A number of prominent authors have recently argued that any abnormal impact of speculators on commodities prices should involve stockpiling as a signature. Others contend, by contrast, that due to the price inelasticity of supply and demand in commodity markets, speculation could distort commodity prices without any change in inventories. Motivated by this debate, this paper examines the relation between the investment flows into the three main commodity index exchange-traded funds (ETFs) and the prices, inventory and term structure of four US-traded energy commodities. Using weekly inventory data from the Energy Information Agency and futures prices from NYMEX energy contracts, we do not find any significant relation between commodity index flows and inventory or term structure. By contrast, we retrieve the short-term impacts of index flows on energy commodities’ futures prices that have already been evidenced in the literature. An extension of our framework of analysis to twelve US-traded agricultural contracts confirms these conclusions. Hence, our results suggest that stockpiling is not necessarily a “signature” of an abnormal impact of speculators on commodities prices.
{"title":"Does the Impact of Exchange-Traded Funds Flows on Commodities Prices Involve Stockpiling as a Signature? An Empirical Investigation","authors":"S. Ohana, Xiaoying Huang","doi":"10.21314/jem.2018.175","DOIUrl":"https://doi.org/10.21314/jem.2018.175","url":null,"abstract":"A number of prominent authors have recently argued that any abnormal impact of speculators on commodities prices should involve stockpiling as a signature. Others contend, by contrast, that due to the price inelasticity of supply and demand in commodity markets, speculation could distort commodity prices without any change in inventories. Motivated by this debate, this paper examines the relation between the investment flows into the three main commodity index exchange-traded funds (ETFs) and the prices, inventory and term structure of four US-traded energy commodities. Using weekly inventory data from the Energy Information Agency and futures prices from NYMEX energy contracts, we do not find any significant relation between commodity index flows and inventory or term structure. By contrast, we retrieve the short-term impacts of index flows on energy commodities’ futures prices that have already been evidenced in the literature. An extension of our framework of analysis to twelve US-traded agricultural contracts confirms these conclusions. Hence, our results suggest that stockpiling is not necessarily a “signature” of an abnormal impact of speculators on commodities prices.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2018-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46142620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines how West Texas Intermediate (WTI) crude oil price returns and volatilities respond to changes in US monetary policy. To do so, it considers daily data collected between 2008 and 2014. It measures the monetary policy shocks as the change in US ten-year government bond yields immediately after the announcement of relevant events. The findings reveal the crude oil market to be highly reactive to unconventional monetary policy surprises. Surprisingly, when working with shorter windows – that is, of one day right around the announcement of a large-scale asset purchase likely to cause a decrease in long-term interest rates – one documents, in general, a decline in oil price returns and an increase in their associated volatilities, despite the more stimulative financial environment. In contrast, the effects of monetary policy on the oil market one day after any significant announcement are different. As a rule, monetary surprises led to significant increases in oil price. In particular, this paper highlights the ways in which the magnitude of the oil market’s response may be influenced by the size of the study window (that is, the period in which monetary policy may affect prices). This observation raises the question of whether transmission channels drive the relationship between monetary policy and the crude oil market. This paper makes an important contribution to the empirical literature dealing with the link between monetary policy and energy markets: namely, the crude oil futures market and the existing literature focusing on the transmission mechanism. The empirical results entail important implications for industry participants and policy makers alike.
{"title":"The Impact of Unconventional Monetary Policy Shocks on the Crude Oil Futures Market","authors":"Tarek Chebbi","doi":"10.21314/JEM.2018.171","DOIUrl":"https://doi.org/10.21314/JEM.2018.171","url":null,"abstract":"This paper examines how West Texas Intermediate (WTI) crude oil price returns and volatilities respond to changes in US monetary policy. To do so, it considers daily data collected between 2008 and 2014. It measures the monetary policy shocks as the change in US ten-year government bond yields immediately after the announcement of relevant events. The findings reveal the crude oil market to be highly reactive to unconventional monetary policy surprises. Surprisingly, when working with shorter windows – that is, of one day right around the announcement of a large-scale asset purchase likely to cause a decrease in long-term interest rates – one documents, in general, a decline in oil price returns and an increase in their associated volatilities, despite the more stimulative financial environment. In contrast, the effects of monetary policy on the oil market one day after any significant announcement are different. As a rule, monetary surprises led to significant increases in oil price. In particular, this paper highlights the ways in which the magnitude of the oil market’s response may be influenced by the size of the study window (that is, the period in which monetary policy may affect prices). This observation raises the question of whether transmission channels drive the relationship between monetary policy and the crude oil market. This paper makes an important contribution to the empirical literature dealing with the link between monetary policy and energy markets: namely, the crude oil futures market and the existing literature focusing on the transmission mechanism. The empirical results entail important implications for industry participants and policy makers alike.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2018-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47134962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Skytte, O. Olsen, Emilie Rosenlund Soysal, Daniel Møller Sneum
The Scandinavian countries Denmark, Norway and Sweden currently deploy large amounts of variable renewable energy (VRE) sources, especially wind power. This calls for additional flexibility in the power market. The right coupling to the underlying national and local district heating (DH) markets can generate large amounts of flexibility. However, regulatory barriers and different energy market designs may hinder the potential benefits from system integration, and lower the potential that can be realized. The Scandinavian countries have a large extension of DH with a good potential for providing flexibility services to the electricity market. We survey and discuss regulatory barriers and drivers for exploiting this potential for flexibility. Combined heat and power (CHP) is widely integrated in the power market, but it is threatened by low electricity prices due to the increasing amounts of wind power. Power-to-heat technologies, electric boilers and heat pumps are blocked by high tariffs and taxes. A calculation of the heat costs of different DH technologies demonstrates that, under the present price and tax conditions in Denmark and Sweden, CHP and power-to-heat are unable to compete with heat-only boilers that use tax-free biomass.
