Oil Prices and Energy Futures

Chen, K. C.; Sears, R. Stephen; Tzang, Dah-Nein

doi:10.1111/j.1540-6288.1987.tb01165.x

Cited by 6 publications

(8 citation statements)

References 15 publications

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“…Combined with the evidence that the volatility is significantly higher on Monday and on the day when the natural gas storage report is released, their findings suggested that information on market fundamentals significantly determines natural gas volatility. Chen et al [ 6 ] examined the role of weather as a short-term demand factor and inventory as a short-term supply factor in explaining price spikes and time-varying volatility in natural gas spot and futures returns.…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Temperature Shock and Inventory Surprises on Natural Gas and Heating Oil Futures Returns

Lin

2014

The Scientific World Journal

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The aim of this paper is to examine the impact of temperature shock on both near-month and far-month natural gas and heating oil futures returns by extending the weather and storage models of the previous study. Several notable findings from the empirical studies are presented. First, the expected temperature shock significantly and positively affects both the near-month and far-month natural gas and heating oil futures returns. Next, significant temperature shock has effect on both the conditional mean and volatility of natural gas and heating oil prices. The results indicate that expected inventory surprises significantly and negatively affects the far-month natural gas futures returns. Moreover, volatility of natural gas futures returns is higher on Thursdays and that of near-month heating oil futures returns is higher on Wednesdays than other days. Finally, it is found that storage announcement for natural gas significantly affects near-month and far-month natural gas futures returns. Furthermore, both natural gas and heating oil futures returns are affected more by the weighted average temperature reported by multiple weather reporting stations than that reported by a single weather reporting station.

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Section: Literature Reviewmentioning

confidence: 99%

Effect of Temperature Shock and Inventory Surprises on Natural Gas and Heating Oil Futures Returns

Lin

2014

The Scientific World Journal

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“…Ma (1989) examined the forecasting accuracy of energy futures for crude oil, heating oil, and leaded gasoline by comparing the market forecast embedded in the futures price to forecasts derived from alternative models (such as multivariate ARIMA), and found that forecasts from futures performed marginally better. Chen et al (1987) examined the hedging potential of energy futures for crude oil, heating oil, and leaded gasoline, and found that hedging is effective in reducing the price risk of energy products. Overdahl (1987) develops an effective strategy to hedge the revenue of oil-producing states like Louisiana using synthetic put options on oil derived from a portfolio of shorted oil futures and long Treasury bills (T-bills).…”

Section: Futures Literature Reviewmentioning

confidence: 99%

Futures and realized cash or settle prices for gold, silver, and copper

Varela

1999

Rev Financ Econ

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This article examines the relation between 15-, 30-, 45-, and 60-day gold, silver, and copper futures, and their realized cash or delivery settle prices, for deliveries on the first, middle, and last business day (FD, MD, and LD, respectively) of the delivery month. Samples of futures prices for gold, silver, and copper, and the realized cash or delivery settle prices, based on fixed maturities for a cross-section of contracts are used, because time-series over fixed maturities are unfeasible owing to the restrictive maturity periods in these contracts. This study contrasts with similar studies for forwards, which are not hampered by this problem (e.g., Baillie and Bollerslev in 1989), studies that use contemporaneous time-series of futures and cash prices to obtain optimal hedge ratios (e.g., Ghosh and Clayton in 1996), and studies that examine for parity between different futures prices (e.g., Franses and Kofman in 1991). Near-term gold, closest to delivery silver and all copper futures (the latter only with settle prices at delivery) are good predictors of the future cash price, except for silver and copper deliveries on the last day of delivery months. These results are consistent with previous studies on short-term cash (Ma in 1985) and futures (Ma and Soenen in 1988) parity between gold and silver, and with Gross's (1988) results for copper. The longer-term gold (45-and 60-day) and silver (30-, 45-, and 60-day) futures reject an unbiased expectations hypothesis. This result is consistent with Leistikow (1990) because cash prices respondless than futures prices in these instances. D 2000 Elsevier Science Inc. All rights reserved.This research examines the relation between futures prices for gold, silver, and copper, and their realized cash or settle prices, for fixed delivery or maturity dates. The research needed to overcome some problems in the analysis of this relation, because of the way that futures contracts are written. One of these is that the delivery or maturity date (henceforth, maturity) of futures for gold, silver, and copper may be any day in the delivery month, because the contracts allow for delivery throughout the maturing delivery month. A more generic problem is the absence, compared to forwards, of contracts with maturity for each day in the year. 1058-3300/00/$ ± see front matter D 2000 Elsevier Science Inc. All rights reserved. PII: S 1 0 5 8 -3 3 0 0 ( 0 0 ) 0 0 0 1 2 -4 Review of Financial Economics 8 (1999) 121 ± 138Instead, in the futures market, relatively few contracts trade per commodity, with maturity fixed to a given day or period of days in a specified month.The early literature offers studies in foreign exchange concerning the relationship between the forward and its realized spot exchange rate, as opposed to the present study concerning futures in commodities. The empirical test results of the early literature are often contradictory depending on technique, countries, or time periods used. Initially, OLS was applied to the spot and forward rates in levels, to the percentage ...

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“…The risk attitude of hedgers as expressed by their utility function has an important role to play in the determination of what is considered optimal from a hedging perspective. While many papers have looked at optimal hedging (Kroner andSultan 1993, Cotter andHanly, 2006) and some have looked specifically at energy hedging (Chen, Sears and Tzang, 1987), to the best of our knowledge none have focused on the impact of differing risk attitudes on optimal energy hedging strategies, Also, the literature has not tended to explicitly model risk aversion. Instead either infinite risk aversion is assumed, or arbitrary values are used to estimate optimal ratios (OHR's).…”

Section: Introductionmentioning

confidence: 99%