Elements of Tokenized Finance

Instructor

Prof. Pramod Viswanath, Princeton, pramodv@princeton.edu

Teaching assistants

  • Kaya Alpturer, kalpturer@princeton.edu
  • Niusha Moshrefi, niusha@princeton.edu

Office Hours

– In person: Tue/Thu 3pm – 4pm, Room B205 Equad
– On Zoom: Mon/Thu 7:30pm-8:30pm, Zoom link will be posted on Ed before each session

Course Material

Lecture Date Theme Lecture Slides Lab Assignment Due Dates
09/03 Introduction Introduction + Logistics Slides Lab  
09/08 Primer on Blockchains Slides    
09/10 EVM and smart contracts Slides Lab Crypto Zombies 1
09/15 DeFi marketplaces Exchanges I — DEXes Slides Lab  
09/17 Exchanges II — Bonding Curves and CFMMs Slides Lab Crypto Zombies 2
09/22 Exchanges III — Improving CFMMs Slides Lab  
09/24 Exchanges IV — DEX aggregation and propAMMs Slides Lab Homework 1
09/29 Derivatives & Prediction Markets Prediction Markets I — Incentives & Design Slides Lab  
10/01 Prediction Markets II — Parlays, Conditional and Decision markets Slides Lab Homework 2
10/06 Options, Derivatives, Perpetuals Slides Lab  
10/08 Perpetuals II Slides Lab Homework 3
10/13   MIDTERM      
10/15 Banking in DeFi Lending Pools Slides Lab  
10/20 FALL BREAK
10/22 FALL BREAK
10/27 Stablecoins Slides Lab Assignment 1
10/29 Bridges and oracles Slides Lab  
11/03 Other topics DePINs Slides Lab Assignment 2
11/05 New banks (Macro DeFi) Slides Lab  
11/10 Old banks vs New banks Slides Lab Assignment 3
11/12   Conclusion Slides    
11/17 Project presentations Project Presentation     Assignment 4
11/19 Project Presentations      
11/24 THANKSGIVING
11/26 THANKSGIVING
12/01 Project Presentations      
12/03 Project Presentations      

Course Outline

Blockchains are digital platforms whose consistency and liveness are maintained by a decentralized set of participants. The combination of programmability, permissionless access and the financial nature of the underlying token has led to tremendous innovation in financial products on the blockchain. Broadly covered under the rubric of decentralized finance or tokenized finance. These innovations, originally restricted to decentralized finance, known informally as “crypto”, have now matured and absorbed into major arteries of the global financial system. This “tokenized finance” has led to creation of “neo banks” offering new financial instruments. This maturity has led to new legislation associated with some of these tokenized financial products; further, central bank and treasury instruments are been directly involved.   

The purpose of this course is to introduce these developments classified as “elements” of tokenized finance, from computer science, economics, engineering and finance points of view. Periodic programming assignments provide a hands-on instruction to the technical material.

Course Notes

  • Lecture videos, slides, lab instructions, and supplementary reading material will be provided for each lecture.
  • Supplemental reading:

Pre-requisites

The basis prerequisites are a maturity with algorithms (COS 226), probability (ORF 245) and computer systems (COS 316). Background in blockchains (ECE/COS 470 and COS 495) and financial mathematics (ORF 335) will be helpful.

Assignments

We will have a 3 part homework, 2 part Crypto Zombies tutorial and a 4 part programming assignment series to build smart contracts in Solidity programming language through which students explore the core elements of DeFi.

Final Project

In-depth study of one of the elements of DeFi covered in the course. The final project report will serve as the final exam of the course.

Assignments and Grading

The course is evaluated in four formats:

  • [14% of the grade] Programming Assignments – This includes completing two Crypto Zombies modules (Introduction to Solidity) and four programming assignments in Solidity. Through these tasks, students gain hands-on experience in coding in DeFi. AI policy: Can consult AI, but students need to complete the work by themselves.
  • [24% of the grade] In-class labs –There are 19 lectures (final four classes are reserved for project presentations) and each lecture has a lab, except lecture 2 (where potential projects will be discussed), lecture 12 (Midterm) and lecture 19 (conclusion). Each of the 16 labs counts as 1.5% of the total grade — we will count the top 14 lab grades allowing students to skip up to two of the labs making space for personal, religious or other scenarios. Students need to sign up to help run the lab in the class for at least one session, counting as 3% of the total grade. So total grade for labs = 21% + 3% = 24%. AI policy: Can consult AI, but students need to complete the work by themselves.
  • [15% of the grade] Homeworks – There are three homeworks(paper/pencil type) in the first part of the course. AI policy: No AI usage allowed for homeworks.
  •  [17% of the grade] Midterm – This exam is in class, closed notes, closed devices, and will be based off the material covered in the first part of the course. The material in the homeworks will provide a guideline for the format and preparation for the midterm. AI policy: obviously no AI is allowed here, so there is an extra incentive to ensure one works on the homeworks without the assistance of AI.
  • [30% of the grade] Final project – Students will do an in-depth study of one of the elements of DeFi covered in the course. Substantial coding and system building is expected. Potential project topics shall be provided by class staff, with a focus on prediction markets. The final project report will serve as the final exam of the course. AI policy: AI usage is encouraged. The introduction, findings and conclusion section should be composed with no assistance from AI.