0839 0.0032 0.1096 0.0006 0.0271

4 -0.0014 -0.0867 0.0037 0.0959 0.0030 0.1027 -0.0015 -0.06275 0.0017 0.1052 0.0005 0.0141 0.0016 0.0517 0.0035 0.13086 -0.0023 -0.2669 -0.0007 -0.0200 -0.0031 -0.0841 -0.0013 -0.03697 0.0009 0.1338 -0.0027 -0.0606 -0.0064 -0.1417 0.0022 0.04498 0.0000 -0.0045 0.0016 0.0316 -0.0156 -0.2623 0.0087 0.14259 -0.0002 -0.0266 -0.0006 -0.0117 -0.0190 -0.3219 0.0066 0.1150

10 -0.0004 -0.0613 0.0004 0.0071 -0.0122 -0.1732 0.0069 0.104811 0.0006 0.0808 -0.0049 -0.1065 -0.0074 -0.1081 0.0136 0.221612 -0.0006 -0.0504 -0.0004 -0.0082 -0.0056 -0.0772 0.0179 0.228613 -0.0004 -0.0660 0.0072 0.1432 -0.0009 -0.0138 0.0202 0.326214 -0.0004 -0.0452 0.0079 0.1493 -0.0034 -0.0524 0.0112 0.189215 0.0007 0.1024 0.0085 0.1494 0.0146 0.3039 0.0184 0.3116

16 0.0002 0.0476 0.0105 0.1707 0.0086 0.1368 0.0096 0.175917 0.0004 0.0555 0.0099 0.1696 0.0049 0.0714 0.0142 0.211518 0.0002 0.0360 0.0153 0.2548 0.0133 0.2220 0.0080 0.124419 -0.0015 -0.1838 0.0159 0.2597 0.0098 0.1508 0.0098 0.149520 0.0001 0.0154 0.0160 0.2566 0.0186 0.2812 0.0130 0.175321 -0.0007 -0.1096 0.0159 0.2690 0.0207 0.3534 0.0203 0.279522 0.0009 0.1362 0.0201 0.3414 0.0203 0.3489 0.0202 0.248023 -0.0011 -0.1801 0.0213 0.3411 0.0231 0.4263 0.0210 0.253724 -0.0007 -0.1008 0.0236 0.3739 0.0318 0.6354 0.0187 0.227325 0.0014 0.2292 0.0229 0.3664 0.0287 0.5345 0.0116 0.138026 0.0003 0.0417 0.0236 0.3839 0.0207 0.3419 0.0143 0.173327 -0.0003 -0.0382 0.0188 0.2898 0.0163 0.2467 0.0193 0.2083

28 0.0006 0.0830 0.0211 0.3085 0.0150 0.2034 0.0161 0.168729 0.0004 0.0660 0.0193 0.2809 0.0103 0.1250 0.0157 0.164830 -0.0008 -0.1336 0.0183 0.2644 0.0169 0.2206 0.0184 0.180931 0.0001 0.0209 0.0172 0.2554 0.0198 0.2863 0.0182 0.178432 0.0014 0.1935 0.0175 0.2551 0.0246 0.3976 0.0208 0.203333 -0.0015 -0.1716 0.0195 0.2628 0.0302 0.4599 0.0263 0.251734 0.0012 0.1161 0.0192 0.2463 0.0253 0.3519 0.0224 0.215835 0.0009 0.1421 0.0233 0.3042 0.0213 0.2696 0.0283 0.301536 -0.0005 -0.0783 0.0239 0.2925 0.0274 0.3712 0.0204 0.219337 0.0003 0.0405 0.0262 0.2993 0.0257 0.3334 0.0188 0.204138 0.0002 0.0301 0.0276 0.3200 0.0327 0.4387 0.0165 0.169739 0.0000 0.0046 0.0278 0.3208 0.0319 0.3899 0.0235 0.2800

