Trading Program Research Articles

Robust multiperiod inventory model considering trade-in program and refurbishment service: Implications to emerging markets

We propose a closed-loop supply chain system that incorporates a trade-in program and refurbishment service simultaneously. Through the trade-in program, retailers collect used old-generation products from customers and provide them with new-generation products at a discount price. It helps to acquire the additional products required for the refurbishment service. The proposed integrated system could be useful to retailers selling the smartphone which has a high potential in emerging markets. We approximate the multistage stochastic optimization model to the robust counterpart which features a second-order cone program. Computational results provide managerial insights that could be beneficial to the retailer.

Optimization of pricing and quality choice with the coexistence of secondary market and trade-in program

Presently, many firms are implementing trade-in programs to promote the sale of new products and collect used products. Furthermore, firms sell the used products to the secondary market to avoid the cannibalization problem between new and remanufactured products. This paper aims to explore how the coexistence of the secondary market and trade-in program affects firms’ decisions on quality choice, prices, and trade-in rebate. To this end, we propose a stylized model that captures the features of the secondary market and trade-in program. Further, we consider three models, namely no trade-in program and secondary market (i.e., benchmark case), trade-in program without secondary market and trade-in program with secondary market. We obtain the optimal outcomes under each case via optimization theory. By comparing to the benchmark case, we find that the firm prefers to reduce product quality level and selling price when the trade-in program exists solely. However, if the trade-in program exists together with the secondary market, the firm prefers to increase product quality when the maximal customers’ willingness to pay in the secondary market is high. Otherwise, the firm prefers to lower product quality.

Transfer of development rights, farmland preservation, and economic growth: a case study of Chongqing’s land quotas trading program

The dilemma between preserving farmland and urbanization has attracted many policymakers’ attention. One sound solution that has been practiced in several developed countries is the “transfer of development rights” (TDR). This study examines a specific TDR program in China—the Chongqing Land Quotas Trading program. We use a synthetic control method on the 2001–2014 statistics of 57 prefectures to quantitatively assess the program’s effect on farmland preservation and economic growth. A mixed method, including both satellite image analysis and qualitative interviews, was also used to obtain some intuitive evidence to understand the mechanism of this program. We find that the Chongqing TDR program has substantially reduced the loss of farmland and played a significant role in stimulating economic growth. We argue that the use of TDR might effectively address the farmland preservation and urbanization dilemma in China.

Joint Advertisement and Trade-In Marketing Strategy in Closed-Loop Supply Chain

With environmental problems becoming severe, many firms, including HP, Huawei, and Apple are simultaneously implementing trade-in programs and advertising to stimulate market demand. Offering trade-in service by the manufacturer is a method of price discrimination by providing replacement consumers with a rebate when they purchase new products. With the recycled, used products, the manufacturer can benefit through a strict series—via a remanufacturing process. Although numerous literatures have investigated the pricing strategy and advertising decisions in the closed-loop supply chain (CLSC), to the best of our knowledge, there is little research that analyzes and compares the economic and social performance of these two marketing strategies. To fill this gap, we establish two supply chain models with two periods, namely, an advertisement model and a joint model, while the equilibrium purchasing behavior of the replacement consumers can be characterized under three conditions: (1) all of the replacement consumers purchasing new products (ATA); (2) partial replacement consumers purchasing (PTA); (3) no replacement consumers purchasing (NTA). These three conditions are decided by the numerous relationships of the parameters. Solving the optimal decisions of the manufacturer in both models, the critical value in the joint model is higher in the advertisement model, which indicates that developing the trade-in program can enhance the robustness of the business model. Furthermore, through numerical example, we find that the market demand in the joint model is higher than in the advertisement model, and the cost of marketing strategy in the joint model is lower in the advertisement model, which means that the efficiency of the marketing strategy is higher than the single marketing strategy. As a result, comparing the economic and social performance between the two models, we conclude that the advertisement elasticity of the market demand is the key factor of the manufacturer’s profits and total social welfare.

Impact of the Saitama Prefecture Target-Setting Emissions Trading Program on the adoption of low-carbon technology

This paper investigates the impacts of the Target-Setting Emissions Trading (TSET) Program launched by Saitama Prefecture in Japan in 2011 on the adoption of low-carbon technology. Using facility-level data on the manufacturing sector, the causal relationship between implementation of the program and investment in high-efficiency equipment is estimated. The results show that the TSET Program promoted the adoption of high-efficiency machines and devices for the first three years of the second compliance period, whereas the program did not spur investments in high-efficiency equipment during the first compliance period. These results suggest that the manufacturing facilities may have adopted relatively cheaper emissions reduction plans in the first compliance period such as improvements to equipment they already owned, whereas in the second compliance period, when the emissions targets became stricter, they allocated money and resources to introduce high-efficiency equipment. These findings indicate that the TSET Program succeeded in encouraging emissions reduction efforts by facilities in the manufacturing sector covered by the scheme, even though the program lacks penalties for noncompliance.

