摘要：
This paper proposes a novel hybrid forecast model to forecast crude oil price on considering the long memory, asymmetric, heavy-tail distribution, nonlinear and non-stationary characteristics of crude oil price. First, we use a signal de-noising method to reduce excessive noise significantly in the crude oil price. Then we employ empirical mode decomposition to transform the de-noised price into different intrinsic mode functions (IMFs). Finally, some complex long memory GARCH-M models are used to forecast different IMFs and a residual. Empirical results show that the proposed hybrid forecasting model WPD-EMD-ARMA-FIGARCH-M achieves significant effect during periods of extreme incidents. The robustness test shows that this hybrid model is superior to traditional models. (C) 2020 Elsevier B.V. All rights reserved.
摘要：
With the rapid development of China's economy, the agricultural industry chain has a new mode of operation. The rise of big data technology can collect the relevant information of the agricultural industry chain in all aspects more rapidly, accurately and comprehensively, so that the agricultural production, logistics and information flow can be unified, so as to realize the optimization of the resource structure of the industrial chain, and the operation efficiency is higher. In this paper, the analysis method combined with big data was used to construct the industrial chain of ecological agriculture. The ecological agriculture industry in Wuwei was regarded as the specific research object, and a large amount of empirical data was collected by means of consulting literatures and field surveys. The input analysis and output analysis of the agricultural production in Wuwei were carried out and the original industrial chain model was evaluated, and the deficiency of the influence factors was improved. The agricultural industry chain was the developmental situation of a dynamic organization, which had important methodological significances. This paper attempted to put forward some suggestions for the rational development of the agricultural industry chain.
作者机构：
[Yue, Liu] Hunan Inst Technol, Sch Econ & Management, Dept Int Econ & Trade, Hengyang 421001, Peoples R China.;[Failler, Pierre] Univ Portsmouth, Portsmouth Business Sch, Econ & Finance Grp, Portsmouth PO1 3DE, Hants, England.;[Peng, Jiaying] Hunan Agr Univ, Sch Econ, Changsha 410128, Peoples R China.;[Zheng, Yuhang] Guangdong Univ Finance & Econ, Sch Finance, Guangzhou 510320, Peoples R China.;[Zheng, Yuhang] Guangdong Univ Finance & Econ, Collaborat Innovat Dev Ctr Pearl River Delta Sci, Guangzhou 510320, Peoples R China.
通讯机构：
Economics and Finance Group, Portsmouth Business School, University of Portsmouth, Portsmouth, United Kingdom
关键词：
Economic policy uncertainty;Exchange rate;Oil price;TVP-VAR model
摘要：
This paper examines the dynamic relationship between crude oil prices and the U.S. exchange rate within the structural break detection context. Based on monthly data from January 1996 to April 2019, this paper identifies structural breaks in movements of oil price and examines the dynamic relationship between crude oil prices and the U.S. exchange rate movement by introducing the economic policy uncertainty and using the TVP-VAR (Time-Varying Parameter-Vector Auto Regression ) model. Empirical results indicate that shocks to crude oil prices have immediate and short-term impacts on movements in the exchange rate which are emphasized during the confidence intervals of structural breaks. Oil price shocks and economic policy uncertainty are interrelated and influence movements in the U.S. exchange rate. Since the U.S. dollar is the main currency of the international oil market and the U.S. has become a major exporter of crude oil, the transmission of price shocks to the U.S. exchange rate becomes complicated. In most cases, the relationship between oil prices and the U.S. exchange rate movements is negative.
期刊：
Agro Food Industry Hi-Tech,2017年28(3):2015-2020 ISSN：1722-6996
通讯作者：
Fang, Li
作者机构：
[Fang, Li] Changsha Univ, Coll English Dept, Changsha 410022, Hunan, Peoples R China.;[Fang, Li] Hunan Agr Univ, Coll Econ, Changsha 410128, Hunan, Peoples R China.
通讯机构：
[Fang, Li] Changsha Univ, Coll English Dept, Changsha 410022, Hunan, Peoples R China.;[Fang, Li] Hunan Agr Univ, Coll Econ, Changsha 410128, Hunan, Peoples R China.
