This book serves as a bridge, leveraging the familiarity of Excel and the power of R to make FinTech accessible to all. Financial Technology (FinTech) has revolutionized areas once dominated by traditional finance. However, the need to learn a programming language often creates a barrier for many learners.

Excel-based learning builds confidence with tools that are already familiar to advanced students, while minimal R programming is requiredno prior R skills needed, just two simple lines of code. Hidden functions unlock powerful FinTech capabilities with ease.

With this book, students can learn to generate public and private keys effortlessly,create a Hash for any given phrase, use the Merkle Tree to combine 100 transactions into a block's Hash, develop QR codes for websites or public keys, verify (x,y) values on the Elliptic curve for cryptography, and run models for both Unsupervised and Supervised Learning.

The book includes definitions, exercises, and solutions for students to develop the skills to navigate and excel in the world of FinTech.

Leverages the familiarity of Excel, allowing students to build knowledge with tools they already know Requires no programming skills Provides roadmaps that simplify complex FinTech tasks, such as generating public and private keys

Autorentext

Dr. Yuxing Yan lives in Rochester, NY (USA). He taught and worked at several universities, including McGill, Wilfrid Laurier, NTU, Loyola, the Wharton School (8 years), Hofstra, and Canisius College. His research focuses on Financial Modeling, FinTech, Cryptocurrency, Market Microstructure, and Financial Data Analytics. His articles have been published in the Journal of Fixed Income, Journal of Banking and Finance, and Journal of Empirical Finance, among others.

Inhalt

Introduction and Excel Basics.- Blockchain (I): Numbers and Alphanumeric.- Blockchain (II): ASCII and Sha256.- Ledge and Distributed Ledger.- Cryptography Basics: public and private keys.- Advanced Cryptography.- Cryptocurrency and Ganache.- Crypto markets, risk and risk-return tradeoff.- Blockchain applications and simulations.- Unsupervised Learning.-Supervised Learning: Classification.- Etc.