Trading Program Research Articles

Does implementing trade-in and green technology together benefit the environment?

In modern manufacturing operations, green technologies are becoming increasingly popular. Meanwhile, trade-in programs are widely implemented to boost sales and enhance product recycling, which would benefit the environment. It is widely observed that many companies implement the green technology (GT) and trade-in program together. However, whether this act is always beneficial to the environment is unclear. We hence build analytical models to address this issue. To conduct a comprehensive study, we follow the real-world practices and examine both the retailer collects (R-collect) and manufacturer collects (M-collect) scenarios in a supply chain. Our results show that the “R-collect scheme with GT” leads to the highest levels of supply chain profit and social welfare but more emissions may be generated. Besides, implementing GT does not always benefit the environment in both R-collect and M-collect schemes. Considering from the environment perspective, we interestingly show that governments should advocate the “M-collect with GT” and “R-collect without GT” schemes. Correspondingly, to motivate both the supply chain and consumers to accept the advocated strategies, we characterize the carbon tax and subsidy based “carrot-and-stick” policy. We further show in the extended analyses that our main results hold under competition, when the emission abatement cost takes different analytical forms, and when consumers are environmentally conscious.

Enhancing Efficacy of Water Quality Trading with Automation: A Case Study in Virginia’s Nutrient Trading Program

AbstractThe complexity of water quality trading (WQT) policy can lead to the promulgation of regulations that are challenging to comply with and to enforce. As a result, transaction costs may be high and administrators have limited ability to monitor the program outcomes. These concerns can be alleviated in part through increased automation of trading compliance procedures. We present a case study of a pilot system designed for the Virginia Department of Transportation that automates compliance and streamlines brokering processes that are a part of the Virginia nonpoint source WQT program. Outcomes of this work reveal opportunities and challenges for implementing automated systems in WQT and suggest a framework for developing automated programs. We conclude that use of automated procedures to facilitate compliance with WQT rules can help identify gaps in data reporting and availability, amend inconsistency in rule interpretation, and reduce transaction costs for credit purchasers by enabling efficient analysis of trading opportunities. Persistent limitations to automation exist, including lack of standardized, machine accessible, and open data sources. Potential long‐term benefits of automating WQT processes include minimizing transaction costs, enabling new environmental data collection and policy analysis, and ultimately yielding improved WQT program efficacy and water resources outcomes.

Collaborative Rebate Strategy of Business-to-Customer Platforms Considering Recycling and Trade-Ins Simultaneously

B2C (business to customer) platforms like JD.com and Suning.com often cooperate with professional recycling companies, and implement recycling programs and trade-in programs simultaneously, especially for electronic products. The former means that platforms recycle old products from customers with cash, whereas the latter means that platforms allow customers to trade in old products for new ones. Under this background, we discuss how to develop the optimal rebate strategy for B2C platforms based on the market recovery price of old products, and give the optimal rebate prices and feasible conditions of single-rebate, dual-rebate, and none-rebate strategies. The results show that the single-recycling rebate strategy is dominant when the residual value of old products is low, and when the residual value of old products is high, platforms should choose in turn the single-trade-in rebate strategy, dual-rebate strategy, single-recycling rebate strategy, and non-rebate strategy with the increase in the cost of new products. In order to obtain higher profits, B2C platforms should provide appropriate rebates to better coordinate the recycling program and the trade-in program on the basis of the market recovery price, the residual value, and the durability of old products as well as the cost, the selling price, and the upgrade range of new products.

