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.
"The framework does not tell you what to do. It tells you what kind of world you are operating in. That distinction matters enormously."
What the TCIF is
The TCIF is a quantitative macro regime classification engine. It scores seven 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 seven 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 seven categories
The Fed balance sheet, the Reverse Repo facility (RRP), the Treasury General Account (TGA), and aggregate bank reserves. The core calculation is deceptively simple:
Net liquidity proxy = Fed balance sheet − RRP − TGA
The RRP and TGA are subtracted because they represent money that sits inside the Federal Reserve system rather than circulating through financial markets. When the RRP drains — as it did dramatically through 2023 and 2024 — that money flows back into money market funds, then into risk assets. When the TGA is drawn down by the Treasury, the same dynamic occurs. Rising net liquidity is the single most important signal for risk asset conditions.
A score above 70 indicates abundant and expanding net liquidity — historically the most supportive environment for equities, credit, and digital assets. Below 30 indicates active contraction.
The real 10-year yield (nominal 10-year Treasury minus the 10-year breakeven inflation rate), the 2s10s yield curve slope, and the trend in breakeven inflation.
Real yields are the price of money after adjusting for inflation expectations. When real yields are deeply negative, holding cash is a guaranteed loss in real terms — money flows aggressively into risk assets. When they are significantly positive, safe assets offer attractive real returns and the incentive to take risk diminishes.
Real yields above 2% are considered restrictive. Below 0% are highly accommodative. The 2s10s slope matters because an inverted curve signals that the market expects the Fed to cut — and historically precedes economic contraction by six to eighteen months.
The DXY level and its 20-day momentum. The dollar is the world's reserve currency and the primary funding currency for global trade and capital flows. A rising dollar tightens financial conditions globally — it raises the cost of dollar-denominated debt for emerging market borrowers, compresses commodity prices (which are denominated in dollars), and tends to reduce risk appetite across asset classes.
The relationship is not symmetric. Dollar strength can be driven by flight-to-safety (bearish for risk) or by US growth outperformance (less bearish). The framework captures direction and momentum rather than attempting to decompose the cause.
DXY above 105 is considered a stress signal for global financial conditions. Below 93 represents a meaningful tailwind for risk assets, emerging markets, and commodity prices.
US High Yield option-adjusted spreads (OAS), US Investment Grade OAS, Emerging Market High Yield spreads, and the VIX. Credit spreads are the market's real-time assessment of default risk and liquidity stress. Unlike equity markets, which can remain elevated on narrative momentum, credit markets tend to respond earlier and more honestly to deteriorating fundamentals.
The VIX — the implied volatility of the S&P 500 — is included because it captures market anxiety more directly than spread levels alone, and because the relationship between rising volatility and tightening credit is consistent and well-documented.
Tight spreads and low VIX signal genuine risk-on conditions. Widening spreads — particularly in high yield — are among the most reliable early-warning indicators of a regime shift from expansion to contraction.
Non-farm payrolls, industrial production, the unemployment rate, the copper/gold ratio, ISM Manufacturing PMI, and ISM Services PMI. This is the broadest category — and deliberately the lowest-weighted.
Growth indicators are lagging, or at best coincident. By the time a recession is confirmed in the data, markets have typically already repriced. The value of this category is not in identifying turning points — it is in confirming that the regime we have already classified from leading indicators is consistent with what the real economy is actually doing.
The copper/gold ratio deserves particular mention. Copper is the most economically-sensitive industrial metal; gold is the ultimate safe-haven asset. Their ratio is a real-time, market-derived growth proxy — rising when industrial demand outpaces defensive positioning, falling when the opposite is true. It is one of the most useful and underappreciated signals in macro analysis.
This category carries the lowest weight in the framework — not because growth does not matter, but because by the time growth data changes, the liquidity and credit signals have already told you what to expect.
The Chicago Fed National Financial Conditions Index (NFCI) and the St. Louis Fed Financial Stress Index (STLFSI). Both are weekly, freely available, and composite — they aggregate dozens of financial market variables into a single standardised number.
The NFCI incorporates money markets, debt and equity markets, and the traditional and shadow banking systems. The STLFSI captures rates, spreads, and other market indicators. Together they provide a robust, independently-constructed cross-check on what the individual category inputs are telling us.
Both indices are centred at zero, with values below zero indicating looser-than-average financial conditions and values above zero indicating tighter-than-average. They are particularly useful during periods when the primary indicators give mixed signals.
The AI capital expenditure cycle has become a structurally significant macro force. Semiconductor equities — NVDA, the SMH ETF — serve as real-time proxies for the pace of AI infrastructure investment. Utilities (XLU) track the data centre power demand signal downstream.
This category scores the momentum of the AI investment cycle: whether the capex build-out is accelerating, stable, or contracting. An expanding AI CapEx cycle is a growth tailwind independent of the traditional business cycle, and its interaction with liquidity conditions determines whether the tailwind is sustainable or speculative.
AI CapEx is the newest category in the framework — added as the scale of the investment cycle became impossible to ignore as a macro input. It is scored primarily from equity momentum rather than hard economic data, which makes it directionally useful but more volatile than the other categories. It carries equal weight to Growth Indicators.
Regime classifications
The seven 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.
"When net liquidity expands, risk assets tend to perform. When it contracts, they struggle — regardless of what growth or earnings are doing in the short term. This is the core of the Tara Capital analytical framework."
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.
How the framework is used
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 framework does not tell you what to do. It tells you what kind of world you are operating in. That distinction matters enormously.
Phase 1 of the TCIF answers one question: what macro regime are we in? Phase 2 will answer the logical next question: given that regime, where should capital be allocated?
We are building three allocation modules that will map directly to the live regime score:
- Country allocation — DM vs EM tilt, driven by the dollar score, real yield level, and liquidity direction. A strong dollar and rising real yields favour DM; a weakening dollar with expanding net liquidity favours EM.
- Sector allocation — which equity sectors the current macro regime supports. In a Liquidity Expansion, the framework tilts toward AI infrastructure, semiconductors, and rate-sensitive growth. In a Credit Contraction, toward energy, healthcare, and cash-generative defensives. In a Mid-Cycle regime like today's, quality cyclicals and selective growth. Regime drives sector — forward-looking, not backward-looking.
- Theme allocation — which structural investment themes the current macro environment is actively supporting. Themes include: AI infrastructure (captured directly by the AI CapEx category), digital assets (regime-sensitive to liquidity and dollar direction), commodity supply (favoured in stagflationary environments with a weak growth score), and fiscal-driven infrastructure (favoured when government spending is the dominant growth driver). These are live, structural themes — not historical pattern-matching.
Each module will generate regime-conditional allocation signals that update automatically each Monday alongside the composite score. The goal is a fully integrated research-to-allocation pipeline — transparent, auditable, and grounded in the same analytical framework that underpins every research call Tara Capital makes.
The framework is reading 60/100 — the environment is balanced and sustainable, with no dominant stress signal. Financial Conditions is the standout tailwind at 83, with NFCI -0.51 (very loose) and STLFSI -0.77 (low stress) — aggregate conditions are materially easier than their historical average. 3 of 7 categories are on improving trajectories, giving the composite a positive short-term bias. The key watch-point is whether Real Yields continue rising — that is the variable most likely to break the current equilibrium.