🍞 Why You Should Learn How To Gamble
How Taking Calculated Risks Can Benefit Your Career
🥯 This edition of the Big Baguette is brand spanking new. In 2023, the Big Baguette will be going deep on a specific topic each month. This month’s topic…risk-taking.
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Hey Loyal Bread Crumbs People 👋🏻,
As you read above, we are switching up the Big Baguette format. This year, we will be writing fewer posts (~1 per month). By pruning quantity, we will increase quality. Each Big Baguette will go deep on a topic we find compelling and think you’d enjoy learning about. Our goal is to have each edition improve your mental, physical, or financial fitness. These categories are guide posts, not rules. If we find a topic particularly compelling, we will write about it whether or not it hits on one of those three themes.
Our aim for the reading time is somewhere between 5-10 minutes. A quick Sunday night read to set you up for a successful week. With that, let’s jump in.
Thinking Like a Gambler
We're all gamblers in some way. Every time we make a decision about an uncertain future, we're placing a bet with our time, money, and resources. Take this newsletter for example. I'm betting my time that writing it will pay off in the future by improving my thinking and economic value. But there's always a chance that it could be a waste of time and energy.
Think about the bets you make in your own life, whether it's investing time and energy into your job, relationships, or other pursuits. Getting married is a huge bet on the future, for example. If we are making bets all the time, why not get better at it?
That's the goal of this month’s deep dive: to help us all become better at making bets with our resources. And what is the best place to start? With one of the biggest betting industries in the world, banking.
How Banks Work
Banks promise to keep your money safe and accessible when you deposit it with them. They also offer you interest but it sucks. I think my Chase savings account pays me a measly interest rate of 0.01%. So how do banks make money? They engage in lending, an activity that dates back to ancient Babylon. Banks lend money to people who need it, like your neighbor who wants to buy a new house. If your neighbor pays back the loan with interest, Chase will make a profit, called Net Interest Income or NIM, which is the interest rate they charge borrowers minus the interest rate they pay depositors. For example, if they charge 7.00% on your neighbor’s loan and pay 0.01% interest to you, their NIM is 6.99%.
NIM = (Interest rate banks charge for a loan) - (Interest rate banks pay depositors)
NIM = (7.00%) - (0.01%) NIM = 6.99%
However, if your neighbor can't pay back the loan, Chase will take the house as collateral and sell it to recover the value of the loan and interest. If the bank can't cover the loan and interest, they record a Loan Loss or LL.
LL = (Outstanding balance of the loan) - (Cash collected by selling the collateral)
For banks, the key is to ensure their NIMs outweigh their LLs; otherwise, they will lose money and may face government intervention. This business model makes banks some of the largest gambling institutions in the world. They are making bets on the future success of borrowers and their ability to repay the loan. By studying how banks manage risk and make bets, we can improve our own gambling skills.
How Banks Gamble: The PD-LGD-ECL Framework
A bank employee's core job before approving a loan is to predict the likelihood that the borrower will default on the loan and the potential losses that could occur in that scenario. Banks use the Probability of Default (PD) to estimate the likelihood of default and the Loss Given Default (LGD) to measure the loss that could occur in the event of a default. To calculate the PD, the bank takes into account the borrower’s creditworthiness. The better the creditworthiness, the lower the PD.
To calculate the LGD, the bank takes the difference between the loan balance and the value of the collateral, in this case, your neighbor’s home. Say your neighbor defaults. The loan balance is $100,000 and the house sells for $70,000. The LGD in that situation is 30%.
LGD = ((Loan Balance) - (Collateral Value)) / (Loan Balance) LGD = ($100,000 - $70,000) / ($100,000)
LGD = $30,000 / $100,000
LGD = 30%
For every new loan, the bank combines the LGD and PD to arrive at the Expected Credit Loss or ECL. Think of the ECL as a crystal ball that banks use to make smart decisions about the future. By using this metric, banks can make calculated bets on whether or not a borrower will repay their loan and if the bank can stomach the loss. The ECL is calculated by multiplying the PD, LGD, and loan value together.
For example, let's say your neighbor is applying for a loan and has good credit, so the bank estimates his PD to be 10%. If the estimated LGD is 30%, then the ECL would be $3,000. ECL = PD x LGD x Loan Value ECL = 10% x 30% x $100,000
ECL = $3,000
Now, what does the bank do with the ECL? They compare it to the profit they could make on the loan, the NIM. For your neighbor’s loan, the NIM is $6,999 (6.99% * $100,000). If the NIM is greater than the ECL, the bank does the deal. In this case, $6,999 is greater than $3,000 so the bank would take the bet and do the deal.
Because the future is unpredictable, banks use the ECL to make informed decisions today about what might happen tomorrow. And we can apply this same approach to our own decision-making process.
Applying the PD-LGD-ECL Framework: Student Loans
Let's use the PD-LGD-ECL framework to help you decide if taking out a loan to pursue a graduate degree is a smart financial move for you.
First, let's talk about PD, which is the probability of you being able to complete your program and secure a job that will enable you to pay back the loan. Assuming you're confident in your abilities, let's estimate your PD to be 10%.
Next, there's LGD, which is the potential loss the bank could incur if you default on the loan. In this case, the LGD is the difference between the loan amount and your future earnings. Let's assume that although you estimate you can earn enough to pay back the loan, there's still a risk that you might not, so we'll estimate your LGD to be 50%.
