原油現(xiàn)貨和期貨價格關(guān)系：協(xié)整,線性和非線性因果關(guān)系【外文翻譯】

1、外文題目： The Relationship between Crude Oil Spot and FuturesPrices: Cointegration, Linear and Nonlinear Causality出 處：Energy Economics作者： Stelios D.Bekiros , Cees GH Diks原文：The Relationship between Crude Oil Spot and Futures Prices:Cointegration, Linear and Nonlinear Causality!AbstractThe present study

2、investigates the linear and nonlinear causal linkages between daily spot and futures prices for maturities of one, two, three and four months of West Texas Intermediate (WTI) crude oil. The data cover two periods October 1991-October 1999 and November 1999-October 2007, with the latter being signifi

3、cantly more turbulent. Apart from the conventional linear Granger test we apply a new nonparametric test for nonlinear causality by Diks and Panchenko after controlling for cointegration. In addition to the traditional pairwise analysis, we test for causality while correcting for the effects of the

4、other variables. To check if any of the observed causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VECM filtered residuals. Finally, we investigate the hypothesis of nonlinear non-causality after controlling for conditional heteroskedasticity in the dat

5、a using a GARCH-BEKK model. Whilst the linear causal relationships disappear after VECM cointegration filtering, nonlinear causal linkages in some casespersist even after GARCH filtering in both periods. This indicates that spot and futures returns may exhibit asymmetries and statistically significa

6、nt higher-order moments. Moreover, the results imply that if nonlinear effects are accounted for, neither market leads or lags the other consistently, videlicet the pattern of leads and lags changes over time.Keywords:Nonparametric nonlinear causality; Oil Futures Market;Cointegration;The role of fu

7、tures markets in providing an efficient price discovery mechanism has been an area of extensive empirical research. Several studies have dealt with the Lead-lag relationships between spot and futures prices of commodities with the objective of investigating the issue of market efficiency. Garbade an

8、d Silber (1983) first presented a model to examine the price discovery role of futures prices and the effect of arbitrage on price changes in spot and futures markets of commodities. The Garbade-Silber model was applied to the feeder cattle market by Oellermann et al. (1989) and to the live hog comm

9、odity market by Schroeder and Goodwin (1991), while a similar study by Silvapulle and Moosa (1999) examined the oil market. Bopp and Sitzer (1987) tested the hypothesis that futures prices are good predictors of spot prices in the heating oil market, while Serletis and Banack (1990) and Chen and Lin

10、 (2004) tested for market efficiency using cointegration analysis. Crowder and Hamed (1993) and Sadorsky (2000) also used cointegration to test the simple efficiency hypothesis and the arbitrage condition for crude oil futures. Finally, Schwarz and Szakmary (1994) examined the price discovery proces

11、s in the markets of crude and heating oil.In theory, since both futures and spot prices“ refect ” the same aggregate valuethe underlying asset and considering that instantaneous arbitrage is possible, futures should neither lead nor lag the spot price. However, the empirical evidence is diverse, alt

12、hough the majority of studies indicate that futures influence spot prices but not vice versa. The usual rationalization of this result is that the futures prices respond to new information more quickly than spot prices, due to lower transaction costs and flexibility of short selling. With reference

13、to the oil market, if new information indicates that oil prices are likely to rise, perhaps becauseof an OPEC decision to restrict production, or an imminent harsh winter, a speculator has the choice of either buying crude oil futures or spot. Whilst spot purchases require more initial outlay and ma

14、y take longer to implement, futures transactions can be implemented immediately by speculators without an interest in the physical commodity per se and with little up-front cash. Moreover, hedgers who are interested for the physical commodity andhave storage constraints will buy futures contracts. T

15、herefore, both hedgers and speculators will react to the new information by preferring futures rather than spot transactions. Spot prices will react with a lag because spot transactions cannot be executed so quickly (Silvapulle and Moosa, 1999). Furthermore, the price discovery mechanism, as illustr

