发布求助
文献互助 智能选刊 最新文献

Journal of Commodity Markets最新文献

筛选
英文 中文
Connectedness between green bonds, clean energy markets and carbon quota prices: Time and frequency dynamics 绿色债券、清洁能源市场和碳配额价格之间的关联性：时间和频率动态
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-11-08 DOI: 10.1016/j.jcomm.2024.100442
Ingrid Emilie Flessum Ringstad , Kyriaki Tselika
{"title":"Connectedness between green bonds, clean energy markets and carbon quota prices: Time and frequency dynamics","authors":"Ingrid Emilie Flessum Ringstad ,&nbsp;Kyriaki Tselika","doi":"10.1016/j.jcomm.2024.100442","DOIUrl":"10.1016/j.jcomm.2024.100442","url":null,"abstract":"<div><div>In this paper, we investigate the time and frequency dynamics of connectedness among green assets such as green bonds, clean energy markets, and carbon prices. Using daily price data, we explore return spillovers across these green financial markets by applying the novel framework on time and frequency dynamics proposed by Baruník and Krehlík (2018). This allows us to identify the direction of spillovers among our variables, and decompose the connectedness to differentiate between short-term and long-term return spillovers. Our results indicate that green bonds and carbon prices act as net receivers of shocks, but mainly in the short-term. We also observe a low level of connectedness among our clean energy markets across both low and high frequency bands, even during times of economic or political crisis. Additionally, there are periods in which connectedness between the clean energy assets is driven by the long-term. In periods of economic and political stability, carbon prices may also provide an interesting diversifying tool for short-term investors. Our results should be of interest for investors and portfolio managers who focus on green financial markets, by strengthening the notion that green financial markets can offer diversification opportunities, for both short-term and long-term investors. Policy makers could also benefit from our insights on conectedness in their work on short-term and long-term climate policies. This paper is the first to use this framework to investigate systematic risks within green financial markets.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100442"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Carbon pricing and the commodity risk premium 碳定价与商品风险溢价
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-11-14 DOI: 10.1016/j.jcomm.2024.100447
Qiao Wang
{"title":"Carbon pricing and the commodity risk premium","authors":"Qiao Wang","doi":"10.1016/j.jcomm.2024.100447","DOIUrl":"10.1016/j.jcomm.2024.100447","url":null,"abstract":"<div><div>This paper examines whether the carbon pricing risk factor is priced in the cross-section of commodity futures. By analyzing unexpected pricing shocks in carbon emission allowances, carbon pricing risk is indeed priced in commodity futures, with a significant positive risk premium. The analysis of carbon pricing risk loadings reveals that individual commodities' sensitivities to carbon pricing risk vary. Additionally, commodity-specific characteristics, such as basis and hedging pressure, impact these risk loadings. Finally, I demonstrate that a portfolio of commodity futures constructed based on carbon pricing beta provides superior out-of-sample hedging performance for climate change risk compared to alternative hedge portfolios using equities or ETFs.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100447"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The role of news sentiment in salmon price prediction using deep learning 新闻情绪在利用深度学习预测鲑鱼价格中的作用
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-10-05 DOI: 10.1016/j.jcomm.2024.100438
Christian Oliver Ewald , Yaoyu Li
{"title":"The role of news sentiment in salmon price prediction using deep learning","authors":"Christian Oliver Ewald ,&nbsp;Yaoyu Li","doi":"10.1016/j.jcomm.2024.100438","DOIUrl":"10.1016/j.jcomm.2024.100438","url":null,"abstract":"<div><div>This paper employs deep learning models and sentiment analysis to predict salmon spot prices. Our data includes historical price data and sentiment scores from 2018 to 2022. We extract sentiment scores from salmon-related news headlines by using FinBERT and TextBlob. We begin with price prediction using only historical price data and then introduce sentiment scores to improve the prediction accuracy of deep learning models. We find that the prediction performance of deep learning models outperforms traditional prediction methods in the salmon market. Our primary hybrid CNN-LSTM model outperforms other deep learning models and traditional models. Additionally, deep learning models incorporating sentiment scores exhibit reduced prediction errors. Our findings confirm the value of sentiment information in improving forecasting performance. These findings highlight the effectiveness and robustness of our CNN-LSTM model combined with sentiment analysis for price prediction in the salmon market.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100438"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
When Chinese mania meets global frenzy: Commodity price bubbles 当中国狂热遇上全球狂热：商品价格泡沫
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-10-05 DOI: 10.1016/j.jcomm.2024.100437
John Hua Fan , Adrian Fernandez-Perez , Ivan Indriawan , Neda Todorova
