Econometric Modeling: Commodity Markets eJournal最新文献

{"title":"The Intertemporal Relation between Expected Returns and Conditional Correlations between Precious Metals and the Stock Market","authors":"Ryuta Sakemoto","doi":"10.2139/ssrn.3177426","DOIUrl":"https://doi.org/10.2139/ssrn.3177426","url":null,"abstract":"This study explores whether conditional correlations between precious metals and stock markets impact upon expected returns on precious metals. The empirical evidence presents that there is no significant trade–off between conditional correlations and expected returns, which means that high returns on precious metals are not related to a lack of diversification benefits. Interestingly, high absolute values of conditional correlations lead to increases in expected returns, suggesting that the unstable cross-asset market condition is associated with the expected returns. This impact is stronger on silver than on gold. Â","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115499720","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":"Determinants of Real Effective Exchange Rates in Emerging Market Economies","authors":"Neha Kataria, Aakash Gupta","doi":"10.2139/ssrn.3144172","DOIUrl":"https://doi.org/10.2139/ssrn.3144172","url":null,"abstract":"This paper uses quarterly data to examine the effect of global and domestic factors on the real effective exchange rates (REER) for 20 emerging market economies for 2000-2015. We find that GDP growth and the domestic policy interest rate are robustly associated with REER appreciation in emerging economies. Among global factors, an increase in global risk is negatively related to the real exchange rate, while the Brent crude oil price is positively related. The overall positive effect of crude oil price is more pronounced for the REER of oil-exporting countries, and negative for oil-importing countries. We also find that a relatively flexible exchange rate regime reduces the negative impact of global risk on REER, but capital account openness does not seem to play a role. These findings have implications for emerging market economies in developing policies to respond to commodity price fluctuations and changes in the global monetary and risk environment.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134536116","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":"Main Trends and Conclusions in Russian Economy in February 2018","authors":"V. Gurevich","doi":"10.2139/ssrn.3131597","DOIUrl":"https://doi.org/10.2139/ssrn.3131597","url":null,"abstract":"The existing geopolitical context is capable of endowing seemingly ordinary business events in one or other economic branch with almost global significance. One of the examples of this trend is the recent announcement, by a Japanese state-owned bank, of its readiness to finance a new natural gas project of Novatek. This means that, in spite of being under sanctions, a Russian company still can get access to foreign financing from a high-profile official source. Moreover, in the case under consideration, this new source of financing will become a competitor to the company’s previous sources of financing (for example, Chinese ones). Thus, the above news story has transmitted two positive signals at once, which overshadow, for the time being at least, the risks that can be brought about by changes in the global market situation, namely global liquefied natural gas demand and LNG prices in the mid-2020s, when this natural gas project, its total cost amounting to about $ 20bn, is planned to be completed.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122369646","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":"Exchange Rates, Oil Prices and World Stock Returns","authors":"A. Mollick, Hamid Sakaki","doi":"10.2139/ssrn.3127547","DOIUrl":"https://doi.org/10.2139/ssrn.3127547","url":null,"abstract":"Abstract This paper examines responses of 14 major currency/USD pairs to two global factors (oil and world equity returns) from January 1999 to July 2017, a period comprising the global financial crisis and oil price boom and collapse. With global equity markets advancing, risk tolerance increases and oil and stock markets impact currencies under two methodologies: transmission of shocks and mean-variance approaches. Vector autoregressions (VARs) suggest large and statistically significant responses: commodity currencies strongly appreciate following positive oil price shocks and depreciate with positive global equity shocks. GARCH models provide similar qualitative results with coefficients typically larger for global equity returns than for oil returns. Emerging market currencies and subsamples for the crisis period are also discussed.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126515332","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 Share Price and Investment: Current Footprints for Future Oil and Gas Industry Performance","authors":"I. Jianu, Iulia Jianu","doi":"10.3390/EN11020448","DOIUrl":"https://doi.org/10.3390/EN11020448","url":null,"abstract":"The share price has become a very important indicator for shareholders, banks, and financial institutions evaluating the performance of companies. The oil and gas industry seems to be in a difficult era of development, due to the market prices for its products. Moreover, climate change and renewable energies are barriers for fossil energy. This state of affairs, and the fact that oil and gas shares are considered one of the most solid and reliable shares on the London Stock Exchange (LSE), have drawn our attention. International institutions encourage the investment in the oil and gas economic sector. This study investigates how investments of oil and gas companies in long-term assets influence the share price. Using the Ohlson share price model for a sample of 51 listed companies on the LSE proves that investments in long-term assets influence the share price in the case of companies which record losses. Investments in long-term assets are responsible for the attractiveness of the oil and gas company shares.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114074714","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":"Nonlinear Intermediary Pricing in the Oil Futures Market","authors":"D. Bierbaumer, Malte Rieth, Anton Velinov","doi":"10.2139/ssrn.3132355","DOIUrl":"https://doi.org/10.2139/ssrn.3132355","url":null,"abstract":"We study the state-dependent trading behavior of financial intermediaries in the oil futures market, using structural vector autoregressions with Markov switching in heteroskedasticity. We decompose changes in futures price volatility into changes in the slopes of traders' demand curves and in the variability of their demand shocks. We find that the downward-sloping demand curve of intermediaries steepens significantly during turbulent times. Moreover, the variance of intermediaries' own demand shocks doubles during these episodes. These findings suggest that the futures pricing of intermediaries is nonlinear and increases the hedging costs of producers and processors of oil when volatility is high.