Econometric Modeling: Commodity Markets eJournal最新文献

{"title":"HAC Covariance Matrix Estimation in Quantile Regression","authors":"Antonio F. Galvao, Jungmo Yoon","doi":"10.2139/ssrn.3936050","DOIUrl":"https://doi.org/10.2139/ssrn.3936050","url":null,"abstract":"This study considers an estimator for the asymptotic variance-covariance matrix in time-series quantile regression models which is robust to the presence of heteroskedasticity and autocorrelation. When regression errors are serially correlated, the conventional quantile regression standard errors are invalid. The proposed solution is a quantile analogue of the Newey-West robust standard errors. We establish the asymptotic properties of the heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimator and provide an optimal bandwidth selection rule. The quantile sample autocorrelation coefficient is biased toward zero in finite sample which adversely affects the optimal bandwidth estimation. We propose a simple alternative estimator that effectively reduces the finite sample bias. Numerical simulations provide evidence that the proposed HAC covariance matrix estimator significantly improves the size distortion problem. We examine the impacts of the expansion of renewable energy resources on electricity prices to illustrate the usefulness of the proposed robust standard error.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122842364","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}

{"title":"Arbitrage in Cost-Based Redispatch: Evidence from Germany","authors":"Philip Schnaars, Grischa Perino","doi":"10.2139/ssrn.3890723","DOIUrl":"https://doi.org/10.2139/ssrn.3890723","url":null,"abstract":"The European Union's push towards market-based procurement of redispatch services has sparked fears of so called Inc-Dec-Gaming, i.e. the incentive to engage in arbitrage between the national wholesale market and the local redispatch market. The latter would increase both likelihood and severity of grid congestions. Such incentives might already be present in Germany where participation is mandatory and reimbursement based on costs if the marginal cost estimates are not accurate. This paper develops a method to identify such behavior. We test for the presence of Inc-Dec-Gaming at the plant level using a random forest prediction model and time series regressions based on a sample of German power plants. We do find evidence of arbitrage among a small cluster of German power plants.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117071084","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}

{"title":"Economic drivers of volatility and correlation in precious metal markets","authors":"The-Hung Dinh, Stéphane Goutte, D. K. Nguyen, T. Walther","doi":"10.2139/ssrn.3894491","DOIUrl":"https://doi.org/10.2139/ssrn.3894491","url":null,"abstract":"We investigate the time-varying dynamics of the precious metal markets. We employ a mixed data sampling technique to identify the impact of macroeconomic and financial drivers from G7 and BRICS countries on the daily volatility and pairwise correlation of gold, silver, platinum, and palladium. We find that the U.S. and Chinese economies especially influence the precious metal markets, but in opposite directions. Besides, the stock markets and trade balance of both G7 and BRICS countries as well as the consumer confidence of G7 countries are the key drivers for the volatility of precious metals. The most influential drivers for correlation are stock markets, money supply, and the inflation rate. Surprisingly, the economic policy uncertainty does not affect the dynamics as much as expected. Lastly, the global financial crisis 2008 affected the direction of most of the macroeconomic and financial drivers.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131312867","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}

{"title":"Using the Three Co's to Jointly Model Commodity Markets: Co-Production, Co-Consumption and Co-Trading","authors":"P. Papenfuß, A. Schischke, A. Rathgeber","doi":"10.2139/ssrn.3860004","DOIUrl":"https://doi.org/10.2139/ssrn.3860004","url":null,"abstract":"In this study, we develop a framework, based on a global vector autoregression (GVAR) model, to unite two perspectives on commodity markets, the commodity-specific, single-market-centered approach, investigating the micro- and macroeconomic drivers of commodity prices, and the market perspective, which observes joint movements of commodity prices on exchanges. Thereby, the GVAR model disentangles single market from inter-market effects, while simultaneously accounting for the impact of macroeconomic factors. We apply the framework to the six industrial metals markets, reflecting their interdependencies via their co-production, co-consumption, or co-trading relation. In particular, the numerous significant spillover effects in the cross-commodity dimension underline the importance of jointly modeling commodity markets. While the strong co-movement between industrial metal prices is represented exceptionally well by our framework, the microeconomic supply and demand attributes of the commodities have significant impact, within and across markets, even on price variables, highlighting their relevance in modern commodity market models. Moreover, we detect global shocks, e.g., an increase in global demand, affect each commodity market to a similar extent.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133143375","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}

{"title":"Correlation Breakdowns, Spread Positions, and CCP Margin Models","authors":"David X. Li, F. Cerezetti, Roy M. Cheruvelil","doi":"10.2139/ssrn.3775828","DOIUrl":"https://doi.org/10.2139/ssrn.3775828","url":null,"abstract":"The default of a participant at Nasdaq Clearing in 2018 and the recent COVID-19 events brought to the attention of risk managers at CCPs the importance of appropriately measuring correlation breakdowns. The sizable price dislocations registered on these occasions suggested that traditional risk models may not be fully equipped to capture the breakdowns. Because correlations are directly impacted by the statistical properties of each variable, any model that lacks the capacity to deal with non-stationarity may inappropriately represent correlation or its alterations. Using a GARCH-DCC approach to accommodate such properties, the objective of the paper is to study the correlation behaviour during adverse market conditions, and the potential subsequent impact to CCP margins. A study case for energy commodities is proposed, with the specific focus on spread positions for the electricity market. The analysis suggests that the correlation breakdowns are more frequent than traditionally expected. When different types of shocks are considered (i.e. September 2018 and March-May 2020), it becomes evident that while the magnitude of the breakdown may differ, its cycle presents a number of similarities. While elevated margin due to correlation breakdown may reduce breaching amount and improve margin coverage rate, this paper also recognizes the potentially increased margin procyclicality, and highlights the challenge of balancing margin responsiveness and stability during correlation breakdown for spread positions, and calls for further study in this area.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127759854","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}

