Case Study: Mortgage Trading Analysis in Power BI
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Play a junior trader at a mortgage lender in Power BI: clean loan data, judge buyer bids, strike a trade and work out what it earned.
Mortgage trading analysis in Power BI puts you on the trading desk of Sooper Mortgage, a mortgage originator, as a new junior trader. You pick a population of loans to sell, weigh each loan and every bid that prospective buyers send in, strike the trade, and then study what it earned. The scenario also traces how money moves through the financial system as it passes between big investment banks, a lending firm and individual borrowers.
What You Will Achieve
- Clean a mortgage dataset in Power BI and amortize loan balances with DAX
- Judge how risky each loan is from its ratios before it goes up for sale
- Rank buyer bids against market benchmarks and decide which ones win
- Measure what a trade earned and argue for a pricing approach based on the results
Program Overview
Mortgage Data and the Financial System
A look at how the financial system works and who plays which role, followed by getting the loan data ready for trading.
- Roles in the financial system and what a mortgage is
- Cleaning mortgage data and checking risky ratios
- Loan statuses and the post-close process
- Principal payments and scheduled balances
Bids, Market Data and Trade Execution
The bids received on the loans are compared with compiled market data so the winners can be picked and the trades struck.
- Trading mortgages in the capital markets
- Compiling market data and benchmarking
- Calculating the trade premium
- Choosing winning bids and executing the trade
Trade Profit and Pricing Analysis
With the trades struck, the analysis turns to their profit and to the business strategy of Sooper Mortgage.
- Pricing in profit and working toward a target profit
- Reviewing the business strategy behind the trades
- Storytelling with the results
- Making a pricing recommendation
Certificate Awarded (Paid)
Job Outlook
Loan pricing and mortgage trading analysis of this kind belong to lending firms, trading desks in the capital markets, and the analysts who build Power BI models and DAX measures on loan data.
Good for: Power BI users comfortable with DAX who want a finance scenario for practicing data modeling on loan data, buyer bids and a trade to price.
Keep in mind: It follows a single trading cycle at one mortgage originator, and the mortgage and market background is taught as the scenario unfolds.
Bottom line: A finance scenario that carries Power BI practice through a full mortgage trade and ends with a pricing recommendation argued from the data.
Frequently Asked Questions
What role do I play in the scenario?
You join the trading desk of Sooper Mortgage, a mortgage originator, as a new junior trader. The desk selects loans to sell, reviews the bids that buyers send and executes the trade, so each task in Power BI serves a business decision.
Which parts of the financial system does the case explain?
It opens with the financial system and the roles within it, explains what a mortgage is and the post-close process, and later covers how mortgages trade in the capital markets and what a trade premium is.
What does the closing chapter ask me to deliver?
After the trades are struck, you price profit into them, work toward a target profit and review the business strategy of Sooper Mortgage. The chapter ends with telling the story of the analysis and making a pricing recommendation.
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