Forecasting the Market with Machine Learning Algorithms: An Application of NMC-BERT-LSTM-DQN-X Algorithm in Quantitative Trading

Although machine learning (ML) algorithms have been widely used in forecasting the trend of stock market indices, they failed to consider the following crucial aspects for market forecasting: (1) that investors’ emotions and attitudes toward future market trends have material impacts on market trend forecasting (2) the length of past market data should be dynamically adjusted according to the market status and (3) the transition of market statutes should be considered when forecasting market trends. In this study, we proposed an innovative ML method to forecast China's stock market trends by addressing the three issues above. Specifically, sentimental factors (see Appendix [1] for full trans) were first collected to measure investors’ emotions and attitudes. Then, a non-stationary Markov chain (NMC) model was used to capture dynamic transitions of market statutes. We choose the state-of-the-art (SOTA) method, namely, Bidirectional Encoder Representations from Transformers ( BERT ), to predict the state of the market at time t , and a long short-term memory ( LSTM ) model was used to estimate the varying length of past market data in market trend prediction, where the input of LSTM (the state of the market at time t ) was the output of BERT and probabilities for opening and closing of the gates in the LSTM model were based on outputs of the NMC model. Finally, the optimum parameters of the proposed algorithm were calculated using a reinforced learning-based deep Q-Network. Compared to existing forecasting methods, the proposed algorithm achieves better results with a forecasting accuracy of 61.77%, annualized return of 29.25%, and maximum losses of −8.29%. Furthermore, the proposed model achieved the lowest forecasting error: mean square error (0.095), root mean square error (0.0739), mean absolute error (0.104), and mean absolute percent error (15.1%). As a result, the proposed market forecasting model can help investors obtain more accurate market forecast information.

Utilization of Electric Vehicles for Vehicle-to-Grid Services: Progress and Perspectives

With every passing second, we witness the effect of the global environmental impact of fossil fuels and carbon emissions, to which nations across the globe respond by coming up with ambitious goals to become carbon-free and energy-efficient. At the same time, electric vehicles (EVs) are developed as a possible solution to reach this ambitious goal of making a cleaner environment and facilitating smarter transportation modes. This excellent idea of shifting towards an entirely EV-based mobility industry and economy results in a range of issues that need to be addressed. The issues range from ramping up the electricity generation for the projected increase in consumption to developing an infrastructure that is large enough to support the higher demand for electricity that arises due to the market penetration of EVs. Vehicle to grid (V2G) is a concept that is largely in a testing phase in the current scenario. However, it appears to offer a solution to the issues created by a mobility sector that the constantly growing EV fleet will dominate. Furthermore, the integration of EVs with the grid seems to offer various cost-wise and environment-wise benefits while assisting the grid by tapping into the idle energy of parked EVs during peak hours. This review aims to present some of the possible ancillary service potentials of such a system while also discussing the potential challenges, impacts, and future market penetration capabilities of V2G technology.

Genetic Diversity in the Italian Holstein Dairy Cattle Based on Pedigree and SNP Data Prior and After Genomic Selection

Genetic diversity has become an urgent matter not only in small local breeds but also in more specialized ones. While the use of genomic data in livestock breeding programs increased genetic gain, there is increasing evidence that this benefit may be counterbalanced by the potential loss of genetic variability. Thus, in this study, we aimed to investigate the genetic diversity in the Italian Holstein dairy cattle using pedigree and genomic data from cows born between 2002 and 2020. We estimated variation in inbreeding, effective population size, and generation interval and compared those aspects prior to and after the introduction of genomic selection in the breed. The dataset contained 84,443 single-nucleotide polymorphisms (SNPs), and 74,485 cows were analyzed. Pedigree depth based on complete generation equivalent was equal to 10.67. A run of homozygosity (ROH) analysis was adopted to estimate SNP-based inbreeding (FROH). The average pedigree inbreeding was 0.07, while the average FROH was more than double, being equal to 0.17. The pattern of the effective population size based on pedigree and SNP data was similar although different in scale, with a constant decrease within the last five generations. The overall inbreeding rate (ΔF) per year was equal to +0.27% and +0.44% for Fped and FROH throughout the studied period, which corresponded to about +1.35% and +2.2% per generation, respectively. A significant increase in the ΔF was found since the introduction of genomic selection in the breed. This study in the Italian Holstein dairy cattle showed the importance of controlling the loss of genetic diversity to ensure the long-term sustainability of this breed, as well as to guarantee future market demands.

