Market Order Research Articles

Order types and natural price change: Model and empirical study of the Chinese market

Order type plays an important role in algorithmic trading and is a key factor of price impact. In this paper, we propose a new framework for studying the discrete price change process, which focuses on the impacts of aggressive orders (market orders and aggressive limit orders) and cancelations. The price change process is driven by states and events of best quotes, and we define the event-based price change as the “natural price change” (NPC). Under the framework, we propose a heteroscedastic linear econometric model for the NPC to explore the impact of different types of orders on the price dynamics. To verify the usability of our model and explore the driving factors of price dynamics, we conduct a thorough empirical analysis for 786 large-tick stocks traded on the Shenzhen Stock Exchange. Empirical results statistically demonstrate that aggressive orders can introduce stronger impact on the NPC than cancelations. Meanwhile, splitting a big order into several small orders can lead to a larger NPC. Our framework can also be applied for the prediction of price change.

Dynamic nonlinear impacts of fossil energy on renewable energy stocks: A quantile perspective

In the global context of advocating low carbon and environmental protection, the renewable energy market has developed rapidly. As a means of combating global climate change, renewable energy has sparked interest from private investors as a new investment opportunity. In this paper, the quantile–quantile regression (QQ) method and the quantile causality (QC) method are used to study the influence relationship between the fossil energy futures market and the renewable energy stock market returns at different periods and under different market conditions. Results show that when the market is in a normal state, the fossil energy market and the renewable energy stock market have a weak positive relationship, and the positive impact is in the order of crude oil market > natural gas market > heating oil market. While in a bear market, the influence relationship would be abnormally strengthened or even reversed, showing extreme asymmetry. Furthermore, we find that the influence of the fossil energy market on the renewable energy market shows country heterogeneity, and the impact is more significant for developed countries. Some meaningful implications can be concluded for investors and policy-makers. Firstly, both investors and policy-makers should be more alert to the impact of the petrochemical energy market on the renewable energy market. Secondly, investors should be more alert to the downside market risks and further distinguish the different impacts of the natural gas market and the heating oil market on the renewable energy market when making portfolios. Thirdly, policymakers should take some targeted measures to buffer the negative impact of the renewable energy stock market in petrochemical energy when the market is bearish.

Squeezed out by the market, seeking strength in the network: Makeshift temples and the spatio‐affective logics of survival in Singapore

AbstractThis paper offers an understanding of the spatio‐affective workings of religious organisations – and the marketplaces they operate in and through – that go beyond capitalist logics. We do so by examining how makeshift temples representing various forms of ‘Chinese religion’ survive in Singapore. Capitalist logics fail to explain how such marginal and precarious religious organisations, which might be ‘squeezed out’ by the market, nonetheless manage to survive amid competition. Moreover, scarce attention has been paid to how religion as a social‐affective system might mediate the functioning of a religious market. This paper fills the lacuna by bringing an understanding of the affective resonances of Chinese religious practices into conversation with religious market theory. Rather than treating the market as a universal mechanism that moderates patterns of competition, growth, and decline, we focus instead on the spatio‐affective conditions through which a plurality of ‘actually existing’ religious marketplaces is made possible. We argue that makeshift temples in Singapore create an alternative order of the religious market that is organised by the affective economies and interpersonal relationships within which different ritual service providers compete, cohabit, and cooperate. These temples dismiss the spatio‐religious boundaries and regulation that define the neoliberal religious marketplace of Singapore by carving out sacred niches instead.

