scholarly journals A Proposal to Fix the Number of Factors on Modeling the Dynamics of Futures Contracts on Commodity Prices

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 973
Author(s):  
Andrés García-Mirantes ◽  
Beatriz Larraz ◽  
Javier Población
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Commodity Prices ◽  
Spot Price ◽  
Futures Prices ◽  
Unleaded Gasoline ◽  
Energy Derivatives ◽  
Number Of Factors ◽  
Two Factors ◽  
Heating Oil

In the literature on modeling commodity futures prices, we find that the stochastic behavior of the spot price is a response to between one and four factors, including both short- and long-term components. The more factors considered in modeling a spot price process, the better the fit to observed futures prices—but the more complex the procedure can be. With a view to contributing to the knowledge of how many factors should be considered, this study presents a new way of computing the best number of factors to be accounted for when modeling risk-management of energy derivatives. The new method identifies the number of factors one should consider in the model and the type of stochastic process to be followed. This study aims to add value to previous studies which consider principal components by assuming that the spot price can be modeled as a sum of several factors. When applied to four different commodities (weekly observations corresponding to futures prices traded at the NYMEX for WTI light sweet crude oil, heating oil, unleaded gasoline and Henry Hub natural gas) we find that, while crude oil and heating oil are satisfactorily well-modeled with two factors, unleaded gasoline and natural gas need a third factor to capture seasonality.

Can energy commodities affect energy blockchain-based cryptos?

2019 ◽  
Vol 36 (4) ◽  
pp. 682-699 ◽  
Author(s):  
Ikhlaas Gurrib
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Autoregressive Model ◽  
Structural Breaks ◽  
Price Index ◽  
Principal Component ◽  
Commodity Price ◽  
Var Model ◽  
Content Type ◽  
Heating Oil

Purpose The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market. Design/methodology/approach Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices. Findings Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model. Research limitations/implications Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil. Originality/value As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

scholarly journals An Auxiliary Index for Reducing Brent Crude Investment Risk—Evaluating the Price Relationships between Brent Crude and Commodities

2021 ◽  
Vol 13 (9) ◽  
pp. 5050
Author(s):  
Yu-Wei Chen ◽  
Chui-Yu Chiu ◽  
Mu-Chun Hsiao
Keyword(s):  
New York ◽  
Crude Oil ◽  
Oil Price ◽  
Spot Price ◽  
Investment Risk ◽  
Crude Oil Price ◽  
Price Relationship ◽  
Heating Oil ◽  
Price Relationships ◽  
Practical Measurement

Examining the price relationships of Brent Crude with 78 global commodities, our study shows that the spot price of a certain commodity, New York Harbor No. 2 Heating Oil Spot Price FOB, can serve as an auxiliary forecasting index of the rise and fall of the monthly Brent Crude oil price. With an innovative view for evaluating the price relationship and prediction based on simple, practical measurement, our findings provide a helpful auxiliary index tool for investors and analysts by offering a high success rate (82.98%) and predicting the rise and fall of the monthly Brent Crude oil price three weeks in advance.

scholarly journals Volatility Spillovers: Evidence On U.S. Oil Product Markets

2012 ◽  
Vol 28 (6) ◽  
pp. 1237 ◽  
Author(s):  
Bernard Ben Sita ◽  
Salah Abosedra
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Transmission Mechanism ◽  
Font Size ◽  
Product Markets ◽  
Volatility Spillovers ◽  
Oil And Natural Gas ◽  
Heating Oil ◽  
Energy Products ◽  
The Relationship

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNormal"><span lang="EN-CA" style="color: black; font-size: 10pt; mso-themecolor: text1; mso-ansi-language: EN-CA;"><span style="font-family: Times New Roman;">This paper provides evidence on the lead, the contemporaneous and the lagged transmission mechanism of extreme shocks across energy products. Our findings reveal a weak leadership of crude oil in guiding hedgers against risk that is specific to natural gas whose changes show a weak reliance on changes in crude oil. Moreover, our findings are consistent with the competitive use of energy products. It follows that substitutability characterizes the relationship between heating oil and natural gas when extreme standardized shocks are considered.<span style="mso-spacerun: yes;"> </span></span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

The Predictive Characteristics of Energy Futures: Recent Evidence for Crude Oil, Natural Gas, Gasoline and Heating Oil

2001 ◽  
Author(s):  
Menzie David Chinn ◽  
Michael LeBlanc ◽  
Olivier Coibion
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Energy Futures ◽  
Heating Oil

