A primer on applying Monte Carlo simulation, real options analysis, knowledge value added, forecasting, and portfolio optimization / by Johnathan Mun, Thomas Housel.

摘要

In this quick primer, advanced quantitative risk-based concepts will be introduced--namely, the hands-on applications of Monte Carlo simulation, real options analysis, stochastic forecasting, portfolio optimization, and knowledge value added. These methodologies rely on common metrics and existing techniques (e.g., return on investment, discounted cash flow, cost-based analysis, and so forth), and complement these traditional techniques by pushing the envelope of analytics, not replacing them outright. It is not a complete change of paradigm; and we are not asking the reader to throw out what has been tried and true, but to shift his/her paradigm, to move with the times, and to improve upon what has been tried and true. These new methodologies are used in helping make the best possible decisions, allocate budgets, predict outcomes, create portfolios with the highest strategic value and returns on investment, and so forth, where the conditions surrounding these decisions are risky or uncertain. These new techniques can be used to identify, analyze, quantify, value, predict, hedge, mitigate, optimize, allocate, diversify, and manage risk for military options.