Journal of Commodity Markets最新文献_第2页

Corporate reputational dynamics and their impact on global commodity markets

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2025-02-06 DOI: 10.1016/j.jcomm.2025.100459

Iris Li , Erdinc Akyildirim , Thomas Conlon , Shaen Corbet

引用次数: 0

A quantitative model of sustainability risk in finance 金融领域可持续性风险的量化模型

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2025-01-22 DOI: 10.1016/j.jcomm.2025.100457

Takashi Kanamura

引用次数: 0

Do different speculation strategies cause distinct impacts on the volatility of the live cattle futures in Brazil? 不同的投机策略会对巴西活牛期货的波动产生不同的影响吗？

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2025-01-11 DOI: 10.1016/j.jcomm.2025.100458

Augusto Seabra Santos, Alexandre Nunes Almeida

引用次数: 0

Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2024-11-29 DOI: 10.1016/j.jcomm.2024.100449

Katarzyna Chȩć, Bartosz Uniejewski, Rafał Weron

{"title":"Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market","authors":"Katarzyna Chȩć, Bartosz Uniejewski, Rafał Weron","doi":"10.1016/j.jcomm.2024.100449","DOIUrl":"10.1016/j.jcomm.2024.100449","url":null,"abstract":"<div><div>Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then combining their forecasts can bring significant accuracy gains in day-ahead electricity price forecasting. However, not much attention has been paid to predicting the LTSC, and the last 24 hourly values of the estimated pattern are typically copied for the target day. To address this gap, we introduce a novel approach which extracts the trend-seasonal pattern from a price series extrapolated using price forecasts for the next 24 h. We assess it using two 5-year long test periods from the German and Spanish power markets, covering the Covid-19 pandemic, the 2021/2022 energy crisis, and the war in Ukraine. Considering parsimonious autoregressive and LASSO-estimated models, we find that improvements in predictive accuracy range from 3% to 15% in terms of the root mean squared error and exceed 1% in terms of profits from a realistic trading strategy involving day-ahead bidding and battery storage.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100449"},"PeriodicalIF":3.7,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181344","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

Time to get mature: Collateral, flexibility and the hedging horizon decision 是时候成熟了：抵押品、灵活性和对冲期限决策

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2024-11-16 DOI: 10.1016/j.jcomm.2024.100448

Håkan Jankensgård , Nicoletta Marinelli , Rafael Schiozer

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 : 2024-11-14 DOI: 10.1016/j.jcomm.2024.100447

Qiao Wang

引用次数: 0

Have the causal effects between equities, oil prices, and monetary policy changed over time? 股票、油价和货币政策之间的因果效应是否随着时间的推移而改变？

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2024-11-13 DOI: 10.1016/j.jcomm.2024.100446

Alexander Kurov , Eric Olson , Marketa Halova Wolfe

引用次数: 0

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 : 2024-11-08 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 , 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":"2024-11-08","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

Commodity market downturn: Systemic risk and spillovers during left tail events 商品市场下滑：左尾事件中的系统风险和溢出效应

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2024-11-03 DOI: 10.1016/j.jcomm.2024.100445

Samet Gunay , Destan Kirimhan , Emrah Ismail Cevik

{"title":"Commodity market downturn: Systemic risk and spillovers during left tail events","authors":"Samet Gunay , Destan Kirimhan , Emrah Ismail Cevik","doi":"10.1016/j.jcomm.2024.100445","DOIUrl":"10.1016/j.jcomm.2024.100445","url":null,"abstract":"<div><div>We investigate systemic risk and spillovers in the commodity network during left-tail events using state-of-the-art methodologies: the Component Exponent Shortfall (CES), Quantile-Vector Autoregression (QVAR) and Causality-in-Risk. Our analysis focuses on five commodity groups: Energy (Crude Oil, Heating Oil, Natural Gas, Coal), Base Metals (Aluminum, Copper, Nickel, Zinc), Ferrous Metals (Iron, Steel), Precious Metals (Gold, Palladium, Platinum, Silver), and Others (Rubber). Across the models utilized, we consistently find that energy commodities and precious metals, along with copper as a standalone commodity, represent the most systemically risky group. Thus, portfolios incorporating these commodities are advised to implement more careful diversification to mitigate risks stemming from systemic factors. This may require additional attention to precious metals, as they are often considered safe-haven assets. Expediting the implementation of regulations that promote the replacement of fossil energy sources with green alternatives could be instrumental in managing systemic risk in the commodity market while also facilitating global sustainability. Finally, the results show that the impact of the Israeli-Palestinian conflict on both systemic risk and spillovers has been limited compared to the effects of COVID-19 and the Russia-Ukraine war.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100445"},"PeriodicalIF":3.7,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651524","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

Forecasting crude oil returns with oil-related industry ESG indices 利用石油相关行业 ESG 指数预测原油回报率

IF 3.7 4区经济学

Journal of Commodity Markets Pub Date : 2024-10-29 DOI: 10.1016/j.jcomm.2024.100444

Kaixin Li , Zhikai Zhang , Yudong Wang , Yaojie Zhang

{"title":"Forecasting crude oil returns with oil-related industry ESG indices","authors":"Kaixin Li , Zhikai Zhang , Yudong Wang , Yaojie Zhang","doi":"10.1016/j.jcomm.2024.100444","DOIUrl":"10.1016/j.jcomm.2024.100444","url":null,"abstract":"<div><div>We construct North American oil-related industry ESG indices based on Elastic Net and PCA/SPCA/PLS dimensionality reduction techniques. We discover that the ESG indices show significant forecasting power for crude oil returns both in- and out-of-sample, and their ability to significantly predict oil returns remains when the delayed ESG release is considered. Additionally, our analysis suggests that the predictive abilities of ESG indices remain robust and unaffected by stock returns in the oil-related industry. The ESG indices can provide information that is heterogeneous and complementary to macroeconomic variables and technical indicators. Based on the analysis over the business cycle, ESG indices show predictability in forecasting crude oil returns during economic expansions rather than recessions. Moreover, ESG indices' predictive ability is also of economic significance, as shown by the substantial economic value it generates for mean-variance investors. Finally, we explore the potential economic channels, and the result reveals that the predictive power of ESG indices arises from speculative behavior in the oil market and oil demand.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100444"},"PeriodicalIF":3.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577461","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