Does Reducing Air Pollution Make Inventors More Innovative? Evidence from the NOx Budget Program

Using the NOx budget trading program (NBP) as a quasi-natural experiment, we examine whether a reduction in air pollution enhances inventor risk-taking, thus making inventors more innovative. We find that inventors located in NBP participating states produce more patents after the introduction of the NBP. These patents also receive more forward citations and have higher economic value. The effect of the NBP is larger for less experienced inventors and inventors living in high-pollution areas. Further, inventors located in NBP participating states engage more in experimental innovation and less in specialization innovation after the NBP, which confirms the risk-taking channel.

The optimal pricing for a trade-in program in remanufacturing supply chain

We develop a model to investigate the optimal pricing for a trade-in program in remanufacturing supply chain. Customer choice behavior is introduced, and the generalized Nash bargaining framework is adopted to model the sale agent’s trade-in program in the business-to-business (B2B) market. Moreover, we analyze the impacts of bargaining power of customers on equilibrium decisions and firm profits.

Exploring the Impact of Magnitude- and Direction-based Loss Function on the Profitability using Predicted Prices from Deep Learning

Researches on predicting prices (as time series) from deep learning models usually use a magnitude-based error measurement (such as ). However, in trading, the error in the predicted direction could affect trading results much more than the magnitude error. Few works consider the impact of ill-predicted trading direction as part of the error measurement. In this work, we first find parameter sets of LSTM and TCN models with low magnitude-based error measurement, and then calculate the profitability using program trading. Relationships between profitability and error measurements are analyzed. We also propose a new loss function considering both directional and magnitude error for previous models for re-evaluation. Three commodities are tested: gold, soybean, and crude oil (from GLOBEX). Our findings are: with given parameter sets, if merchandise (gold and soybean) is of low averaged magnitude error, then its profitability is more stable. The proposed loss function can further improve profitability. If it is of larger magnitude error (crude oil), then its profitability is unstable, and the proposed loss function cannot improve nor stabilize the profitability. Furthermore, the relationship between profitability and error measurement for models of LSTM and TCN with or without customized loss function is not, as commonly believed, highly positively correlated (i.e., the more precise the predicted value, the more trading profit) since the correlation coefficients are rarely higher than 0.5 in all our experiments. However, the customized loss functions perform better in TCN than in LSTM.

The effect of air pollution on criminal activities: Evidence from the NOx Budget Trading Program

This paper examines the impacts of air pollution on criminal activities by exploiting three dimensions of variations observed under a rich quasi-experiment: the NOx Budget Trading Program. This program has been well documented to decrease air pollution concentrations in participating states. Employing a triple-difference estimator, we find evidence showing that the program significantly reduced violent and property crimes in participating states by roughly 3.7% and 2.9%, respectively. Instrumental variable estimates suggest that lowering air pollution may play an important role in reducing criminal behaviors.

Climate Policy Risk and Corporate Capital Structure: Evidence from the NOx Budget Trading Program

We find that manufacturing firms adopt more conservative capital structures in response to the NOx Budget Trading Program (NBP) of 2004, a regional cap-and-trade program aimed at mitigating the NOx emissions of power plants in 11 midwestern and southeastern states in the United States. Our further analysis demonstrates that, because the NBP induces an electricity price shock, it affects manufacturers’ financial decisions by raising their operating leverage and distress risk. We also find that firms respond to the NBP’s adoption heterogeneously: they adjust their financial leverage more dramatically when facing greater electricity intensity, financial-distress threats, or competitive pressure. In addition, firms adapt not only capital structure but also other financial policies in response to the regulation. Overall, our study shows that climate policy risk constitutes an essential consideration in firm financial decisions. It also highlights potential unintended consequences of policy responses to climate change for the corporate sector.