关键词：
English network language;linguistic economics;economic value
摘要：
With the continuous development of economy and the integration of the Internet information network, the network language is playing an increasingly important role in people's lives. Since the economists put forward the linguistic economics in 1965, the economic value of language has become the consensus of the people of all countries, and now it is a new and hot topic to study and analyze the English network language. In this paper, a system for evaluating the economic value of English network language was designed. Analytic hierarchy process (AHP) and qualitative methods were used, and the economic value of network language was quantified.
摘要：
This paper develops an incomplete-markets model of investment timing by a firm's controlling shareholder, who is exposed to idiosyncratic risk and pursues private benefits at the expense of outside shareholders. We show that the timing of investment selected by the controlling shareholder reflects a tradeoff between his incentives to pursue private benefits and the costs of nondiversification. The firm may overinvest or underinvest depending on the magnitude of the agency conflicts. Moreover, our theoretical model predicts that increasing the cash flow ownership of the controlling shareholder will decease the total social welfare, which provides novel testable empirical implications for investment. (C) 2017 Elsevier B.V. All rights reserved.
通讯机构：
School of Economics, Hunan Agricultural University, Changsha, China
关键词：
Quantile dependence;Directional predictability;Cross-quantilogram;Oil volatility;Stock returns;BRICS countries
摘要：
While numerous studies have investigated the relationship between oil volatility and stock returns, it is surprising that little research has examined the quantile dependence and directional predictability from oil volatility to stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries. We address this issue by using the cross-quantilogram model proposed by Han et al. (2016). The empirical results show that, overall, oil volatility has a directional predictability for the stock returns in BRICS countries. When the oil volatility is in a low quantile (lower than its 0.1 quantiles), it is less likely to show either a large loss or a large gain in the stock market. In contrast, there is an increased likelihood of either large loss or a large gain in the stock market when the oil volatility is in a high quantile (higher than its 0.9 quantiles). The directional predictability from the oil volatility to stock returns depends on the net position of oil imports and exports of these BRICS countries in the oil market. The net oil exporters (Russia and Brazil) are less likely to have large gains and large losses in the stock market than are the net oil importers (India, China, and South Africa) when the oil volatility is in a low quantile. The net oil exporters are more likely to have large gains and large losses than are the net oil importers when the oil volatility is in a high quantile. The results are robust to change in the variable of oil volatility and the sample interval.
摘要：
Economics and finance are extremely complex nonlinear systems involving human subjects with many subjective factors. There are numerous attribute properties that cannot be described by the theory of integer-order calculus; so it is necessary to theoretically study the internal complexity of the economic and financial system using the method of bifurcation and chaos of fractional nonlinear dynamics. Fractional calculus can more accurately describe the existence characteristics of complex physical, financial or medical systems, and can truly reflect the actual state properties of these systems; therefore the application of fractional order in chaotic systems has great significance to study the mathematical analysis of nonlinear dynamic systems, and the use of fractional calculus theory to model the complexity evolution of fractional chaotic financial systems has attracted more and more scholars' attention. On the basis of summarizing and analyzing previous studies, this paper qualitatively analyzes the stability of equilibrium solution of fractional-order chaotic financial system, and explores the complexity evolution law of the financial system near the equilibrium point and the occurring conditions of asymptotic chaotic state near this equilibrium point, and simulate the complexity evolution of chaotic financial systems using the Admas-Bashforth-Moulton finite difference method for mapping, phase diagram and time series graph. The research results of this paper provide a reference for government to formulate relevant economic policies, decision-making or further research on the complexity evolution of fractional-order chaotic financial systems. (C) 2019 Elsevier Ltd. All rights reserved.