{"title":"Investigating the Impact of COVID-19 Outbreak on Canada's Commodity Market","authors":"Achu Dobgima Destin, Ben Bardis","doi":"10.2139/ssrn.3775259","DOIUrl":"https://doi.org/10.2139/ssrn.3775259","url":null,"abstract":"SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia of a clear cause. The virus has now spread across the globe considerably more than 200 countries and territories, and the world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partially or totally lockdown. This situation disrupted global supply chain, and induced a significant fall in both economic activity and financial asset prices. Canada, being one of the country affected by the Virus with 731 000 Cases, and 18 622 Deaths as at the 21 of January 2020. Recently vaccines have been developed but the contamination wave keeps on increasing every day. On the socioeconomic front, COVID-19 has led more than 200 countries into partial or total lockdown, disrupted global supply chains, and induced a fall in both economic activity and financial asset prices. It’s of prime importance to study how COVID-19 impact’s on Canada’s commodity market. The commercial and financial effect of COVID-19. The impact of COVID-19 is unclear because the public health crisis is still unfolding. There is limited amount of studies concerning this topic, because the crisis is still unfolding. The objective of this study is to investigate the impact of Covid-19 on Canada’s Commodity markets. The author uses extreme bound analysis for market interpretation and sourced data from Bank of Canada and Our World in Data COVID-19, from January 1 to December 31 2020. The result of the study show that, Total deaths per million have an impact on the monthly Bank of Canada’s commodity price index of energy because of the robust relationship between them. Furthermore, the result also show that, commodity price index of energy and total deaths per million are determinants to total commodity price index. Furthermore, commodity price index excluding energy, commodity price index of energy, commodity price index of minerals and metals, commodity price index of forestry and total deaths per million are robust determinants of monthly Bank of Canada total commodity Prices. M.BCNE, M.ENER, M.MTLS, M.MTLS, M.FOPR, M.FOPR, M.AGRI, M.FISH, TC, TD have a positive relationship with MBCPI. M.BCPI, M.BCNE, M.MTLS, M.AGRI and M.FISH.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114341776","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}

{"title":"The Macroeconomic Effects of Commodity Price Uncertainty","authors":"T. Tran","doi":"10.2139/ssrn.3768938","DOIUrl":"https://doi.org/10.2139/ssrn.3768938","url":null,"abstract":"This paper studies the macroeconomic effects of commodity price uncertainty (CPU) shocks. Using Australia as a case study, an econometric-based CPU index is proposed to reveal that Australia has experienced an unprecedented increase in uncertainty from the commodity market recently. Evidence from a VAR model shows that CPU shocks have a larger recessionary impact than other relevant uncertainty shocks such as financial, economic and trade policy uncertainty. The empirical results are then interpreted in a non-linear multisector DSGE model of the Australian economy by estimating key parameters in the DSGE model to match its responses to the VAR responses. CPU shocks in the DSGE model, via foreign commodity export demand with price rigidity, trigger a precautionary response and cause a decline in real economic activity.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123325256","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}

{"title":"Class of Skewed Generalized Distributions Based on a Two-Piece Generalized Framework","authors":"Panayiotis Theodossiou","doi":"10.2139/ssrn.3763625","DOIUrl":"https://doi.org/10.2139/ssrn.3763625","url":null,"abstract":"This paper introduces a two-piece generalized distributional framework based on some minimum requirements for the probability density function used as the basis for the two-way split. These requirements are symmetricity, unimodality and continuity. The basic characteristics of the two-piece generalized distribution are discussed and its moments including the Pearson’s mode of skewness and moment coefficients of skewness and kurtosis are derived. The results are useful to researchers using these distributions in empirical and theoretical studies, as well as students taking courses in mathematical and applied statistics and econometrics.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127538756","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}

{"title":"Jumps in Commodity Prices: New Approaches for Pricing Options.","authors":"Carme Frau, J. Crosby","doi":"10.2139/ssrn.3754835","DOIUrl":"https://doi.org/10.2139/ssrn.3754835","url":null,"abstract":"We present a new term-structure model for commodity futures prices based on Trolle and Schwartz (2009) which we extend by incorporating multiple jump processes. Our work explores the valuation of plain vanilla options on futures prices when the spot price follows a log-normal process, the forward cost of carry curve and the volatility are stochastic variables, and the spot price and the forward cost of carry allow for time-dampening jumps. We obtain an analytical representation of the characteristic function of the futures prices and, hence, also for plain vanilla option prices using the fast Fourier transform (FFT) methodology. We price options on WTI crude oil futures contracts using our model and extant models. We obtain higher accuracy than earlier models and save significantly in computing time.<br>","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127870883","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}

{"title":"Volatility of International Commodity Prices in Times of COVID-19: Effects of Oil Supply and Global Demand Shocks","authors":"H. Ezeaku, S. Asongu, J. Nnanna","doi":"10.2139/ssrn.3754734","DOIUrl":"https://doi.org/10.2139/ssrn.3754734","url":null,"abstract":"Abstract This study examines the effects of oil supply and global demand shocks on the volatility of commodity prices in the metal and agricultural commodity markets using the SVAR model. The empirical evidence is based on real time daily closing international commodity prices covering the period 2 December 2019 to 1 October 2020. The findings are presented in cumulative impulse responses and variance decompositions. The former is utilized to examine the accumulated influence of structural shocks on the volatility of agricultural and metal commodities whereas the latter reflect the share of variation in the volatility of each commodity arising from each structural shock. Various patterns are provided on how metal and agricultural commodity prices have been influenced by the COVID-19 pandemic. Policy implications are discussed.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117111882","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}