The Tara Capital
Investment Framework

Every research call we make at Tara Capital is filtered through a single quantitative engine: the Tara Capital Investment Framework, or TCIF. This is a plain-English guide to how it works, what it measures, and why we built it the way we did.

The fundamental problem with macro research is subjectivity. Every analyst has a mental model of the world. Those models are shaped by experience, by temperament, by recency bias, and by whatever happened to be the dominant narrative when they first entered markets. Left unchecked, those biases produce outputs that feel rigorous but are ultimately anchored to prior conviction rather than current evidence. The TCIF is our answer to that problem.

It does not replace judgement. It structures it. By forcing every input category to be scored on a consistent, 0–100 scale — every single week — it creates an auditable, comparable record of where the macro regime actually sits, stripped of whatever narrative happens to be dominating the news cycle.

What the TCIF is

The TCIF is a quantitative macro regime classification engine. It scores eight input categories on a 0–100 scale, produces a weighted composite score, and classifies the current environment into one of six regimes — from Risk-On Expansion at the top of the cycle to Recessionary Environment at the bottom.

It runs every Monday morning at 07:45 UTC. It fetches current data from FRED and Yahoo Finance, scores each category, computes the weighted composite, classifies the regime, and delivers the full report automatically via Telegram and email — including year-to-date charts showing composite score and category breakdowns. The entire process, from data pull to delivered report, takes under two minutes.

The eight categories are not weighted equally. The weights reflect our analytical conviction about which inputs have the highest signal-to-noise ratio for predicting risk asset conditions. Liquidity leads. Real yields follow. Credit conditions and the dollar are significant. Growth indicators — counterintuitively — carry the lowest weight, because by the time they confirm a regime shift, markets have typically already moved.

The eight categories

Regime classifications

The eight input categories are scored, weighted, and combined into a single composite score between 0 and 100. That score maps to one of six macro regimes:

Why liquidity is the primary lens

Every analytical framework makes a claim about what matters most. The TCIF makes a clear, empirically-grounded claim: net system liquidity is the single highest-correlation leading indicator for risk asset conditions.

This is not a novel idea. Michael Howell at CrossBorder Capital has written extensively on global liquidity cycles. Lyn Alden has documented the relationship between Fed balance sheet expansion and risk asset performance across multiple cycles. The data is consistent and compelling: when net liquidity — defined as the Fed balance sheet minus the RRP minus the TGA — expands, risk assets tend to perform. When it contracts, they struggle. This holds regardless of what growth or earnings are doing in the short term.

The intuition is straightforward. Liquidity is the fuel for the financial system. It determines how much capital is chasing a given set of assets, and therefore at what price equilibrium is reached. When the Fed expands its balance sheet, that expansion flows through primary dealers into money markets, into bond markets, and ultimately into equities, credit, and digital assets. The transmission is not instant — it operates with lags that vary by asset class — but it is consistent.

The RRP and TGA adjustments are critical and frequently overlooked. The gross Fed balance sheet is widely reported and widely misunderstood. What matters is not how large the balance sheet is in absolute terms, but how much of that liquidity is available to circulate through financial markets. Money parked in the reverse repo facility or sitting in the Treasury's account at the Fed does not support risk asset prices. Only the net figure matters.

This is why the liquidity category carries the highest weight in the TCIF — not because the other five categories are unimportant, but because the evidence across multiple cycles suggests that net liquidity is the factor most likely to be right when everything else is giving mixed signals.

A note on the weightings

Liquidity carries the highest weight (1.6×) because it is the first mover — changes in Fed balance sheet, RRP, and reserve dynamics typically precede shifts in real yields, credit, and risk appetite by weeks. Real yields follow at 1.4×, because they are the most direct transmission mechanism: real yield direction drives the dollar, which drives EM financial conditions, which drives risk appetite. Credit conditions (1.3×) and financial conditions (1.2×) are confirmatory — they validate what liquidity and yields are signalling, and tend to lead equities. Dollar (1.2×) reflects the singular importance of dollar direction as a cross-asset transmission variable, particularly for real assets and emerging markets. Inflation (1.1×) sits just above neutral weight — it is a regime-shaping force, but its impact on equities depends heavily on whether we are in a demand-pull or cost-push environment, so it warrants analytical weight without dominance. Growth indicators (1.0×) are genuinely lagged; by the time payrolls confirm a regime turn, markets have already priced it. AI CapEx carries the lowest weight (0.8×) not because it matters less analytically, but because it is the most volatile category — a single NVDA earnings report can move the score without reflecting a genuine regime shift.