Hyaluronic Acid Allows Enzyme Immobilization for Applications in Biomedicine

Enzymes are proteins that control the efficiency and effectiveness of biological reactions and systems, as well as of engineered biomimetic processes. This review highlights current applications of a diverse range of enzymes for biofuel production, plastics, and chemical waste management, as well as for detergent, textile, and food production and preservation industries respectively. Challenges regarding the transposition of enzymes from their natural purpose and environment into synthetic practice are discussed. For example, temperature and pH-induced enzyme fragilities, short shelf life, low-cost efficiency, poor user-controllability, and subsequently insufficient catalytic activity were shown to decrease pertinence and profitability in large-scale production considerations. Enzyme immobilization was shown to improve and expand upon enzyme usage within a profit and impact-oriented commercial world and through enzyme-material and interfaces integration. With particular focus on the growing biomedical market, examples of enzyme immobilization within or onto hyaluronic acid (HA)-based complexes are discussed as a definable way to improve upon and/or make possible the next generation of medical undertakings. As a polysaccharide formed in every living organism, HA has proven beneficial in biomedicine for its high biocompatibility and controllable biodegradability, viscoelasticity, and hydrophilicity. Complexes developed with this molecule have been utilized to selectively deliver drugs to a desired location and at a desired rate, improve the efficiency of tissue regeneration, and serve as a viable platform for biologically accepted sensors. In similar realms of enzyme immobilization, HA’s ease in crosslinking allows the molecule to user-controllably enhance the design of a given platform in terms of both chemical and physical characteristics to thus best support successful and sustained enzyme usage. Such examples do not only demonstrate the potential of enzyme-based applications but further, emphasize future market trends and accountability.

Quantitative Research on Profitability Measures in the Polish Meat and Poultry Industries

Business entities strive for continuous adaptation to changing situations and needs. The decisions of business entities entangled in multifaceted processes of economic, social, and environmental progress must be taken on the basis of reliable knowledge, developed know-how, scrupulous recognition of the initial state, and foresight of the multiple consequences of business actions over a long horizon. In such a situation, the measurement of financial efficiency in terms of the profitability of enterprises in meat and poultry industries is extremely desired and provides valuable information on the necessary modifications to reduce the potential risks of business operation. The Polish meat and poultry industries should take into account current and future market requirements, competition, and consumer response. The dynamic progress of technology is forced to take appropriate steps to improve and modernize products, services, and methods of solving profit losses. The aim of the paper is to calculate and evaluate the statistical relationships between profitability ratios in Polish meat and poultry enterprises divided into four groups: slaughterhouses, meat enterprises (small, medium, and large), poultry meat enterprises, and meat trade enterprises. In the theoretical part of the study, methods of descriptive, comparative, deductive, and synthetic analyses were used. In the practical part of the study, panel data from the entire meat and poultry industries in the period from 2010 to 2019 were used. For the measurement of financial efficiency, methods, such as financial indicator analysis, panel database modeling, and nonparametric ANOVA, were applied. The ANOVA method was used to test only the statistically significant relationships between profitability ratios across all groups of examined enterprises in the meat and poultry industries. To summarize, the optimal level of profitability was achieved by all groups of examined enterprises, except small meat enterprises. The highest financial efficiency in the area of profitability was reached by poultry enterprises. Moreover, financial support for small companies in the meat industry can bring tangible benefits such as maintaining a diversified product range locally and transforming small meat companies into buying centers for the local community. Both are effective solutions, especially in view of the post-pandemic situation.

Understanding traceability: its relevance in the adoption of quality and safety measures across the supply chain

The article is based on a previous case study of a certified papaya producer from Colima which currently implements traceability in its operations. Traceability can be defined as an instrument to respond and avoid risks in the supply chain of a product. For Small and Medium Enterprises (SMEs) the use of traceability can be a competitive advantage, adding value to their products; or either an entry barrier to access to new international markets. The article analyzes the importance of traceability and the adoption of new practices to respond to future market requirements in a competitive globalized environment.