A stochastic block model approach for the analysis of multilevel networks: An application to the sociology of organizations

A multilevel network is defined as the junction of two interaction networks, one level representing the interactions between individuals and the other the interactions between organizations. The levels are linked by an affiliation relationship, each individual belonging to a unique organization. A new Stochastic Block Model is proposed as a unified probabilistic framework tailored for multilevel networks. This model contains latent blocks accounting for heterogeneity in the patterns of connection within each level and introducing dependencies between the levels. The sought connection patterns are not specified a priori which makes this approach flexible. Variational methods are used for the model inference and an Integrated Classified Likelihood criterion is developed for choosing the number of blocks and also for deciding whether the two levels are dependent or not. A comprehensive simulation study exhibits the benefit of considering this approach, illustrates the robustness of the clustering and highlights the reliability of the criterion used for model selection. This approach is applied on a sociological dataset collected during a television program trade fair, the inter-organizational level being the economic network between companies and the inter-individual level being the informal network between their representatives. It brings a synthetic representation of the two networks unraveling their intertwined structure and confirms the coopetition at stake.

Predicting the Existence and Prevalence of the US Water Quality Trading Markets

Water quality trading (WQT) programs aim to efficiently reduce pollution through market-based incentives. However, WQT performance is uneven; while several programs have found frequent use, many experience operational barriers and low trading activity. What factors are associated with WQT existence, prevalence, and operational stage? In this paper, we present and analyze the most complete database of WQT programs in the United States (147 programs/policies), detailing market designs, trading mechanisms, traded pollutants, and segmented geographies in 355 distinct markets. We use hurdle models (joint binary and count regressions) to evaluate markets in concert with demographic, political, and environmental covariates. We find that only one half of markets become operational, new market establishment has declined since 2013, and market existence and prevalence has nuanced relationships with local political ideology, urban infrastructure, waterway and waterbody extents, regulated environmental impacts, and historic waterway impairment. Our findings suggest opportunities for better projecting program need and targeting program funding.

Unfairly Defiled: A Long Term Perspective on Portfolio Insurance as a Strategy for Limiting Portfolio Losses

The invention of portfolio insurance as a strategy for limiting portfolio losses was introduced in the early 1980s and gained spectacular popularity throughout the decade, attracting between $60 billion to $90 billion from institutional money managers. The method provided downside protection against a long equity position by synthetically replicating a long put option using equity futures during an era when exchange-traded equity options were not sufficiently liquid. Unfortunately, the strategy came to a catastrophic end on the “Black Monday” of October 19, 1987, when the president of the New York Stock Exchange shut down the nascent technology used by index arbitrage program trading groups. This caused significant mispricings between futures and cash markets, making the required synthetic put option replication trading impossible. The portfolio insurance strategy was declared a complete failure and never has since regained widespread popularity. Three decades later, modern markets now fully embrace program trading, and the likelihood that program trading would be shut down for any reason ever again seems impossible. This paper examines how portfolio insurance would have performed during the 1991 to 2020 time period, during which 3 major stock market crashes occurred and program trading was never shut down. The paper concludes that portfolio insurance received unjust blame for the 1987 crash and its abandonment since then has been irrational and unfortunate for those seeking long equity exposure with a cost-efficient strategy for limiting portfolio losses.

Imperfect Markets versus Imperfect Regulation: Reevaluation of an Emissions Trading Program: Reclaim

Imperfect Markets versus Imperfect Regulation: Reevaluation of an Emissions Trading Program: Reclaim

Generating and Optimizing Human-Readable Quantitative Program Trading Strategies through a Genetic Programming Framework

In this paper, we provide a highly flexible genetic programming framework for automatic generation and optimization of program trading strategies. We propose the input/output modules and their implementation methods, decoupled from the GP kernel, making it a priori-posteriori framework for trading practitioners. For human-readable purposes, we also give various empirical regularization methods, including NSGA-II multi-objective selection, as well as experimentally effective performance measures.

