Hello everyone!ΒΆ
Today, lets
- Finish all of your CAPM projects for all your finance classes for the rest of your college life in 3 minutes
- Do an auction to learn how to save $381m per quarter
- Learn how we're all connected
- Get our hands dirty!
Ambitious, but fun; This class in miniature!
MotivationΒΆ
Where $V$ is the NPV of your education, $B$ is biz/econ skills, and $T$ is the technical skills covered in this class:
- $\delta V/\delta B > 0$ (good choice in your major!)
- $\delta V/\delta T > 0$, and $\delta T$ is achievable
- $\delta^2 V/\delta T \delta B > 0$ is important but overlooked
On #2: Who has estimated beta for a stock in FIN323, FIN328, or FIN335?
On #3: Let's play a game!
- Raise your hand if you've ever bid in an auction
Terms of the auctionΒΆ
- I will give a $20 bill to the winner
- Bids in $1 increments
- The winner pays what they bid, and the 2nd place player pays what they bid
What did you learn from that auction?ΒΆ
There are only 2 ways to avoid "death spiral":
- The Star Trek solve: Turn win-loss into no-win: split the $18 gain from incrementing the bid
- The War Games solve: "The only winning move is not to play"
The two solutions have commonalities:
- Plan before doing: "Measure twice, cut once"
- Think about big pic! Especially important on coding tasks where it's easy to get lost in minutiae...
- What's the economics of the situation?
- The problem dictates the tool! I'm very excited about skills you will learn in this class... but when you have a hammer everything looks like a nail!
- Here, valuation isn't the tool you need! It's game theory.
"That's silly!" Fine.. let's look at a real auctionΒΆ
Well... thousands of them. Enter: Zillow.
- Zillow's plan: Predict price Zillow can sell the house for, offer to buy for less, <do stuff quickly>, sell
- Profit hopes: liquidity provision, price appreciation
- Economics:
- Have to outbid other buyers (Winner's curse)
- Home owner knows most about the house! (Asym. Info)
Outcome of Zillow's planΒΆ
Good valuation wasn't a good enough toolΒΆ
Let's define a model, and let Zillow's valuation be 2x better than homeowners:
Here is a simple model:
- True value of a house is $v$ (unknown to owner and Zillow)
- Owners think the value is $v*(1+e_o)$, with $e_o \sim N(0,10\%)$
- Zillow's algo predicts $v*(1+e_z)$, with $e_z \sim N(0,5\%)$
- Because of winner's curse and the transaction cost owners face moving, Zillow is only able to buy houses when it offers more than 20% above what the owner thinks the house is worth. Talk about adverse selection.
- If Zillow buys the house, they subsequently sell the house at the true value.
These assumptions seem plausible!
What happens in this model?ΒΆ
So, if Zillow looks at 100k houses with values uniformly ranging from 0.25m-2.5m, and the above steps play out...
(You can figure this out with under 15 lines of python. It's in the "handouts" folder of the class repo.)
It buys 6k houses and loses $300m!ΒΆ
"But hindsight is 20/20!"ΒΆ
Except... we didn't need hindsight. An NBER working paper from 2020 discussed the issues this business model faces
- Adv. selection is key, limits scope for profits
- Profits plummet when liquidity is low (downturns)
- Better valuation models don't help!
- Winner's curse increases with competition
- Hedge funds like front running but this is the reverse: Zillow's valuations are public knowledge!
What do we learn?ΒΆ
Recall, my three initial assertions:
- $\delta V/\delta B > 0$ (good choice in your major!)
- $\delta V/\delta T > 0$, and $\delta T$ is achievable
- $\delta^2 V/\delta T \delta B > 0$ is important but overlooked
The Zillow case study illustrates the last one.
The Zillow team got obsessed with the technical skills and how good their pricing model could be. A little attention to the business forces could have saved them a lot of money!
The goal in this class is to bothΒΆ
- add some powerful skills to the bottom of your resume ($T \uparrow$)
- think about how business settings impact the use of those skills ($T*B \uparrow$)
So that you get the good jobs, but avoid losing $381m!
OnboardingΒΆ
If that sounds good (great?), let's continue:
- What are we working towards?
- Icebreaker - chain
- Syllabus, norms, and expectations
- Getting going
What are we working towards?ΒΆ
Skills you can benefit from over your career, yes.
A grade? Sure!
But that's not what I'm talking about...
The penultimate assignment is about glory
The LeDataSciFi LeContestΒΆ
About meΒΆ
About youΒΆ
- Name (your choice of name)
- Where you're from (pithy/short description)
- Year/program
- One thing about you (appropriate, unique, doesn't need to be "interesting")
Syllabus highlightsΒΆ
- Read it! Ledatascifi.github.io, then use right arrow to "flip" to next page
- Course oriented towards skills in Objectives
- Structure (read it)
- $E(Outcomes) = f(work)$, but lots of support
- 15 minute rule + help
- Announcements via on GitHub "classmates" team only!
- Grades: "Participation" is big, many ways
- Dashboard (BOOKMARK IT!) has schedule, tasks, key links
- I'm usually here 10 min before and after class to chat
Year of Learning themeΒΆ
The independency of government and business? "Regulation, public/private partnerships, incentives"
We will talk about
- Regulatory approaches to AI (e.g. Europe vs US)
- R&D incentives
- Projects may focus on this theme
NormsΒΆ
- Please interrupt when you have a question!
- Community: Help each other! (Especially in class, but not on assignments)
- The website and notes are not comprehensive - you can look around the web!
- Help, resources, and hacks pages -- read them!
Enough already! Let's get going!ΒΆ
This class depends heavily on GitHub, so let's jump in.
GitHub is good for
- cloud storage
- collaboration
- version control
It's like Word's Track Changes had a baby with Dropbox, and it was marketed to and designed for software developers.
Let's learn by doingΒΆ
(There is background info on the website, chapters 1.3-1.4.)
- You need a GitHub username and picture (Not your Lehigh username!)
- You need GitHub Desktop (GH-D)
- Click on the gradebook and assignment links in coursesite
- Follow the directions here: https://github.com/LeDataSciFi/ledatascifi-2024/blob/main/handouts/GitHub%20exercises.ipynb
- Ledatascifi.github.io > click GH logo > "repository" > "handouts" > "GitHub exercises.ipynb"
Note: Slides are available on the website after class each day.
Before next time:
- Finish the GitHub exercises
- Finish tasks in the schedule https://ledatascifi.github.io/ledatascifi-2024/content/about/schedule.html
- Accept invite to the organization when you get the email.
- Go to the classmates discussion board, and look through the "pinned" discussions
- Notice in the grade section of the website: Posts and replies to the discussion board will help your grade.
- Tag @classmates-2024, @donbowen, @brookswalsh, or specific classmates in issue posts to get help
- If you don't get any email announcements from GitHub this week, email me - something is wrong!
- Post 2 truths and a lie in the introductions post
- Poll: What is my lie?
- Any questions you want to cover in the next class? You can email if more comfortable, but even better: Use the class discussion board (classmates can help!)