Uticaj berzanskih indeksa i cena sirovina na kretanje prinosa hartija od vrednosti kompanije Caterpillar

Abstract

The goal of this paper is to examine the effect of selected stock market indices and the market prices of chosen raw materials on the movement of future daily returns of Caterpillar's shares. Historical data on stock returns and other relevant factors can be utilized to build statistical models for forecasting future market movements. Daily time-series data were collected from Yahoo finance for a five-year period. In this study, we use multiple linear regression to predict the returns of CAT shares. The model results can be analyzed to identify patterns, trends, and insights that may be useful for forecasting. The results show that the prediction accuracy of the proposed model, with four additional predictors, is 13.3% higher than the benchmark model, which only used the SPY market index (SPDR S&P 500 ETF) to explain the variability in CAT stock returns. The research confirmed that, in addition to the SPY market index, the performance of the PKB (Invesco Dynamic Building and Construction ETF) fund, as well as the prices of copper, steel, and aluminium have a statistically significant impact on the movement of CAT stock returns. The practical implication of this study is that investors, when deciding whether to invest in CAT shares, must consider not only systematic factors but also the performance of shares within its supply chain. The implication highlights the importance of analyzing Caterpillar's entire business system when making investment decisions. Such predictions contribute to a better understanding of the characteristics that enable optimal aggregation of information and efficient price determination. They also assist investors in selecting an investment strategy aligned with their objectives