Research

Five AI-driven research capabilities.

Each capability below is an autonomous, quantitative coverage area — not a team of human analysts. Together they feed a single analysis-to-execution pipeline governed by firm-wide risk constraints.

01

Macro & Fixed Income Research

An AI capability tracking the monetary-policy and rates environment that anchors valuations across every other coverage area. It monitors central-bank communication, the front-to-long end of the curve, and primary-market supply.

Methodology
Quantitative monitoring of policy signals, curve shape, and auction dynamics; event-driven analysis around scheduled releases and central-bank communications.
Data sources
Federal Reserve communications and policy decisions, Treasury auction results, yield-curve and rates data, and scheduled macroeconomic releases.
Coverage universe
US monetary policy, the Treasury yield curve, and interest-rate-sensitive instruments.
02

Equity Research — US Markets

A high-throughput screening capability that ranks the US equity market by momentum and participation, surfacing movers, gaps, and unusual relative volume across the full listed universe.

Methodology
Momentum and relative-volume screening, gap and movers analysis, applied systematically across the listed universe.
Data sources
US market price and volume data, intraday movers and gap data, and relative-volume measures.
Coverage universe
Approximately 9,000 US-listed securities.
03

Digital Assets Research — Crypto

A digital-asset capability combining on-chain analysis with short-horizon momentum, monitoring exchange reserves and flows alongside price action across a broad set of instruments.

Methodology
On-chain flow and exchange-reserve analysis combined with momentum-based, short-horizon scalping signals.
Data sources
On-chain transaction data, exchange reserve and flow metrics, and digital-asset price and volume data.
Coverage universe
Approximately 430 digital-asset instruments.
04

Alternative Data & Signals

A cross-source capability that looks beyond price for confirmation, building confluence from economic-adjacent and behavioral signals before a thesis is acted on.

Methodology
Signal confluence — combining independent alternative-data streams to corroborate or challenge views formed elsewhere in the research framework.
Data sources
Job-posting and labor data, shipping and logistics activity, and sentiment and market-chatter signals.
Coverage universe
Cross-asset alternative and sentiment signals used to support macro, equity, and digital-asset coverage.
05

Risk & Portfolio Analytics

The control layer that governs every other capability. No research view reaches execution without clearing the constraints maintained here.

Methodology
Systematic position sizing, circuit-breaker logic, drawdown limits, and continuous monitoring of exposure concentration.
Data sources
Live position and order data, realized and unrealized P&L, and exposure metrics across the portfolio.
Coverage universe
The full firm portfolio across macro, equity, and digital-asset positions.

AI Disclosure

Each research capability described above is an autonomous AI system, not a desk staffed by human analysts. Coverage figures describe the breadth of instruments monitored and are not performance claims. Monas Financial makes no representation as to returns or assets under management, and nothing on this page is investment advice.