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The topic of supply and demand for jobs is a very current and important topic, as their prediction contributes to the future operation of an organization. The base source of data is information and data obtained from online databases of the Ministry of Labor and Social Affairs of the Czech Republic. The aim of this work is to predict the supply and demand for jobs up to 2022, using the method of exponential alignment of time series. With the existence of natural unemployment, not all job positions will be filled. In such a situation, organizations will have to demand labor from abroad. In the event that organizations are unable to secure labor from abroad, they will have to reduce their activities and the associated volume of production they produce. Last but not least, the organization can start going bankrupt. In the forecast, we do not address the structure of unemployment by the highest attained education or by profession. We see the application benefits of the work in companies that manage human resources. At present, the prediction of future development is mostly at the national level and in the Czech Republic it is at the beginning of its journey. The developed methodology will enable organizations to monitor the current situation on the labor market and respond to changes in the short and long term.

The Phillips curve was supposed to mean an expansion of the doctrine based on the original regulatory ideas of J. M. Keynes. At the time of its inception (1950s), it gave governments theoretical hope, coming from the possibility of choosing a negative correlation between the price level (P) and the product (Y). Her early denial (at least in the short term) by Milton Friedman, on the other hand, has not changed anything about other applications that are still relevant until present time. In the fact, advantage of Phillips curve is her ability based on broad-spectrum use for any type of national economy. The aim of this work is to determine the shape of the Phillips curve for the Czech Republic in the period from 2000 to the present and to compare its shape with the shape of the original Phillips curve. The method of regression analysis is used here, comparison and prediction are performed using time series. In this paper, we find out what the short-term Phillips curve looks like for the Czech Republic, that it does not coincide with the original Phillips curve, and that in the future we can count on a growing correlation between inflation and unemployment.

This paper examines the development of the global copper market using sentiment analysis to analyse the opinions, feelings, and subjectivities of the research subject. Particular attention is paid to one of the most important international mining companies in the world, Freeport-McMoRan. Texts related to Freeport-McMoRan and the relevant copper market were processed using MS Excel software and artificial intelligence, specifically recurrent neural networks. Sentiment analysis was followed by regression analysis to track the copper price trend over the same period. Confirmed the existence of inverse relationship between the copper price and the results of the sentiment analysis performed. Positive results of the sentiment analysis affect the sentiment of the copper market, thereby affecting the copper price with a time lag. [ABSTRACT FROM AUTHOR]

The paper analyses the current Czech methodology of accounting for experimental animals and animals sold as pets at retail pet stores while assessing whether the methodology is in line with ethical principles, as pets sold at retail are treated as goods in the accounts and experimental animals are accounted for as material. The paper proposes procedures for accounting for experimental animals and animals sold at retail. [ABSTRACT FROM AUTHOR]

Making investment decisions in modern conditions is quite complicated. On the example of the construction industry, the article tests the approach based on WACC and WARA analyses. The risk and profitability of the specified markets were analyzed based on the Efficient Frontier method. The Polish market and the group of Euronext markets were selected for comparison. The necessity of calculation of WARA based on only significant assets was determined. The differentiation between WARA and WACC in the Polish construction market can be overcome by maximizing goodwill and intangible assets and minimizing tangible assets. It reveals problems not in the stock market, but in the industry and the economy as a whole, particularly the lack of functioning markets such as the stock market for individual assets. The role of intangibles is different for Euronext markets. On the other hand, the requirement of the international accounting standards to transfer goodwill from assets to "other income" in case of a negative value (bad will) makes adequate consideration of goodwill in the WARA model virtually impossible. Another problem is a calculation of relative weights of assets in conditions of occurrence of both positive and negative values, which creates prerequisites for different approaches and interpretations. Building material that is used in the construction industry tries to improve the environment. the source of building materials are natural resources such as sandstone. [ABSTRACT FROM AUTHOR]

Copper and aluminium prices have long been influenced mainly by non-renewable resources and the industry's widespread use of copper and aluminium for their desired properties. Metal commodities are irreplaceable for the industry of developed countries, and their shortage in the covid times also increases the price and consequently the price of products made from them. As copper ore stocks continue to decline, suitable substitutes should be sought. The paper discusses the potential of copper substitution by aluminium and subsequently the development of prices and production of copper and aluminium, including a prediction about the future development. Research data were obtained from Market. business insider (2021) and Investing.com (2022) converted to time series. The price is shown in US dollars per tonne and the production value in millions of tonnes. Development data were processed using artificial intelligence and recurrent neural networks, including the Long Short Term Memory layer. Neural networks, as such, have great potential to predict these types of time series. The annual copper and aluminium production data were processed using a regression function. Neural networks could not be used due to the smaller data range. The results show that the 1NN30L neural network with an LSTM layer and considered a 30-day delay is the most suitable network for forecasting future copper prices, and the 3NN30L neural network with an LSTM layer and considered a 30-day delay is the most suitable network for forecasting future aluminium prices. The forecast has confirmed that the price of copper will fall at the end of 2021, and the trend will be constant in the next planned period. Aluminium will also fall sharply at the end of 2021; at the beginning of 2022, the price level is predicted to rise to that of 30 October 2021, and thereinafter the trend will be almost constant. Research has confirmed that copper and aluminium may be imperfect substitutes in some respect, but they can generally be considered complementary. Copper mining has stabilised in recent years, but aluminium production has increased significantly in the last decade, and it can be expected to grow in the near future. [ABSTRACT FROM AUTHOR]