{"title":"Commodities’ Common Factor. An Empirical Assessment of the Markets’ Drivers","authors":"Johannes Lübbers, Peter N. Posch","doi":"10.2139/ssrn.2718009","DOIUrl":"https://doi.org/10.2139/ssrn.2718009","url":null,"abstract":"Using a generalized dynamic factor model, we identify a latent common factor in a broad sample of thirty-one commodity futures’ returns between 1996 and 2015. An investigation of sub-periods reveals an increasing correlation between the common factor and changes in gold and oil prices during the financial crisis. We also consider whether the common factors of commodity subsectors give an advantage to the pricing of commodity futures’ returns. In the cross-section of individual futures’ returns we suggest that two- or three-factor models that include energy's or agriculture's common factors can explain commodity returns. Thus, our results indicate an increasing homogeneity of the commodity markets in recent years.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"4 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126164289","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":"On the Role of Structural Breaks in Identifying the Dynamic Conditional Linkages between Stock and Commodity Markets","authors":"Chebbi Tarek, Abdelkader Mohamed Sghaier Derbali","doi":"10.21314/JEM.2016.152","DOIUrl":"https://doi.org/10.21314/JEM.2016.152","url":null,"abstract":"As the nexus between Islamic financial market indexes and energy commodities becomes more global, the question of whether any specific shock considerations are still relevant that might affect this relationship arises. In order to answer it, our paper examines this question by testing the dynamic conditional correlation (DCC) betwee the Qatar Exchange Al Rayan Islamic Index and two energy commodities (crude oil and natural gas) by including structural breaks in the DCC-generalized autoregressive conditional heteroscedasticity (GARCH) model, as introduced by Engle in \"Dynamic conditional correlation: a simple class of multivariate GARCH models\" (2002), over the period from March 15, 2011 to December 25, 2014. Our findings reveal that the volatility of commodity returns is strongly correlated to that of the Al Rayan Islamic Index, and the volatility persistence decreases by its lowest amount after incorporating structural breaks. Interesting implications emerge from this paper for both policy makers and portfolio risk managers.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129019291","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":"Risk Factors in Energy Utility Returns: An Augmented-Four-Factor Model","authors":"Eucers Newsletter, D. Tulloch, I. Diaz‐Rainey","doi":"10.2139/ssrn.2739401","DOIUrl":"https://doi.org/10.2139/ssrn.2739401","url":null,"abstract":"In this paper we utilise the risk factors from both the finance and energy economics literatures to develop an improved asset pricing model (the Augmented-Four-Factor Model or AFFM) in the context of the European energy utility sector. In addition, we undertake inter-sectoral and inter-temporal analyses using the risk factors in our AFFM. Our results show our AFFM captures the greatest proportion of returns relative to other models. Further, stock market risk factors (most notably the market, size, value and momentum premia) explain a much greater proportion of average returns than term and commodity risk factors. Our inter-sectoral results show that, relative to other sectors, energy utilities are defensive stocks over the period analysed (1996 to 2013). However, our inter-temporal analysis shows that market beta has been increasing through time, from 0.710 in 1996 to 1.037 in 2013; the European energy utility sector is becoming increasingly exposed to systematic risk. Further, despite regulatory changes, designed to counteract the dominance of big energy utilities, the size premium has increased over time. Finally, the value and momentum premia are evident one to two years after the three EU energy sector liberalisation packages of 1996 and 1998, 2003, and 2009. In particular, the energy sector becomes extremely distressed following the third liberalisation package.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125144340","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}
Marco Haase, Yvonne Seiler Zimmermann, H. Zimmermann
{"title":"The Impact of Speculation on Commodity Futures – A Review of the Findings of 100 Empirical Studies","authors":"Marco Haase, Yvonne Seiler Zimmermann, H. Zimmermann","doi":"10.2139/ssrn.2729452","DOIUrl":"https://doi.org/10.2139/ssrn.2729452","url":null,"abstract":"There are numerous empirical studies on the impact of speculation on commodity futures prices. The papers strongly differ in terms of the focus variable (e.g. price, volatility, spillover effects) of speculative effects, the speculation measure used, and their methodological sophistication and quality. We review and evaluate the methodology and results of 100 papers which have been published (or are at least frequently quoted) on this subject over the past decade. While the overall picture indicates that the number of studies which report reinforcing and weakening effects is about the same, the results shift in favor of finding (clear or mixed) weakening effects if studies use direct measures of speculation.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114626756","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":"Trading on Their Terms? Commodity Exporters in the Aftermath of the Commodity Boom","authors":"Aqib Aslam, Samya Beidas-Strom, Rudolfs Bems, Oya Celasun, Sinem Kilic Celik, Z. Kóczán","doi":"10.5089/9781498338158.001.A001","DOIUrl":"https://doi.org/10.5089/9781498338158.001.A001","url":null,"abstract":"Commodity prices have declined sharply over the past three years, and output growth has slowed considerably among countries that are net exporters of commodities. A critical question for policy makers in these economies is whether commodity windfalls influence potential output. Our analysis suggests that both actual and potential output move together with commodity terms of trade, but that actual output comoves twice as strongly as potential output. The weak commodity price outlook is estimated to subtract 1 to 21/4 percentage points from actual output growth annually on average during 2015-17. The forecast drag on potential output is about one-third of that for actual output.