{"title":"Barriers for District Heating as a Source of Flexibility for the Electricity System","authors":"K. Skytte, O. Olsen, Emilie Rosenlund Soysal, Daniel Møller Sneum","doi":"10.21314/JEM.2017.161","DOIUrl":"https://doi.org/10.21314/JEM.2017.161","url":null,"abstract":"The Scandinavian countries Denmark, Norway and Sweden currently deploy large amounts of variable renewable energy (VRE) sources, especially wind power. This calls for additional flexibility in the power market. The right coupling to the underlying national and local district heating (DH) markets can generate large amounts of flexibility. However, regulatory barriers and different energy market designs may hinder the potential benefits from system integration, and lower the potential that can be realized. The Scandinavian countries have a large extension of DH with a good potential for providing flexibility services to the electricity market. We survey and discuss regulatory barriers and drivers for exploiting this potential for flexibility. Combined heat and power (CHP) is widely integrated in the power market, but it is threatened by low electricity prices due to the increasing amounts of wind power. Power-to-heat technologies, electric boilers and heat pumps are blocked by high tariffs and taxes. A calculation of the heat costs of different DH technologies demonstrates that, under the present price and tax conditions in Denmark and Sweden, CHP and power-to-heat are unable to compete with heat-only boilers that use tax-free biomass.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45887071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laura Cucu, R. Döttling, P. Heider, Samuel C. Maina
Natural gas demand in Western Europe depends strongly on temperature. The analysis of historical gas spot prices and temperatures shows a dependency between day-ahead prices and temperature, especially in time periods of low temperatures. Typically, natural gas consumption peaks during the cold winter months. We propose a stochastic model for coupled natural gas spot prices and temperature. The dynamics of price and temperature are modeled by two factor processes, calibrated to implied data and historical realizations. As an application of the model, we present the evaluation of an energy quanto swap.
{"title":"Managing Temperature-Driven Volume Risks","authors":"Laura Cucu, R. Döttling, P. Heider, Samuel C. Maina","doi":"10.21314/jem.2016.145","DOIUrl":"https://doi.org/10.21314/jem.2016.145","url":null,"abstract":"Natural gas demand in Western Europe depends strongly on temperature. The analysis of historical gas spot prices and temperatures shows a dependency between day-ahead prices and temperature, especially in time periods of low temperatures. Typically, natural gas consumption peaks during the cold winter months. We propose a stochastic model for coupled natural gas spot prices and temperature. The dynamics of price and temperature are modeled by two factor processes, calibrated to implied data and historical realizations. As an application of the model, we present the evaluation of an energy quanto swap.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2016-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67703986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We test the performance of popular option strategies in the Nordic power derivative market using 12 years of data. We find that protective put strategies outperform long forward and covered call strategies on risk-adjusted basis, because the payoff function of the protective put seems a good fit to the market dynamics in both good and bad times. Detailed analysis reveals differences across moneyness levels and holding periods that can be further exploited. Different delta levels of the analyzed strategies allow for flexible hedging solutions.
{"title":"Covered Option Strategies in Nordic Electricity Markets","authors":"Antti Klemola, Jukka Sihvonen","doi":"10.21314/jem.2015.120","DOIUrl":"https://doi.org/10.21314/jem.2015.120","url":null,"abstract":"We test the performance of popular option strategies in the Nordic power derivative market using 12 years of data. We find that protective put strategies outperform long forward and covered call strategies on risk-adjusted basis, because the payoff function of the protective put seems a good fit to the market dynamics in both good and bad times. Detailed analysis reveals differences across moneyness levels and holding periods that can be further exploited. Different delta levels of the analyzed strategies allow for flexible hedging solutions.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2015-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67703929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimating a static coefficient for a deseasoned gas storage or weather variable implicitly assumes that market participants react identically throughout the year (and over each year) to that variable. In this analysis we model natural gas returns as a linear function of gas storage and weather variables, and we allow the coefficients of this function to vary continuously over time. This formulation takes into account that market participants continuously try to improve their forecasts of market prices, and this likely means they continuously change the scale of their reaction to changes in underlying variables. We use this model to also calculate conditional natural gas volatility and the proportion of volatility attributable to each factor. We find that return volatility is higher in the winter, and this increase is attributable to increases in the proportion of volatility due to weather and natural gas storage. We provide time series estimates of the changing proportion of volatility attributable to each factor, which is useful for hedging and derivatives trading in natural gas markets.
