1Doctor of Economic Sciences, Professor, Department of Finance, Accounting and Audit, Faculty of Economics, Ukrainian State University of Railway Transport, Kharkiv, Ukraine
2PhD in Economics, Associate Professor, Professor, Kyiv School of Economics Graduate Business School (KSE GBS), Kyiv, Ukraine
3Doctor of Economic Sciences, Professor, Head of the Department of Enterprise Economics, Accounting and Audit, Bohdan Khmelnytsky Cherkasy National University Educational-Scientific, Institute of Economics and Law, Cherkasy, Ukraine
4Doctor of Sciences in Economics, Professor, Head of the Department of Finance, Accounting and Taxation, Chernivtsi Institute of Trade and Economics of SUTE, Chernivtsi, Ukraine
5PhD in Economics, Associate Professor of the Department of Management, Faculty of Management and Business, Kharkiv National Automobile and Highway University, Kharkiv, Ukraine
*Corresponding author: polkya@meta.ua (ORCID ID:: 0000-0003-2042-8277)
Online published on 18 February, 2025.
The ARIMA, VAR, and GARCH models are examined at in this corporate finance study to see how they affect strategy planning, risk management, and choosing investments. The work explains about how statistical models can be used to guess important financial factors like how the stock market will do, interest rates, and market changes. By adding predicted future cash flows to the equation for how stock prices change, our method makes models better at predicting the future and gives businesses more accurate financial predictions. The review of the study showed that the ARIMA model is very good at guessing how much a stock will return. The VAR model fit past data very well, which means it can be used to make accurate financial forecasts. There are some doubts about how accurate the GARCH model is, but it is still useful for assessing risk because it is very good at predicting market instability. Including expected cash flows in our models improved our research by giving us a clearer picture of how the changes would impact our future investment and financial plans. The results show that mixing ARIMA, VAR, and GARCH models might help in figuring out how well a company will do financially. However, there is not a single model that works perfectly for everyone. This could help decide what decisions to make, come up with plans, and lower the risks. The results of the study helped corporate finance experts to choose better strategies. Based on the data, we need to find new ways to predict the future that can adapt to changing market conditions and help businesses succeed in the long run in an always changing circumstances.
⓿ The exploration result showed that ARIMA, VAR, and GARCH models demonstrated good predictive ability regarding future cash flows. The GARCH model demonstrated the least accuracy because it cannot fully estimate market volatility.
⓿ The simultaneous use of ARIMA, VAR, and GARCH models gives a broader picture of economic processes and makes forecasts more accurate. These models can be adapted to constantly changing market conditions, allowing you to make more informed investment decisions.
Econometric Models, ARIMA, VAR, GARCH, Stock Market Analysis, Risk Analysis, Financial Projections, Economic Modeling