The ‘Optimistic Cruelty’ of Hayek’s Market Order: Neoliberalism, Pain and Social Selection

This article argues that cruelty, as a willingness to see or orchestrate the suffering of others, is not an unfortunate side-effect of neoliberal theories put into practice but is constitutive of the neoliberal project from its theoretical inception. Drawing on Lisa Duggan’s concept of ‘optimistic cruelty’ and treating the canonical texts of neoliberal economic theory as literary artefacts, the article develops this argument through a close reading of one of the central architects of the neoliberal project, the philosopher and economist Friedrich Hayek. The first part of the article examines how Hayek attempts to justify the brutality of the market order he imagines – the catallaxy – by arguing that this brutality is the natural consequence of the spontaneous evolutionary processes that move civilisation forward. The second part brings to the fore the eugenicist undertones that suffuse this vision, despite Hayek’s apparent rejection of Social Darwinism. I analyse how Hayek’s market order operates through a series of disciplinary and biopolitical technologies that use pain, frustration, punishment and stigmatisation to eliminate bad habits, practices and subjectivities. These cruel mechanisms enable the catallaxy to sort between productive and unproductive lives to ensure that available resources are directed towards the former – even if it means that the others might be left to die. As such, cruelty is an affective atmosphere that permeates the catallaxy.

Market versus limit orders of speculative high-frequency traders and price discovery

The Korea Composite Stock Price Index (KOSPI) 200 futures market is one of the largest and most liquid index derivatives markets globally. We utilize high-quality intraday data on KOSPI 200 futures and find that high-frequency traders’ (HFTs’) market orders contribute much more to price discovery than their limit orders, as opposed to the findings of Brogaard, Hendershott, and Riordan (2019) in the Canadian equity market. To explain this phenomenon, we suggest that HFTs in the KOSPI 200 futures market are more speculative traders rather than market makers, which makes market orders more informative.

Varieties of capitalism or variegated state capitalism? East Germany and Yugoslavia in comparative perspective

This essay is a contribution to comparative capitalism studies. We begin with a critique of the ‘Varieties of Capitalism’ school, before presenting the ‘variegated’ alternative. We note difficulties of both schools in characterising statist challengers to the dominant market order. The rise of China has made this a pressing issue, one that raises questions: Is China capitalist, and since when? And how should one analyse the communist world, which has since the 1920s represented a substantial swathe of the global economy? We next present an account of capitalism that explains étatiste variants as the product of late development, and the ‘communist’ economies as a state-capitalist model geared to catch-up industrialisation. This obliges us to consider how to account for their differences. In the second half we take up this challenge, via comparative analysis of two state-capitalist economies: the GDR (representing the orthodox Soviet model) and Yugoslavia (a maverick, market-friendly variant).

A deep learning approach to estimating fill probabilities in a limit order book

Deciding between the use of market orders and limit orders is an important question in practical optimal trading problems. A key ingredient in making this decision is understanding the uncertainty of the execution of a limit order, that is, the fill probability or the probability that an order will be executed within a certain time horizon. Equivalently, one can estimate the distribution of the time-to-fill. We propose a data-driven approach based on a recurrent neural network to estimate the distribution of time-to-fill for a limit order conditional on the current market conditions. Using a historical data set, we demonstrate the superiority of this approach to several benchmark techniques. This approach also leads to significant cost reductions while implementing a trading strategy in a prototypical trading problem.

Neoliberalism and its criticism by well-known defenders of the market order

The article critically examines the philosophy of neoliberalism. The author finds a wide destructive potential of neoliberalism for society and the state. The privatization promoted by the neoliberal ideology, the withdrawal of the state from the economic and social spheres, the rejection of protectionism have a negative impact on the development of the economy and on the standard of living of society. The economic freedom exalted by liberal philosophy makes it possible for speculative activity to develop. Ethical foundations are undermined by the substitution of personal responsibility for social protection. Liberal philosophy creates numerous myths, with the help of which an ideological defense of the growth of inequality and many other socially unacceptable results of the functioning of the liberal economic and political system is built. The article proves the mythological nature of liberal theses about free competition and equality of chances, about hard work as the key to success. The unreasonableness of pairing neoliberalism with democracy is postulated. Anti-democracy seems to be inherent in neoliberalism. The social disfunctionality of neoliberal reforms and their anti-national character are proved. The growth of inequality, the loss of sovereignty by states, the expansion of poverty, the development of the corporate sector (including socially irresponsible speculative capital) is a natural result of the functioning of the neoliberal project. This project is a methodology in the hands of transnational business for opening up the economies of sovereign states and enslaving societies. The growth of inequality in the world is associated with the policy of neoliberal reforms. The modern “postmodern economy” is characterized by virtualization, simulacrization, and financial speculation. In the article, the greatest attention is paid to the development of the speculative financial sector, which has become widespread due to the implementation of neoliberal policies. Financial speculation is considered as a socially harmful phenomenon, bearing its share of responsibility for the growth of inequality. Special attention in the article is paid to the recently expressed positions of analysts who have long stood on the ideological ground of defending neoliberalism. However, it is interesting that due to the disastrous results that this project brings to humanity, they have in some way changed their attitude towards it.