40 -0.0010 -0.1366 0.0222 0.2590 0.0407 0.4349 0.0221 0.225041 0.0005 0.0808 0.0253 0.2806 0.0386 0.4055 0.0168 0.161742 -0.0010 -0.1803 0.0273 0.2881 0.0375 0.3926 0.0181 0.162243 0.0012 0.1922 0.0290 0.2977 0.0242 0.2827 0.0160 0.152044 0.0010 0.1520 0.0255 0.2615 0.0203 0.2389 0.0204 0.179245 -0.0011 -0.1962 0.0252 0.2449 0.0147 0.1580 0.0184 0.168546 0.0007 0.0964 0.0298 0.2731 0.0096 0.1020 0.0144 0.108047 0.0001 0.0223 0.0243 0.2294 0.0254 0.3074 0.0222 0.177948 0.0008 0.1370 0.0249 0.2349 0.0284 0.3498 0.0234 0.182349 -0.0001 -0.0160 0.0283 0.2686 0.0259 0.3301 0.0264 0.223450 0.0002 0.0328 0.0241 0.2253 0.0219 0.3368 0.0227 0.1944


21/26

21

LIFFE-Wheat SFE-Greasy Wool SFE-Broad Wool SFE-Fine WoolT Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat51 0.0004 0.0791 0.0171 0.1587 0.0366 0.5245 0.0298 0.271752 0.0006 0.1182 0.0123 0.1173 0.0323 0.5726 0.0302 0.286853 0.0004 0.0558 0.0192 0.1882 0.0265 0.4934 0.0310 0.2826

54 0.0005 0.0799 0.0209 0.2066 0.0270 0.4789 0.0217 0.212755 0.0009 0.1485 0.0191 0.1900 0.0279 0.5845 0.0278 0.267656 0.0012 0.1878 0.0215 0.2170 0.0373 0.7642 0.0155 0.158257 0.0005 0.0828 0.0259 0.2591 0.0339 0.7868 0.0142 0.149358 0.0009 0.1622 0.0319 0.3118 0.0418 0.8870 0.0139 0.131559 0.0005 0.0834 0.0338 0.3325 0.0444 0.9206 0.0180 0.150960 0.0001 0.0168 0.0350 0.3523 0.0442 1.0581 0.0144 0.120661 -0.0003 -0.0526 0.0384 0.3927 0.0584 1.2407 0.0252 0.207362 -0.0021 -0.3770 0.0432 0.4312 0.0622 1.1694 0.0210 0.181163 0.0001 0.0201 0.0481 0.4629 0.0573 1.1904 0.0199 0.159864 0.0003 0.0584 0.0474 0.4519 0.0528 1.1658 0.0164 0.121065 0.0003 0.0262 0.0464 0.4348 0.0602 1.2474 0.0128 0.0941

66 -0.0006 -0.0892 0.0484 0.4686 0.0620 1.0261 0.0207 0.159167 0.0007 0.1297 0.0460 0.4286 0.0626 1.0375 0.0085 0.061068 0.0002 0.0307 0.0465 0.4353 0.0629 1.1193 0.0141 0.098969 0.0011 0.1884 0.0479 0.4299 0.0639 1.0040 0.0118 0.081270 0.0016 0.2544 0.0477 0.4232 0.0653 1.0117 0.0138 0.095671 -0.0005 -0.0868 0.0461 0.4053 0.0606 1.1321 0.0041 0.030472 -0.0003 -0.0383 0.0469 0.3984 0.0553 0.9808 0.0026 0.017073 0.0002 0.0253 0.0511 0.4248 0.0590 1.3462 0.0079 0.052474 -0.0005 -0.0651 0.0501 0.4131 0.0551 1.2851 0.0008 0.005375 -0.0002 -0.0238 0.0508 0.4220 0.0344 0.5899 -0.0045 -0.031376 -0.0004 -0.0629 0.0497 0.4092 0.0353 0.6367 0.0036 0.023677 -0.0022 -0.2953 0.0475 0.3860 0.0527 0.7958 -0.0083 -0.0571

