2021. No. 4 Vol.15

      The modern global debt market features historically low average interest rates, convergence of yields on bonds with different maturities, an increase of yield curve inversion emergence frequency and a large-scale trend to automate financial decision making. The researchers’ attention in these fields is mainly focused on designing models that describe the state of the debt market as whole or its individual instruments in particular, as well as on risk management methods. At the same time, the specialized literature offers very few works concerning the topic of computer algorithms for bond portfolio selection based on traditional or advanced investment strategies. The aim of the present research is to create a modification of the existing algorithm of riding the yield curve strategy application, employing, first, average bond yield over the holding period instead of traditional bond yield to maturity; second, a developed algorithm for calculating the market spread on bonds; and, third, alternative risk evaluation indicators (compensation coefficients), which allow us to measure objectively price risk,  liquidity risk, transaction costs risk and a general risk. The modification and the development of the algorithm for calculating the market spread were carried out using the direct measurement of the result technique, which entails application of the strategy to the data on bond issues received through the Moscow Exchange API. The selection of financial instruments was conducted in all sectors of the Russian debt market: public bonds, sub-federal and municipal bonds, corporate bonds. The modified algorithm enabled us to get extra yield for each selected bond issue, thereby proving the high effectiveness of the technique compared to the traditional strategy. Software implementation of the algorithm can be integrated into any robotized or semi-robotized stock exchange trading application.

      In business informatics, one of the research subjects is the analysis of data on processes in applied subject areas; here problems of qualitative analysis arise. Such problems arise, for example, in the qualitative study of log files of business processes, in the analysis and prediction of time series and other processes of a different nature. Quite often, to represent information about the processes under study, the methods of qualitative analysis use symbolic coding, which makes it possible to remove unnecessary detailing of numerical descriptions. The relevance of this study is due to the fact that when working with the raw data, researchers often face the presence of noise and distortions of the data, which significantly complicates the solution of the problems of qualitative analysis. When working with symbolic representations of the processes under study, which quite often have a periodic nature, we observe noise of deletion, insertion and replacement of symbols, which complicate the solution of the problem of revealing and analyzing the periodicity. This article deals with the problem of recovering periodic symbolic sequences obtained by coding from samples of continuous periodic functions and distorted by noise of insertion, replacement and deletion of symbols. Trigonometric functions are considered as a specific example of synthetic time series data. To encode trigonometric functions, alphabets of various cardinalities are used. The article presents an experimental study of the dependence of the quality characteristics of the method of period and a periodically repeating fragment recovery, previously proposed by the authors and improved in this study. For alphabets of different cardinalities at fixed sampling intervals, the fraction of sequences with a satisfactorily reconstructed period and the relative error in determining the period are given. The quality of reconstruction of a periodically repeating fragment is estimated by the edit distance from the reconstructed periodic sequence to the original sequence distorted by noise.

      Under conditions of intense competition, the creation of new products and their promotion to the market requires marketing support. The central element of marketing innovation management is marketing positioning. In contrast to the methodological aspect, there is almost no procedural component of positioning in scientific works and publications. Moreover, due attention is not paid to the issues of market segmentation and the allocation of the competitive advantage of such high-tech products as civil aircraft. This determines the relevance of the task of developing a procedure for marketing positioning within the framework of managing the product offer of the aircraft industry enterprises. From the standpoint of a systematic approach, the necessity of studying the adjacent air transportation market is reasonable, as well as the analysis of the correlation of its segmentation with the allocation of target segments of the aircraft market. When conducting a competitive analysis, we propose to consider the market position not only of certain types of civil aircraft, but also of aircraft families. Modeling marketing management shows the role of positioning in the processes of creating, manufacturing and operating aircraft. A distinctive feature of the procedure is the proposed stage of evaluating the effectiveness of the selected product position implementation, which allows us to analyze the feasibility of marketing decisions throughout the product life cycle. Special attention is paid to the issues of information support. The research results presented here reflect the specifics of the marketing activities of aviation industry enterprises and contribute to the development of the conceptual foundations of industrial marketing.

      This article deals with probabilistic and statistical modeling of managerial decision-making in the economy based on sample data for the previous periods of time. For better definition, the study is limited to Markowitz’s models in the problem of finding an effective portfolio of the field in the third information situation. The third information situation is a widespread decision-making situation and is characterized by the fact that the decision-maker sets, according to his opinion, are a linear order relation on the components of an unknown probabilistic distribution of the states of the economic environment. Often, from the point of view of the decision-maker, the components of an unknown probability distribution of the states of the economic environment must satisfy a partially reinforced linear order relation. As a result, the use of traditional statistical estimates turns out to be impossible, while the following question arises, which is practically not studied in the scientific literature. In this case, what formulas should be used to find statistical estimates and, above all, estimates of unknown probabilities of the state of the economic environment? As an estimate of an unknown probability distribution, we proposed to use the Fishburne sequence that satisfies all available constraints, while corresponding to the opinion of the decision maker and the linear order relation given by him. Fishburne sequences are a generalization of the well-known Fishburne formulas. It is fundamentally important that any Fishburne sequence satisfies a simple linear order relation, and under certain conditions, a partially strengthened linear order relation. Particular attention is paid to the entropic properties of generalized Fishburne progressions, which represent the most important class of Fishburne sequences, as well as the use of generalized Fishburne progressions to take into account the opinion of the decision maker. Such a scheme for estimating an unknown probability distribution has been developed, which makes it possible to achieve the correctness of probabilistic and statistical modeling, as well as appropriate consideration of the opinion of the decision-maker, uncertainty and risk.

      The creation of network enterprises based on the digital technologies of the Industrie 4.0 (the 4th Industrial Revolution, i4.0) opens broad opportunities for increasing production flexibility, customer focus and continuous innovation in products and services provided. At the same time, new opportunities necessitate the development of new methods and technologies for designing innovative processes in the context of digital i4.0 platforms, all of which highlights the relevance of the presented research topic. This work aims to define technologies for designing innovative processes to create products and services using i4.0 systems which are based on multi-agent interaction of asset administration shells (AAS), displaying digital twins of product components, and the use of ontological and cognitive methods for forming and justifying design decisions. The work presented here uses the Domain-Driven Design approach, an architectural framework for building i4.0 systems, methods of ontological engineering, quality function deployment (QFD), analysis of the types and consequences of potential inconsistencies (FMEA) and processing of fuzzy sets. The paper proposes principles for identifying bounded contexts of the domain under the design activities for the stages of the life cycle and products’ subsystems (components). For bounded contexts of the domain, it is envisaged to create AAS of i4.0 systems, with the help of which the innovative process is supported and the multi-agent interaction of its participants is carried out. As cognitive tools for making design decisions, we proposed to use services for assessing the importance of the determined quality characteristics of products and minimizing deviations of the proposed solutions from the formed functional and non-functional requirements. The methods of ontological engineering and data modelling allow us to dynamically develop an innovative project and support various versions of the project in the design process. Application of the proposed technology for designing innovative processes to create products and services at network enterprises using i4.0 systems will improve the quality of design decisions, increase the dynamism and continuous design of innovative projects.