The increasingly meagre copper ore resources constitute one of the decisive factors influencing the price of this commodity. The demand for copper has been showing an accelerating trend since the Covid pandemic broke out. It is thereby imperative to estimate the future price movement of this material. The article focuses on a daily prediction of the forthcoming change in prices of copper on the commodity market. The research data were gathered from day-to-day closing historical prices of copper from commodity stock COMEX converted to a time series. The price is expressed in US Dollars per pound. The data were processed using artificial intelligence, recurrent neural networks, including the Long Short Term Memory layer. Neural networks have a great potential to predict this type of time series. The results show that the volatility in copper price during the monitored period was low or close to zero. We may thereby argue that neural networks foresee the first three months more accurately than the rest of the examined period. Neural structures anticipate copper prices from 4.5 to 4.6 USD to the end of the period in question. Low volatility that would last longer than one year would cut down speculators’ profits to a minimum (lower risk). On the other hand, this situation would bring about balance which the purchasing companies avidly seek for. However, the presented article is solely confined to a limited number of variables to work with, disregarding other decisive criteria. Although the very high performance of the experimental prediction model, there is always space for improvement – e.g. effectively combining traditional methods with advanced techniques of artificial intelligence.

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China is the second-largest economy in the world. Recently it has shown a significant trend of financialization. The financial industry is becoming increasingly influential across the whole country. However, there is much negative information about its prevalent luxurious lifestyle. According to the finding presented in this paper, corporate financialization may cause the luxury culture of the financial industry to spread to non-financial companies, and the excessive perquisites reflect the luxury consumption of non-financial companies’ managers. This paper aims to determine the relationship between corporate financialization and excessive perquisites, as well as explore the mutual relationship between the two, in particular the role of luxury culture. Based on a sample of A-share companies listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2021, this paper uses the difference between the total perquisites and the expected normal perquisites determined by economic factors to identify excessive perquisites. The Penman-Nissim framework is employed to measure corporate financialization and OLS regression analysis is performed. The empirical results show that the phenomenon of corporate financialization has a significant positive impact on excessive perquisites. Further research shows that such an impact is only evident during the period associated with established luxury culture excessive perquisites. This relationship can also be influenced by the skills and professional experience of managers, the level of corporate cash holdings, and investment income. This paper confirms the effect of luxury culture on firms’ financial behaviour and identifies new factors influencing excessive perquisites.