Stock price analysis based on the research of multiple linear regression macroeconomic variables

Abstract

The article uses SPSS statistical analysis software to establish a multiple linear regression model of short-term stock price changes of domestic agricultural listed companies. The article uses a stable time series based on the ARMA model for stable agricultural value-added, fiscal expenditure and market interest rates. The regression method is used to study its impact on the stock price index. Compared with the existing stock forecasting methods, this method has simple data collection and no specific requirements for data selection, and the prediction results have a high degree of fit. Therefore, this method is suitable for most stocks.

Pre and Post-COVID-19 Financial Performance of Oil and Gas Companies: An Absolute and Relational Study of Financial Variables

“…Energy consumption in India has fallen due to the outbreak of the COVID-19 pandemic [2] and reduced the demand for oil and gas [3]. The profits and profitability of the firms depend on the demand and the sale prices of the products while the sale prices are also governed by demand and supply [4][5][6]. In COVID-19 pandemic period, supply of the oil and gas from overseas and domestic demand for oil and gas decreased.…”

“…The financial success of enterprises is critical to accomplishing this goal [11]. Financial performance analysis is a useful criteria for firms to fulfill their objectives, adjust to changing market circumstances, enhance their company practices, and be prepared to respond to potential difficulties [5,6,12]. As a result, financial performance is becoming an increasingly crucial problem not just for enterprises but also for national economies [13].…”