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Research Methodologies

Boxwood has core competencies in statistical and financial modeling that are applied in various client projects and are also reflected in models and reports on SmallBalance.com. These skills are outlined below.

Statistical Modeling

  • Univariate and multivariate time series analysis
  • LISREL, measurement, reliability and structural equation modeling
  • Advanced multivariate linear and non-linear modeling
  • Principal components and factor analysis
  • Statistical analysis of property transactions and survey data
  • Statistical sampling design for survey administration
  • Experimental design and evaluation
  • Neural network design

Financial Modeling

  • Maximization of objective functions through numerical optimization, i.e., portfolio optimization
  • Factor-based risk model estimation and implementation
  • Volatility and risk estimation

Monte Carlo Simulation

Monte Carlo simulation can be an effective approach for analysts attempting to solve complex business problems involving uncertainty or risk. The Monte Carlo approach begins with the modeling of a business or economic process - with particular attention to measuring uncertainty in the process. This information is then used in simulations to understand not only the most likely outcome of a process, but the range of possible outcomes and their probabilities.

Boxwood has employed Monte Carlo techniques in a variety of real estate and investment projects where understanding and quantifying the risks and probabilities of future events is paramount. These applications include econometric/real estate forecasts, portfolio analysis, diversification studies and the construction of investment/hedge funds.

For more information on Boxwood's Monte Carlo methodologies applied to a real estate setting, see the two citations of research articles on the Publications page (i.e., the references to The RMA Journal and Real Estate Finance articles).

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