investment-education

Learn how commercial mortgages work — CRE loan types, balloon payments, recourse vs non-recourse structure, prepayment protection, effective mortgage yield, and the refinancing decision.

Learn how depreciation tax shields, after-tax cash flow (ATCF), depreciation recapture, and the APV approach affect commercial real estate investment returns with worked examples.

Learn how leverage amplifies both returns and risk in commercial real estate. Covers the equity yield equation, positive vs negative leverage, CRE capital structure, and practical analysis steps.

Learn how to build a commercial real estate cash flow proforma, project reversion value, choose a CRE discount rate, and apply DCF valuation to commercial property investments.

Learn the DiPasquale-Wheaton four-quadrant model linking rents, property values, construction, and building stock in commercial real estate markets.

Learn how to calculate net operating income (NOI) in commercial real estate. Covers the NOI formula, PGI, vacancy, EGI, operating expenses, two worked examples, and common mistakes.

Learn how CRE investors analyze markets before committing capital. Covers vacancy, absorption, rent, construction indicators, the eight-task structural analysis framework, trend vs structural forecasting, market cycle timing, and common analytical mistakes.

A unified framework for causal inference in econometrics. Covers the potential outcomes framework, selection bias, ATE vs ATT vs LATE, randomized controlled trials, regression adjustment, propensity score matching, IPW, doubly robust estimation, and regression discontinuity design — with finance examples and a comparison of when to use each method.

The linear probability model (LPM) applies OLS to a binary dependent variable, interpreting coefficients as percentage-point changes in probability. Learn its advantages, limitations, when to use it vs. logit or probit, and why robust standard errors are mandatory.

Learn how logit and probit models handle binary dependent variables using maximum likelihood estimation. Covers odds ratios, marginal effects, and model comparison with worked loan default examples.