These weights reflect analytical judgement about sequencing in the cycle, not a formal optimisation. They will be reviewed over time as history accumulates.

What the framework is — and is not

The TCIF is not a trading signal. It does not produce buy or sell recommendations. What it produces is a structured, consistent characterisation of the macro regime — and a regime classification changes how we interpret everything else.

In a Risk-On Expansion regime, we interpret pullbacks in risk assets as buying opportunities and weight our analysis towards assets that benefit most from abundant liquidity: high-beta equities, digital assets, emerging market risk. In a Credit Contraction regime, the same pullback is treated as an early warning and we look for confirmation from credit spreads and the financial conditions indices before drawing conclusions.

The framework also prevents the most common analytical error in macro research: changing your framework to fit the current narrative. Because the TCIF scores every category on a fixed methodology every single week, it creates a running record that is immune to hindsight revision. The scores from January are the scores from January. They cannot be quietly updated to fit February's news.

In practice, the Monday morning report is the foundation on which the week's research is built. It does not replace the analytical work — it structures it. Every subsequent piece of research we publish at Tara Capital, whether on digital assets, emerging markets, or geopolitics, is written with a clear understanding of the current regime score and what that means for the risk environment.

The Convergence Principle

A regime score on its own answers one question: what kind of macro environment are we in? The Convergence Principle answers the next question: given that environment, where are the specific opportunities — and how confident should we be in them?

The framework runs three independent allocation engines from the same regime input. Each asks a different question:

• Country allocation — where should capital be deployed, given policy divergence, currency direction, and capital flows?
• Sector allocation — which types of business does the current cyclical position support?
• Theme allocation — which structural transformation forces are being accelerated by the current environment?

These three engines are parallel, not sequential. None is upstream of the others. Each receives the same regime classification as its input and runs its own logic entirely independently.

The Convergence Principle states: when all three engines independently arrive at the same conclusion, that alignment is the signal — not any one engine alone. A Country OW call on its own is a view. A Sector OW call on its own is a view. When both are OW on a specific country-sector pair, and the Theme engine is simultaneously OW on the structural force that drives that pair, the three independent processes have triangulated on the same opportunity from three different analytical starting points. That is not a view. That is a high-conviction call.

When they conflict — when Country says underweight a region but Theme says overweight the structural force that dominates it — the conflict is surfaced explicitly rather than resolved by averaging. Tension in the signals is information. It tells you that the macro environment is sending mixed messages about that opportunity, and that a position there requires additional analytical justification.

This architecture grew out of years managing emerging market portfolios, where no single signal was ever sufficient. Dollar direction, local real yields, political risk, and global liquidity all mattered simultaneously — and you had to know which one was dominant at any given moment. At CLIG, the discipline was country allocation alone. At Ashmore, country and sector combined. The TCIF adds the third lens — structural theme — because AI, industrial policy, digital assets, and geopolitics now cut across both countries and sectors in ways that neither geography nor cyclical rotation can capture independently.

The convergence table in practice

Each Monday, after the three engines have run, the convergence engine maps their outputs against each other. It looks for combinations where country, sector, and theme are all simultaneously OW or Strong OW — and where there is a genuine analytical reason those three belong together, not just mathematical coincidence.

A worked example illustrates the principle:

Convergence is not a buy signal. It is a prioritisation tool. It identifies where the macro environment is simultaneously supportive across geography, cyclical positioning, and structural theme. Investment judgement, valuation, and position sizing remain human decisions — made with the benefit of knowing that three independent analytical lenses are pointing in the same direction.

The framework does not tell you what to do. It tells you what kind of world you are operating in — and where, within that world, the evidence is strongest. That distinction matters enormously.