{"title":"When Chinese mania meets global frenzy: Commodity price bubbles","authors":"John Hua Fan ,&nbsp;Adrian Fernandez-Perez ,&nbsp;Ivan Indriawan ,&nbsp;Neda Todorova","doi":"10.1016/j.jcomm.2024.100437","DOIUrl":"10.1016/j.jcomm.2024.100437","url":null,"abstract":"<div><div>This paper examines price bubbles in global commodity markets. We find that positive bubbles are more driven by fundamental shocks, while negative bubbles are more influenced by pessimistic market views on prices and the economy. Furthermore, bubble determinants vary across geographic regions. Trader behavior and policy uncertainty play prominent roles in influencing price bubbles in China, while global bubbles are predominantly shaped by rational responses to inventory, growth, and inflation. Finally, only positive bubbles exhibit contagion across regions. Overall, our findings suggest that asset price bubbles arise from traders' behavioral responses to a combination of fundamental, macroeconomic, and idiosyncratic shocks.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100437"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Diversifying crude oil price risk with crude oil volatility index: The role of volatility-of-volatility 用原油波动指数分散原油价格风险：波动率的作用
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-08-23 DOI: 10.1016/j.jcomm.2024.100425
Leon Li , Peter Miu
{"title":"Diversifying crude oil price risk with crude oil volatility index: The role of volatility-of-volatility","authors":"Leon Li ,&nbsp;Peter Miu","doi":"10.1016/j.jcomm.2024.100425","DOIUrl":"10.1016/j.jcomm.2024.100425","url":null,"abstract":"<div><p>To understand the diversification benefit of crude oil volatility, we examine the return-volatility relation in the crude oil market, given the interaction of the volatility (VOL) and the volatility-of-volatility (VOV). We develop a novel empirical model of the crude oil price and crude oil volatility index (OVX) returns incorporating both time-varying and state-dependent variances and correlations, thus allowing us to identify distinct market regimes of VOL and VOV. We find that the behavior of the return-volatility relation is contingent on the prevailing VOV regimes. Specifically, in a low (high) VOV regime, the relation becomes less (more) negative as VOL increases. These empirical results therefore imply that the diversification benefit of crude oil volatility is far from uniform across the different market states. Finally, using our proposed empirical model, we demonstrate the economic significance of recognizing both the time-varying and state-dependent variances/correlations in portfolio risk forecasting and construction.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100425"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405851324000448/pdfft?md5=0fd7e8f45700b2753a2bc06abc6f3b1f&pid=1-s2.0-S2405851324000448-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142098459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Oil jump tail risk as a driver of inflation dynamics 石油跃升尾部风险是通胀动态的驱动因素
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-12-01 Epub Date: 2024-08-29 DOI: 10.1016/j.jcomm.2024.100434
Laurent Ferrara , Aikaterini Karadimitropoulou , Athanasios Triantafyllou
{"title":"Oil jump tail risk as a driver of inflation dynamics","authors":"Laurent Ferrara ,&nbsp;Aikaterini Karadimitropoulou ,&nbsp;Athanasios Triantafyllou","doi":"10.1016/j.jcomm.2024.100434","DOIUrl":"10.1016/j.jcomm.2024.100434","url":null,"abstract":"<div><p>In this paper, we look at the role of various oil jump tail risk measures as drivers of both U.S. headline and core inflation. Those measures are first computed from high-frequency oil future prices and are then introduced into standard regression models in order to (i) assess in-sample determinants of inflation, (ii) assess overtime the evolution of inflation drivers, (iii) estimate impulse response functions and (iv) forecast inflation out-of-sample for various horizons. Empirical results suggest that oil jump tail risk measures contain useful information to describe inflation dynamics, generally leading to upward inflationary pressures. Even after controlling from standard variables involved in a Phillips curve, goodness-of-fit measures show evidence of a gain, in particular for headline inflation. Overall, we observe that oil jump tail risk measures are contributing more to inflation dynamics since the Covid-19 crisis.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100434"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405851324000539/pdfft?md5=5d89b9e4b9ec4a970908e9abe8f70468&pid=1-s2.0-S2405851324000539-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Seasonality patterns in LNG shipping spot and time charter freight rates 液化天然气航运即期和定期包船运费的季节性模式
IF 3.7 4区 经济学
Journal of Commodity Markets Pub Date : 2024-09-01 Epub Date: 2024-08-10 DOI: 10.1016/j.jcomm.2024.100424
Dionysios Polemis, Christos Bentsos
{"title":"Seasonality patterns in LNG shipping spot and time charter freight rates","authors":"Dionysios Polemis,&nbsp;Christos Bentsos","doi":"10.1016/j.jcomm.2024.100424","DOIUrl":"10.1016/j.jcomm.2024.100424","url":null,"abstract":"<div><p>The aim of this paper is to investigate the existence and the nature of seasonality in LNG freight rates of different duration contract, over different market conditions (peak and troughs) for the period from December 2010 to June 2023. We employ the HEGY method and seasonal dummy variables to test for stochastic and deterministic seasonality, respectively. Then we use Markov Switching models to test for asymmetries in seasonal fluctuations across different market conditions. We reject the existence of stochastic seasonality for all freight series while results on deterministic seasonality indicate increases in rates in June, October, and November. We also found that seasonal patterns vary across market conditions, revealing that seasonal rate movements are more pronounced when the market is in downturn. Moreover, we found that the seasonal movements present similar patterns across different trading routes. The results have implications for stakeholders across the LNG value chain.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"35 ","pages":"Article 100424"},"PeriodicalIF":3.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The asymmetric effect of G7 stock market volatility on predicting oil price volatility: Evidence from quantile autoregression model 七国集团股市波动对预测油价波动的非对称效应：量化自回归模型的证据
