Frequently Asked Questions About Capital Flows Macro Regime Framework
21 answers covering everything from basics to advanced usage.
// Basics
What is a macro regime and how many types are there?
A macro regime is the prevailing combination of growth, inflation, macro liquidity, and credit cycle conditions that determines which asset correlations are live and how capital flows globally. Rather than fixed categories, the framework classifies across four axes: growth accelerating or decelerating, inflation rising or falling, liquidity expanding or contracting, and credit cycle phase (early, mid, late, or stress).
What is the difference between macro liquidity and the Fed policy rate?
Macro liquidity is the aggregate availability of money and credit flowing through the global financial system, distinct from the Fed's policy rate. Expanding macro liquidity supports risk assets while contracting liquidity pressures them. Critically, liquidity can appear to contract while positioning is too short, producing forced melt-ups — a signal invisible if you only watch the policy rate.
What inputs do I need to run the framework on a new trade?
You need three required inputs: a description of the current macro regime (inflation direction, liquidity, credit cycle phase), the specific asset or instruments under consideration, and your time horizon intent (intraday, intra-week, or multi-week). Optionally, list existing positions that could interact with the thesis and relevant country or market context like Japan carry dynamics or CAD as an oil proxy.
Do I need live market data to use this framework?
Live data helps but isn't mandatory to start. The framework references a STIR Replication Playbook to build a CME FedWatch-type tool if you lack live SOFR pricing. The foundational move — classifying the regime across four axes and running country structural analysis — can be done from public rates, FX, and commodity data plus pre-built dashboards run each morning.
// How To
How do I start my trading day using this framework?
Run AI scripts and pre-built dashboards to update sector flows, short interest, vol premiums, options skew, and order book signals before doing anything else. Do not open futures and ask 'what's up on the day?' — that is the pre-framework habit. Let aggregated data surface what deserves attention, then ask whether you know something the market is pricing at near-zero probability.
How do I run a Country Structural Analysis?
For each country in your thesis, map its demographic profile, commodity long/short position (e.g. Japan is structurally short oil), GDP composition (private versus public spending trend), central bank balance sheet trajectory, and FX regime. This surfaces fundamental currency and flow pressures. Understanding US markets deeply requires understanding foreign markets, because the structural differences reveal the connections.
How do I calibrate position size to my time horizon?
Match sizing to the volatility implied by your declared time horizon, not the volatility you wish it had. Check whether the SOFR strip creates a near-term rate floor or ceiling that anchors your entry/exit window. If ranges are tight, tighten the horizon; expand risk aggressively only when the Move Index or commodity vol spikes into genuine dislocations.
How do I express an oil spike across FX and bonds?
Check the SOFR strip for rate anchoring, then classify the regime as an inflation shock. Country analysis shows Japan (short oil) weakens JPY while Canada (net exporter) strengthens CAD, making CADJPY the cleanest FX expression that historically leads oil. Cross-collateralise by shorting ZN/ZB as the shock transmits. CADJPY confirming both the rally and any double-top reversal validates the signal.
// Troubleshooting
My thesis feels right but the trade keeps losing — what's wrong?
You likely started with a feeling and hunted for confirming data, which fails the coherence test outright. Rebuild from evidence outward: confirm causality is correctly directed rather than reverse-engineered from your desired outcome, and verify every sub-component connects without contradiction. If any part contradicts, the thesis is incoherent and should be revised or exited, not averaged into.
How do I know if an intraday sell-off is a real signal or just hedging?
Distinguish institutional hedging from a directional signal. Ahead of events, players sell ES/NQ to go market-neutral — not because the macro thesis changed. Check the SOFR strip: if the near contract has limited downside before the next FOMC, that rate floor sets a bottom in ES. The flush is a hedging artifact you can use as an entry, not a directional reversal.
Why does my rally in a single stock keep reversing?
Run the MFRA Stock Attribution Model to decompose the return into sector flows versus fundamental flows. If sector flows are positive but fundamental flows are negative and deteriorating, the stock is being lifted by the macro tide, not earnings power. When the fundamental catalyst arrives, the fundamental flow reversal will reprice the stock more than all sector flows combined.
I keep sizing up and getting stopped out — what am I doing wrong?
You are probably sizing on comfort or on the obvious trade at the obvious catalyst and price level. These setups are easiest to define risk on but historically have the lowest edge. Reserve maximum size for setups where flows make structural sense, timing is obscure rather than catalyst-anchored, and coherence is highest. Size proportional to evidence weight, not familiarity.
// Comparisons
How does this framework compare to technical analysis alone?
This framework treats TA as valid only after foundational reps — knowing what beats what, why TA is or isn't relevant, the Greeks, how futures rolls work. It anchors decisions to interest rates and macro regime first, mapping data points to specific price levels rather than trading patterns in isolation. TA becomes a tool for defining entry within a coherent macro thesis, not the thesis itself.
How does this compare to trading scheduled economic catalysts?
The framework explicitly favors obscure flow-driven setups over obvious catalysts. Obvious trades attract the most size but have the lowest edge, while obscure setups in 'no man's land' — away from clean support/resistance and scheduled events — have higher hit rates. Catalysts are used as entry points within a higher-time-horizon thesis, never as standalone scalp opportunities.
How is this different from a top-down macro fund's process?
The core distinction is coherence and cross-collateralisation over directional conviction. Rather than a single big directional bet, this framework stacks multiple independent expressions of the same macro force, weights data by true causal importance rather than tallying it, and calibrates volatility to time horizon. It is executable at retail scale using replicable tools like a STIR curve replication playbook.
// Advanced
What does 'earn the right to go meta' mean in practice?
Qualitative, intuitive market reads are only valid after accumulating foundational reps — understanding what beats what, why TA is or isn't relevant, the Greeks, and how futures rolls work. Trying to operate at the intuitive meta level before earning that foundation produces esoteric theorising with no executable output. Build the mechanical foundation first, then intuition becomes reliable.
How do futures calendar spread extremes fit into the framework?
When a front/second month spread hits a historical extreme during a roll period, cross-collateralise by checking if related commodity complexes are also bidding. The asymmetric bet is a mean-reversion fade toward partial reversion, not the full historical high, with a tight stop below the extreme. Time horizon is roll-specific; size modestly until the order book confirms roll-seller exhaustion, then scale.
What is 'getting on sides' and how do I use it?
Getting on sides means establishing an initial intraday or intra-week position that, if it moves in your favor, gives you optionality to hold for a larger multi-week macro view. You bat singles intraday to build the position, then hold for the bigger picture if the thesis remains coherent — rather than closing at the intraday target and forfeiting the macro swing.
When does a contracting-liquidity environment produce a melt-up?
A melt-up occurs precisely when liquidity appears to be contracting but positioning is too short. Underexposed investors are forced to buy back at progressively higher prices, producing a rapid forced rally. This counterintuitive setup is why positioning data matters as much as liquidity direction — the crowd being wrong-footed creates the asymmetric fuel.
How do I know when rate markets go from boring to high-edge?
Watch the Move Index, the implied volatility index for US Treasuries. A spike signals interest rate markets are entering a high-volatility, high-opportunity phase where tectonic macro shifts are being priced. That is the moment rate products go from boring instruments to the highest-edge trades available, warranting aggressive risk expansion into genuine dislocations.
What is the positioning premium and how does it create trades?
The positioning premium is a price dislocation created by crowded or one-sided market positioning that opens an entry for a contrarian or mean-reversion trade with asymmetric risk/reward. When positioning becomes extreme, the marginal buyer or seller is exhausted, so the flow-driven reversal offers a defined, skewed payoff — a core source of edge in the framework.