Market Model Research Articles

Price Impact for Different Market Models in Cryptocurrency Trading

Price impact in cryptocurrency trading plays a crucial role in understanding market dynamics and liquidity. The study presents a detailed mathematical analysis of price impact across three different market models: constant sum, constant product, and order book. Each model provides a unique perspective on how asset prices are influenced by trade execution, market depth, and available liquidity. By examining these models, the analysis highlights the relationship between trade volume and price changes, offering important insights into how large transactions affect the stability and behavior of prices in various liquidity environments. The results are relevant for traders and investors aiming to optimize their strategies in volatile markets, as well as for regulators seeking to mitigate the systemic risks posed by large-scale trades in the cryptocurrency space.

A maximal Riesz-Kantorovich theorem with applications to markets with an arbitrary commodity set

By analyzing proofs of the classical Riesz-Kantorovich theorem, the Mazón-Segura de León theorem on abstract Uryson operators and the Pliev-Ramdane theorem on C-bounded orthogonally additive operators on Riesz spaces, we find the most general (to our point of view) algebraic structure, which we call a complementary space, for which the theorem can be generalized with a similar proof. By a complementary space we mean a PO-set $G$ with a least element $0$ such that every order interval $[0,e]$ of $G$ with $e \neq 0$ is a Boolean algebra with respect to the induced order. There are natural examples of complementary spaces: Boolean rings, Riesz spaces with the lateral order. Moreover, the disjoint union of complementary spaces is a complementary space. Our main result asserts that, the set of all additive (in certain sense) functions from a complementary space to a Dedekind complete Riesz space admits a natural Dedekind complete Riesz space structure, described by formulas which are close to the classical Riesz-Kantorovich ones. This theorem generalizes the above mentioned Mazón and Segura de León and Pliev-Ramdane theorems. In the final section, we construct a model of market with an arbitrary commodity set, connected to a complementary space.

MODELS OF MARKETING ACTIVITY IN AN INDUSTRIAL ENTERPRISE

The article presents the results of a study of theoretical, methodological and practical aspects of marketing activities at industrial enterprises, systematized in the form of three functional models of marketing activities implemented at industrial enterprises, taking into account the specific features of changes in marketing activities depending on the functional marketing model implemented at the enterprise. The research uses traditional methods of scientific analysis, including technical, economic and logical analysis, systematization and ranking. The analysis takes into account that the dynamic nature of the external environment of enterprises implies constant changes in the criteria of competitiveness and efficiency, leading to the emergence of new business goals, new tools and methods of work, changes in the ownership structure, relationships, the development of new functions and directions, diversification and integration. The obtained results can be used at an industrial enterprise when changing the model of marketing activities, as in the conditions of the formation of technological independence of the Russian Federation the most important task is to ensure the market orientation of the production capabilities of domestic enterprises.

Bachelier’s Market Model for ESG Asset Pricing

Environmental, Social, and Governance (ESG) finance is a cornerstone of modern finance and investment, as it changes the classical return-risk view of investment by incorporating an additional dimension to investment performance: the ESG score of the investment. We define the ESG price process and include it in an extension of Bachelier’s market model in both discrete and continuous time, enabling option pricing valuation.

Exploring Consumer Behavior in Indonesian Online Marketplaces

The burgeoning landscape of online marketplaces in Indonesia has prompted an exploration into the intricate interplay between consumer browsing behaviors and their impact on e-satisfaction, electronic word-of-mouth (e-WOM), and repurchase intention. This study investigates these relationships within Indonesian online marketplaces, employing a robust quantitative methodology. Surveys were conducted with 962 users of Indonesian online markets, and data was analyzed using SPSS 29 and Smart PLS 3. Findings reveal significant associations between utilitarian browsing and both e-satisfaction and repurchase intention. Hedonic browsing also significantly influences e-satisfaction, though its impact on e-WOM is less pronounced. E-satisfaction emerges as a critical precursor to both repurchase intention and e-WOM, underscoring its pivotal role in shaping consumer behavior within online marketplaces. Practical implications suggest businesses in Indonesian online marketplaces should adopt a multifaceted approach to platform design, prioritizing user satisfaction and transactional efficiency. Proactive customer satisfaction initiatives, coupled with leveraging satisfied customers as brand advocates, are essential for fostering long-term loyalty and advocacy. Theoretical contributions refine existing models in e-commerce and marketing, emphasizing the dynamic nature of online consumer behavior and its implications for managerial decision-making. While the study provides valuable insights, acknowledging its limitations underscores the need for future research. Longitudinal studies, qualitative approaches, and comparative analyses across cultural contexts are recommended to further explore online consumer behavior in Indonesian marketplaces and beyond. This research contributes to both scholarly understanding and managerial practices in the dynamic realm of online retail.