16、ated by Garbade and Silber (1983), supports the hypothesis that futures prices lead spot prices. Their study of seven commodity markets indicated that, although futures markets lead spot markets, the latter do not just echo the former. Futures trading can also facilitate the allocation of production

17、 and consumption over time, particularly by providing a market scheme in inventory holdings (Houthakker, 1992). In this case, if futures prices for late deliveries are above those for early ones, delay of consumption becomes attractive and changes in futures prices result in subsequentchangesin spot

18、 prices. According to Newberry (1992) futures markets provide opportunities for market manipulation by the better informed or larger at the expenseof other market participants. For example, it is profitable for the OPEC to intervene in the futures market to influence the production decisions of its

19、competitors in the spot market. Finally, support for the hypothesis that causality runs from futures to spot prices can also be found in the model of determination of futures prices proposed by Moosa and Al-Loughani (1995). In their model the futures price is determined by arbitrageurs whose demand

20、depends on the difference between the arbitrage and actual futures price and by speculators whose demand for futures contracts depends on the difference between the expected spot and the actual futures price. The reference point in both casesis the futures price and not the spot price (Silvapulle an

21、d Moosa, 1999).The aim of the present study is to test for the existence of linear and nonlinea causal lead-lag relationships between spot and futures prices of West Texas Intermediate(WTI) crude oil, which is used as an indicator of world oil prices and is the underlying commodity of New York Merca

22、ntile Exchanges (NYMEX) oil futures contracts. We apply a three-step empirical framework for examining dynamic relationships between spot and futures prices. First, we explore nonlinear and linear dynamic linkages applying the nonparametric Diks-Panchenko causality test, and after controlling for co

23、integration, a parametric linear Granger causality test. In the second step, after filtering the return series using the properly specified VR or VECM model, the series of residuals are examined by the nonparametric Diks-Panchenko causality test. In addition to applying the usual bivariate VAR or VE

24、CM model to each pair of time series, we also consider residuals of a full five-variate model to account for the possible effect of the other variables. This step ensures that any remaining causality is strictly nonlinear in nature, as the VAR or VECM model has already purged the residuals of linear

25、 dependence. Finally, in the last step, we investigate the null hypothesis of nonlinear non-causality after controlling for conditional heteroskedasticity in the data using a GARCH-BEKK model, again both in a bivariate and in a five-variate representation. Our approach incorporates the entire varian

26、ce-covariance structure of the spot and future prices interrelationship. The empirical methodology employed with the multivariate GARCH-BEKK model can not only help to understand the short-run movements, but also explicitly capture the volatility persistence mechanism. Improved knowledge of the dire

27、ction and nature of causality and interdependence between the spot and futures markets, and consequently the degree of their integration, will expand the information set available to policymakers, international portfolio managers and multinational corporations for decision-making.The remainder of th

28、e paper is organized as follows. Section 2 briefly reviews the linear Granger causality framework and provides a description of the Diks-Panchenko nonparametric test for nonlinear Granger causality. Section 3 describes the data used and Section 4 presents the results. Section 5 concludes with a summ

29、ary and suggestions for future research.Figure 1 displays the spot and future price and returns time series. The following notation is used: WTI Spot ” is the spot price and , “ WTI FWTI FWTI F3”and “ WTI F4 are the futures prices for maturities of one, two, three and four months respectively. Descr

30、iptive statistics for WTI spot and futures log-daily returns are reported in Table 1. Specifically, the returns are defined as where Pt is the closing price on day t. The differences between the two periods are quite evident in Table 1 where a significant increase in variance can be observed as well

31、 as a higher dispersion of the returns distribution in Period II reflected in the lower kurtosis. Additionally, Period II witnessed many occasional negative spikes as it can be also inferred from the skewness. The results from testing nonstationarity are presented in Table 2.Specifically, Table 2 re