Evidence of infinite and finite jump processes in commodity futures prices: Crude oil and natural gas

2018 ◽  
Vol 502 ◽  
pp. 629-641 ◽  
Author(s):  
Wenbin Cao ◽  
Scott B. Guernsey ◽  
Scott C. Linn
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Commodity Futures ◽  
Jump Processes ◽  
Futures Prices ◽  
Oil And Natural Gas

scholarly journals Comparison of the Impact of Econometric Models on Hedging Performance by Crude Oil and Natural Gas

2018 ◽  
Vol 66 (2) ◽  
pp. 423-429
Author(s):  
Luděk Benada
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Risk Reduction ◽  
Econometric Models ◽  
Spot Price ◽  
Spot Prices ◽  
Oil And Natural Gas ◽  
Risk Protection ◽  
High Level ◽  
The Impact

The paper examines the performance of hedging spot prices in crude oil and natural gas. The subject of the research are spot prices of West Texas Intermediate and Henry Hub. The risk protection is provided by the application of futures contracts of underlying assets. In our analysis three econometric models (OLS, Copula, GARCH) and a naive portfolio are applied to obtain the optimal hedge ratio. Afterwards, the calculated weights for futures are verified for the ability to reduce the spot price risk over twelve months. The success of each model in risk reduction is measured over the test period by a conventional tool and across the models by proper metric. The results of the analysis confirm high level of risk reduction by crude oil across models. On the contrary, the results of hedging in natural gas significantly lag in comparison to crude oil. In addition, the analysis confirms a strong variability over the tested period and models.

scholarly journals How Selected Energy Commodity Prices Volatility Impacts Gross Domestic Product (GDP) Fluctuation with Respect to Selected European Countries

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Robert RANOSZ ◽  
Barbara KOWAL
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Raw Materials ◽  
Commodity Prices ◽  
Price Volatility ◽  
European Countries ◽  
Regression Approach ◽  
Natural Gas Prices ◽  
Oil And Natural Gas ◽  
The Russian Federation

The article examines price volatility of the following energy raw materials: uranium, coal, crude oil and natural gas, and its influence on GDP fluctuation with regard to selected European countries. The study was carried out using linear regression approach, in which the volatility of raw materials prices was determined as independent variables and GDP fluctuation as a dependent variable. The article examines 33 European countries and the examined period covered 28 years (from 1990 to 2018). As demonstrated in the study, energy raw materials prices volatility influences GDP fluctuation, especially in the countries involved in their extraction and processing. Attention was also drawn to the fact that uranium and coal are the most significant energy raw materials for the European countries. In the case of crude oil, its volatility turned out to be significant only for two countries, i.e. Norway and the Russian Federation. It was a surprise that natural gas prices volatility slightly affects GDP fluctuation in selected European countries.

Analyzing the financial and economic momentum as a result of changes in the interest rate

2020 ◽  
Vol 16 (9) ◽  
pp. 1656-1673
Author(s):  
V.V. Smirnov
Keyword(s):  
Interest Rate ◽  
Natural Gas ◽  
Central Bank ◽  
Crude Oil ◽  
Oil Prices ◽  
Global Capitalism ◽  
Positive Effects ◽  
Russian Economy ◽  
Oil And Natural Gas ◽  
The Interest Rate

Subject. The article discusses financial and economic momenta. Objectives. I determine financial and economic momenta as the interest rate changes in Russia. Methods. The study is based on a systems approach and the method of statistical analysis. Results. The Russian economy was found to strongly depend on prices for crude oil and natural gas, thus throwing Russia to the outskirts of the global capitalism, though keeping the status of an energy superpower, which ensures a sustainable growth in the global economy by increasing the external consumption and decreasing the domestic one. The devaluation of the national currency, a drop in tax revenue, etc. result from the decreased interest rate. They all require to increase M2 and the devalued retail loan in RUB, thus rising the GDP deflator. As for positive effects, the Central Bank operates sustainably, replenishes gold reserves and keeps the trade balance (positive balance), thus strengthening its resilience during a global drop in crude oil prices and the COVID-19 pandemic. The positive effects were discovered to result from a decreased in the interest rate, rather than keeping it low all the time. Conclusions and Relevance. As the interest rate may be, the financial and economic momentum in Russia depends on the volatility of the price for crude oil and natural gas. Lowering the interest rate and devaluing the national currency, the Central Bank preserves the resource structure of the Russian economy, strengthens its positions within the global capitalism and keeps its status of an energy superpower, thus reinforcing its resilience against a global drop in oil prices.

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