To calculate the ECL, we just multiply the PD by the LGD and the amount of the loan. So for a $50,000 loan, the ECL would be:
ECL = PD x LGD x Amount of loan
ECL = 0.1 x 0.5 x $50,000
ECL = $2,500
So, if you think you can earn enough to pay back the loan, pay your living expenses, and still make a profit, an ECL of $2,500 might be acceptable. However, if you're uncertain about your ability to repay the loan or if the potential profit is low, then taking out this loan might not be the best decision for you.
Now, let's say the degree only costs $25,000. Would that change things? To find out, we can turn to the next biggest betting industry in the world, poker.
The Poker Analogy
In the context of getting a loan for a graduate degree, we can use the poker concept of expected value to make a decision. The expected value in poker is the average amount you can win or lose based on probabilities and potential gains or losses.
To apply this framework to the decision of taking out a loan for a degree, we can think of the potential future earnings as the "pot" and the loan amount as the "chips" we're willing to bet to pursue higher wages. The “strength of our hand” is our ability to complete the degree and secure a well-paying job. The "strength of other hands" represents competition for jobs in the industry.
Just like in poker, economic conditions can be seen as "community cards" that affect the value of our degree. These conditions could include the job market, industry trends, and overall economic conditions.
Applying the Poker Analogy: Expected Value v1
Let's use the expected value framework for two scenarios: (1) deciding between the two degree options and (2) deciding between two job offers.
For the degree options, let's say you have the choice between a $50,000 degree that will guarantee you a $100,000 annual salary, or a $25,000 degree that will secure you an $80,000 annual salary. We'll assume a five-year time horizon for this decision.
To determine which degree option is the better bet, we need to calculate the expected value for each option. The expected value is the sum of the probability of winning multiplied by the amount won, minus the probability of losing multiplied by the amount lost. To do this, we need to consider factors like your academic background, experience in the field of study, and the competition in the job market for each degree option.
Let's assume that you have a 60% chance of completing the $50,000 degree and securing a job that pays $100,000 annually and a 90% chance of completing the $25,000 degree and securing a job that pays $80,000 annually.
For the $50,000 degree:
Expected Value = (0.60 * $100,000 * 5) - (0.40 * $50,000) = $300,000 - $20,000 = $280,000
For the $25,000 degree:
Expected Value = (0.90 * $80,000 * 5) - (0.10 * $25,000) = $360,000 - $2,500 = $357,500
Based on these assumptions, the expected value for the $50,000 degree is $280,000, and the expected value for the $25,000 degree is $357,500. Therefore, the $25,000 degree is the better bet, all else being equal. It's important to note that if we change the time horizon or other factors like program duration, location, and financial aid available, the results may change.
Applying the Poker Analogy: Expected Value v2
Now, let's apply the expected value framework to a different scenario: deciding between two job offers.
Let's say you have Job A that pays $100,000 per year, but it's in an industry that you're not passionate about, so there's a 50% chance you'll stick with it for 10 years and a 50% chance you'll stick with it for 5 years. Job B pays $80,000 per year, but it's in a field you're deeply interested in, so there's a 90% chance you'll stay for 10 years and a 10% chance you'll stay for 5 years.
We want to calculate the expected value for each option.
For Job A:
Expected Value = (0.5 * $100,000 * 10) + (0.5 * $100,000 * 5) = $750,000
For Job B:
Expected Value = (0.9 * $80,000 * 10) + (0.1 * $80,000 * 5) = $760,000
The expected value for Job A is $750,000, and the expected value for Job B is $760,000. Therefore, it comes down to personal preference and priorities. If you value job satisfaction and passion more than yearly earning potential, then Job B may be the better option. If you prioritize financial stability and yearly earning potential, then Job A may be the better choice. Ultimately, the expected value framework is a useful tool for making decisions, but it's important to weigh the pros and cons and consider personal priorities before making a final decision.
The Bottom Line
Today we talked about two cool frameworks that can help us make better decisions in our careers and personal life. First, we learned how to "think like a banker" using the PD-LGD-EL framework. This framework helps us analyze and manage the risk involved in big decisions, like taking out a loan for education. With this framework, we can break down a scary decision into smaller parts and see the potential losses in the future.
Next, we moved on to "thinking like a poker player" using the expected value framework. This framework teaches us how to compare and value two choices. For instance, we can use it to see how our passion for a field affects our earnings over the long term. Sometimes, a lower-paying job that we love can actually be a smarter choice in the end.
Thinking like a banker or poker player makes us better at gambling. Improving our gambling abilities helps us take a calculated approach to decision-making. Instead of just going with what looks good on the surface, we consider the probabilities and possible outcomes of each choice to make a more informed decision. This way, we can maximize our chances of long-term success and happiness.
These frameworks are the best tools to have in your arsenal if you want to be a successful risk-taker. As Estee Lauder, the founder of the $90 billion cosmetics empire, once said, "Risk-taking is the cornerstone of empires." With these frameworks, we can better navigate the uncertain terrain of our careers and personal lives and lay strong cornerstones for our own future empires.
🎉 P.S. Congrats on making it all the way to the end! If you found this article helpful or entertaining, why not share it with 3 friends? And if you do, you'll be rewarded with a FREE ticket to our Chicago Holiday Party in December! Spread the love and get ready to party with us!
All Love,
Paul