Components:Finance Theory,Programming,Machine Learning, Robo-advising, and Blockchain

    Can teaching schools compete with research schools? A FinTech Case

Area #1: Finance and Statistics (current ones)

• Corporate Finance by Welch | syllabus | Portfolio Analysis by Bodie at al. | syllabus
• Business Analytics using Excel, syllabus | my Excel web
• Options & Futures by Hull | syllabus | Business Statistics by Anderson et al. | syllabus

Area #2: Programming

• Python,Anaconda: Home | Download | Module index | Cheat sheets: Pointal | basic | quickref | Reg | wilfredinni | colab |
• R: download | packages | TaskViews: | Fin | Econome | ML | Dist |
• My book #1 (2023): R/Python | Amazon | Preface | GitHub | syllabus | paper
• My book #2 (2017): Python for Finance 2nd | 1st | Korean | Chinese | GitHub2 |
• My book #3 (2018): Financial Modeling using R: syllabus | book cover |
• My papers: course | 1 semester,2 languages | new way to teach

Area #3: Machine Learning

• Unsupervised Learning: def | def2 | k-means | code/stock | deepCluster |
• Supervised Learning: def | def2 | code |
• Deep Learning: def | def2 | code | code2 | code3 | Tinker
• Sklearn: index | user guide | examples | blog | fixes || R taskViews:ML | NLP |
• My book #4 (with James,2018): Data Science with Anaconda | GitHub

Area #4: ChatGPT and Chatbot

• OpenAI: Home | login | docs | API keys | pricing |
• AWS: Home | account | doc | Lambda | pricing |
• Videos: AWS chatbot & lambda | <-code | Web app (AWS) |

Area #5: Blockchain & Cryptocurrency

• home | BitCoin price | latest | 1st | ether converter | etherScan | Pinata/NFT | kucoin |
• Private/public keys: mnemonic | BIP:39 | wordList | English | raw |
• Ganache | Remix: launch | home | doc | videos | MetaMask |
• Solidity: examples | 721 | Standards: 20 | 721 | cheatSheets: 1 | 2 | Manoj |
• Books/papers: DeFi/future of finance | 2 | policy | Guide2Crpto | web3 |
• Videos: mine#2 | Keith Bear | trust | Remix:v7:38 | 8:22 | 17:56 | <-code | metaMask | 2 |
• My GitHub: Blockchain | Python,Ganache and Crypto |

Area #6: Robo-advising using Python

• Black-Litterman:exp | steps | code: dcajasn | mkc940 | RcodeZip |
• Parametric Portfolio Policies: paper | Deep | code: Seaaann | R |
• Streamlit: home | docs | gallery | blog | deploy | Binomial tree | Remove background | Mine:Mortgage | APR/ER/EAR |
• Packages: glmnet | Git || Videos:Robo Advisor | Promises/pitfalls | trust |
• My papers: Course | Financial Planners

Programs: boot camps, master, bachelor, & others

• Boot camps: Arizona State | Berkeley | Columbia | Denver | Miami | Minnesota | Northwestern | Rice | Rutgers | Toronto | HKU |
• Master: Guide | Kennesaw | NYU | 2 | UCF | UCONN | Stevens | Duke | Brandeis | Boston U. | GuangZhou/China | Keiser
• Bachelor: Bentley | Creighton |
• Others: Fintech degrees | Guide | UCI | Harvard | 2 | NYU | Chicago | NUS | Coursera | GetSmarter | Texas | Columbia | Ranks | Cornell | Rutgers |