Agricultural land use management responses to a cap and trade regime for water quality in Lake Taupo catchment, New Zealand

Managing the effects on water quality of diffuse nitrogen pollution from agriculture is a widespread problem. Cap and Trade is a policy approach which limits nitrogen discharge (the cap) but provides flexibility in land management (using trading of nitrogen). Lake Taupo Nitrogen Trading Programme (LTNTP) in New Zealand is an exemplar case in applying nitrogen discharge limits at both catchment and farm levels, with positive environmental effects at catchment scale. Less is known about the effects on land management at farm scale. This article investigates the land use and farming practice outcomes of the LTNTP. Analysis used landscape biographies focused on different scales of effect. Results identify five pathways of change in the catchment. The dominant trajectory is lowered production with little on- farm reinvestment. Lack of viable alternative low nitrogen land-uses is a major constraint, and non-financial influences on farmer trading behaviour are also significant. To achieve its socio-economic goals, Cap and Trade policy requires farmer social values aligned to cap and trade, and research that supports practice innovation.

Does program trading contribute to excess comovement of stock returns?

Abstract Daily returns of stocks with high program trading comove more with each other but less with others. This significant comovement is disconnected with market movements and news of fundamentals and becomes stronger when market uncertainty is higher. It can be explained by neither the hypotheses of gradual information diffusion and liquidity provision nor the effects of quantitative trading signals, earnings announcements and index fund trading. Its non-fundamental nature is further demonstrated by the observation of program trading stimulating return reversals. Underlying this comovement is the high persistence of program trading. Our findings support the theory of habitat investing and demonstrate program trading creates a distinct source of excess return comovement.

Water Quality Trading in the Presence of Conservation Subsidies

Most studies of water quality trading analyze its cost-effectiveness in isolation from existing policies like conservation subsidy programs that pay farmers to use conservation practices. We investigate the interaction between trading and conservation subsidy programs using an integrated assessment model that combines farmer behavioral responses with a biophysical water quality model. Current subsidy program enrollees with comparative advantage in nitrogen abatement will sort into the trading program, worsening adverse selection. Actual increases in abatement from trading depend on incentivizing additional conservation practice acreage without inducing the conversion of vegetative cover to cropland.

Reducing power sector emissions under the 1990 Clean Air Act Amendments: A retrospective on 30 years of program development and implementation

The 1990 Clean Air Act Amendments (CAAA) launched a new era in environmental protection. New provisions created the innovative Acid Rain Program to curtail acid-rain-causing emissions from the electric power sector through an allowance trading program. Success implementing this new type of program led to its expanded use to achieve additional power plant emission reductions in support of the CAAA "Good Neighbor" requirements. As a result, air pollution and its environmental effects have decreased dramatically in the last 30 years. Implementation of power plant regulations under the acid rain and Good Neighbor provisions of the CAAA provides insights into the efficacy of legislative versus regulatory policy and holds valuable lessons for future environmental policy.

On the profitability and errors of predicted prices from deep learning via program trading

Researches on using deep learning models to predict prices usually take magnitude-based error measurements (such as R2) to measure the quality of learning models. Whether the forecasted prices for the models with the lowest error measurement can produce the most profit in actual trading is an issue with little research. In this study, we first find the parameter sets of LSTM and TCN models with low magnitude-based error and then use program trading to find out their profitability. The relationships between these profitability and error measurements are analyzed and studied on three commodities: 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. If it is of a more significant magnitude error (crude oil), then its profitability is unstable. A high positive correlation does not exist between the profitability and error measurement, and TCN outperforms LSTM in almost all our examples. Our research indicates that, in assessing the performance of deep learning, how to use the predicted values in applications and the application results could also be part of the quality measurement for the model assessment in the learning.