32、ports the Augmented Dickey-Fuller (ADF) test for the logarithmic levels and log-daily returns. The lag lengths which are consistently zero in all caseswere selected using the Schwartz Information Criterion (SIC). All the variables appear to be nonstationary in log-levels and stationary in log-return

33、s based on the reported p-values. Table 1 also reports the correlation matrix at lag 0 (contemporaneous correlation) for both periods. Significant sample cross-correlations are noted for spot and futures returns indicating a high interrelationship between the two markets. However, since linear corre

34、lations cannot be expected to fully capture the long-term dynamic linkages in a reliable way, these results should be interpreted with caution. Consequently, what is needed is a long-term causality analysis.15*Wujt 】:胃Tl prke and return ;iit指 的一1必口心出7 值2 hi Pl:lfr?2inWMflW9/99? dnJSUT;ible 1: Descri

35、ptive Starts LiesPeriod K10/21/1W1-10/29/1W9IM 丁1 SpHM Tl FlWTI FNVTI F3*n f+5.000044J .00005-D.OODOS-a.OODG40 00 004sndand Devijrinn0.020600.0197S0.017023.015420.01432Soinplc Variance0.00042O.OOC390.OD029D.0D0240.DDD21Kurt 口 Ke6.144.474.72一二 m4.51SkeTe=i5013790,170270 J 60220.096160 10314G)rrn (air

36、o n Mat rixWTJ SptK7/nHT/ F?WTi F377 F4TlSpnt1HR 770.84&-rUT/ Fl0.9350,955J0.S240 3360.993rWT/ F40.8f30.91709830.9&61Period H (.U/1/1W9- l(V3V2O07jYTI SpotHT1 FlWTI HWTI F3U TI F4XfennCLODOB9db誕J?0D5G9Q.OOD6S,nDD69Standard Dcviaiion01O238&0.022760.0 20830.0145o.oi a?gSample Vajiance0.000570.000520.0

37、00430400036O.DDO35KlLTtQSL?4.043.062 651 .3B3.05Skeuiies-3.56 317038。3 44623J3&B36Girrclnrion Sirix卬療牛*WTJF7WTJ F2*77 F3WTI F4TlSpni1WTiFi08711tm F2門州9Q0TQ7&S490.9570.9941IE F40.8230.9320.9730,983JTabk 2t Unit rout Lesli、iriablADF-EtuiEli(? (PIADF-tatistic(.PII)HF Spot iR0.0390.943工WH即h(UHNTCLUOOWTl

38、Flffl)0.0440.967tifiao.ooo-0,000WTI F2 010.070Q.974WTI F：1口O.OOO-(hOOfTUTI F3 班OjOSS0.9 7Rr u.TJ fi(00.000*r.oooTl F4 50.003加UlTI FJ. Qo.onoc.oon-In the present paper we investigated the existence of linear and nonlinear causal relationships between the daily spot and futures prices for maturities o

39、f one, two, three and four months of West Texas Intermediate (WTI), which is the underlying commodity of New York Mercantile Exchanges (NYMEX) oil futures contracts. The data covered two separate periods, namely PI: 10/21/1991-10/29/1999 and PII: 11/1/1999-10/30/2007， with the latter being significa

40、ntly more turbulent. The study contributed to the literature on the lead-lag relationships between the spot andfutures markets in several ways. In particular, it was shown that the pairwise VECM modeling suggested a strong bidirectional Granger causality between spot and futures prices in both perio

41、ds, whereas the five-variate implementation resulted in a uni-directional causal linkage from spot to futures prices only in PII. This empirical evidence appears to be in contrast to the results of Silvapulle and Moosa (1999) on the futures to spot prices uni-directional relationship. Additionally,

42、whilst the linear causal relationships have disappeared after the cointegration filtering, nonlinear causal linkages in some cases were revealed and more importantly persisted even after multivariate GARCH filtering during both periods. Interestingly, it was shown that the five-variate implementatio

43、n of the GARCH-BEKK filtering, as opposed to the bi-variate, captured the volatility transmission mechanism more effectively and removed the nonlinear causality due to second moment spillover effects. Moreover, the results imply that if nonlinear effects are accounted for, neither market leads or la