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130377065","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":"Media Coverage and Food Commodities: Agricultural Futures Prices and Volatility Effects","authors":"M. Almanzar, M. Torero","doi":"10.2139/ssrn.3067949","DOIUrl":"https://doi.org/10.2139/ssrn.3067949","url":null,"abstract":"We examine how media coverage of fluctuations in the price of agricultural commodities affects these prices and their volatility. We develop a unified empirical framework to analyze the media’s effects on both returns and volatility using insights from the literature. We use daily prices of futures contracts for soybeans, hard wheat, soft wheat, rice, and maize, complemented by a unique dataset that follows a comprehensive set of global media outlets and uses an algorithm to determine sophisticated relationships among phrases in a news article which signal an increase or decrease in the price of those four commodities. We find price effects that are economically important in size. Our estimates imply a net increasing effect of media coverage on the price of these four commodities; these effects are mostly concentrated in 2012 and from 2015 onwards, meaning that these effects are important in periods of both high and low prices. Across commodities, the price effects are concentrated in soybeans and maize. We find robust evidence that media coverage decreases volatility for these agricultural commodities on average for the period we study. The effects on volatility balance each other, with decreasing price coverage decreasing the variance of returns and increasing price coverage increasing the variance of returns of futures contracts of these commodities; however, the increase is than the decrease. Our results suggest that media coverage increases periods of normal volatility and decreases periods of excessive volatility. These results point to the potential of using media coverage to bring attention to price surges and to decrease volatility during food crises or times when there is above-normal volatility. The dynamics between the price of agricultural commodities and media coverage may help prevent knee-jerk policy reactions by discouraging market overreaction, encouraging market stability, and promoting food security. They highlight crucial role of providing appropriate information as fast as possible so media coverage and reflects the fundamentals that drive food commodity prices.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122797461","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 Forward Dynamic Optimization Strategy Under Contango Storage Arbitrage with Frictions","authors":"B. Ghafouri, M. Davison","doi":"10.21314/JEM.2017.166","DOIUrl":"https://doi.org/10.21314/JEM.2017.166","url":null,"abstract":"The goal of this paper is to explain and improve the offshore oil storage trade observed in a contango market using a forward dynamic optimization strategy. The strategy is developed using trades in forward contracts and contrasted with the literature. By simulating forward prices based on realistic May 2009 market conditions, our strategy, when compared with selling the oil on the spot in a base case scenario, gains an extra US$8.99/barrel, which is comprised of US$6.19 generated by the initial forward maximization and US$2.80 achieved by the subsequent trades. The impact of the forward curve dynamics is studied by examining the trading decisions based on the realized slope and mean level of the forward curve. The path of the realized slope and stepwise changes in the slope are found to be able to explain most of the trading decisions. The effect of initial conditions, the frequency with which the position is readjusted and the storage cost are also examined. The optimal frequency depends on the storage cost. Friction is introduced into the problem by penalizing the refund of the storage cost when a decision to advance the short position in time is made, where its influence, which depends on the storage cost, is at most US$1.40.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133255086","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":"Strategic Default in the International Coffee Market","authors":"A. Blouin, Rocco Macchiavello","doi":"10.1093/QJE/QJZ004","DOIUrl":"https://doi.org/10.1093/QJE/QJZ004","url":null,"abstract":"This article studies strategic default on forward sale contracts in the international coffee market. To test for strategic default, we construct contract-specific measures of unanticipated changes in market conditions by comparing spot prices at maturity with the relevant futures prices at the contracting date. Unanticipated rises in market prices increase defaults on fixed-price contracts but not on price-indexed ones. We isolate strategic default by focusing on unanticipated rises at the time of delivery after production decisions are sunk and suppliers have been paid. Estimates suggest that roughly half of the observed defaults are strategic. We model how strategic default introduces a trade-off between insurance and counterparty risk: relative to indexed contracts, fixed-price contracts insure against price swings but create incentives to default when market conditions change. A model calibration suggests that the possibility of strategic default causes 15.8% average losses in output, significant dispersion in the marginal product of capital, and sizable negative externalities on supplying farmers.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127215485","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 Spillovers and Heavy Tails: A Large T-Vector Autoregressive Approach","authors":"Luca Barbaglia, C. Croux, I. Wilms","doi":"10.2139/ssrn.3068730","DOIUrl":"https://doi.org/10.2139/ssrn.3068730","url":null,"abstract":"Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR) model. We account for the possible fat-tailed distribution of the VAR model errors using a VAR model with errors following a multivariate Student t-distribution with unknown degrees of freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation of the VAR model with t-distributed errors. We study volatility spillovers among energy, biofuel and agricultural commodities and reveal bidirectional volatility spillovers between energy and biofuel, and between energy and agricultural commodities.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115795490","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}