Learn how to evaluate strategic investments under uncertainty with AI Scenario Planning and Real Options Analysis. Explore stochastic scenario planning, probabilistic forecasting, and investment valuation methods that go beyond traditional discounted cash flow (DCF) analysis.

Designed for financial analysts, investment managers, corporate strategists, and professionals working with complex investment decisions, this course starts with probabilistic scenario architectures. Examine Brownian motion, mean-reverting processes, jump diffusion, and multi-factor models to assess financial uncertainty. You'll then apply real options analysis to value managerial flexibility in investment timing, expansion, abandonment, and staged capital commitments. Explore risk-neutral valuation, compound options, binomial lattices, trinomial trees, and Monte Carlo simulation to evaluate strategic choices. Bring these approaches together through applications in energy projects, pharmaceutical R&D, and strategic investment planning. By the end, you'll be able to integrate stochastic scenarios with real options, calculate option values, and assess investment decisions under uncertainty. What makes this course distinctive is its focus on connecting probabilistic modeling with real options valuation and sector-specific investment decisions, helping you assess risk and strategic flexibility beyond DCF alone.