44、gs the other consistently, or in other words the pattern of leads and lags changes over time. Given that causality can vary from one direction to the other at any point in time, a finding of bi-directional causality over the sample period may be taken to imply a changing pattern of leads and lags ov

45、er time, providing support to the Kawaller et al. (1988) hypothesis. Hence it can be safely concluded that, although in theory the futures market play a bigger role in the price discovery process, the spot market also plays an important role in this respect. These conclusions, apart from offering a

46、much better understanding of the dynamic linear and nonlinear relationships underlying the crude oil spot and futures markets, may have important implications for market efficiency. For instance, they may be useful in future research to quantify the process of market integration or may influence the

47、 greater predictability of these markets.An interesting subject for future research is the nature and source of the nonlinear causal linkages. As presented, volatility effects may partly account for nonlinear causality. The GARCH-BEKK model partially captured the nonlinearity in daily spot and futur

48、e returns, but only in some cases. An explanation could be that spot and futures returns may exhibit statistically significant higher-order moments. A similar result was reported by Scheinkman and LeBaron, (1989) for stock returns. Alternatively, parameterized asymmetric multivariate GARCH models co

49、uld be employed in order to accommodate the asymmetric impact of unconditional shocks on the conditional variances.外文題目： The Relationship between Crude Oil Spot and FuturesPrices: Cointegration, Linear and Nonlinear Causality出 處：Energy Economics作者： Stelios D.Bekiros , Cees GH Diks譯文：原油現(xiàn)貨和期貨價格關(guān)系：協(xié)整，線

50、性和非線性因果 關(guān)系摘要本文研究探討原油現(xiàn)貨價格日報價和西德克薩斯中質(zhì)油(WTD距到期1個月，2個月，3個月，4個月的期貨價格的線性及非線性關(guān)系。數(shù)據(jù)包括 1991年 10月至1999年10月和1999年11月至2007年10月兩個時期，而且后者明顯 更加動蕩。除了傳統(tǒng)的線性格蘭杰檢驗，在Diks和Panchenko進(jìn)行協(xié)整控制后， 我們還進(jìn)行了非線性因果關(guān)系的非參數(shù)檢驗。除了傳統(tǒng)的成對分析，我們還做了 校正其他變量后的因果關(guān)系。為了檢測所有研究的非線性都是完全的非線性，我們分析了向量誤差修正模型的濾波殘差的非線性因果關(guān)系。最后，我們在使用GARCH-BEKK型控制了數(shù)據(jù)中的異方差后對非線性的

51、非因果關(guān)系的假設(shè)進(jìn)行了研究。 雖然線性因果關(guān)系在向量誤差修正模型協(xié)整過濾后消失， 非線性因果關(guān)系在GARCHI型2次過濾后在一些情況下仍然堅持。這表明，現(xiàn)貨與期貨回歸可能會出現(xiàn)顯著不對稱和高階矩。此外，研究結(jié)果表明，如果非線性效應(yīng)被解釋，市場不會一直領(lǐng)先或滯后，也就是說，領(lǐng)先或滯后的形式會隨時間而變化。關(guān)鍵詞： 非參數(shù)的非線性因果關(guān)系；石油期貨市場；協(xié)整；期貨市場在有效的價格發(fā)現(xiàn)機(jī)制的作用， 一直是有廣泛實證研究的領(lǐng)域。 一些研究以調(diào)查市場效率問題為目標(biāo)來處理商品的現(xiàn)貨和期貨價格之間的超前滯后關(guān)系。Garbade和Silber (1983)首先提出了一個模型，來檢驗期貨價格價格發(fā)現(xiàn)的作用和套利