HANDLING TEMPORAL COMPLEXITY IN THE DESIGN OF NON-TRANSPORT SHIPS USING EPOCH-ERA ANALYSIS

A core aspect of temporal complexity in the design of non-transport vessels is the uncertainty related to the future market and contract opportunities, and the corresponding changeability that should be incorporated into the ship design to meet this uncertainty. The development of an appropriate design specification for a new ship represents a core strategic decision for ship owners as part of a fleet renewal or expansion programme, with a high financial risk and a long time horizon of typically 20-30 years. This type of temporal complexity is one out of several complexity aspects to be handled as part of a ship design process. In this paper we model possible realizations of an uncertain future for a vessel using the Epoch-Era Analysis (EEA) method. Here, we use the epochs as the primary instrument for capturing major market developments, such as the opening of new offshore areas, new emission regulatory regimes, or the availability of new, disruptive technologies. From these, more specific epoch variables are derived, for which specific contract opportunities can be generated. The epoch-specific performance of the vessels is found by solving a Ship Design and Deployment Problem (SDDP) of concurrently identifying both a preferable ship design and the corresponding path of consecutive contracts that maximizes total revenue. We present a case study related to the design of an Anchor Handling Tug Supply (AHTS) vessel. The study illustrates the complexity in striking the correct balance between optimizing the vessel for an initial scenario, while at the same time providing addition performance capabilities to be competitive in the context of future market requirements.

Digital onboarding in finance: a novel model and related cybersecurity risks

Over the last few years, the financial sector has undergone a digital revolution that has had a severe impact on different related areas such as, the entities, the cybersecurity of systems, regulations and, of course, customers. SOTER project takes the challenge providing a complete set of tools to enhance the cybersecurity levels by implementing, in addition to non-technological tools, an innovative onboarding process has been implemented with the goals of increasing security, improving the user experience and integrity in the sector, and facilitating the customer entry into the digital marketplace by combining a set of breakthrough technologies. The cybersecurity research plays a crucial role in the conception and implementation of the onboarding process and for this kind of processes it has to be studied as an individual area by itself, as it is necessary to analyze the possible threats that can affect them, their origin and the solution(s) that can be taken to address them. Therefore, the SOTER project presents a fully digital onboarding process, innovative, adaptable to both current and future market needs and to possible changes in regulation, based on the most advanced technologies available today, and above all guaranteeing the cybersecurity of both entities and end users.

The Optimistic View to Uncertainty. Benefits of Real Option Valuation Methodology in Project Valuation; Example of its Application for a Rail Terminal Modification Project

The two main factors that drive the shift to liquid cracking in the Middle East are the restricted availability of ethane and the fact that naphtha or mixed feed cracking provides us with a much more diverse product mix. This opens the path to a higher share of performance chemicals. Building petrochemical complexes based on liquid or mixed feed cracking requires very complicated downstream configurations at a high level of integration with refinery streams. The value created by such a project rests on the ability of the operator to solve complex optimization problems in a volatile market environment. Inevitably, the correctness of the investment decision rests on the ability of the management to determine the value of the project under conditions of uncertainty regarding the future market prices. This paper demonstrates how the approach that was developed originally for the option valuation, can be used to address the problem of project assessment under the conditions of uncertainty. A real-life example of an investment decision about a modification of a rail terminal is used to illustrate the problem and to present a solution to it. Building on this example further, the paper argues that the method of Real Option valuation can support a creation of a competitive advantage in the conditions of uncertainty.

Heterogeneity in Generational Effects: Case Study of Ride-hailing Behavior Among Millennials

This paper presents an investigation of the use and frequency of use of ride-hail services. In particular, we explored the role of generational effects and the heterogeneity involved in Millennials’ decision making when it comes to ride-hail choices. Using an ordered logistic regression structure, different statistical models were developed and tested, including fixed-effects and random parameter models, as well as the inclusion of interaction effects and attitudinal factors. Initial results from the fixed-effects model showed that the younger cohorts, including Millennials and Generation Z, showed a significantly positive preference for more frequent ride-hail use, whereas the older cohorts’ preferences (Generation X, Baby Boomers, and older) did not show any significant effects on ride-hail frequency. In the next step, the presence of heterogeneity among Millennials was tested using random parameters. The results confirmed that Millennials’ usage of ride-hail was heterogeneous, and this was statistically significant at the 90% confidence interval [Formula: see text]. To identify sources of heterogeneity, interaction effects were added to the model. Accordingly, use of ride-hail was more popular among middle-aged Millennials (30 to 34 years old) and Millennials with higher incomes. Likewise, attitudes such as cost sensitivity (toward private vehicle ownership), and being a rational user resulted in higher frequency ride-hail use across Millennials. On the contrary, unemployed Millennials were less likely to utilize ride-hail. The results from this study provide a more transparent picture of current ride-hail market segmentation, which could help predict the future market comprising autonomous vehicles and other emerging mobility options.