Opportunity Cost: An Economic Concept That May Improve the Functioning of Federal Milk Marketing Orders and the U.S. Dairy Industry

AbstractIn the United States, over 70% of milk production is priced under Federal Milk Marketing Orders (FMMOs). A primary purpose of FMMOs is to facilitate orderly allocation of milk as a limited, perishable resource among alternative uses. Fundamental to FMMOs are the regulatory prices applicable to milk used in cheese and whey (Class III), and nonfat dry milk and butter (Class IV). This work examines a novel milk pricing method based on the concept of opportunity cost for milk used in cheese and whey. This novel method may improve the functioning of FMMOs and the U.S. dairy industry.

The Development Status, Policy Demand and Rescue Measures of Small and Micro Enterprises in Wenzhou in the "Post-Epidemic Period"

In the post epidemic period, the lag “post-epidemic period” effect and diffusion effect on the economy after the epidemic still have a significant impact on small and micro enterprises. In order to support the development of small and micro enterprises, based on the questionnaire survey and analysis on small and micro enterprises in Wenzhou, this paper finds that there are two main factors affecting the recovery and development of small and micro enterprises in Wenzhou, which are market orders and funds. In terms of policy evaluation, small and micro enterprises have a good overall evaluation of the current support policies, but also put forward new requirements for the applicability, pertinence and timeliness of current support policies. In terms of policy demand, enterprises in different industries have both common policy needs and different policy needs. In the post epidemic period, enterprises have put forward common demands for expanding markets and improving core competitiveness. Finally, this paper puts forward targeted policy suggestions in the post epidemic period on how to improve the policy efficiency, provide efficient, accurate, timely and long-term government services, and promote the high-quality development of small and micro enterprises.

The importance of harmful and potentially harmful constituents in the implementation of the 2009 US Family Smoking Prevention and Tobacco Control Act.

Implementing the 2009 US Tobacco Control Act established a new infrastructure for tobacco and nicotine science. At its heart is the Food and Drug Administration (FDA) Center for Tobacco Products (CTP). A key challenge facing FDA CTP is determining whether nicotine products are "appropriate to the protection of the public health," and this is the central component of the Premarket Tobacco Application (PMTA) and Modified Risk Tobacco Application (MRTP) processes. CTP has granted such marketing orders for only a few products but has been consistent in its reasoning: the applicant demonstrated that the product(s) has low levels of Harmful and Potentially Harmful Constituents (HPHCs). By doing so, FDA has equated low levels of HPHCs with public health benefit. Other factors will be increasingly important, but the regulatory history indicates that no product will be granted a marketing order unless it has low levels of HPHCs. This science-driven regulatory approach has been possible due to the rapid evolution of the knowledge base and expansion of scientific human resources, including establishment of a robust CTP Office of Science to evaluate the extensive dossiers that manufacturers must submit. Companies therefore established internal regulatory science programs, and contract research organizations developed capabilities needed to support regulatory dossiers. This article focuses on the chemistry and toxicology part of the regulatory science process and also presents the industry side of the regulatory process by examining the experience of one company-Swedish Match-that was granted the first PMTA and MRTP marketing authorizations.

