Analytical Architectures

Frameworks for organizing financial information and transforming raw data into structured insights that support sound investment decisions.

Framework Design

Layered Models

Effective analysis requires multiple layers of examination. Each layer reveals different aspects of the same underlying reality, and synthesis across layers produces richer understanding than any single perspective.

Macro Layer

The macro layer examines broad economic conditions: GDP growth trajectories, inflation dynamics, monetary policy stances, and fiscal balances. These factors establish the backdrop against which all other analysis occurs.

South African investors must track both domestic indicators and global conditions that affect capital flows and currency valuations. The interplay between local and international macro factors creates unique complexities requiring dedicated attention.

Sector Layer

Between macro conditions and individual companies sits the sector layer. Industry dynamics—competitive intensity, regulatory environment, technological disruption potential—shape returns across entire groups of companies.

Sector analysis identifies which industries benefit from current macro conditions and which face headwinds. It also reveals relative attractiveness within asset classes, guiding allocation decisions before individual security selection begins.

Company Layer

The company layer focuses on individual business quality: competitive advantages, management capability, financial health, and growth prospects. Here, fundamental analysis techniques—ratio analysis, cash flow modeling, competitive positioning assessment—take center stage.

Strong companies can outperform weak sectors, and weak companies can disappoint despite favorable industry tailwinds. Company-level analysis determines which specific securities deserve capital allocation within sectors deemed attractive.

Integration principle: The three layers must align for highest-conviction opportunities. A great company in an attractive sector during favorable macro conditions presents the clearest case. Misalignment—such as a strong company facing macro headwinds—requires position sizing adjustments and shorter holding period expectations.

Decision Frameworks

Logical Diagnostics

Investment decisions benefit from structured diagnostic processes that systematically evaluate key factors. Ad hoc analysis leads to inconsistent outcomes; disciplined frameworks produce more reliable results over time.

Thesis Articulation

Every position should have a clearly articulated thesis—a specific reason why this investment makes sense at this price at this time. Fuzzy reasoning produces fuzzy outcomes. Force yourself to write down the thesis in concrete terms: what must happen for this investment to succeed, and by when?

Disconfirmation Search

Actively seek reasons why your thesis might be wrong. This runs counter to natural human tendencies—we prefer confirming evidence—but provides crucial protection against overconfidence. What would have to happen to prove your thesis incorrect? How likely are those scenarios?

Risk-Reward Calibration

Estimate the range of plausible outcomes and their approximate probabilities. What's the upside if things go well? What's the downside if they don't? Does the expected value justify the risk? This calibration exercise often reveals that attractive-seeming opportunities don't actually offer adequate risk-reward profiles.

Exit Criteria Definition

Before entering, define what would trigger an exit—both on the upside (thesis realized, valuation stretched) and downside (thesis invalidated, fundamental deterioration). Pre-commitment to exit criteria helps overcome the psychological difficulty of actually selling when those conditions materialize.

Diagnostic Checklist

  • Can I state my thesis in two sentences?
  • What are three reasons I might be wrong?
  • What's the base case, bull case, and bear case?
  • What probability do I assign to each scenario?
  • At what price does the thesis no longer make sense?
  • What catalysts could accelerate the thesis timeline?
  • What risks exist that I cannot hedge?
  • How does this position fit my overall portfolio?
Pattern Recognition

Pattern Disassembly

Markets repeat patterns because human nature doesn't change. Learning to decompose these patterns into their constituent elements enables recognition in new contexts.

Technical Patterns

Price patterns reflect collective psychology playing out across time. Head-and-shoulders formations, double tops, ascending triangles—these shapes emerge because participants respond similarly to recognizable situations. Understanding the psychology behind patterns matters more than memorizing formations.

Sentiment Cycles

Market sentiment oscillates between extremes of pessimism and optimism. These cycles have characteristic shapes and typical durations. Reading sentiment accurately helps identify when consensus has become too one-sided, creating conditions for reversal.

Historical Analogues

Current situations rarely match historical precedents exactly, but analogies provide useful reference points. Studying how similar conditions resolved previously—while remaining humble about imperfect matches—enriches scenario analysis.

Structural Recurrences

Certain structural arrangements—crowded trades, leverage concentrations, liquidity mismatches—repeatedly create conditions for disorderly adjustments. Recognizing these structures before they unwind provides defensive advantages.

Data Visualization

Visual Analytics

Data visualization transforms abstract numbers into intuitive insights. Well-designed charts reveal patterns and relationships that spreadsheets obscure.

Market Flow Trends

12-Month View

Sector Performance

Relative Strength

Asset Allocation

Model Portfolio

Risk Profile Comparison

Strategy Analysis
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Share Your Frameworks

Have analytical approaches that have worked well? Questions about building better decision frameworks? Let's exchange ideas.