scholarly journals Crude oil: does the futures price predict the spot price?

Author(s):  
Pyung Kun Chu ◽  
Kristian Hoff ◽  
Peter Molnár ◽  
Magnus Olsvik
Keyword(s):  
2020 ◽  
Vol 8 (3) ◽  
pp. 224-239
Author(s):  
Jingjing Li ◽  
Ling Tang ◽  
Ling Li

AbstractWith the boom of web technology, Internet concerns (IC) have become emerging drivers of crude oil price. This paper makes the first attempt to measure the frequency-varying co-movements between crude oil price and IC in five domains (i.e., fundamentals, supply-demand, crisis, war and weather) by using the frequency causality test method. Based on the monthly Brent spot price and search volumes (SVs) captured by Google Trends from January 2004 to September 2019, new and complementary insights regarding the co-movements between crude oil price and IC are obtained. 1) The co-movements between crude oil price and the IC of supply-demand, war, and weather support a neutral hypothesis at all frequencies due to the characteristics (low value or volatility) of these IC data. 2) There is a unidirectional causal relationship between crude oil price and the IC of fundamentals, running from the latter to the former at low frequencies (long-term). 3) There is a feedback relationship between crude oil price and the IC of crisis, with the IC of crisis driving crude oil price at medium and low frequencies (mid- and long-term) and crude oil price causing the IC of crisis to change permanently. The conclusions of this paper provide important implications for both oil market economists and investors.


1972 ◽  
Vol 4 (1) ◽  
pp. 123-128 ◽  
Author(s):  
David Holland ◽  
Wayne D. Purcell ◽  
Terry Hague

Much of the research in commodity hedging has concentrated upon the development of theoretical models describing the optimum position in cash and futures markets. Other studies have shown that the difference between current spot price and futures price represents the market price for storage, processing services, or both. The revenue stabilizing potential of futures markets for commodities with continuous as opposed to noncontinuous inventories has also received attention. However, very little work or literature is publicly available on how different hedging strategies actually would have performed for a particular commodity over time.


Energies ◽  
2014 ◽  
Vol 7 (5) ◽  
pp. 2761-2779 ◽  
Author(s):  
Shangkun Deng ◽  
Akito Sakurai

2007 ◽  
Vol 15 (1) ◽  
pp. 73-100
Author(s):  
Seok Kyu Kang

This study is to examine the unblasedness hypothesis and hedging effectiveness in KOSPI20() futures market. The unbiasedness and efficiency hypothesis is carried out using a cointegration methodology. And hedging effectiveness is measured by comparing hedging performance of the naive hedge model, OLS hedge model. and constant correlation bivariate GARCH (1. 1) hedge model based on rolling windows. The sample period covers from May. 3. 1996 to December. 8, 2005. The empirical results are summarized as follows: First, there exists the cOintegrating relationship between realized spot prices and futures prices of the 10 day. 22 day. 44 day. and 59 day prior to maturity. Second. futures prices of backward the 10 day. 22 day. 44 day from maturity provide unbiased forecasts of the realized spot prices. The KOSPI200 futures price is likely to predict accurately future KOSPI200 spot prices without the trader having to pay a risk premium for the privilege of trading the contract. Third. for shorter maturity. the futures price appears to be the best forecaster of spot price. Forth, bivariate GARCH hedging effectiveness outperforms the naive and OLS hedging effectiveness. The implications of these findings show that KOSPI200 futures market behaves as unbiased predictor of future spot price and risk management instrument of KOSPI200 spot portfolio.


2014 ◽  
Vol 6 (3) ◽  
pp. 470-484
Author(s):  
Yunxian Yan ◽  
Lu Tian ◽  
Yuejie Zhang

Purpose – The purpose of this paper is to discover an effective maize price for trading and policy-making reference by assessing the price transmission of the US spot and futures maize prices to Chinese counterparts. Design/methodology/approach – The authors apply a systematic, quantitative method to analyze the integration between US and Chinese maize markets. Based on the residuals of the variables through error correction model, the directed acyclic graph (DAG) among six price variables is conducted. With consideration of the dependence on and direction of six price variables, the variance decomposition of each variable is calculated. Findings – This paper shows that the vertical price transmission passes from wholesale price to farm-gate price. The horizontal price transmission ranges from spot price to futures price at the domestic market and from the American spot price to domestic spot price, from the American spot price to domestic futures price and from the American futures price to domestic futures price. The American maize spot and futures prices, and in particular the spot price, have greater effects on domestic maize prices contemporaneously. It also indicates that the American spot price is the leader price in the long run at both maize markets. Originality/value – This paper contributes by using the DAG method in this paper. It also contributes by helping policy makers and market participants find the leading prices and offers insight into ways of gaining power of price setting in the maize market.


2002 ◽  
Vol 8 (4) ◽  
pp. 324-333 ◽  
Author(s):  
Michael Ye ◽  
John Zyren ◽  
Joanne Shore

2019 ◽  
Vol 15 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Anis Erma Wulandari ◽  
Harianto Harianto ◽  
Bustanul Arifin ◽  
Heny K Suwarsinah

Indonesia is the world 4th largest coffee producer after Brazil, Vietnam and Colombia with export potential and higher national consumption concluded in 2017 while the coffee production was relatively stagnant. This was led the producer to not only the production risk but also the price risk which then emphasize the importance of futures markets existence as price risk management. This study is performed to examine the impact of futures price volatility to spot market using ARCH-GARCH toward primary data of coffee futures and spot prices of 1172 trading days starting from January 2014 to June 2018. The ARCH-GARCH analysis result indicates that futures price volatility and monetary variables are impacting the volatility of spot price. Arabica spot price volatility is impacted by volatility of Arabica futures price, inflation and exchange rate while Robusta spot price is impacted by Robusta futures price volatility and exchange rate. This is confirming that futures market plays dominant role in spot price discovery. Local futures and spot prices are also found to be significantly influenced by volatility of offshore futures prices which indicates that emerging country futures market is actually influenced by offshore futures market which the price itself used as price reference.


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