78 -0.0013 -0.1452 0.0458 0.3763 0.0508 0.7658 -0.0146 -0.097279 0.0012 0.1752 0.0470 0.3790 0.0604 0.9985 -0.0042 -0.027880 0.0010 0.1188 0.0501 0.4116 0.0511 0.7871 -0.0009 -0.006481 0.0011 0.1542 0.0518 0.4300 0.0481 0.6605 0.0034 0.020882 0.0008 0.1350 0.0587 0.4785 0.0493 0.7178 0.0067 0.040183 0.0008 0.1519 0.0629 0.4970 0.0450 0.6056 0.0147 0.086384 -0.0001 -0.0277 0.0616 0.4859 0.0487 0.5950 0.0218 0.120285 0.0006 0.1221 0.0564 0.4490 0.0536 0.5687 0.0174 0.094686 -0.0006 -0.0974 0.0606 0.4678 0.0434 0.4496 0.0097 0.052487 0.0001 0.0196 0.0587 0.4508 0.0480 0.5819 0.0185 0.099588 -0.0014 -0.2914 0.0602 0.4600 0.0712 0.5512 0.0234 0.125289 -0.0006 -0.0866 0.0601 0.4528 0.0490 0.6821 0.0193 0.1083

90 0.0008 0.1259 0.0587 0.4338 0.0587 0.7434 0.0277 0.1533

Avg 0.0000 0.0284 0.0304 0.0142Std Dev 0.0009 0.0187 0.0219 0.0093

t-Stat 0.0413 1.5165 1.3885 1.5228# Pos 55 84 81 82# Neg 35 6 9 8% Neg 38.89% 6.67% 10.00% 8.89%


22/26

22

SFE-Wheat SFE-NSW Electric SFE-Vic Electric SIMEX-Crude Oilt Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat1 -0.0036 -0.2146 -0.0080 -0.2973 -0.0002 -0.0084 0.0009 0.03702 0.0032 0.1590 0.0100 0.1444 0.0037 0.0717 -0.0013 -0.03913 0.0007 0.0311 -0.0126 -0.1580 -0.0023 -0.0373 -0.0020 -0.0545

4 0.0021 0.0807 -0.0142 -0.1500 -0.0111 -0.0730 0.0011 0.02535 -0.0015 -0.0526 -0.0113 -0.1120 0.0020 0.0130 0.0064 0.12196 0.0045 0.1498 -0.0126 -0.1194 0.0300 0.1235 0.0054 0.09747 0.0112 0.3060 0.0008 0.0062 -0.0125 -0.0694 0.0071 0.12178 0.0050 0.1625 0.0139 0.0856 0.0052 0.0274 0.0069 0.11319 0.0068 0.2083 0.0275 0.1661 0.0316 0.1463 0.0054 0.0777

10 0.0049 0.1427 0.0136 0.0736 0.0513 0.2106 0.0034 0.047711 0.0050 0.1391 0.0425 0.2155 0.0665 0.2547 0.0015 0.022612 0.0071 0.1889 0.0472 0.2634 0.0899 0.3063 0.0049 0.070013 0.0112 0.2822 0.0524 0.2389 0.1378 0.3754 0.0015 0.021114 0.0138 0.3363 0.0498 0.2271 0.1096 0.3116 0.0035 0.048515 0.0172 0.4640 0.0488 0.1927 0.0764 0.2109 0.0006 0.0081

16 0.0245 0.4657 0.0653 0.2440 0.0899 0.2273 0.0028 0.034017 0.0185 0.3859 0.0895 0.3010 0.1421 0.3233 0.0002 0.002118 0.0208 0.3931 0.0751 0.2779 0.1360 0.3191 -0.0057 -0.069919 0.0167 0.3134 0.0755 0.2904 0.1400 0.3224 -0.0029 -0.035020 0.0185 0.3656 0.0748 0.2772 0.1295 0.3202 -0.0032 -0.038921 0.0140 0.3125 0.0826 0.2866 0.1497 0.3464 -0.0001 -0.000922 0.0136 0.2856 0.1035 0.3747 0.1506 0.3599 -0.0004 -0.004723 0.0144 0.2826 0.0875 0.3165 0.1393 0.3521 0.0020 0.020024 0.0130 0.2383 0.0938 0.3417 0.1484 0.3657 0.0012 0.011625 0.0229 0.3927 0.0975 0.3427 0.1620 0.3830 0.0033 0.032026 0.0188 0.3534 0.0955 0.3284 0.1484 0.3691 0.0030 0.028027 0.0190 0.3311 0.0845 0.2945 0.1430 0.3515 0.0046 0.0427

