Econometric Modeling: Commodity Markets eJournal最新文献_第3页

The Impact of Margin Changes on Commodity Futures Markets: Evidence From India 保证金变动对商品期货市场的影响:来自印度的证据

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-12-07 DOI: 10.2139/ssrn.3500093

Nagaraju Thota, Neel Shah

引用次数: 0

Oil and Risk Premia in Equity Markets 股票市场的石油和风险溢价

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-11-06 DOI: 10.2139/ssrn.3481593

Satish Kumar, Rıza Demirer, A. Tiwari

{"title":"Oil and Risk Premia in Equity Markets","authors":"Satish Kumar, Rıza Demirer, A. Tiwari","doi":"10.2139/ssrn.3481593","DOIUrl":"https://doi.org/10.2139/ssrn.3481593","url":null,"abstract":"\u0000Purpose\u0000This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.\u0000\u0000\u0000Design/methodology/approach\u0000This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.\u0000\u0000\u0000Findings\u0000The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.\u0000\u0000\u0000Practical implications\u0000The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.\u0000\u0000\u0000Originality/value\u0000This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.\u0000","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128001343","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}

引用次数: 3

A New Approach to Evaluating the Cost-Efficiency of Complex Hedging Strategies: An Application to Electricity Price–Volume Quanto Contracts 一种评估复杂套期保值策略成本-效率的新方法:在电价-量权合约中的应用

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-09-19 DOI: 10.21314/jem.2018.187

S. Kang, M. Ong, Jialin Zhao

{"title":"A New Approach to Evaluating the Cost-Efficiency of Complex Hedging Strategies: An Application to Electricity Price–Volume Quanto Contracts","authors":"S. Kang, M. Ong, Jialin Zhao","doi":"10.21314/jem.2018.187","DOIUrl":"https://doi.org/10.21314/jem.2018.187","url":null,"abstract":"Electricity quanto contracts improve the efficiency of financial risk management by accommodating the correlated price and volumetric risks of energy suppliers. The use of electricity quanto contracts, however, suffers from the high risk premiums associated with such tailor-made and illiquid financial instruments. As a result, it is of great interest to properly evaluate the cost-efficiency of these complex hedging deals. To address this concern, we propose a new hedging assessment model, the economic value of the incremental expected shortfall (EVIES), from a cost-efficiency perspective. Using EVIES, we develop a Monte Carlo simulation-based hedging framework. This framework overcomes the limits of traditional models by not resting on risk neutrality, market completeness or unobservable inputs. In our numerical examples, we assume that a fictitious power supplier has access to electricity price derivatives, weather derivatives and electricity quanto contracts, and we show that our proposed model can be applied to: \u0000 \u0000(1) construct a cost-effective hedge against an electricity price–volume joint risk, \u0000 \u0000(2) find a partial equilibrium for the valuation of electricity quanto contracts and \u0000 \u0000(3) locate hedging solutions for achieving a specific risk management target.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128191041","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}

引用次数: 1

Monopoly Power in the Oil Market and the Macroeconomy 石油市场的垄断力量与宏观经济

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-08-21 DOI: 10.2139/ssrn.3059613

Nicole Branger, René Marian Flacke, Nikolai Gräber

引用次数: 12

World Oil Market: Prices Have Stabilized 世界石油市场:价格趋于稳定

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-08-06 DOI: 10.2139/ssrn.3432933

Yuri Bobylev

引用次数: 1

Разработка и построение конкурентной модели российского рынка черных и цветных металлов (Development and Construction of a Competitive Model of the Russian Market of Ferrous and Non-Ferrous Metals)

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-06-20 DOI: 10.2139/ssrn.3407917

P. Pavlov, A. Kaukin

{"title":"Разработка и построение конкурентной модели российского рынка черных и цветных металлов (Development and Construction of a Competitive Model of the Russian Market of Ferrous and Non-Ferrous Metals)","authors":"P. Pavlov, A. Kaukin","doi":"10.2139/ssrn.3407917","DOIUrl":"https://doi.org/10.2139/ssrn.3407917","url":null,"abstract":"Russian Abstract: В работе представлены результаты апробации методики оценки уровня рыночной власти производителей металлургической продукции на основе агрегированных отраслевых данных. В первой главе представлен обзор теоретических и эмпирических подходов к моделированию конкуренции и оценке уровня рыночной власти на рынке металлургической продукции. Во второй приведена характеристика российского рынка черных и цветных металлов. В третьей охарактеризована базы данных, которая использовалась для оценки модели, включающей уравнения спроса и предложения металлургической продукции. В четвертой главе приводятся результаты эконометрических оценок уровня рыночной власти на рынке черных и цветных металлов (последний исследуется на примере продукции алюминиевой отрасли). Ключевые слова: черные металлы, цветные металлы, модели конкуренции, уровень рыночной власти, функция спроса, функция предложения, пределы арбитража, микроданные, отраслевые данные. English Abstract: A methodology for assessing the level of market power of metallurgical products producers was deveoped in the paper with the use of aggregated industry-level data. The first chapter of the paper presents an overview of theoretical and empirical approaches to modeling competition and assessing the level of market power in the metallurgical products market. The second chapter presents the characteristics of the Russian ferrous and non-ferrous metals markets. The third chapter describes the characteristics of the database, which was used to estimate the demand-supply system for metallurgical products market. The fourth chapter presents the results of econometric estimates of the level of market power in the market of ferrous and non-ferrous metals (the latter is examined on the example of products of the aluminum industry).","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133137055","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}

引用次数: 0

Forecasting in Blockchain-based Local Energy Markets 基于区块链的本地能源市场预测

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-06-02 DOI: 10.3390/EN12142718