IF 4.2 4区 经济学
Journal of Commodity Markets Pub Date : 2024-09-01 Epub Date: 2024-05-21 DOI: 10.1016/j.jcomm.2024.100409
Feipeng Zhang , Hongfu Gao , Di Yuan
{"title":"The asymmetric effect of G7 stock market volatility on predicting oil price volatility: Evidence from quantile autoregression model","authors":"Feipeng Zhang ,&nbsp;Hongfu Gao ,&nbsp;Di Yuan","doi":"10.1016/j.jcomm.2024.100409","DOIUrl":"10.1016/j.jcomm.2024.100409","url":null,"abstract":"<div><p>This paper investigates the asymmetric effect of G7 stock market volatility on predicting oil price volatility under different oil market conditions by using the quantile autoregression model. Both in- and out-of-sample results demonstrate the prediction superiority and effectiveness of the quantile autoregression model. The US and Canada's stock markets exhibit the strongest predictive ability across the entire distribution, while the UK demonstrates strong predictive power specifically during periods of high oil price volatility. Japan, Germany, France, and Italy as oil importers can predict low and median oil volatility. The strong predictability of G7 stock volatility may be attributable to their significant impact on the business cycle and investor sentiment. This asymmetric prediction ability arises not only from the average volatility shocks at various quantiles but also from the bad and good stock volatility at different quantiles. Further research suggests that bad stock volatility appears to be more predictable than good stock volatility, especially in high oil price fluctuations. Furthermore, the superiority and effectiveness of the quantile autoregression model in predicting oil volatility are proven to be applicable to emerging markets. This study may provide useful insights for policymakers, businesses, and investors to improve crude oil risk prediction and risk management under different market conditions.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"35 ","pages":"Article 100409"},"PeriodicalIF":4.2,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Stock return predictability using economic narrative: Evidence from energy sectors 利用经济叙事预测股票回报率：能源行业的证据
IF 4.2 4区 经济学
Journal of Commodity Markets Pub Date : 2024-09-01 Epub Date: 2024-05-31 DOI: 10.1016/j.jcomm.2024.100418
Tian Ma , Ganghui Li , Huajing Zhang
{"title":"Stock return predictability using economic narrative: Evidence from energy sectors","authors":"Tian Ma ,&nbsp;Ganghui Li ,&nbsp;Huajing Zhang","doi":"10.1016/j.jcomm.2024.100418","DOIUrl":"https://doi.org/10.1016/j.jcomm.2024.100418","url":null,"abstract":"<div><p>This paper applies the Narrative-based Energy General Index (NEG) to forecast stock returns in the energy industry. The index is constructed using natural language processing (NLP) techniques applied to news topics from <em>The Wall Street Journal</em>. The results indicate that NEG outperforms in predicting future returns of the energy industry in both in-sample and out-of-sample, and the predictive power surpasses that of other macroeconomic variables. The asset allocation exercise demonstrates the substantial economic value of NEG. Furthermore, we document that NEG not only exhibits superior predictive power for energy sector returns but also provides valuable insights for the whole stock market.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"35 ","pages":"Article 100418"},"PeriodicalIF":4.2,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141243347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Implied parameter estimation for jump diffusion option pricing models: Pricing accuracy and the role of loss and evaluation functions 跃迁扩散期权定价模型的隐含参数估计：定价准确性以及损失和评估函数的作用
IF 4.2 4区 经济学
Journal of Commodity Markets Pub Date : 2024-09-01 Epub Date: 2024-05-27 DOI: 10.1016/j.jcomm.2024.100408
Jimmy E. Hilliard , Jitka Hilliard , Julie T.D. Ngo
{"title":"Implied parameter estimation for jump diffusion option pricing models: Pricing accuracy and the role of loss and evaluation functions","authors":"Jimmy E. Hilliard ,&nbsp;Jitka Hilliard ,&nbsp;Julie T.D. Ngo","doi":"10.1016/j.jcomm.2024.100408","DOIUrl":"https://doi.org/10.1016/j.jcomm.2024.100408","url":null,"abstract":"<div><p>There is extensive literature on problems involved in estimating implied parameters in the Merton Jump Diffusion model. Using simulated data, we use weighted non-linear least squares to estimate implied parameters in the four parameter jump diffusion model (JD) and in an eight parameter jump diffusion model with convenience yield (JDC). We find reliable and accurate implied parameter estimates for the JD model but biased and unreliable estimates for some parameters in the JDC model. However, for both models we estimate accurate option prices, usually within several basis points. We also use Bitcoin real data to estimate parameters and test the out-of-sample performance of the JDC model.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"35 ","pages":"Article 100408"},"PeriodicalIF":4.2,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141243346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信
小红书