Hedging Or Speculation in Derivative Markets: the Case of Energy Futures Contracts
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Applied Financial Economics Letters, 2006, 2, 189–192 Hedging or speculation in derivative markets: the case of energy futures contracts Cetin Ciner Cameron School of Business, University of N. Carolina – Wilmington, Wilmington, NC 28403, USA E-mail: [email protected] This study examines whether hedging or speculation is the principal motive behind trading in energy futures markets. This question is important since facilitating risk allocation is considered to be one of the main benefits of the futures markets, while excess speculation in futures markets could destabilize the underlying spot market. Studying the linkage between volume and subsequent price movements leads to the conclusion that hedgers dominate speculators in all of the markets examined. I. Introduction spot markets. Thus, the amount of risk allocation, relative to speculation, is important to regulators and An important benefit of futures markets to society, policy makers. along with price discovery, stems from the facilitation Ederington and Lee (2002) report on the first study of risk allocation (hedging). While many empirical that examines who actually trades in a major futures studies focus on the accuracy of price discovery, few market. They document the trading activities of the papers provide evidence on the relative importance of 223 largest traders in the heating oil futures market, hedging versus speculation as the main form of who account for almost 80% of the total trading trading activity in futures markets.1 This bifurcation volume and open interest. They show that potential is important because futures markets are sometimes hedgers, defined as traders who have positions on portrayed as forums where informed traders can both spot and futures markets, dominate the trading fleece unsophisticated investors, leading to regulatory activity. attempts to control the amount of trading in The present study further investigates whether futures markets.2 Furthermore, if speculators domi- hedging or speculation is more prevalent in energy nate the futures markets, it could be argued that futures (crude oil, heating oil and unleaded gasoline) futures market trading might destabilize underlying markets by relying on a relatively new approach 1 The main reason why there is little empirical work is data limitation. To determine whether futures markets properly facilitate hedging, hedgers need to be segregated from speculators in total market activity. In prior work, researchers, such as Wang (2003), de Roon et al. (2000), Chang et al. (2000) and Bessembinder and Senguin (1993), use the commercials versus non-commercials classification by the Commodity Futures Trading Commission (CFTC) to disaggregate total market activity into hedgers and speculators. 2 Chang et al. (2000) report that over 100 bills have been introduced to lower or even abolish the amount of trading in futures markets, although almost always the attempt was unsuccessful. Applied Financial Economics Letters ISSN 1744–6546 print/ISSN 1744–6554 online ß 2006 Taylor & Francis 189 http://www.tandf.co.uk/journals DOI: 10.1080/17446540500461729 190 C. Ciner by Llorente, Michaely, Saar and Wang (2002, current period and therefore, prices will continue to LMSW).3 Their model, which is discussed further change in the same direction in the next period. below, suggests that trading volume on a financial Consequently, speculative trades generate positive market acts as a signal to market observers about return autocorrelations. whether hedging or speculation is the main motive to Volume has a prominent role in the LMSW model. trade. They conduct an empirical investigation of Specifically, LMSW argue that volume can be used their model using US stock market data and find to distinguish between price changes due to public supportive evidence. Moreover, Lucey (2005) and information and those due to hedging or speculation. Ciner and Karagozoglu (2004) apply the model in Public news is incorporated into prices via normal Irish and Turkish equity markets, respectively.4 trading, while hedging and speculative trades are However, this is the first study to focus on the characterized by extensive volume. Hence, as stated futures markets within the LMSW framework. in the introduction, the central implication of the In empirical analysis, the study shows that days LMSW approach is that high volume days will be with high trading volume are followed by price followed by price reversals, when hedging is the reversals (negative return autocorrelations) in all primary motive to trade, however, price continua- three energy futures contracts, namely, the crude tions will be observed when speculation is the primary oil, heating oil and unleaded gasoline futures. This motive. This proposition can be examined by esti- finding suggests that hedging is relatively more mating the following equation: important than speculation as the main motive to 2 1=2 trade in energy futures markets, which is perfectly Rt ¼ þ 0 þ 1VtÀ1 þ 2VtÀ1 