Examining the Information Efficiency of Indonesia Equity Market: Evidence from Earnings Announcements

The main objective of this study is to examine the semi-strong form of market efficiency in the Indonesia Equity Market on publicly available information. The study uses a market model to analyze the significance of abnormal returns before and after earnings releases. It analyzes the cumulative average abnormal returns of the daily trades before and after the earnings release. The study reveals that there are no significant abnormal returns during the pre-announcement periods, suggesting that there is no significant leakage of information before the disclosures. An analysis of the post-announcement documents reveals a delay in the market response, indicating that the market is inefficient in rapidly and accurately transmitting the information from earnings releases to investors. It also observes significant abnormal returns within the initial week of the release periods and a post-earnings announcement drift of up to 30 days. The findings indicate that the market does not possess the attributes of a semi-strong form of market efficiency. The results imply that the market’s financial reporting processes have the potential for digital technology improvement to enhance transparency, accountability, and information efficiency within the market.

Measure‐valued processes for energy markets

AbstractWe introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free modeling in infinite dimensions, while allowing for the incorporation of important stylized facts, in particular stochastic discontinuities, that is, jumps or spikes at pre‐specified (deterministic) dates. We derive an analog to the HJM‐drift condition and then treat in a Markovian setting existence of non‐negative measure‐valued diffusions that satisfy this condition. To analyze mathematically convenient classes we consider measure‐valued polynomial and affine diffusions, where we can precisely specify the diffusion part in terms of continuous functions satisfying certain admissibility conditions. For calibration purposes these functions can then be parameterized by neural networks yielding measure‐valued analogs of neural SPDEs. By combining Fourier approaches or the moment formula with stochastic gradient descent methods, this then allows for tractable calibration procedures which we also test by way of example on market data.

Stochastic Approaches to Energy Markets: From Stochastic Differential Equations to Mean Field Games and Neural Network Modeling

This review paper examines the current landscape of electricity market modelling, specifically focusing on stochastic approaches, transitioning from Mean Field Games (MFGs) to Neural Network (NN) modelling. The central objective is to scrutinize and synthesize evolving modelling strategies within power systems, facilitating technological advancements in the contemporary electricity market. This paper emphasizes the assessment of model efficacy, particularly in the context of MFG and NN applications. Our findings shed light on the diversity of models, offering practical insights into their strengths and limitations, thereby providing a valuable resource for researchers, policy makers, and industry practitioners. The review guides navigating and leveraging the latest stochastic modelling techniques for enhanced decision making and improved market operations.

A tri-level model for optimal management of active distribution networks enabling two-layer local markets

The deregulation of distribution systems enable local energy trading under the umbrella of local market strategies, which are launched and cleared by local entities like distribution system operators. The emergence of active players connected to distribution networks such as microgrids path the way to two-layer market structures, within which different local markets must coexist and coordinate. This new paradigm advocates for developing new management and market models suitable for multi-level local markets. This paper focuses on this issue. In particular, a new management model for active distribution networks enabling two-layer local markets is developed, which casts as an original tri-level optimization approach. This paper applies the developed methodology to the case in which different microgrids connected to a distribution market launch local markets for energy trading within the microgrid, but it could be applied to similar frameworks such as energy communities or virtual power plants. The new approach stablishes a game-oriented market coordination which preserves the hierarchical feature of the coordinated market strategy. A case study on a 33-bus radial distribution network serves to validate the model and illustrates how active players such as distributed generators and flexible demands perform under local market rules. A number of scenarios are studied under different distributed generation and microgrid penetration, showing that incrementing the number of both leads to improve the economy of the distribution system operator and microgrids. Finally, a sensitivity analysis regarding the renewable generation potential is studied.

