What Is Financial Modeling?
Financial modeling refers to the use of mathematical methods or computer methods to classify, sort, and link various types of information of an enterprise according to the main line of value creation, and complete functions such as analysis, forecasting, and value evaluation of the financial situation of the enterprise.
Financial modeling
Right!
- Chinese name
- Financial modeling
- Method
- Mathematical method or computer method
- Main line
- Value Creation
- Evaluation
- Analysis, forecasting and valuation of financial conditions
- Financial modeling refers to the use of mathematical methods or computer methods to classify, sort, and link various types of information of an enterprise according to the main line of value creation, and complete functions such as analysis, forecasting, and value evaluation of the financial situation of the enterprise.
- Financial Modeling-Decision Modeling
- Forecasting operating financial results, inputting core factors of revenue, cost and expenses, and predicting possible operating results of decision-making
- The more uncertain the external operating environment is, the more necessary it is to use forecasting tools to evaluate the business results that decisions may bring. Although the industries are different, the influencing factors of net profit are the same. Cool analysis combines EXCEL with a financial professional perspective to complete the forecasting model. For example: forecast profit statement, forecast cash flow, break-even point, sensitivity analysis.
- Financial modeling covers a very broad area: from simple tabulation to cost summation and turning it into a complex risk model for a project. In addition, many other aspects need to be considered in the design of the model. Specifically, financial modeling must consider: establishing special operating procedures for the answer to specific business problems. Such as the cash flow statement and its volatility; analysis and processing of the data; incorporating future factors into the model consideration, and examining the future situation; quickly and accurately transforming the data into management information; testing hypotheses in a "safe" environment, Such as project plans; a structured approach to support management decisions; a more accurate understanding of the relevant variables and rules in the problem; a better understanding of the changing process of the variables and how they change; identifying key variables and examining their sensitivity .