Classifying Asset Nature: The FICC Dual Track and the Broken-Transmission-Chain Trap

The first step in major-asset-class research is asset classification, not market-direction judgment: assets whose financial-attribute weight is large and that possess T+0 liquidity depth belong in the FICC framework and are studied via macro-strategy logic; assets whose own intrinsic attributes dominate (agricultural products, niche commodities) are studied under an independent micro framework; gold follows bond logic and silver follows commodity logic; the real bridge between macro and trading is researching the contradictions and inferred actions of policy-makers — not being drawn into value judgments of the “will China collapse?” variety; the most common fatal error is skipping the transmission path between the macro narrative and the operational conclusion.

The Framework As It Stands

This section is compiled from the compilation research manuscript: the original framework’s structure, terminology, and key formulations are preserved, including editorial bridges and external factual annotations; diagrams are drawn by the compiler following the original structure.

The framework was presented in June 2019 as a complete introduction to major-asset-class research, covering asset-classification criteria, the FICC taxonomy, market-scope demarcation, and the methodology from macro to trading. Data anchors reflect the 2019 reference point.

I. Classifying Assets: Financial-Attribute Weight + T+0 Hard Criteria

The most fundamental principle of the major-asset-class framework: not all assets can be placed in the same bucket. Two fundamentally different research methods apply:

Major asset classes: driven by a macro-strategy logic framework, requiring analysis of the global environment
Niche assets: driven by their own micro factors, requiring no macro analysis

Classification criterion: the higher the financial-attribute weight, the more the asset belongs in FICC (studied via macro strategy); the stronger its own intrinsic attributes, the more it falls under micro research. Futures do not automatically equal major asset classes, nor can equities be lumped together — what matters is the asset’s attributes and driving factors, not the trading instrument or category label.

Hard criteria: liquidity, depth, trading mechanism (T+0). The New Zealand equity market does not qualify as a major asset class because its liquidity and depth are insufficient and settlement is non-T+0 (five-day settlement).

Cardinal error: treating all price instruments as homogeneous (looking only at prices across Bitcoin, Dogecoin, and pork). Major asset classes require attention to the depth dimension.

II. Asset Segmentation within the FICC Framework

Bonds: primarily refers to interest-rate bonds (instruments: ETFs/derivatives, avoiding single-bond micro exposure).

Equities: minimize individual stock selection (only trade directly in companies you know extremely well; otherwise use passive ETFs and collaborate with stock-pickers).

Commodities: only copper and oil qualify as major asset classes; coffee, jujubes, and apples have no macro relationship — study them on the micro level.

Crude oil: holds both commodity attributes and interest-rate-influence-variable attributes, hence placed in FICC
Among base metals the focus is copper; aluminum and zinc can be used for cross-commodity hedging (hedging out micro variables to isolate the macro signal)
Critical precious-metals segmentation: gold is essentially a bond (classified as commodity but analyzed under bond logic); silver must be analyzed under commodity logic — confusing the two leads to massive errors (in 2011–2012 some Chinese institutions treated silver as gold, overlooked its commodity attributes, and were caught by Wall Street)
Agricultural products belong in the research universe under a pure commodity framework with little macro relevance

Core market scope: primary focus on the five major markets of the United States, Europe, Japan, Hong Kong, and China (the core of global economic integration); Australia monitored for sector leaders integrated into the global economy; emerging markets (Turkey, Brazil, Russia) are watch-list items — most of the time the approach is to find substitute relationships (when logic is clear, use a corresponding liquid asset as a proxy, rather than entering those markets directly). FX participation is mainly in the seven major currency pairs; KRW/TWD/ZAR and similar can be monitored for feedback signals but direct trading is not recommended.

III. Connecting Macro to Trading: Research Policy-Maker Contradictions and Complete the Transmission Chain

Discussing without right or wrong — only mechanisms: macro-economics discussions are fundamentally not about right or wrong — they debate causes, consequences, and methods; “will China collapse?” type disputes have no practical significance for market participants, who should not be drawn in.

Connecting the thread: research the contradictions facing policy-makers and their internal logic → infer the actions they are likely to take → determine how to respond in that environment (the starting point is not “is this right?” but “what will the decision-maker do?”).