A Neural Network Based Prediction System of Distributed Generation for the Management of Microgrids

In the modern scenario of smart-grids, the concept of virtual power plant (VPP) is undoubtedly a cornerstone for the smooth integration of renewable energy sources into existing energy systems with a high penetration level. A VPP is the aggregation of decentralized medium-scale power sources, including photovoltaic and wind power plants, combined heat and power units, as well as demand-responsive loads and storage systems, with a twofold objective. On one hand, VPP relieves the stability and dispatchability problems on the external smart grid since it can be operated on an individual basis, appearing as a single system on the whole. On the other hand, VPP improves flexibility coming from all the networked units and enable traders to enhance forecasting and trading programs of renewable energies. This paper proposes a novel distributed decentralized prediction method for the management of VPPs. The novelty of the proposed technique is to effectively combine the concepts of neural networks and machine learning with a distributed architecture that is suitable for the aggregation purposes of the VPP.

The active construction of passive investors: roboadvisors and algorithmic ‘low-finance’

Abstract How does algorithmic finance operate in society as it crosses the threshold into the hands of lay investors? This article builds on original ethnographic research into a new class of algorithmic trading programs known as ‘roboadvisors’—inexpensive, automated, digital financial platforms that enable ordinary people to invest very small minimum amounts and that rely to a large extent on passive, index strategies that follow the prescripts of Modern Portfolio Theory. The main argument of the article is that roboadvisors, representing an ethos of ‘low-finance’, are actively constructing passive investors by disciplining them through technologies that embody canonical models of financial economics. Roboadvisors and their algorithms reconfigure their users and objectify them through automating investment decisions and enforcing a principle of ‘don’t do’ vis-à-vis the market. Implications that bear on agency, market structure and regulatory regimes are discussed.

Programs trades and trade regulation: An evidence of the Korean securities market

AbstractThis study addresses the effects of program trade regulation during large market moves. To address this issue, we analyze the effect of sidecars (halts that only affect program trades) on trade imbalance using Korean intraday data. We find that sidecars, as currently designed to halt all program trades, are not effective at controlling trade imbalance around volatile markets. Resolution of trade imbalance is more effective when program trade is unrestricted. Program trade, at least a subset, provides liquidity when it is at a premium. We conclude that current sidecars should be more carefully crafted as some program trades are market stabilizing.

Organizational and economic principles of modernization of technical means as a basis of reproduction of material and technical base of agricultural enterprises

Introduction. Technical potential is the key to innovative management and economic growth of agricultural production. In the conditions of poor quality and reliability of the machines, the dealer service of the manufacturing plants is poorly developed, the main task of which is the elimination of defects in machinery. In this regard, the task of modernizing the technical means of farms in the corporate sector of the agrarian economy arises. Methods. The following methods and techniques are used for realization of the set tasks: monographic, statistical groups, correlation and regression analysis, graphic – for comprehensive study of the current state of agricultural production and to determine the factors influencing its technical modernization. Results. In the conditions of decrease of technical support of agricultural producers of primary importance becomes the support in the working condition of the machine and tractor park, timely repair and restoration of technical resources, which implies the development of a system of complex engineering service. In turn, it became necessary to create a system of information and consulting and staffing for agricultural producers. Discussion. One of the effective ways of modernizing the technical base of agricultural producers involves the use of the program Trade in. This program is a system of offsetting, in which used equipment can be used as a means of partial payment for new equipment. The equipment, which was used and purchased from customers under the scheme Trade in, undergoes pre-sales training with the replacement of all defective components and assemblies, then it is offered for sale. Keywords: agricultural enterprise, modernization, repair, agricultural machinery, technical base.

Mutual information based stock networks and portfolio selection for intraday traders using high frequency data: An Indian market case study.

In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network based on mutual information and study their topology. The year 2014 saw the conduct of general elections in India and the data allows us to explore their impact on aspects of the network, such as the scale-free property and sectorial clusters. Second, having established the presence of non-linear relations, we would like to be able to exploit them. Previous authors have suggested that peripheral stocks in the network would make good proxies for the Markowitz portfolio but with a much smaller number of stocks. We show that peripheral stocks selected using mutual information perform significantly better than ones selected using correlation.

Benthic marine litter in shallow fishing grounds in the NW Mediterranean Sea

Fisheries are one of the main economic sectors affected by marine litter, which can damage gear, reduce catch, and require time to repair or clean nets. This study aims to evaluate the type and density of marine litter in two shallow fishing grounds in the NW Mediterranean Sea, both belonging to the Natura 2000 network. Moreover, it quantifies the fraction of marine litter within the total catch to help understand the potential influence of marine litter on fisheries. Two study areas were selected, one in the vicinity of urban populated areas and high navigational traffic and one in a rural site off an agricultural area. The urban area had more benthic marine litter (393 to 198 kg km−2) including clinker (residue from coal-burning steamships), fabric, plastics, and processed wood and accounting for up to 38% of the total catch. The rural area had far less marine litter (34–56 kg km−2), accounting for only 5% of the total catch. Marine litter may have potential negative effects on fisheries; thus we propose that government credit trading programs could be promoted to help recover litter from fishing catches, to reduce fishing costs and hazards to marine ecosystems.