通讯机构：
School of Finance, Nanjing Audit University, Nanjing, China
关键词：
Brent crude oil market and London gold market;Stock markets (Chinese and European);CEEMDAN approach;Fine to coarse algorithm;Linear and nonlinear granger causality;Long memory and asymmetry GARCH effect;Quantile granger
摘要：
In this paper, we investigate the risk contagion among the Brent crude oil market, London gold market and stock markets (Chinese and European). In the paper, we employ the CEEMDAN method and fine to coarse algorithms to decompose these market returns into different components. Then, we use the Granger causality test to assess the risk contagion between these markets under different time and frequency components. The results show that single direction risk contagion running from the Brent crude oil market and the London gold market to the stock markets (Chinese and European) is found in irregular events. Similarly, irregular events can also cause the single direction risk contagion to run from European stock markets to the Brent crude oil market. However, bidirectional risk contagion among the Brent crude oil market, London gold market and stock markets (Chinese and European) are found in extreme events. Second, bidirectional risk contagion among the Brent crude oil market, London gold market and European stock markets is demonstrated in irregular events. In addition, there exists only unidirectional risk contagion running from stock markets (Chinese and European) to the Brent crude oil market under extreme events. Third, long memory and asymmetry GARCH effects with fat tail distributions are significant in assessing risk contagion between the London gold market and European stock markets under extreme events. Finally, nonlinear Granger causality running from crude oil markets to the stock markets (Chinese and European) is found in bull and bearish markets. In addition, nonlinear Granger causality running from Chinese stock markets to the gold market and from the gold market to the European stock markets is found in extreme bearish markets.
期刊：
Finance Research Letters,2019年29:245-254 ISSN：1544-6123
通讯作者：
Zhou, Z.
作者机构：
[Lin Ling] Hunan Agr Univ, Sch Econ, Changsha 410128, Hunan, Peoples R China.;[Liu Qing; Zhou Zhongbao; Jiang Yong] Hunan Univ, Sch Business Adm, Changsha 410082, Hunan, Peoples R China.
通讯机构：
School of Business Administration, Hunan University, Changsha, China
关键词：
Risk transmission;Hedging strategy;Regime switching;Long memory and asymmetry GARCH;Natural gas market;Chinese and America stock markets
摘要：
This paper investigates the risk transmission and hedging strategies between natural gas market and stock markets. We propose a multivariate GARCH framework which combines regime switching with multivariate long memory and asymmetry GARCH. Results show that there exists granger causality from natural gas market to the Chinese stock markets in crisis regime. Dynamic correlations between these markets are vulnerable to extreme weather, government policies and financial crisis. When looking at the optimal design of a natural gas-stock portfolio, we find that investors in stock markets should have more stocks than natural gas asset in order to reduce their portfolio risk.
摘要：
This paper investigates the impact of relative economic policy uncertainty between China and the United States (the Sino-US EPU ratio) on the Chinese exchange rate volatility by employing a GARCH-MIDAS model. Moreover, we compare the out-of-sample volatility forecasting performance of the GARCH-MIDAS model with that of traditional GARCH-type models. The empirical results suggest that: (i) the Sino-US EPU ratio has a positive impact on the long-term volatility of the Chinese exchange rate, (ii) the GARCH-MIDAS model performs better than the traditional GARCH-type models.
摘要：
Research on manufacturing scheduling has historically emphasized production efficiency. With rising environmental consciousness, manufacturing companies are paying increasing attention to energy efficiency on the shop floor. Manufacturing consumes a large amount of electricity globally. The mismatch between electric supply and demand has been a huge problem, which even becomes worse when renewable energy becomes more popular. The time-of-use (TOU) pricing policy is a widely used demand response (DR) approach, trying to align demand to supply. This paper considers energy-efficient scheduling of a single batch processing machine with non-identical job sizes and release times under a TOU electric tariff so as to simultaneously minimize total electricity cost, a criterion of environmental and energy sustainability, and makespan, a criterion of productivity. A mathematical formulation is developed to optimize electricity cost and makespan. Due to computational complexity, a hybrid multi-objective meta-heuristic algorithm is developed to find the Pareto front. Two constructive heuristics are presented to group jobs into batches. Two different approaches are presented to improve total electricity costs. The performance of the proposed model and algorithms is evaluated through extensive numerical experiments. Production managers can use the model and algorithms provided in this work to make a trade-off between productivity and sustainability. (C) 2020 Elsevier Ltd. All rights reserved.
