Evaluation of the Accuracy of Machine Learning Predictions of the Czech Republic’s Exports to the China

The objective of this contribution is to predict the development of the Czech Republic’s (CR) exports to the PRC (People’s Republic of China) using ANN (artificial neural networks). To meet the objective, two research questions are formulated. The questions focus on whether growth in the CR’s exports to the PRC can be expected and whether MLP (Multi-Layer Perceptron) networks are applicable for predicting the future development of the CR’s exports to the PRC. On the basis of previously obtained historical data, ANN with the best explanatory power are generated. For the purpose specified, three experiments are carried out, the results of which are described in detail. For the first, second and third experiments, ANN for predicting the development of exports are generated on the basis of a time series with a 1-month, 5-month and 10-month time delay, respectively. The generated ANN are the MLP and regression time series neural networks. The MLP turn out to be the most efficient in predicting the future development of the CR’s exports to the PRC. They are also able to predict possible extremes. It is also determined that the USA–China trade war has significantly affected the CR’s exports to the PRC

Analysis of government bonds and prediction of their development after the pandemic caused by COVID-19

This paper describes the current state of the government bond market and predicts the future development of government bond yields using the yield curve to bond maturity, spot yield curve, credit rating and simple prediction. The ongoing economic crisis caused by the COVID-19 pandemic is changing the lives of many people. In order for each individual country to help its households, prevent mass job lay-offs and high mortality, their fiscal budget deficits are growing to unexpected heights. The aim of this paper is to analyse government bonds as one of the tools that can help both the state and individual households at this time. Government bond yields are analysed and compared with other countries based on the development of government bonds using credit ratings, yield curves to maturity, spot yield curves and simple historical development of government bonds from the previous economic crisis in 2008. Based on the results, we conclude that countries severely affected by the COVID-19 pandemic and subsequent mortality, such as Italy, have a relatively stable yield. In contrast, for countries such as the Czech Republic and South Korea, yields to maturity at both ends are relatively declining

Bitcoin: an alternative currency to pay for goods and services or a useful investment tool?

Research background: Bitcoin is defined as digital money in a peer-to-peer decentralized payment network, an amalgam hybrid between fiat and commodity currency without a real value. This digital currency is also independent of any government or currency administration. Purpose of the article: This article explores whether bitcoin works as a medium of exchange or relates to assets, focusing on its current use and future utility regarding its characteristics. Methods: Analysing bitcoin statistical features, we found no connection with traditional asset categories such as stock, bonds and commodities either in intermediate time, or periods of financial crises. Findings & Value added: The study suggests that investors’ abiding interest in bitcoins can have a positive impact on their liquidity in the real time

Corporate Environmental Responsibility through the Prism of Strategic Management

This contribution considers the theoretical, methodological, and analytical aspects of implementing a strategic approach to the management of corporate environmental responsibility in practice. The economic and normative approach to understanding the essence of corporate environmental responsibility is revealed; the key factors are systematized. Based on the generalization of theoretical and methodological provisions for corporate environmental responsibility, the authors formulated a concept for the strategic management thereof. An approach to understanding the content and forms of environmental responsibility at different stages of a company’s lifecycle is formulated. The main indicators that enable the analysis of corporate environmental responsibility from the point of view of the chain “inputs-processes-outputs” are systematized. Analytical studies of corporate environmental responsibility are conducted on the basis of information concerning automotive companies, in particular in terms of the following main areas: the study of global trends, monitoring of environmental goals and their reflection in development strategy, comprehensive analysis of environmental responsibility, the study of the balance of environmental and economic indicators. To achieve the aforementioned, the following were used: quantitative and qualitative methods, analytical and comparative methods of processing, analysis and synthesis of statistical information, economic and mathematical modelling, etc. The mechanism of transforming global environmental challenges into environmental responsibility management in practice is substantiated. An organizational mechanism is put forward for developing an environmental responsibility management system based on a strategic approach focused on implementation in practice. The key tools for implementing theoretical and methodological provisions in management practice are also identified

Bankruptcy or Success? The Effective Prediction of a Company’s Financial Development Using LSTM

There is no doubt that the issue of making a good prediction about a company’s possible failure is very important, as well as complicated. A number of models have been created for this very purpose, of which one, the long short-term memory (LSTM) model, holds a unique position in that it generates very good results. The objective of this contribution is to create a methodology for the identification of a company failure (bankruptcy) using artificial neural networks (hereinafter referred to as “NN”) with at least one long short-term memory (LSTM) layer. A bankruptcy model was created using deep learning, for which at least one layer of LSTM was used for the construction of the NN. For the purposes of this contribution, Wolfram’s Mathematica 13 (Wolfram Research, Champaign, Illinois) software was used. The research results show that LSTM NN can be used as a tool for predicting company failure. The objective of the contribution was achieved, since the model of a NN was developed, which is able to predict the future development of a company operating in the manufacturing sector in the Czech Republic. It can be applied to small, medium-sized and manufacturing companies alike, as well as used by financial institutions, investors, or auditors as an alternative for evaluating the financial health of companies in a given field. The model is flexible and can therefore be trained according to a different dataset or environment

Impact of Selected Socio-Demographic Characteristics on Branded Product Preference in Consumer Markets

A successful brand is one of the most valuable resources a company has. Should the brand become powerful, it is supposed to reflect rational and emotional expectations of consumers, which, however, might change over time. The ability to recognize the consumers changing attitudes towards the brand is thus the prerequisite for effective brand management. The aim of the paper is to identify the correlation between selected socio-demographic characteristics and preferences for branded products by Slovak consumers, using a mathematical and statistical modelling. For this purpose, a comprehensive marketing survey has been carried out involving Slovak consumers of the minimum age of 16. The findings of the survey show a direct correlation, but varying in character and intensity, between the selected socio-demographic characteristics of respondents (gender, age, education, income) and their preferences for branded products; and based on the survey findings, the paper then provides further recommendations for non-adopting current trends in attitudes and preferences towards brands on Slovak consumer markets, that are recognized as significant sales and marketing tools, into the branding processes. However, considering different cultural, social and economic situations of different markets, it is not possible to generalize about the results of the paper as also being relevant for other markets. A successful brand in the domestic market is not a prerequisite of success in global markets

ĮSA koncepcija ir numanomas jos įgyvendinimas Cišegrado šalių MVĮ versle

The papers' objective was to present essential factors of CSR conception, quantify their intensity and compare these factors within the countries of V4. The research was conducted through an online questionnaire in the countries of V4 (Czech Republic. Slovak Republic, Poland, and Hungary) from September 2019 to March 2020. The total amount of valid questionnaires was 1,585. Stated research hypotheses were tested by chi-square and Z-score Some interesting conclusions as low knowledge of CSR concept, low intensity of (SR implementation. low ability to identify positive effects of CSR were revealed by the research whereby the opinions differ in the Czech Republic and other countries of V4. Despite some research limitations, the study's findings should be considered in light of new trends and findings. It could be argued that the corona crisis would highly determine the results of the empirical research. On the other hand. it could be assumed that the economy will gradually recover and return to normal, which causes that these results will become relevant again