Michael Kostmann, W. Härdle

{"title":"Forecasting in Blockchain-based Local Energy Markets","authors":"Michael Kostmann, W. Härdle","doi":"10.3390/EN12142718","DOIUrl":"https://doi.org/10.3390/EN12142718","url":null,"abstract":"Increasingly volatile and distributed energy production challenges traditional mechanisms to manage grid loads and price energy. Local energy markets (LEMs) may be a response to those challenges as they can balance energy production and consumption locally and may lower energy costs for consumers. Blockchain-based LEMs provide a decentralized market to local energy consumer and prosumers. They implement a market mechanism in the form of a smart contract without the need for a central authority coordinating the market. Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of individual households’ energy consumption and production. Often, such accurate forecasts are simply assumed to be given. The present research tested this assumption by first evaluating the forecast accuracy achievable with state-of-the-art energy forecasting techniques for individual households and then, assessing the effect of prediction errors on market outcomes in three different supply scenarios. The evaluation showed that, although a LASSO regression model is capable of achieving reasonably low forecasting errors, the costly settlement of prediction errors can offset and even surpass the savings brought to consumers by a blockchain-based LEM. This shows that, due to prediction errors, participation in LEMs may be uneconomical for consumers, and thus, has to be taken into consideration for pricing mechanisms in blockchain-based LEMs.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129824492","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}

引用次数: 18

Machine-Learning-Based Simulation for Estimating Parameters in Portfolio Optimization: Empirical Application to Soybean Variety Selection 基于机器学习的组合优化参数估计模拟:在大豆品种选择中的实证应用

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-06-01 DOI: 10.2139/ssrn.3412648

D. Sundaramoorthi, Lingxiu Dong

{"title":"Machine-Learning-Based Simulation for Estimating Parameters in Portfolio Optimization: Empirical Application to Soybean Variety Selection","authors":"D. Sundaramoorthi, Lingxiu Dong","doi":"10.2139/ssrn.3412648","DOIUrl":"https://doi.org/10.2139/ssrn.3412648","url":null,"abstract":"Many new seed varieties with traits desirable for different planting environments are developed every year and marketed to farmers. However, farmers lack decision support tools to utilize the vast amount of historical yield performance data to make informed seed variety selection decisions for their individual farms. An informed decision requires accurate estimation of yield performances of seed varieties on the targeted farmland and balancing trade-offs between the expected yield and the risk associated with the seed varieties selected to grow. For that purpose, this paper proposes an analytics framework that integrates machine-learning, simulation, and portfolio optimization to optimally select soybean varieties to grow at the target farm. Using a soybean seed testing dataset collected between 2008 and 2014 by Syngenta, an agribusiness, we choose a machine learning model, which simulates the yield performance of soybean varieties under different plausible weather scenarios at the target farm. The simulated yields are then used to estimate parameters in a portfolio optimization formulation that selects the optimal portfolio of seed varieties to grow at the target farm. Our analysis indicates that an average farmer will gain as much as $177,369 per year in revenue by utilizing the analytics framework. The methodology developed in this research can be applied to variety selection decisions for other crops and influences farming practice positively.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123025802","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}

引用次数: 4

The Climate Spread of Corporate and Sovereign Bonds 公司债券和主权债券的气候扩散

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-05-08 DOI: 10.2139/ssrn.3376218

S. Battiston, I. Monasterolo

{"title":"The Climate Spread of Corporate and Sovereign Bonds","authors":"S. Battiston, I. Monasterolo","doi":"10.2139/ssrn.3376218","DOIUrl":"https://doi.org/10.2139/ssrn.3376218","url":null,"abstract":"Aligning finance to sustainability requires metrics and methods to price forward-looking cli-mate risks and opportunities in financial contracts and in investors' portfolios. Traditionalapproaches to financial pricing cannot incorporate the nature of climate risks, i.e. deep uncertainty, non-linearity, complexity and endogeneity. To fill this gap, we develop a frameworkfor climate-financial risk assessment and management under uncertainty. We consider a riskaverse investor with an information set given by past market valuation, information on futureclimate economic shocks, and utility maximization based on the minimization of the ClimateValue at Risk (VaR) in presence of incomplete markets. We then consider a disorderly policy transition to 2°C scenarios that leads to unanticipated shocks in economic trajectories of fossil fuel and renewable energy sectors, estimated using Integrated Assessment Models. We model the shock transmission from the change in sectors' Gross Value Added to firms' profitability and to sovereign fiscal revenues. We then introduce the forward-looking climatepolicy shocks in sovereign bonds valuation introducing scenario- conditioned financial riskmetrics (Climate VaR, Climate Spread). We provide an application to OECD sovereignbonds of Austrian National Bank's portfolio. We find that investments' climate alignmentcan strengthen the sovereign fiscal and financial position by decreasing the climate spread. In contrast, misalignment can negatively affect countries' economic competitiveness and financial stability, and thus the performance of investors who own such bonds. Our analysissupports investors' portfolios risk management strategies in the low-carbon transition andand financial supervisors in the design of prudential risk measures.","PeriodicalId":292025,"journal":{"name":"Econometric Modeling: Commodity Markets eJournal","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127860134","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}

引用次数: 43

When Do Commodity Prices Matter for the Carry Trade? The Role of FX Liquidity 什么时候商品价格对套利交易有影响?外汇流动性的作用

Econometric Modeling: Commodity Markets eJournal Pub Date : 2019-04-16 DOI: 10.2139/ssrn.3379090

A. Jeanneret

引用次数: 1