Older Adult's Opinion About Colorectal Cancer Screening based on Social Marketing Model

Older Adult's Opinion About Colorectal Cancer Screening based on Social Marketing Model

The EU’s Geopolitical Awakening Following the Russian Invasion of Ukraine: How the Commission Shifted from a Regulatory Market-Based Approach to a Geopolitical Approach in Its External Energy Policy

The Ukraine invasion has been a watershed moment in EU-Russia gas relations, which has resulted in a shift in the European Commission’s (EC’s) approach towards Russia and European energy policy. Whilst the EC has traditionally followed a rule-based market approach in its external energy relations with Russia, there appears to have been a shift from the prevailing liberal market model to a more strategic and geopolitical approach focused on energy security.Although the EC has sometimes displayed tendencies of a realist nature, these realist elements in its external action have been exacerbated following the invasion of Ukraine. This article engages in a theoretical debate between the conceptualizations of the EU as a liberal actor versus the perception of the EU as a realist actor. Whilst there is literature to support both views, the debate can be further developed after the war in Ukraine. Since the invasion, the EC appears to have undertaken a more robust and coherent stance towards Russia in its commitment to decouple European economies from Russian gas to ensure EU energy security. The change in objectives illustrate a shift in the EU’s energy policy from the liberal paradigm of markets to geopolitics, as the new dynamics of EU-Russia energy relations, following the invasion of Ukraine.

Modelling intervention: Barbara Bergmann’s micro-to-macro simulation projects

Over a period of 12 years, Barbara Bergmann developed several models of the labour market using microsimulation, eventually integrated in a “Transactions Model” of the entire US economy, built with Robert Bennett and published in 1986. The paper reconstructs the history of this modelling enterprise in the context of the debates on the micro-foundations of macroeconomics and the role of macroeconomic expertise from the 1970s to the late 1980s. It shows how her focus on the distributional effects of policies was central to the criticism of macroeconomic modelling and how both her epistemological and political positions were marginalised in the 1980s.

Analysis of the Economic Model of Influencer Marketing in Social Media: The Case of Douyin

With the rapid growth of social media platforms, the number of influencers has proliferated. Influencers have become a key link between brands and consumers. Through their personal identities or social accounts, influencers use their influence to promote products or services for brands, and this Netflix economy model has been widely used in various industries. This paper aims to explore the specific forms of influencer marketing and analyse its application in different fields, focusing on the positive and negative impacts on brands and consumers. It has been observed that influencers across various sectors have implemented unique marketing strategies that can significantly enhance brand visibility and foster consumer confidence. However, issues such as false promotions and inappropriate personal remarks by influencers may also have negative impacts. In light of these findings, this study advocates for brands to exercise greater discernment in their partner selection and to motivate influencers to uphold authenticity in their promotional activities. The research significance of this paper lies in the fact that through the in-depth analysis of influencer marketing, it provides a reference for brands to optimise their social media marketing strategies, as well as a basis for further research on influencer marketing in different fields.

A Review of the State of the Art 3D Generative Models and Their Applications

Ever since 2022, there has been a large number of 3D generative models that have been devised and published, such as AvatarGen, CityDreamer, and HOLOFUSION. Generally speaking, these models can perform tasks such as generating a 3D human model, creating an unbounded city scene, and constructing a 3D object. And it is not a surprise that 3D generative models are very popular these years because there has been a witness of huge need for 3D models in the global market and the models themselves also serve as both convenient and productive tools for the relevant industries. For instance, 3D generative models can utilize a combination of Generative Adversarial Network (GAN) and Multi-Layer Perceptron (MLP) or Neural Radiance Field (NeRF) or Diffusion Model to produce 3D human model; Autoregressive Model or Feature Extraction + Volume Rendering to generate 3D scenes; Diffusion Model or GAN + MLP to produce 3D objects. This paper tries to present a taxonomy of the main 3D generative models from the angle of the kinds of outputs and strategies employed by different models.

The Magnet Effect of Price Limits: An Agent-Based Approach

ABSTRACT In this paper, we study the magnet effect within the context of circuit breaker events that transpired in global stock markets during March 2020. Our analysis encompasses nine such events across six countries. Employing a time-distanced quadratic function to model trading activities leading up to limit hits, we observe a substantial acceleration in return movement and the convergence of traders’ behavior preceding limit hits. Furthermore, most circuit breaker events manifest a distinct reduction in trading volume and amplified market stability during this crucial phase. To gain deeper insights into the magnet effect, we employ an agent-based model of the stock market that incorporates price limits. Our model replicates the stylized facts associated with limit hit events and the magnet effect. Importantly, our simulation results closely align with empirical observations. We also emphasize the importance of market environment changes and shifts in traders’ behavior in influencing limit hit events and the magnet effect.