Metaphorization as a basis for transterminologization in the sphere od subject terminological nominations

The purpose of the article is to analyze the phenomenon of terminological metaphorization in the context of the hypothesis that this process is the cognitive basis for transsterminologization in the field of subject terminological nominations. The authors have selected such areas as programming and stock trading as an empirical base. To solve the research issues, the authors used the following general scientific and linguistic methods: descriptive method, method of definition analysis, method of continuous selection. The selection of 78 metaphorical terms of software development and exchange trading selected by the method of continuous selection from the total corpus of 2870 analyzed terms has served as the material for the research. The analysis has shown that a significant number of terms in the areas of programming and exchange trading are formed on the basis of metaphorical transfer. Subject terminological nominations designating certain fragments of the professional picture of the world has moved into this area without changing their form (simple terms) and served as the basis for the construction of derived term combinations based on a metaphorical transfer in new subject areas. The transition of a term to a different field of knowledge is conditioned by an analogy in the description of the phenomenon, or an analogy in the structure of the term, in its stylistic properties, in the functional and lexical meaning of the words that make up the term. The process of transsterminologization appears as a multi-stage and multidimensional phenomenon, which includes both the discursive use of the term, and its formal and semantic-stylistic characteristics. In general, the process of metaphorization plays an important role in term formation. The properties of metaphors suggest that the metaphor should be considered within the framework of an anthropocentric approach with the help of the cognitive-linguistic analysis.

Sustainable Oyster Aquaculture, Water Quality Improvement, and Ecosystem Service Value Potential in Maryland Chesapeake Bay

The United States has a $16 billion seafood deficit that the U.S. Department of Commerce and states are attempting to close by legislative policies, encouraging expansion of aquaculture in the United States. One of these policies, the 2011 National Shellfish Initiative, recognizes the benefits to water quality of cultivation of bivalve shellfish aquaculture in addition to the provision of seafood product. More recently, research addressing these policies has resulted in approval of the use of harvested oysters as a nutrient best management practice in the Chesapeake Bay region. Also discussed, but not yet fully implemented, is the inclusion of oyster growers in nutrient credit trading programs where economic compensation is provided to oyster growers for the nutrient removal ecosystem service that their oysters provide. This study used field sampling and a local-scale oyster production model to compare water quality, oyster production, and oyster associated nitrogen removal at two bottom and four water-column Maryland Chesapeake Bay oyster farms. Objectives were to highlight differences in water quality (i.e., oyster food), resultant differences in oyster production, and differences in estimated oyster-associated nutrient removal among farms. An avoided, or replacement, cost economic valuation analysis was performed to also compare the potential payment to the oyster growers for the nutrient removal service if they were included in a fully developed nutrient credit trading program. Production at the six sites varied from 1.78 to 25 metric tons of harvestable oysters acre–1 y–1. Oyster filtration–related N removal was estimated to be at a range of 28–457 kg N acre–1 y–1. The potential economic value of the total N removed by a farm was estimated to be at a range of $0.56 × 103–$12,446 × 103 y–1 among farm sites, depending on the alternative management measure used to assign the value.

Mistakes in Algorithmic Trading of Cryptocurrencies

AbstractHow should the doctrine of unilateral mistake apply when a programming error results in a buyer's algorithmic trading programme accepting an offer generated by the seller's trading programme to exchange cryptocurrencies at 250 times the current market rate? How should the knowledge element be adapted given that algorithmic trading necessarily means that the traders’ minds were not engaged at the moment the contract was formed? These novel issues came before the Singapore Court of Appeal in Quoine Pte Ltd v B2C2 Ltd. The decision further cautions customers of cryptocurrency exchanges not to assume that they have property rights in the cryptocurrencies held by the exchange and to examine carefully the nature of asset holding arrangement found in the documentation.

A method for predicting participation in a performance-based water quality trading program

One innovative way to solve water pollution problems is through water quality trading programs. However, participation levels and the price of offsets/credits tend to be low, which raises questions about the effectiveness of the policy. To offer more tools for policymakers, this paper provides a method for predicting participation in performance-based water quality trading programs, which accounts for field-level heterogeneity. We frame the economic problem in terms of derived demand, i.e., as a farmer Best Management Practice (BMP) input decision rather than a farmer output decision about supplying offsets. Specifically, this approach offers a straightforward way for farmers and policymakers to frame the decision to add a marginal unit of BMP—rather than a marginal unit of abatement—and take advantage of existing performance-based scientific models of nutrient loading. The paper uses actual market and field data in Maryland to illustrate the method and demonstrate the heterogeneity within and among BMPs. We also run sensitivity analyses to test the effects of different levels of farmer subsidies and transaction costs. The application results find, first, the extensive field-level heterogeneity in BMP abatement productivity. Second, the results show that far more farmers will adopt the high-abatement, medium-cost buffer BMPs than low-abatement, low-cost and high-abatement, high-cost BMPs.