Financial Fraud Identification Based on Stacking Ensemble Learning Algorithm: Introducing MD&A Text Information

In recent years, there have been frequent incidents of financial fraud committed through various means. How to more efficiently identify financial fraud and maintain capital market order is a problem that scholars from all walks of life are discussing and urgently seeking to resolve. In this study, a financial fraud identification model is constructed based on the stacking ensemble learning algorithm, and the text of the management discussion and analysis (MD&A) chapter in annual reports is introduced based on financial and nonfinancial variables, using sentiment polarity, emotional tone, and text readability as text variables. The results show that when considering financial and nonfinancial variables and introducing text variables, the recognition effect of the stacking ensemble learning model constructed in this study is significantly better than the classification results of each single classifier model. In addition, the model recognition effect is better after adding text variables. Therefore, the model is expected to provide a new and more effective method of identifying financial fraud.

Analysis of the Public Opinion Evolution on the Normative Policies for the Live Streaming E-Commerce Industry Based on Online Comment Mining under COVID-19 Epidemic in China

Recent years have witnessed the intensive development of live streaming E-commerce, an emerging business mode. Although it contributes to economic growth, various forms of chaos show up and disturbs the market order. Therefore, from 1 July 2020, the official release of the first domestic document on live streaming E-commerce, the Code of Conduct for Online Live Streaming Marketing, to the end of the first half of 2021, China has witnessed so intensive release of relevant policies that are rare over the past years. Introducing these policies will inevitably attract the general public’s attention and discussions. Based on online comments, this paper uses the LDA models to extract topics from online comments related to live streaming E-commerce and identifies sentiment polarity and sentiment intensity by the analysis models of different emotion dictionaries to study policy implementation effects and the main topics of concern before and after the policy implementation. The analysis results show that people between the age of 20 and 40 attach more importance to the implementation of the normative policy for live streaming E-commerce. Women, the main force of live streaming users, are less enthusiastic about the policy implementation than men. Moreover, the analysis results of the LDA models and online HDP (online hierarchical Dirichlet process) models demonstrate that the most discussed topics are the contribution of live streaming E-commerce to traditional economic transformation, public welfare activities, resumption of work and production, and poverty alleviation, as well as fraud, counterfeit goods, supervision, rights protection and other incidents in this industry. Overall, the majority of the public holds a positive attitude towards the policy implementation. After further analysis of comments under the relevant topics, it is found that compared with the first two policies released on 1 July and 5 November in 2020, although the proportion of netizens with positive emotions during the implementation of the follow-up policy has increased, the increment is not significant, indicating that the implementation of the new normative policy in a short term will hardly curb the occurrence of industry chaos. In turn, the governments should transfer their attention to actual regulatory problems, and intensify efforts to implement normative policies.

Hyperspectral imaging combined with chemometrics for rapid detection of talcum powder adulterated in wheat flour

Detection of illegal additives in wheat flour is of crucial practical significance to ensure the market order and people's health. In this study, the potential of hyperspectral imaging in 900–1700 nm for the rapid detection of talcum powder adulterated in wheat flour was investigated. The raw spectral information within the hyperspectral images of samples were extracted and preprocessed with standard normal variate (SNV), baseline correction (BC), multiplicative scatter correction (MSC) and Gaussian filter smoothing (GFS), respectively. Partial least square (PLS) quantitative models with the preprocessed spectra were constructed and assessed to predict the talcum powder concentration in wheat flour. The results showed that the SNV-PLS model had best performance, with correlation coefficient (r) of 0.98 for both calibration and prediction, residual predictive deviation (RPD) of 4.69, and root mean square error of calibration (RMSEC), cross-validation (RMSECV) and prediction (RMSEP) of 2.86%, 2.99%, 3.13%, respectively. The characteristic wavelengths were then respectively selected by regression coefficient (RC), successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) algorithm to simplify the SNV-PLS model. Based on the four characteristic wavelengths (907.135, 1339.866, 1392.573 and 1394.22 nm) selected by CARS method, the SNV-CARS-PLS model was constructed and had best performance in predicting talcum powder content, leading to rP of 0.98, RMSEP of 2.88% and RPD of 5.09. The whole study indicated that the hyperspectral imaging in 900–1700 nm range combined with CARS method could be used for further developing a portable detection equipment to realize the rapid and accurate talcum detection in wheat flour.