52、在商品現(xiàn)貨和期貨市場的價格變動的影響。 Garbade-Silber模型被 Oellermann 等 (1989) 用在肉牛市場， 被 Schroeder 和 Goodwin (1991)用在生豬商品市場中，被Silvapulle 和 Moosa (1999) 用在石油市場用來做類似的研究。 Bopp 和 Sitzer (1987) 測試了在燃料油市場期貨價格是現(xiàn)貨價格的良好預(yù)測的假設(shè)，而Serletis ， Banack (1990) 和 Chen ， Lin (2004) 利用協(xié)整分析測試了市場效率。 Crowder ， Hamed (1993)和 Sadorsky (2000) 也利用協(xié)

53、整檢驗了簡單的效率假說和原油期貨套利條件。最后， Schwarz 和 Szakmary (1994) 研究了在原油和取暖油市場的價格發(fā)現(xiàn)過程。從理論上講， 因為期貨價格和現(xiàn)貨價格反映了相關(guān)資產(chǎn)的相同的總價值， 并且考慮到瞬間套利的可能， 期貨價格不會引導(dǎo)或滯后于現(xiàn)貨價格。 不過， 實驗證據(jù)是多種多樣的， 大多數(shù)研究表明， 期貨影響現(xiàn)貨價格但不是反之亦然。 這樣的結(jié)果通常是， 由于更低的交易成本和賣空的靈活性， 期貨價格比現(xiàn)貨價格可以更快的對新信息作出反映。 參照石油市場， 如果有新信息表明石油價格可能會因為OPEC決定限制生產(chǎn)或嚴(yán)酷的冬季即將到來，一個投機(jī)者有購買期貨原油或現(xiàn)貨原油的選擇。 現(xiàn)

54、場購買需要更多的初始費(fèi)用和更長的時間來實現(xiàn)， 而期貨交易可以立即實現(xiàn)， 且只需少量的預(yù)付金。 此外， 對實物商品感興趣卻有存儲限制的人將購買期貨合約。 因此， 套期保值者和投機(jī)者都將對期貨的新信息作出反應(yīng)而不是現(xiàn)貨交易。因為 現(xiàn) 貨交易 的 實行比 較 慢，所以 現(xiàn)貨價 格會有滯后 反應(yīng) (Silvapulle 和 Moosa, 1999) 。此外，價格發(fā)現(xiàn)機(jī)制，如 Garbade 和 Silber (1983) 所示， 支持期貨價格引導(dǎo)現(xiàn)貨價格的假說。 他們的七個商品市場的研究表明， 雖然期貨市場領(lǐng)先現(xiàn)貨市場， 后者不只是回應(yīng)前者。 期貨交易也可以在一段時間內(nèi)促進(jìn)生產(chǎn)和消費(fèi)的分配，尤其是提供

55、一個市場計劃中的庫存量 (Houthakker, 1992) 。在這種情況下，如果逾期交貨的期貨價格高于早期的，消費(fèi)的延遲和期貨價格的變化會導(dǎo)致隨后現(xiàn)貨價格的變化。 根據(jù) Newberry( 1992) ， 期貨市場通過靈通的消息和其他市場參與者更大的損失來為市場操縱提供機(jī)會。例如，OPEC!過干預(yù)期貨市場來影響現(xiàn)貨市場競爭對手的生產(chǎn)決策，這對他來說是有利可圖的。 最后， 關(guān)于對期貨和現(xiàn)貨價格因果關(guān)系的假設(shè)的支持也可以在Moosa 和 Al-Loughani (1995) 提出的期貨價格確定模型中找到。 在他們的模型中期貨價格取決于需求來自套利和實際期貨價格之間的差異的套利者和需求來自存在預(yù)期現(xiàn)貨和實際期貨價格差異的期貨合約的投機(jī)者。 在這兩種情況下的參考點(diǎn)是期貨價格，而不是現(xiàn)貨價格 (Silvapulle 和 Moosa, 1999) 。本研究的目的是測試西德克薩斯中質(zhì)油( WT原油的現(xiàn)貨與期貨價格之間的線性和非線性超前滯后因果關(guān)系的存