Answering Investment Questions Using Data Science: Finance and Investing Problems -- Econometric Solutions
Stop guessing future outcomes. Answering Investment Questions Using Data Science gives you the econometric toolkit behind modern finance-without heavy math or matrix algebra. In nine hands-on chapters you'll learn how to structure investment questions, run the right models, and interpret results you can trust.
What you'll learn
Regression that fits markets: Build, diagnose, and improve models for returns, spreads, and risk.
Predict expected returns: Apply Fama-MacBeth techniques to select investments-and know their limits.
Causal answers: Use difference-in-differences and instrumental variables to separate correlation from causation.
Practical risk modeling: Work with factor models (Barra-style), Value at Risk (VaR), and GARCH to measure and manage risk.
From classroom to desk: Examples drawn from quant investing, portfolio construction, and regulatory stress tests.
Who it's for
Finance students, aspiring quants, early-career analysts, and senior professionals (PMs, risk leaders, executives) who want to understand the field intuitively-without diving into heavy math or matrix algebra.
By the end, you'll know various methods to use, how to avoid common pitfalls, and how to communicate results that withstand scrutiny.
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