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124337157","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":"Impact of Crude Oil Price and Exchange Rate on Performance of Indian Stock Market","authors":"Saurabh Singh, Ritika Kapil","doi":"10.5958/2249-7323.2016.00002.x","DOIUrl":"https://doi.org/10.5958/2249-7323.2016.00002.x","url":null,"abstract":"This paper attempts to investigate empirically the dynamic relationship among crude oil price, exchange rate and Indian stock market. Using daily data of Crude oil price, Dollar-Rupee value and Nifty returns from April 2010 to March 2015, correlation, regression and Granger-causality approach in a bi-variate VAR framework has been used to investigate the causality between crude oil and nifty returns; exchange rate and nifty returns. Augmented Dickey Fuller (ADF) test has been used to test whether the data is stationary or not. The outcome of the study was there is a significant negative correlation between nifty returns and exchange rate and significant positive correlation between nifty returns and crude oil, and a unidirectional causality running from nifty returns to exchange rates and crude oil price to nifty returns.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"89 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120939675","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 Market Value of Wind and Solar Power: An Analytical Approach","authors":"Lion Hirth, Alexander Radebach","doi":"10.2139/ssrn.2724826","DOIUrl":"https://doi.org/10.2139/ssrn.2724826","url":null,"abstract":"Several studies have shown that the revenues of wind and solar power generators on spot markets (“market value”) decline with increasing deployment. This “value drop” is often discussed quantitatively but infrequently analytically, a gap that this paper aims to fill. We derive a formal expression of the market value as a function of the penetration rate. At low deployment, the market value is driven by the covariance over time between winds or sunshine and electricity consumption. In countries where power demand peaks at noon during summer, the value of solar power is initially high; the equivalent is true for wind power in those regions where stormy winters coincide with periods of high demand for heating. As deployment increases, however, we show that the market value declines linearly with the penetration rate in energy terms (market share). The slope of the decline is determined by the relative variance of wind or sun: the more the output is concentrated in a few hours of the year, the steeper the drop in value. It is in this sense that variability (intermittency) “causes” the value drop. A drop in market value is also a feature of a power generation technology that operates constantly, but the drop is smaller in size.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116153007","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}
I. Felipe, A. Mól, Bernardo Luiz Rodrigues de Andrade
{"title":"Predictable and Price Volatility Risk in the Brazilian Market Integration of Shrimp","authors":"I. Felipe, A. Mól, Bernardo Luiz Rodrigues de Andrade","doi":"10.18028/2238-5320/rgfc.v5n4p83-107","DOIUrl":"https://doi.org/10.18028/2238-5320/rgfc.v5n4p83-107","url":null,"abstract":"The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. It´s presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Society of General Warehouses of Sao Paulo (CEAGESP).The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of \"One Step Ahead\" with 12 periods horizon , proved to be statistically more robust. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130426517","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":"Long-Short Commodity Investing: A Review of the Literature","authors":"J. Miffre","doi":"10.2139/ssrn.2700719","DOIUrl":"https://doi.org/10.2139/ssrn.2700719","url":null,"abstract":"This article reviews recent academic studies that analyze the performance of long-short strategies in commodity futures markets. Special attention is devoted to the strategies based on roll-yields, inventory levels or hedging pressure that directly arise from the theory of storage and the hedging pressure hypothesis. Alternative strategies based on past performance, risk, value, skewness, liquidity or inflation betas are also studied, alongside with recent attempts to enhance performance by modifying or combining the original signals. Overall, the literature highlights the superiority of being long-short in commodity futures markets relative to being long-only.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132750117","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":"A Boosting Approach to Forecasting the Volatility of Gold-Price Fluctuations Under Flexible Loss","authors":"Christian Pierdzioch, M. Risse, Sebastian Rohloff","doi":"10.2139/ssrn.2513830","DOIUrl":"https://doi.org/10.2139/ssrn.2513830","url":null,"abstract":"We use a boosting approach to study the time-varying out-of-sample informational content of various financial and macroeconomic variables for forecasting the volatility of gold-price fluctuations. We use an out-of-sample R2 statistic to evaluate forecasts as a function of the shape of a forecaster’s loss function. We show that, when compared to an autoregressive benchmark forecast, those forecasters tend to benefit from using predictions implied by the boosting approach who encounter a larger loss when underestimating rather than overestimating the future volatility of gold-price fluctuations. We use a simulation experiment to study the significance of this benefit.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128762082","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}