The broken-transmission-chain trap: the most common error is narrating a long macro story and then jumping directly to an operational conclusion (“oil will rise,” “gold must surge”), with the transmission path entirely missing in between — and the omitted intermediate links are precisely the most critical part. Examples:

The Iran situation implies higher oil prices, but Saudi Arabia had already pledged to increase output; that effect is distal, while the proximate effect is merely sentiment and does not affect actual supply-demand → high backwardation structure, price action contradicts the “geopolitics → price rise” intuition
“Gold preserves value against inflation → gold must rise” is a pseudo-logic that leaps from a broad financial narrative to a conclusion; the transmission links of rates/credit/monetary substitution must be filled in

Avoid both extremes: macro omnipotence (macro replaces micro and the middle tier) vs. macro nihilism (only pure trading matters). The correct approach is to keep the macro-meso-micro three-layer chain as complete as possible and clarify what each layer discusses. The first part of this framework — the macro worldview — may seem broad, but it is the foundation of the entire framework; without the foundation all upper layers fail.

IV. Research Methodology: Single-Entry Growth + 2008 Calibration + Forward Signals + Short-Seller Respect

The framework did not begin as a complete whole; it entered from a single point (FX — the most direct reflection of cross-border capital flows, interest differentials, and carry trading) and then extended to asset allocation, primary and secondary markets, global cross-border arbitrage, and commodities, building the full picture over five to six years.

2008 financial crisis calibration: completed understanding of the terminal end of positive feedback systems; having experienced both the positive and negative sides, the analyst no longer believes in any unidirectional trend (positive feedback does not last forever; nor does negative feedback — the key is to identify the cycle position).

Foresight comes from signal-tracking: in mid-2006, no-income borrowers obtaining mortgages and the problems at Northern Rock were risk signals, tracked contemporaneously with The Big Short, not relying on post-hoc explanations.

Short-seller respect and the Soros-style hedge: in mature markets passive ETFs are a dividend of the era (over the prior decade buying ETFs even beat Buffett — earning the era’s returns, as of 2019); what truly tests a fund manager is not low-volatility returns but the ability to sense and avoid risk during high volatility, even profiting while doing so; Soros-style strategy = delegate long exposure to fund managers (paying management fees, enjoying their annual returns), maintain personal high sensitivity, add short hedges when risk signals appear, remove the hedges when risk subsides to let the long continue — the best combination strategy in mature markets.

Compiler’s Perspective

Coordinates: Category | Cognitive Algorithm, axis_h | Fa (Method), axis_v | What It Is

Bridging Layer

The core distinction of this framework from the typical “chart-reading” research is that it uses financial-attribute weight and T+0 liquidity depth as two hard prior-classification criteria — assets that fail to qualify (New Zealand equities with five-day settlement, agricultural products, niche commodities) are excluded from the macro-strategy framework from the outset, rejecting the cognitive trap of “explaining all prices with a macro framework.” This sequence — classification first, modeling second — shares a starting point with The Three Yardsticks of Asset Pricing: A Unified Framework for Equities, Rates, and Currencies’s “anchor the pricing factor first, then build the linkage relationship,” the difference being that this framework emphasizes the entry-point segmentation of methodology rather than the pricing formula itself.

The concrete error of the old way of thinking: in 2011–2012, certain Chinese institutions operated silver as if it were gold — because silver and gold share the precious-metals label — ignoring silver’s commodity attributes (industrial-demand driven, high position concentration, Wall Street big money with control over warehouse inventory). The result was that when gold’s price trajectory diverged from silver’s, those institutions were caught; the loss originated at the asset-classification step. Another typical error: a macro researcher narrated the Iran–Saudi geopolitical game and immediately predicted “crude oil prices will rise” — but Saudi Arabia had publicly committed to production increases to offset the distal effect, and the actual influence was the backwardation structure in the near-dated spread, with price action contradicting the “geopolitics → price rise” intuition. Both errors are variants of “omitting one step in asset classification / the transmission chain.”

The framework’s proprietary increment: the real bridge between macro and trading is “researching the contradictions facing policy-makers, inferring their actions, then deciding one’s own response” — this path separates the economics discussion (a right-or-wrong dispute) from market participation (a probability-and-odds dispute) into two distinct levels; entering the former yields no conclusion, while the latter only asks “if the decision-maker acts this way, what position should I hold?” Only after reading the precious-metals segmentation section (gold under bond logic, silver under commodity logic) can one understand: the institutions that operated silver as gold made a cognitive error not at the market-direction layer but at the asset-classification layer — the correction must go one layer up, not redraw trend lines.

Sources

“Compilation manuscript z-0084 · collected 2026-07”
“External course material: Introduction + 1.1 + 1.2 of the Major-Asset-Class Investment Research Framework (June 2019, external public course, three episodes combined)”

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