Decarbonizing the Energy Mix: Carbon Pricing Implications and Path Forward

Debates are being had around the globe on how to reduce carbon emissions most efficiently and economically. Whether though a carbon tax or carbon trading program, or through wholesale market pricing schemes, carbon mitigation strategies for reducing carbon dioxide emissions in the electricity sector are gaining traction. With the aggressive fiscal and monetary policies and stimulus programs in place across the globe, attempting to soften a global economic downturn and speed the economic recovery from the COVID‐19 pandemic, governments and businesses alike are voicing concerns about pending large budget deficits and their potential to slow and prolong economy recovery. Governments around the world will be forced to reduce spending in coming years or find ways to raise revenues. The tax code is a very efficient and effective way to steer investments toward innovative and transformative capital projects, including projects that support decarbonization.

An Empirical Research of Futures Program Trading Based on RSI And CCI Indicators

Over the years, many scholars have conducted a wealth of empirical research on the effectiveness of technical indicator analysis in the financial market, and the conclusions are obviously different. Among them, two program trading models based on RSI and CCI indicators achieve an annual return rate of more than 180% in the empirical research of palm oil futures program trading, but the amount of data used in this study is too small, and the transaction cost is not considered. As the actual trading process has the characteristics that investors pay more attention to the sustainability of the model's profitability, and that investors’ trading varieties are diverse and with high transaction cost, this paper further verifies the sustainability and general applicability of these two models: using the closing price of 1-day and 30-minute K-line of 18 kinds of commodity futures in recent 10 years to investigate the changes of annual return rate, maximum withdrawal ratio etc. under different transaction costs and K-line cycles. The results show that the model’s profitability is time-varying, and the transaction cost has a greater influence on the rate of return of 30-minute K-lines than that of 1-day K-lines.

Cost benefits of forest restoration in a tropical grazing landscape: Thiaki rainforest restoration project

Global forest restoration is vital to mitigate climate change. Tropical forests are under the greatest threat from clearing while offering significant potential for restoration. Forest carbon credits through trading schemes have the potential to enable restoration, providing landholders with incentives to restore forests. Impediments to restoration are numerous, with one of the main ones being the unknown costs of forest restoration and uncertain returns from payment schemes, such as carbon trading programs. Many research and modeling papers on the potential of carbon markets to stimulate reforestation in agricultural landscapes rely on general estimates of reforestation. The reality, though, is that the benefits, returns, and break-even points of the reforestation costs and carbon price are highly sensitive to actual costs. Few papers actually investigate the real costs of farm-level restoration. Nearly all recent papers have used modeled scenarios in calculating Net Present Value (NPV), and so estimates of restoration cost and a return from carbon vary widely depending on modeled assumptions. Real data from a demonstration project in the Wet Tropics of Australia are provided in this paper. Three land use scenarios are compared: carbon only, cattle only, and a combination of carbon and cattle using on-ground data for restoration. Not surprisingly, scenarios of the highest carbon prices generate the highest net benefits in both carbon only and mixed carbon and cattle scenarios. A minimum carbon price of AUD$37 per ton of carbon dioxide equivalent is required to match income derived from cattle. The current policy environment that rewards the lowest cost abatement runs counter to Australia playing its role in the urgent need to limit global temperature rise to 2 degrees Celsius and preferably 1.5 degrees Celsius.