*We link to standard definitions, and add color specific to QCF.*

**Capital structure** See Wikipedia. Any introductory corporate finance text will cover this topic well. For a more pragmatic discussion, check Damodaran‘s valuation books. For more theoretical, Copeland.

**Charting** Inspiration: Kaiser Fung. Jorge Camoes. Stephen Few. Robert Mundigl. The Why Axis. Tools: Purna Duggirala. Jon Peltier. Fabrice Rimling.

**Econometrics** See Wikipedia. After examining dozens of titles I would say that this field uniformly supports great technical writing; it’s hard to find a bad econometrics text. I’ve read Barreto and like it; Greene and Hayashi and Wooldridge are popular recommendations. Kennedy is an outstanding companion.

**Monte Carlo analysis** A quick Excel tutorial.

**Regression analysis** A statistical technique to discover the relationship among variables; see Wikipedia. Excel gives us OLS easily via the Data Analysis package; for financial analysis we often prefer LAD though it’s computationally more difficult.

**Risk** Exposure to low-utility outcomes. Though risk often increases with volatility, the latter (like uncertainty) is more a measure of dispersion.

**Scenario analysis** See Wikipedia. Since the likelihood of downside scenarios isn’t usually well known, it is difficult to support optimal economic recommendations using this technique. Its best use may be in driving brainstorming sessions that help participants agree on salient risks to performance.

**Time series analysis** Using econometric techniques to examine a time series. Most QCF time series are financial; they may differ in sampling frequency (such as *quarterly* for historical financials, or *daily* for closing share prices) and typically need to be adjusted for trend and seasonality (see Ghysels for the latter).