Кафедра "Підприємництво, торгівля і логістика"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/32369

Офіційний сайт кафедри http://web.kpi.kharkov.ua/business

Від 2021 року кафедра перейменована та має назву "Підприємництво, торгівля i логістика" (Наказ 552 ОД від 26.11.2021 року), попередня назва – "Підприємництво, торгівля та експертиза товарів", первісна – кафедра комерційної, торговельної та підприємницької діяльності.

Кафедра комерційної, торговельної та підприємницької діяльності заснована в 2017 році.

Кафедра входить до складу Навчально-наукового інституту економіки, менеджменту і міжнародного бізнесу Національного технічного університету "Харківський політехнічний інститут". Викладачі кафедри є членами Харківського осередку Українського товариства товарознавців і технологів (УТТТ), що входить до Міжнародній асоціації товарознавства, інновацій та сталого розвитку (International Association of Commodity Science, Innovation and Sustainability) IACSIS.

У складі науково-педагогічного колективу кафедри працюють: 3 доктора наук: 2 – економічних, 1 – технічних; 7 кандидатів наук: 4 –економічних, 3 – технічних; 3 співробітника мають звання професора, 6 – доцента.

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  • Ескіз
    Публікація
    Investigation of modern investment opportunities with cryptocurrency market: optimization
    (2024) Chernova, Natalia; Serhiienko, Olena; Bril, Mykhailo; Bilotserkivskyi, Oleksandr; Kochorba, Valeriia
    The research aim is to study effects of cryptocurrencies inclusion into an in vestment portfolio. To achieve the aim, portfolios with different composition of traditional and crypto assets are to be formed and compared. Methodology. It is proposed to conduct the following steps of the appropriate algorithm of investigating modern opportunities with cryptocurrency market: 1) preliminary analysis of the relationships and interdependencies between traditional assets and crypto assets; 2) formation of the initial set of crypto assets that can be potentially included into portfolio; 3) efficient frontier assessment for portfolios with different initial composition of assets; 4) comparative assessment and result analysis. Findings. The algorithm was implemented for the initial set of five most common traditional assets and ten cryptocurrencies. The latter constituents list was formed according to the value of market capitalization. Than the initial set of crypto assets was reduced according to their multidimensional distances from traditional assets. The results obtained allow to conclude that there are opportunities of portfolio efficiency increase via crypto assets inclusion in its structure. The increase value varies noticeably and depends on the particular kind of crypto assets, their total share and number. Originality. This research suggests to conduct additional preliminary procedures to choose potential candidates to be included into the traditional portfolio among initial set of crypto assets. Firstly, market capitalization value and low correlations with traditional portfolio constituents are taken into account. Secondly, all assets are presented as points in two-dimensional risk-return space and crypto assets are chosen according to the multidi mensional distance measure value.
  • Ескіз
    Публікація
    Wavelet Analysis Methodology as a Tool for Predicting Cryptocurrency Price Dynamics
    (2021) Lyashenko, Vyacheslav; Sergienko, Olena; Stepurina, Svitlana
    The stock market allows you to attract free investment resources, redistribute free financial resources between various spheres of the economy, business entities. For this, various tools and mechanisms for raising funds are used. Cryptocurrency is one of the tools of the modern stock market. The attractiveness of cryptocurrency, sharp and rapid changes in cryptocurrency prices necessitate various studies. At the same time, it is important to consider not only the dynamics of prices for cryptocurrencies, but also the mutual dynamics of prices between different types of cryptocurrencies. This is important in the aspect when choosing and building various forecasting models, assessing the mutual dynamics of cryptocurrency prices. To solve such a problem, it is necessary to carry out a complex and comprehensive analysis of the data. At the same time, it is important to obtain additional information that will be useful in the corresponding analysis. For this, it is proposed to use the wavelet ideology. We consider wavelet coherence as a data analysis tool. This choice is justified, and also the feasibility of its use on various datasets is confirmed. The paper deals with the mutual dynamics of prices for various types of cryptocurrencies. For this purpose, the corresponding estimates of the wavelet coherence are considered in the work. These estimates are based on real data. These estimates allow a number of conclusions to be drawn about cryptocurrency price prediction. In the work, information is presented in the form of various graphs and diagrams. This allows us to repeat and check the obtained estimates of the wavelet coherence, to evaluate the results that have been obtained.