Spreadsheets Tutorial : Continuing simple models with balance sheets

DataCamp · Beginner ·💰 FinTech & AI for Finance Professionals ·6y ago

Key Takeaways

This video tutorial covers creating balance sheet models in spreadsheets, including formatting cells, calculating section subtotals, and creating common size statements to analyze financial data.

Full Transcript

now that you have created income statement models we can continue with balance statement models Palace statements are the second part to modeling finances and we will use income and balance statements to build our final model in the next section these sheets contain three important parts assets liabilities and equity under assets you might see accounts receivable which is money owed to the company and other items like inventory and equipment under liabilities you might include money owed to others such as accounts payable debts and other income tax to pay later finally equity includes money paid into shareholders and retained earnings here is an example of balance statement you can format this statement in a similar way to an income statement in these models the assets should be equal to equity and liabilities added together so we have a way to check our finalized numbers after adding formulas to finalize our balance statement you will complete the same steps as the income statement first format the cells into financial format by highlighting the cells clicking format number and then financial next you will create section subtotals by typing equals sum open parenthesis selecting the cells in that section and close parentheses the total equity and liabilities section is the sum of the subtotals for equity and liability this sum should be equal to the sum we find in the total assets line to check the model to extend the two models you've learned you can use these completed sheets to create a common size statement common size statements are converted to percentages to help compare and see where money is allocated on income statements you would convert each value to a percent of sales while balance statements convert values into percent of assets or the combined total for equity and liabilities the formulas for the common size calculations are shown on the left and here on the right you can see how to enter these values in the assets section for cash and securities and column F you will type equals click on the cell for 2018 and column E and then divide by the total assets for 2018 in E 11 we want to copy this formula to all the other asset rows so we should use an absolute reference to the total assets in e 11 that means the cell reference will not change when we copy it over to do that use the dollar signs before the e and the 11 to ensure that cell does not change when you paste the formula you would repeat this process for the equity and liabilities section using the total of both to convert to a percentage your turn to practice creating balance statements including a common size version of assets

Original Description

Want to learn more? Take the full course at https://learn.datacamp.com/courses/financial-modeling-in-spreadsheets at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Now that you have created income statement models, we can continue with balance statement models. Balance statements are the second part of modeling finances, and we will use income and balance statements to build our final model in the next section. These sheets contain three important parts: assets, liabilities, and equity. Under assets, you might see accounts receivable, which is money owed to the company, and other items like inventory and equipment. Under liabilities, you might include money owed to others, such as accounts payable, debts, and other income tax to pay later. Finally, equity includes money paid into shareholders and retained earnings. Here is an example balance statement. You can format this statement in a similar way to an income statement. In these models, the assets should be equal to equity and liabilities added together, so we have a way to check our finalized numbers after adding formulas. To finalize our balance statement, you will complete the same steps as the income statement. First, format the cells into the financial format by highlighting the cells, clicking format, number, and then financial. Next, you will create section subtotals by typing equals sum open parentheses, selecting the cells in that section, and close parentheses. The total equity and liabilities section is a sum of the subtotals for equity and liability. This sum should be equal to the sum we find in the total assets line to check the model. To extend the two models you've learned, you can use these completed sheets to create a common size statement. Common size statements are converted to percentages to help compare and see where the money is allocated. On income statements, you would convert each value to a percentage of sales, while ba
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from DataCamp · DataCamp · 0 of 60