Environmental regulation, innovation capability, and green total factor productivity of the logistics industry

PurposeThe purpose of this paper is to test the relationship between environmental regulations and green total factor productivity (GTFP) of China's logistics industry. The high-factor input, high-energy consumption, and high-pollution emissions model of the logistics industry developed within China faces challenges from severe resource and environmental constraints. It is generally believed that environmental regulations effectively restrain pollution emissions and help protect the environment.Design/methodology/approachThe authors employ the undesirable slack-based Malmquist Luenberger model to calculate the GTFP across the provincial logistics industry and use the mediation effect model and threshold effect model to explore the effects and mechanics of environmental transmission regulations on the GTFP.FindingsThe main results show significant regional differences in the GTFP of logistics industry across China. In the transmission path of the impact of environmental regulations on the GTFP, regional innovation capabilities have mediation effects. Regional innovation capacities have a masking effect on the transmission path of environmental regulations on accumulated technical efficiency changes (AEC) and accumulated technical changes (ATC). The threshold effect test results show a dual-threshold effect between environmental regulations and the GTFP, with environmental regulations as threshold variable. Furthermore, the impact of regional innovation capability on the GTFP has a dual-threshold effect, with environmental regulation as threshold variable.Practical implicationsFirst, it is advisable to plan the environmental regulation policy system thoroughly and add supporting measures to ensure the efficiency and smooth implementation of the nation's environmental policies. Second, it is important to further understand the critical role of innovation capability in improving the GTFP. Third, there is an urgent need to standardize the operating behavior and market order of the leading players in the logistics market and to improve the operational efficiency of logistics enterprises.Originality/valueSo far, a systematical study researched on effect of environmental regulation on the GTFP in logistics industry was not published. This study can provide experience for the high-quality development of the logistics industry.

Overallocation and secondary market outcomes in corporate bond offerings

Bond underwriters, lacking “Greenshoe options” and formal systems to track “flipping” activity, have fewer tools than equity underwriters to manage secondary market order flow uncertainty. We show that bond underwriters respond by selectively “overallocating” some issues to attain net short positions. Overallocations are economically substantive, facilitate the syndicate's price stabilization efforts, and are largely offset in the days after issuance. These issues on average experience more net selling by institutional investors and, despite large syndicate purchases, appreciate less in the secondary market. Thus, overallocation is an observable indicator that underwriters anticipate weakness in net secondary market demand.

Retail trader sophistication and stock market quality: Evidence from brokerage outages

We study brokerage platform outages to examine the impact of retail investors on financial markets. We contrast outages at Robinhood, which caters to inexperienced investors, with outages at traditional retail brokers. For stocks with high retail interest, we find that negative shocks to Robinhood investor participation are associated with reduced market order imbalances, increased market liquidity, and lower return volatility, whereas the opposite relations hold following outages at traditional retail brokerages. The findings suggest that herding by inexperienced investors can create inventory risks that harm liquidity in stocks with high retail interest, while other retail trading improves market quality.

