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Competitive advantage is the key to a company's success, and the business strategy represents a long-term plan to achieve a competitive advantage by affecting the company's financial behavior. This research studies the interaction of business strategy, competitive advantage, and financial strategy to explore whether companies choose different financial strategies based on their business strategies as well as what role competitive advantage plays in their decision-making. By building a composite index and observing maturity mismatched investment, this research quantifies the risk level of business strategies and financial strategies. Using text analysis of a company's annual report, the research builds a dummy variable to measure the competitive advantage. Based on the samples of A-shares listed on the China Shanghai and Shenzhen stock exchanges from 2007 to 2016, the research shows that the risk level of business strategy and financial strategy tends to move in opposite directions. If a company embraces an aggressive business strategy, it is more likely to choose a conservative financial approach in terms of lower overall risks, but for the company with a competitive advantage, the negative correlation between these two strategies is weakened. Further analysis found that company ownership, free cash flow, and the quality of internal control also play a significant role in the interaction between business strategy and financial strategy. Our findings not only enrich research on business strategy and financial behavior, but also deepen the understanding of competitive advantage and corporate financial strategy theoretically. [ABSTRACT FROM AUTHOR]

Companies listed on the stock market must devote a great deal of attention to their market position. They must increase their competitive advantage in the undeniably key process of the issuance of stocks. As the issuance of preferred stocks has increased after the last crisis and in the current period of low interest rates in Europe, they are becoming more favoured investment instruments, we decided to analyse the real properties of preferred stocks in Europe in order to increase the efficiency of joint-stock companies. Using a dataset comprising all companies having both common and preferred stocks issued and traded on European markets between 2009- 2016, we determined the relationship of risk (measured by beta coefficients) and price volatility among common and preferred stocks and bonds in Europe. Our findings show beta coefficients of preferred stocks as systematically lower than beta coefficients of common stocks. Considering a difference of up to 10% as negligible, however, preferred stocks showed a similar or higher beta coefficient than corresponding common stocks of the same company in 53% of cases, whereas for 33% of cases, the difference is only ±10%. Coefficients of variation in prices showed a similar relationship, with only a negligible portion of preferred stocks bearing fixed (stable) dividends. This result implies that currently traded preferred stocks in Europe in fact do not possess such characteristics they are typically said to have, and in many cases they incur as comparable a risk as do common stocks. This essential information should help to increase the efficiency and competitiveness of joint-stock companies. [ABSTRACT FROM AUTHOR]

Gold belongs, thanks to its extraordinary qualities, to the most interesting and well-known precious metals as far as investment is concerned. The paper aims to estimate the future development of the gold price and determine whether the gold price actually increases in times of economic recession. For the purpose of the analysis, data about the daily gold price from 2006 to July 2020 is used. To elaborate this paper, five methods of time series balancing were employed, namely Neural Networks, Decision Tree, Gradient Boosted Tree, Linear Regression, and Nearest Neighbours. The methods are applied to a training data set, and the final model is tested on the testing data set. The respective models' residues are presented in a graphic form as well as the Probability Density Histogram, Training Data Set Residues Histogram, and a graph of testing data set residues. The future development of the gold price for the next calendar year is predicted. Market participants buy gold in the first moments of the economic recession in order to keep the value of their property. Consequently, however, they lack cash and are forced to sell the gold again. A similar development can be expected now too. A global economic recession can be expected. Debtors will have to get rid of their investments, which will cause the gold price to fall dramatically. The gold price reaches its maximum value at the end of the observed period; then, it should decrease progressively to the end of 2020. At the beginning of 2021, the price should slump. Then, in the following six months, it should follow a growth path again. [ABSTRACT FROM AUTHOR]