Strategic Implications of Intellectual Property in Shaping Corporate Image and Branding

This paper explores the critical role of intellectual property (IP) in shaping corporate image and branding in the digital age. The main objective of this paper is to examine the evolution of the IP-based marketing model, focusing on how it attracts consumers and brand loyalty. Through an in-depth literature review and theoretical analysis, this study explores the practical application of intellectual property in brand strategy. Using case studies of established brands such as Sanrio and emerging brands such as Chiikawa, this paper demonstrates the impact and challenges of integrating IP into marketing campaigns. The results show that IP can build deep consumer connections and serve as a dynamic brand communication platform. Even in the face of declining traditional sales channels and the need to embrace digital transformation, strategic IP integration can increase brand awareness and enhance consumer loyalty. The report concludes that a prudent and innovative approach to intellectual property is essential for brands seeking to resonate with consumers on a deeper level. A well-designed IP strategy has the potential to significantly expand a brand's market presence and foster a unique consumer experience.

Regulation by enforcement: the impact of Securities and Exchange Commission enforcement actions on crypto valuation

Purpose This paper aims to examine the impact of enforcement actions by the US Securities and Exchange Commission (SEC) on the valuation of major crypto assets. Design/methodology/approach Given the recent increase in regulatory efforts to combat fraudulent activity within the market, the paper concentrates on the period from 2019 to 2023 and uses the event study approach. Findings The analysis reveals a negative and economically significant effect of SEC actions on crypto valuations, ranging from −0.7% to −1.4% over a three-day window surrounding the announcement of enforcement actions for the entire sample. Particularly, a pronounced negative reaction is observed from crypto investors to SEC enforcement actions in 2022 and those where individuals are charged. Originality/value The findings align with existing literature, even though the study uses more conservative methodological approaches and data selection criteria. Specifically, the author uses a market event study model, account for potential confounding events, and use initial news reports about investigations rather than official SEC communications as event dates.

Trading signals of the relative strength index and market valuation of State Treasury companies listed on the Warsaw Stock Exchange

Abstract Accurate forecasting of the level of volatility of financial instrument prices is important from the point of view of stock exchange investors. The aim of this paper is to measure the value relevance of transaction signals (buy/sell) by the relative strength index (RSI) in the case of State Treasury companies listed on the Warsaw Stock Exchange (WSE). The research covered the two hypotheses stating that stock buy (sell) transaction signals generated by the RSI indicator cause the occurrence of statistically significant positive (negative) abnormal returns (AR). These, in turn, support that RSI generates value-relevant signals, which are valuable investment tools and can be used to earn money on the stock exchanges. Based on the final research sample, including 75 buy signals and 88 sell signals, generated by the RSI indicator on the shares of State Treasury companies listed on WSE, an event study methodology was carried out. In 7-day event windows, calculations were made of AR, which is the difference between the realized and the expected return (estimated on the basis of the market model). The averaged ARs did not differ statistically significantly from zero on any of the tested days for both buy and sell signals. Therefore, research results do not indicate that share purchase (sell) transaction signals generated by the RSI indicator result in the occurrence of statistically significant positive (negative) average abnormal returns (AAR).

Evaluating and Analysing Digital Entrepreneurship: Innovation, Competitive Advantage, and Sustainability in the Modern Business Landscape

This review paper examines the transformative impact of digital entrepreneurship on the modern business landscape, focusing on its ability to drive innovation, provide competitive advantages, and contribute to economic growth. The study explores key components of successful digital enterprises, including digital literacy, creativity, and critical reasoning, while analyzing emerging trends such as artificial intelligence, digital marketing, and subscription-based models. Through case studies of successful companies like Shopify and Airbnb, the paper highlights how digital platforms disrupt traditional industries and enhance customer experiences. Despite the benefits, digital entrepreneurship faces challenges like high competition, data security concerns, and customer trust issues. The review concludes that, by embracing technological advancements and innovative strategies, digital enterprises can thrive, create value, and shape a sustainable and inclusive global economy.

Comparative Study of Domestic and International Art Museum Derivatives

With the continuous improvement of the national economy, the quality of cultural consumer groups generally improve, the museum as a place of convergence of cultural essence, through the derivatives produced by the arts is worth studying, this paper is mainly through the introduction of domestic art derivatives of the development and construction of art derivatives with foreign art derivatives to compare the different, view design thinking and marketing model, put forward some reflections and constructive thinking, especially in the era of consumerism. Derivatives with what kind of innovative ideas, art and culture and the public clever connection.