Environmental regulation as a double-edged sword for housing markets: Evidence from the NOx Budget Trading Program

We investigate the effects of environmental regulations on housing markets using a quasi-experimental setting—the NOx Budget Trading Program (NBP). Hedonic theory predicts that house prices should rise as pollution levels decrease. However, environmental regulations may also affect labor markets, and thus housing demand. Employing a difference-in-differences framework, we find that house prices shifted up in the regulated areas with low manufacturing intensity, whereas in the areas with high manufacturing intensity, housing markets were weakened. We also find that in high-manufacturing-intensity areas, loan application volume declined, rejection rate augmented, and the probability of loan default increased.

Key challenges for China's carbon emissions trading program

AbstractChina's national carbon emissions trading program is expected to become the world's largest carbon market and is critical for achieving China's domestic mitigation goals. But China's trading program is likely to face significant challenges, due to its large scale and high complexity. First, the accuracy and credibility of China's emissions data have been widely criticized. There are significant inconsistencies between the national and provincial emissions inventories, and the facility‐level data are even less satisfying. Institutional capacities related to the carbon market need to be significantly enhanced to strengthen monitoring, reporting, and verifying capabilities. Second, compared to emissions trading programs in other parts of the world, China's program is likely to face greater market volatility, due to the country's economic structural transition from a manufacturing‐based to a service‐based economy. Wise cap‐setting and allowance allocation methods and proper price containment mechanisms are needed to maintain market stability. And third, China is a market economy with many features of a central planning system, particularly in the energy sector. Large state‐owned enterprises (SOEs) do not act as profit‐maximizing entities, and their behaviors could undermine the efficiency of the cap‐and‐trade program. To address these challenges, we provide a series of policy recommendations, including capacity building from central to local levels, wise selection of allowance allocation methods to cope with changing economic realities, and deepening market‐oriented reforms in energy sectors and SOEs.This article is categorized under: The Carbon Economy and Climate Mitigation > Policies, Instruments, Lifestyles, Behavior

How does emission trading reduce China's carbon intensity? An exploration using a decomposition and difference-in-differences approach

Emission trading is a market-driven method to more quickly reduce carbon intensity, and has been widely used in countries with significant carbon emissions. In 2013, the Chinese government established pilot carbon emission trading programs in seven provinces. However, there is incomplete research on the effect and influencing channels of emission trading on carbon intensity reduction. To explore these problems, this study conducted an empirical analysis, using a decomposition and difference-in-differences approach. The main conclusions are as follows: (1) Overall, China's emission trading pilots have driven a significant decline in the carbon intensity, resulting in an average annual decline of approximately 0.026 tons/10,000 yuan in the pilot provinces. (2) In the sample period, emission trading pilots had a sustained and stable effect on carbon intensity with no time lag. (3) Emission trading pilots reduce the carbon intensity by adjusting the industrial structure. In contrast, energy structure and energy intensity channels have not yet been realized.

A method for emission allowances allocation in air transportation systems from a system-of-systems perspective

Market-based mechanisms, especially emission trading schemes, are proposed as a means to control system-wide aviation emissions. Although auctioning has gained some recent popularity, free allocation of emission allowances is still favored by many to incentivize airlines’ participation in the outset of an emission trading program. However, current methods for free allocation – grandfathering method and benchmarking method – have their limitations, such as placing heavy workload on regulators and a lack of transparency and flexibility. To overcome some of the limitations, this paper proposes a multi-stakeholder dynamic optimization method from a system-of-systems perspective. The method delegates part of the regulators’ responsibility to airlines, and grants airlines flexibility to plan, negotiate, and request for emission allowances. The inclusion of the regulators’ allowance allocation decision-making and airlines’ fleet allocation decision-making ensures a holistic understanding of the problem. Specifically, the method combines transfer contract coordination mechanism and approximate dynamic programming to coordinate the allowance consumption between the participants. We apply the method to a ten-route air transportation network where two representative airlines compete for the allowances. The results demonstrate that the total network-wise profit from each airline’s independent decisions can approach the globally efficient solution in an ideal centralized case without violating the emission constraint.