How every report is produced.
Every monthly report on StockMarketAgent.AI is produced by the same disciplined, 9-phase workflow. We classify the business archetype, calibrate the discount rate to that archetype, run accounting-quality gates before trusting earnings, build the required valuation models, stress-test the result, and only then write the narrative — risks first. The goal is to separate the quality of the business from the attractiveness of the price, and to make every load-bearing assumption auditable.
Methodology
Archetype detection
Each stock is classified into one of 9 archetypes. This calibrates every downstream parameter — discount rate, terminal growth, probability weights, scorecard weights, model applicability.
Parallel data collection
Four research agents run concurrently: current ratios and analyst data; 5-year historical financials; peer multiples; WACC inputs and segments.
Cost of capital
CAPM Ke with adjusted beta (raw, industry, Bloomberg-blended). After-tax Kd. Market-weight WACC.
Quality gates
ROIC vs WACC trajectory, accounting quality (OCF/NI, accruals, Beneish M-score). Gate failures increase required margin of safety.
Valuation models
SBC-adjusted discounted earnings (dual Ke), multi-stage moat fade, 5-year forward earnings (bull/base/bear), reverse DCF, Owner Earnings floor, PEG-adjusted peer.
Sensitivity
5×5 Ke × terminal growth, TV concentration, growth × terminal P/E matrix.
Risk analysis — bear first
Top 5 kill scenarios, formal stress tests, quality deterioration signals. Built before bullish synthesis to counteract confirmation bias.
Supplementary + actionable
Moat quantification, peer cohort, industry cycle, earnings decision tree, technical positioning, position sizing, dynamic margin of safety.
Scorecard
9-category phase-adjusted score and 6-factor 100-point overlay with hard-fail guardrails.
Report assembly + 18-locale rendering
Assembled into a 500–900 line markdown document, translated on-view.