28 0.0156 0.2664 0.0671 0.2422 0.1529 0.3410 0.0092 0.083229 0.0202 0.3242 0.0897 0.2890 0.1512 0.3190 0.0104 0.091430 0.0208 0.3348 0.0750 0.2434 0.1546 0.3299 0.0080 0.068131 0.0215 0.3370 0.0889 0.2732 0.1525 0.3210 0.0091 0.076132 0.0242 0.3359 0.0945 0.2861 0.1678 0.3343 0.0068 0.056933 0.0228 0.3393 0.1076 0.3177 0.1731 0.3351 0.0075 0.063034 0.0273 0.3962 0.1066 0.3104 0.1878 0.3577 0.0042 0.034435 0.0286 0.3933 0.1179 0.3249 0.1990 0.3510 -0.0001 -0.000536 0.0217 0.2794 0.1069 0.3098 0.1790 0.3336 0.0028 0.023037 0.0238 0.2997 0.1069 0.2898 0.1801 0.3432 0.0031 0.025438 0.0225 0.2810 0.1072 0.3011 0.1879 0.3527 0.0032 0.025339 0.0283 0.3502 0.0999 0.2848 0.1875 0.3496 -0.0012 -0.0097

40 0.0316 0.3814 0.1027 0.2963 0.1867 0.3553 -0.0023 -0.018841 0.0237 0.2758 0.1028 0.3037 0.1985 0.3590 0.0004 0.002842 0.0242 0.2736 0.1154 0.2900 0.1899 0.3551 0.0031 0.024043 0.0305 0.3056 0.1192 0.3028 0.1828 0.3508 0.0011 0.008944 0.0274 0.2448 0.1252 0.3142 0.1851 0.3510 0.0045 0.033145 0.0240 0.2222 0.1328 0.3247 0.2343 0.4605 0.0041 0.030946 0.0214 0.1960 0.1364 0.3410 0.2304 0.4451 0.0057 0.040547 0.0336 0.2781 0.1481 0.3542 0.2643 0.4492 0.0059 0.040348 0.0323 0.2683 0.1390 0.3641 0.2484 0.4519 0.0099 0.066049 0.0341 0.2772 0.1138 0.3110 0.2176 0.4375 0.0084 0.054750 0.0317 0.2642 0.1110 0.3160 0.2292 0.4469 0.0104 0.0672


23/26

23

SFE-Wheat SFE-NSW Electric SFE-Vic Electric SIMEX-Crude Oilt Avge. t-Stat Avge. t-Stat Avge. t-Stat Avge. t-Stat

51 0.0266 0.2260 0.1343 0.3495 0.2036 0.4231 0.0120 0.074852 0.0308 0.2411 0.1272 0.3312 0.2142 0.4179 0.0113 0.069653 0.0327 0.2576 0.1284 0.3277 0.2060 0.4062 0.0095 0.0582