Corporate Financing Constraints and Information Disclosure: An Analysis of Corporate Investment Dilemmas under the Wave of Counter-Globalization

Open and transparent market information is a prerequisite to maintain the order of financial market and guarantee the normal financing of enterprises. In the real financial market, there is inevitably market information asymmetry. Information asymmetry has become a key factor in corporate financing constraints, and capital market information disclosure is conducive to solve problems such as information asymmetry in the capital market and smooth the financing channels of companies. In the process of economic globalization, some developed countries and industrial classes with damaged interests have set off a wave of counter-globalization, under which export-oriented enterprises in various countries are facing a series of investment dilemmas, which affect their choice of investment direction. In this paper, we study the relationship between corporate financing constraints and information disclosure, introduce information disclosure quality indicators and financing constraint measurement models, and analyze corporate investment dilemmas based on international disputes under the wave of counter-globalization.

Application of Blockchain Technology in Water Rights Trading in the Irrigation Area under the Internet-of-Things Environment

Water rights trading is an important way to solve the shortage of water resources. Combined with the characteristics of water resources and the requirements of the market economy, the organic combination of the government and the market should be strengthened. Through the establishment of a water rights system and a water rights trading market, the implementation of water rights trading will be promoted. Due to the decentralized and distributed structure, blockchain technology greatly reduces its intermediary cost in the application process. The tamper-resistant timestamp feature can realize data tracking and information anticounterfeiting, and flexible programming attributes can promote the specification of market order. Firstly, the reasons for water rights trading are studied, and the water rights trading system is analyzed. It is found that the system has the problems of the cumbersome transaction process and high transaction costs. According to the characteristics of water rights trading, the alliance chain Hyperledger Fabric is selected as the underlying network system of the trading system. Secondly, combined with water rights trading, Hyperledger Fabric multichannel technology is used to design a three-channel accounting method, and the chain code for water rights trading is designed and implemented based on the Go language. CouchDB is adopted to store key-value data, and Ubuntu, Docker, and Docker Compose are used to construct an operating environment of the chain code. Finally, the proposed system is tested. The test findings reveal that the distributed water volume of experimental area 1 is 41.8368 million m3, the current water volume is 23.831 million m3, and the quota management water volume is 20.432 million m3. The distributed water volume in area 2 is 40.4605 million m3, the current water volume is 4317.64 m3, and the quota management water volume is 77.4795 million m3. The distributed water volume in area 3 is 65.6928 million m3, the current water volume is 77.472 million m3, and the quota management water volume is 64.412 million m3. The water rights trading system based on Hyperledger Fabric can record each transaction data, which can be stored in each node, and the data stored in each node are the same. The proposed scheme provides a certain reference for the application of blockchain technology in water rights trading in irrigation areas.

Does the National Credit Demonstration Policy Affect Urban Green Economy Efficiency? Evidence from the Yangtze River Delta Region of China.

A more scientific green economy efficiency indicator is constructed based on OH (2010), and a multiperiod spatial DID model is used to examine the impact of national credit demonstration policies on urban green economy efficiency in a sample of cities above the prefecture level in the Yangtze River Delta. The study confirms the following: (1) The national credit demonstration policy makes a significant contribution to the green economic efficiency of cities, and it is conducive to strengthening awareness of the rule of law in the market to regulate market order. (2) The demand for credit regulation in coastal areas has increased under the new development pattern, and the national credit demonstration policy has effectively enhanced green economy efficiency through institutional supply. (3) Under the national credit demonstration policy, the subprovincial level and above can mobilise more resources for policy refinement and support, reducing transaction costs and improving the efficiency of the green economy. (4) The impact of the national credit demonstration policy on the efficiency of Zhejiang’s green economy is more obvious; but, under the overall framework of the Yangtze River Delta, the policy has a more prominent role in promoting green economy efficiency in other provinces. Policy insights are as follows: (1) Different cities have different degrees of impact on the efficiency of the green economy from the national credit demonstration policy, and they should implement differentiated measures based on regional heterogeneity; (2) regulating the use of administrative resources and avoiding undue administrative intervention are important prerequisites for promoting regional integration to enhance the efficiency of the green economy; and (3) strengthening interprovincial credit policy synergies can help to alleviate administrative distortions of policy implementation and enhance the efficiency of the regional green economy.