{"title":"Parameter Variation and the Components of Natural Gas Price Volatility","authors":"Matthew Brigida","doi":"10.2139/ssrn.2597319","DOIUrl":"https://doi.org/10.2139/ssrn.2597319","url":null,"abstract":"Estimating a static coefficient for a deseasoned gas storage or weather variable implicitly assumes that market participants react identically throughout the year (and over each year) to that variable. In this analysis we model natural gas returns as a linear function of gas storage and weather variables, and we allow the coefficients of this function to vary continuously over time. This formulation takes into account that market participants continuously try to improve their forecasts of market prices, and this likely means they continuously change the scale of their reaction to changes in underlying variables. We use this model to also calculate conditional natural gas volatility and the proportion of volatility attributable to each factor. We find that return volatility is higher in the winter, and this increase is attributable to increases in the proportion of volatility due to weather and natural gas storage. We provide time series estimates of the changing proportion of volatility attributable to each factor, which is useful for hedging and derivatives trading in natural gas markets.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2015-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2139/ssrn.2597319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68218140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we employ a fundamental principle of classical mechanics known as the Least Action Principle to model the complex relationship between expected load and expected price in electricity spot markets. We consider here markets that feature a centralised electricity dispatch system that optimises grid parameters to determine the minimum spot nodal prices. Using the example of the Australian National Electricity Market (NEM) and a calibrated stochastic demand model, we develop the mathematical approach that determines the price evolution including intra-day and seasonal features. The proposed model links the concept of a deterministically-modelled price with a stochastically-modelled demand. The demand-price relationship is complex, and must include not only the level of demand within the constraint of maximum generating capacity, but also the change in demand within the constraints of generator ramping rates. While this paper uses the NEM as an example, the proposed approach is applicable to any energy market that satisfies the above conditions.
{"title":"A Method of Forecasting Wholesale Electricity Market Prices","authors":"J. Maisano, A. Radchik, I. Skryabin","doi":"10.2139/ssrn.2542052","DOIUrl":"https://doi.org/10.2139/ssrn.2542052","url":null,"abstract":"In this paper we employ a fundamental principle of classical mechanics known as the Least Action Principle to model the complex relationship between expected load and expected price in electricity spot markets. We consider here markets that feature a centralised electricity dispatch system that optimises grid parameters to determine the minimum spot nodal prices. Using the example of the Australian National Electricity Market (NEM) and a calibrated stochastic demand model, we develop the mathematical approach that determines the price evolution including intra-day and seasonal features. The proposed model links the concept of a deterministically-modelled price with a stochastically-modelled demand. The demand-price relationship is complex, and must include not only the level of demand within the constraint of maximum generating capacity, but also the change in demand within the constraints of generator ramping rates. While this paper uses the NEM as an example, the proposed approach is applicable to any energy market that satisfies the above conditions.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2014-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68197456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the problem of designing a financial instrument aimed at mitigating the joint exposure of energy-linked commitments to random price and volume delivery fluctuations. We formulate a functional optimization problem over a set of regular payoff functions: one is written on energy price, while the other is issued over any index exhibiting statistical correlation to volumetric load. On theoretical grounds, we derive closed-form expressions for both payoff structures under suitable conditions about the statistical properties of the underlying variables; we pursue analytical computations in the context of a lognormal market model and deliver explicit formulas for the optimal derivative instruments. On practical grounds, we first develop a comparative analysis of model output through simulation experiments; next, we perform an empirical study based on data quoted at EPEX SPOT power market. Our results suggest that combined price-volume hedging performance improves along with an increase of the correlation between load and index values. This outcome paves the way for a new class of effective strategies for managing volumetric risk upon extreme temperature waves.
{"title":"Static Mitigation of Volumetric Risk","authors":"Rachid Id Brik, Andrea Roncoroni","doi":"10.2139/ssrn.2689112","DOIUrl":"https://doi.org/10.2139/ssrn.2689112","url":null,"abstract":"We consider the problem of designing a financial instrument aimed at mitigating the joint exposure of energy-linked commitments to random price and volume delivery fluctuations. We formulate a functional optimization problem over a set of regular payoff functions: one is written on energy price, while the other is issued over any index exhibiting statistical correlation to volumetric load. On theoretical grounds, we derive closed-form expressions for both payoff structures under suitable conditions about the statistical properties of the underlying variables; we pursue analytical computations in the context of a lognormal market model and deliver explicit formulas for the optimal derivative instruments. On practical grounds, we first develop a comparative analysis of model output through simulation experiments; next, we perform an empirical study based on data quoted at EPEX SPOT power market. Our results suggest that combined price-volume hedging performance improves along with an increase of the correlation between load and index values. This outcome paves the way for a new class of effective strategies for managing volumetric risk upon extreme temperature waves.","PeriodicalId":43528,"journal":{"name":"Journal of Energy Markets","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2139/ssrn.2689112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68255592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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