54 0.0292 0.2179 0.1373 0.3547 0.2250 0.4119 0.0089 0.054055 0.0263 0.1946 0.1300 0.3300 0.2440 0.4181 0.0117 0.070756 0.0419 0.3049 0.1231 0.3210 0.2438 0.4282 0.0090 0.053357 0.0487 0.3492 0.1278 0.3152 0.2468 0.4340 0.0087 0.051458 0.0460 0.3409 0.1402 0.3370 0.2497 0.4335 0.0086 0.050759 0.0490 0.3407 0.1356 0.3218 0.2534 0.4343 0.0097 0.057160 0.0455 0.3373 0.1412 0.3352 0.2415 0.4277 0.0095 0.054561 0.0387 0.2914 0.1365 0.3296 0.2512 0.4248 0.0075 0.043462 0.0391 0.2893 0.1386 0.3366 0.2467 0.4245 0.0059 0.034963 0.0359 0.2718 0.1306 0.3285 0.2357 0.4150 0.0064 0.037964 0.0353 0.2591 0.1448 0.3497 0.2373 0.4184 0.0069 0.040165 0.0426 0.2955 0.1474 0.3584 0.2553 0.4347 0.0066 0.0382

66 0.0393 0.2780 0.1504 0.3654 0.2409 0.4350 0.0094 0.054567 0.0412 0.2870 0.1503 0.3616 0.2625 0.4369 0.0096 0.055568 0.0444 0.3043 0.1179 0.3272 0.2272 0.4264 0.0153 0.085069 0.0416 0.2818 0.0949 0.2602 0.2104 0.3953 0.0136 0.073870 0.0464 0.2709 0.1021 0.2725 0.2214 0.3843 0.0181 0.096671 0.0414 0.2636 0.0924 0.2506 0.2089 0.3628 0.0153 0.080272 0.0428 0.2777 0.0935 0.2494 0.2128 0.3729 0.0172 0.089973 0.0381 0.2675 0.0895 0.2298 0.2248 0.3837 0.0225 0.113374 0.0402 0.2929 0.0880 0.2374 0.2083 0.3728 0.0189 0.096475 0.0432 0.2843 0.0980 0.2503 0.2224 0.3676 0.0177 0.089576 0.0414 0.2490 0.1051 0.2525 0.2195 0.3603 0.0158 0.080677 0.0404 0.2431 0.0921 0.2341 0.2263 0.3734 0.0158 0.0807

78 0.0382 0.2334 0.0906 0.2303 0.2008 0.3489 0.0153 0.076879 0.0422 0.2680 0.0942 0.2359 0.2147 0.3763 0.0167 0.083480 0.0446 0.2681 0.0977 0.2379 0.2135 0.3731 0.0174 0.087781 0.0507 0.3298 0.1057 0.2514 0.2242 0.3801 0.0188 0.093782 0.0534 0.3490 0.0896 0.2223 0.2129 0.3677 0.0160 0.079483 0.0564 0.3804 0.0857 0.2214 0.2134 0.3740 0.0171 0.083584 0.0572 0.3553 0.0698 0.1939 0.2201 0.3856 0.0145 0.071285 0.0635 0.3745 0.0785 0.2207 0.2118 0.3891 0.0183 0.091686 0.0559 0.3382 0.0802 0.2243 0.2109 0.4061 0.0185 0.092687 0.0587 0.3442 0.0842 0.2301 0.2306 0.4090 0.0163 0.082288 0.0578 0.3372 0.0792 0.2203 0.2191 0.3907 0.0170 0.083189 0.0555 0.3326 0.0974 0.2819 0.2320 0.3958 0.0218 0.1060

90 0.0552 0.3163 0.0542 0.1588 0.1593 0.3027 0.0234 0.1113

Avg 0.0295 0.0910 0.1744 0.0080Std Dev 0.0161 0.0412 0.0729 0.0068

t-Stat 1.8324 2.2108 2.3918 1.1774# Pos 88 85 86 80# Neg 2 5 4 10% Neg 2.22% 5.56% 4.44% 11.11%


