
This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including the predictability of asset returns, tests of the random walk hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the random walk hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications.
That said, it really depends on what types of assets you are looking to trade. At the risk of stating the obvious if you are doing any type of derivatives, you'll need pricers and data for those.
As a start, look for what is the easiest way to obtain a near complete data set and go from there. Good luck!
Jane Street's podcast and blog are insightful too [2]. I read somewhere that Dr. Simons (one of the founds of RenTech) has this book in his office [3].
0. https://blog.headlandstech.com/2017/08/03/quantitative-tradi...
1. https://blog.headlandstech.com/
2. https://blog.janestreet.com/ and https://signalsandthreads.com/
3. The Econometrics of Financial Markets, https://www.amazon.com/gp/product/0691043019/