þ 3htÀ1 RtÀ1 þ ut consistent with the conclusions of Ederington and ð1Þ Lee (2002). in which Vt denotes log volume series, Rt denotes returns, calculated as log price differences, and htÀ1 is the conditional volatility series obtained from the II. Background and Hypotheses following GARCH model5: R ¼ " LMSW propose a simple equilibrium model to t R,t examine the relation between trading volume and "R,tj tÀ1 t:dð0, ht, vÞ price movements in asset markets. Their model 2 2 ht ¼ 0 þ 1"R,tÀ1 þ 2htÀ1 þ et suggests that returns are generated by three separate sources: public information, hedging and speculation. in which the residual term "R,t follows a conditional It is assumed that public news causes only a white Student’s t distribution (t.d) with degrees of noise component, while returns generated by hedging freedom and a conditional variance ht. tÀ1 is the and speculation are serially correlated. Hedging information set that contains all relevant information trades do not reflect new information and the at time t À 1. expected payoff from the asset remains the same. The model in Equation 1 is a modified version of Hence, the asset must be sold at a discount to attract the regressions in LSMW.6 It measures the inter- other traders to take the other side of the transaction. action between return autocorrelation and lagged Price rises back to its original level in the next period, volume by 1, lagged volume squared by 2, and since the fundamental value is unchanged. In a conditional volatility by 3. Squared volume series hedging trade, therefore, an initial negative return is are included to account for nonlinear relations followed by a positive return in the second period, between return autocorrelations and volume and 3 generating negative return autocorrelations. examines linkages between conditional variance and Speculative trades, on the other hand, are caused volume (see, Karpoff (1987) for a survey of volume- by the asymmetric information of informed volatility linkages). traders. LMSW argue that private information However, the main coefficient interest in the will be only partially incorporated into prices in the investigation is 1, the measure of interaction between 3 The study focuses on the energy futures markets for two main reasons. First, the energy futures markets are among the most active and liquid futures markets. Second, the recent work of Ederington and Lee (2002), suggesting that potential hedgers are more active on the heating oil futures market, provides a priori expectations to compare the results of the present study. 4 Lucey (2005) argues that the conclusions of LMSW do not obtain on the Irish market, while Ciner and Karagozoglu (2004) find supportive evidence in the Turkish case. 5 In a strict sense, returns do not exist in futures markets since there is no initial investment. 6 The regression estimated by LMSW does not include a conditional volatility term. Hedging or speculation in derivative markets 191 Table 1. Sample summary statistics Crude oil Heating oil Unleaded gasoline Returns Volume Returns Volume Returns Volume Mean À0.00003 0.014 À0.00009 0.014 À0.00003 0.016 Std. Deviation 0.023 0.342 0.0275 0.343 0.026 0.314 Skewness À1.733 À0.601 À1.529 À0.147 À0.461 À0.215 Kurtosis 27.895 1.033 25.352 0.223 11.859 0.358 Note: This table provides descriptive statistics of the data set. The sample covers the period between 2 January 1990 and 26 December 2001, for a total of 3002 observations. The volume series are detrended using a 200-day moving average component. return autocorrelation and lagged volume. If hedging residual; hence, the error terms are modelled as is relatively more important than speculation on the autoregressive processes and reestimate the regres- energy futures markets, high volume days will be sions by the maximum likelihood (ML) method. Lags followed by price reversals and 1 will be negative of one through five are considered and the appro- and statistically significant. On the other hand, if priate lag determined for the autoregressive structure speculation is the primary trading motive, price by calculating the Godfrey test against white noise continuations are expected following high volume alternatives.8 days and 1 will be positive and significant. The findings, reported in Table 2, indicate that 1 is negative and statistically significant in all cases, suggesting that days with high trading volume are followed by price reversals. This finding implies that, III. Data and Findings within the context of LMSW, hedging is relatively more important in energy futures markets, in line The data consist of daily closing prices and trading with the arguments of Ederington and Lee (2002). volume for crude oil, heating oil and unleaded This is also consistent with the overall conclusions of gasoline futures contracts traded on the NYMEX. Chang et al. (2000) on stock index futures markets. The data span the period between 2 January 1990 and Furthermore, estimates of 2 suggest significant 26 December 2001, for a total of 3003 observations nonlinearities in the volume-return autocorrelation and are obtained from the NYMEX.