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Financial Forecasting in Python

中级技能水平
更新时间 2021年12月
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.
免费开始课程
PythonApplied Finance
4小时
12 视频
49 道练习
4,050 XP
13,126
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课程描述

In Financial Forecasting in Python, you will step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast, the basics of income statements and balance sheets, and cleaning messy financial data. During the course, you will examine real-life datasets from Netflix, Tesla, and Ford, using the pandas package. Following the course, you will be able to calculate financial metrics, work with assumptions and variances, and build your own forecast in Python!

先决条件

Introduction to PythonIntermediate Python
1

Income statements

In this chapter, we will learn the basics of financial statements, with a specific focus on the income statement, which provides details on our sales, costs, and profits. We will learn how to calculate profitability metrics and finish off what we have learned by building our profit forecast for Tesla!
开始章节
2

Balance sheet and forecast ratios

In this chapter, we will learn a bit more about the balance sheet, covering assets and liabilities and specific ratios to help evaluate the financial health and efficiency of a company, as well as how these ratios can assist us in building a great forecast.
开始章节
3

Formatting raw data, managing dates and financial periods

We have gotten a basic understanding of income statements and balance sheets. However, consolidating data for forecasting is complex, so in this chapter, we will look at some basic tools to help solve some of the complexities specifically relating to finance - working with dates and different financial periods, and formatting our raw data into the correct format for financial forecasting.
开始章节
4

Assumptions and variances in forecasts

In this chapter, we will be exploring two more aspects to creating a good forecast. First, we will look at assumptions, what drives them and what happens when an assumption changes? Next, we will look at variances, as a forecast is built at one point in time, but what happens when the actual results do not correspond to our forecast? We need to build a sensitive forecast that can be sensitive to changes in both assumptions and take into account variances, and this is what we will explore in this chapter.
开始章节
Financial Forecasting in Python
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