← Previous Next →
1 SQL Server Tutorial: Date manipulation
SQL Server Tutorial: Date manipulation
DataCamp
2 R Tutorial: Intermediate Interactive Data Visualization with plotly in R
R Tutorial: Intermediate Interactive Data Visualization with plotly in R
DataCamp
3 R Tutorial: Adding aesthetics to represent a variable
R Tutorial: Adding aesthetics to represent a variable
DataCamp
4 R Tutorial: Moving Beyond Simple Interactivity
R Tutorial: Moving Beyond Simple Interactivity
DataCamp
5 Python Tutorial: Why use ML for marketing? Strategies and use cases
Python Tutorial: Why use ML for marketing? Strategies and use cases
DataCamp
6 Python Tutorial: Preparation for modeling
Python Tutorial: Preparation for modeling
DataCamp
7 Python Tutorial: Machine Learning modeling steps
Python Tutorial: Machine Learning modeling steps
DataCamp
8 R Tutorial: The prior model
R Tutorial: The prior model
DataCamp
9 R Tutorial: Data & the likelihood
R Tutorial: Data & the likelihood
DataCamp
10 R Tutorial: The posterior model
R Tutorial: The posterior model
DataCamp
11 R Tutorial: An Introduction to plotly
R Tutorial: An Introduction to plotly
DataCamp
12 R Tutorial: Plotting a single variable
R Tutorial: Plotting a single variable
DataCamp
13 R Tutorial: Bivariate graphics
R Tutorial: Bivariate graphics
DataCamp
14 Python Tutorial: Customer Segmentation in Python
Python Tutorial: Customer Segmentation in Python
DataCamp
15 Python Tutorial: Time cohorts
Python Tutorial: Time cohorts
DataCamp
16 Python Tutorial: Calculate cohort metrics
Python Tutorial: Calculate cohort metrics
DataCamp
17 Python Tutorial: Cohort analysis visualization
Python Tutorial: Cohort analysis visualization
DataCamp
18 R Tutorial: Building Dashboards with flexdashboard
R Tutorial: Building Dashboards with flexdashboard
DataCamp
19 R Tutorial: Anatomy of a flexdashboard
R Tutorial: Anatomy of a flexdashboard
DataCamp
20 R Tutorial: Layout basics
R Tutorial: Layout basics
DataCamp
21 R Tutorial: Advanced layouts
R Tutorial: Advanced layouts
DataCamp
22 Python Tutorial: Time Series Analysis in Python
Python Tutorial: Time Series Analysis in Python
DataCamp
23 Python Tutorial: Correlation of Two Time Series
Python Tutorial: Correlation of Two Time Series
DataCamp
24 Python Tutorial: Simple Linear Regressions
Python Tutorial: Simple Linear Regressions
DataCamp
25 Python Tutorial: Autocorrelation
Python Tutorial: Autocorrelation
DataCamp
26 R Tutorial: The gapminder dataset
R Tutorial: The gapminder dataset
DataCamp
27 R Tutorial: The filter verb
R Tutorial: The filter verb
DataCamp
28 R Tutorial: The arrange verb
R Tutorial: The arrange verb
DataCamp
29 R Tutorial: The mutate verb
R Tutorial: The mutate verb
DataCamp
30 R Tutorial: What is cluster analysis?
R Tutorial: What is cluster analysis?
DataCamp
31 R Tutorial: Distance between two observations
R Tutorial: Distance between two observations
DataCamp
32 R Tutorial: The importance of scale
R Tutorial: The importance of scale
DataCamp
33 R Tutorial: Measuring distance for categorical data
R Tutorial: Measuring distance for categorical data
DataCamp
34 Python Tutorial: Plotting multiple graphs
Python Tutorial: Plotting multiple graphs
DataCamp
35 Python Tutorial: Customizing axes
Python Tutorial: Customizing axes
DataCamp
36 Python Tutorial: Legends, annotations, & styles
Python Tutorial: Legends, annotations, & styles
DataCamp
37 Python Tutorial: Introduction to iterators
Python Tutorial: Introduction to iterators
DataCamp
38 Python Tutorial: Playing with iterators
Python Tutorial: Playing with iterators
DataCamp
39 Python Tutorial: Using iterators to load large files into memory
Python Tutorial: Using iterators to load large files into memory
DataCamp
40 SQL Tutorial: Introduction to Relational Databases in SQL
SQL Tutorial: Introduction to Relational Databases in SQL
DataCamp
41 SQL Tutorial: Tables: At the core of every database
SQL Tutorial: Tables: At the core of every database
DataCamp
42 SQL Tutorial: Update your database as the structure changes
SQL Tutorial: Update your database as the structure changes
DataCamp
43 Python Tutorial: Classification-Tree Learning
Python Tutorial: Classification-Tree Learning
DataCamp
44 Python Tutorial: Decision-Tree for Classification
Python Tutorial: Decision-Tree for Classification
DataCamp
45 Python Tutorial: Decision-Tree for Regression
Python Tutorial: Decision-Tree for Regression
DataCamp
46 Python Tutorial: Census Subject Tables
Python Tutorial: Census Subject Tables
DataCamp
47 Python Tutorial: Census Geography
Python Tutorial: Census Geography
DataCamp
48 Python Tutorial: Using the Census API
Python Tutorial: Using the Census API
DataCamp
49 R Tutorial: A/B Testing in R
R Tutorial: A/B Testing in R
DataCamp
50 R Tutorial: Baseline Conversion Rates
R Tutorial: Baseline Conversion Rates
DataCamp
51 R Tutorial: Designing an Experiment - Power Analysis
R Tutorial: Designing an Experiment - Power Analysis
DataCamp
52 R Tutorial: Introduction to qualitative data
R Tutorial: Introduction to qualitative data
DataCamp
53 R Tutorial: Understanding your qualitative variables
R Tutorial: Understanding your qualitative variables
DataCamp
54 R Tutorial: Making Better Plots
R Tutorial: Making Better Plots
DataCamp
55 SQL Tutorial: OLTP and OLAP
SQL Tutorial: OLTP and OLAP
DataCamp
56 SQL Tutorial: Storing data
SQL Tutorial: Storing data
DataCamp
57 SQL Tutorial: Database design
SQL Tutorial: Database design
DataCamp
58 Python Tutorial: Introduction to spaCy
Python Tutorial: Introduction to spaCy
DataCamp
59 Python Tutorial: Statistical Models
Python Tutorial: Statistical Models
DataCamp
60 Python Tutorial: Rule-based Matching
Python Tutorial: Rule-based Matching
DataCamp

This video teaches how to create balance sheet models in spreadsheets, including formatting cells and calculating section subtotals, and how to create common size statements to analyze financial data.

Key Takeaways
  1. Format cells into financial format
  2. Create section subtotals
  3. Calculate total equity and liabilities
  4. Create a common size statement
  5. Convert values to percentages
  6. Use absolute references to copy formulas
💡 Using common size statements can help compare and analyze financial data by converting values to percentages.

Related AI Lessons

Up next
Quality Costing Meaning Features | Objective Advantages | Life Cycle Costing | Target Costing
Accounting MasterClass
Watch →