24/26

Table 5REGRESSION RESULTS a: D i,t = i + it + i,t

Commodity HCSE ( ) t-stat ( ) HCSE ( ) t-stLIFFE-Barley -0.007374 0.001624 -4.540864 0.000137 0.0000153 8.958261LIFFE-Cocoa 0.059004 0.004098 14.39764 0.000111 0.0000205 5.395005LIFFE-Coffee 0.011360 0.005267 2.156779 -0.000125 0.0000436 -2.861777LIFFE-Sugar 0.001658 0.003234 0.512535 0.000017 0.0000209 0.816978LIFFE-Wheat -0.007648 0.002236 -3.420443 0.000162 0.0000201 8.063265SFE-Greasy Wool -0.007723 0.004017 -1.922810 0.000788 0.0000288 27.37942SFE-Broad Wool -0.015388 0.003153 -4.879934 0.001126 0.0000201 56.10775SFE-Fine Wool 0.030892 0.005543 5.572997 0.000130 0.0000392 3.320046SFE-NSW Electricity 0.150014 0.008634 17.37431 -0.001549 0.0000501 -30.94482SFE-Vic. Electricity 0.243595 0.012487 19.50767 -0.001930 -0.0000685 -28.17755SFE-Wheat 0.032156 0.003561 9.029763 0.000161 0.0000180 8.938615SIMEX-Crude Oil -0.008245 0.004437 9.330567 0.003900 0.0000418 -1.858294

a Using a maximum of 5000 randomly selected observations and White's correction for heteroskedasticity.


25/26

25

References

Bera, A. K. and C. M. Jarque (1981) An efficient large-sample test for normality of observations in regression residuals, Australian National University Working Papersin Econometrics, 40, Canberra.

Black, F., 1976, The pricing of commodity contracts, Journal of Financial Economics3, 167-179.

Bodie, Z. and V.I. Rosansky, 1980, Risk and return in commodity futures, FinancialAnalysis Journal 36, 27-39.

Cootner, P.H., 1960, Returns to speculators: Telser vs Keynes, Journal of PoliticalEconomy 68 (August), 396-404.

Cootner, P.H., 1967, Speculation and hedging, Food Research Institute Studies 7,Supplement, 65-106.

Deaves, R. and I. Krinsky, 1995, Do futures prices for commodities embody risk premiums, Journal of Futures Markets 15, pp. 637-648.

Dusak, K.,1973, Futures trading and investor returns: an investigation of commoditymarket risk premiums, Journal of Political Economy 8, 1387-1406.

Fama, E.F. and K.R. French, 1987, Commodity futures prices: some evidence onforecast power, premiums, and the theory of storage, Journal of Business 60, 55-73.

Hardy, C., 1940, Risk and risk bearing (Chicago: University of Chicago Press).

Hicks, J.R.,1946, Value and capital (2nd Edition, London: Oxford University Press).

Houthakker, H.S.,1957, Can speculators forecast prices?, The Review of Economicsand Statistics 39, 143-151.

Kawai, M., 1989, Normal backwardation (entry in The New Palgrave Dictionary of

Finance, The Macmillan Press, London) 89-90.

Keynes, J.M., 1923, Some aspects of commodity markets, The Manchester GuardianCommercial reconstruction Supplement 29, March. Reprinted in The CollectedWritings of John Maynard Keynes, Vol 7 (London, Macmillan; New York: St.Martins Press, 1971).

Keynes, J.M., 1930, A treatise on money, Vol 2. London: Macmillan: Reprinted inThe Collected Writings of John Maynard Keynes, Vol 7 (London, Macmillan; NewYork: St. Martins Press, 1971).

Kolb, R.W., 1992, Is normal backwardation normal?, The Journal of Futures Markets12, 1, .75-91.


26/26

Litzenberger, R.H. and N. Rabinowitz, 1995, Backwardation in oil futures markets:theory and evidence, Journal of Finance 5, 1517-1645.

Rockwell, C., 1967, Normal backwardation, forecasting and returns to commodityfutures traders, Food Research Institute Studies 7, Supplement, 107-130.

Telser, L.G., 1958, Futures trading and the storage of cotton and wheat, Journal of Political Economy 66 (June), 233-55.

White, H., 1980, A heteroskedasticity-consistent covariance matrix and a direct testfor heterskedasticity, Econometrica 48.

Working, H., 1948, The theory of the price of storage, American Economic Review39 (December), 1254-62.

Documents

Backwards to the Future: A Test of Three Futures Markets