In Quantitative Methods for ESG Finance, distinguished risk and finance experts Dr. Cyril Shmatov and Cino Robin Castelli deliver a startlingly insightful combination of the theoretical and quantitative bases underlying risk factor investing and risk management with ESG applications. Written from the quantitative analyst's perspective, this book discusses both investment management (buy-side) and investment banking (sell-side) applications. It also offers explanations of the proliferation of newly available, alternative data sources available to analysts and the quantitative techniques necessary to process them. The authors pay particular attention to climate risk because of its increasing general importance. They offer an overview of recent quantitative advances and the evolving regulatory landscape in the climate risk space, as well as an in-depth discussion of the financial impact assessment of various climate risk-driven scenarios. In every chapter, theoretical discussions are accompanied by functional code snippets and walkthroughs of a Python Jupyter notebook containing publicly available data and demonstrating practical examples that apply the techniques introduced in the book. Investment managers will be particularly interested in the authors' exposition of risk factor investing, portfolio and index construction, and ESG scoring, while bankers will likely focus on the discussion of a newly emerging class of ESG-driven financial products and new financial risk management applications, many of which are driven by new financial regulations. An indispensable resource for finance professionals--including investment managers and investment bankers--and researchers, Quantitative Methods for ESG Finance will also earn a place in the libraries of graduate students of business and finance seeking a one-stop reference for the latest quantitative applications in ESG finance.