If you really want to dive into the technical details there's really no better book than Hull's "Options, Futures, and Other Derivatives". It's extremely well written and if you have a basic understanding of calculus and probability the math isn't too difficult. The only catch is that it is a very expensive book, but if you buy a used copy a few editions back it is more affordable. Also don't worry about the "derivatives" subject matter, if you want to understand derivatives you naturally have to understand the underlying instrument. If you just read the first 100 or so pages (covering Futures pricing) you'll have a pretty good sense of the basics of thinking about financial markets.

I really recommend this book even if you're not interested in Finance as a general guide for thinking about stochastic processes in a practical manner. Nearly all "basic" business/web metrics can be understood best if you understand how to correctly model financial instruments. Personally, I think the basics of quantitative finance are just as relevant to Data Science as machine learning is.