Data Ownership
Self-controlled ingestion, storage, labeling, and metric pipelines reduce dependency on opaque vendor feeds.
MAMAKQUANT
VERTICALLY INTEGRATED QUANT INFRASTRUCTURE
From blockchain nodes to market intelligence, research engines, and automated execution.
Primary infrastructure path
1
Raw Blockchain Data
2
MQNODE
3
MQENGINE
4
MQBOT
5
OMS / Execution
Signal loop
Market Data
Research
Strategy
Execution
Feedback
ingest.stream(status=clean)
metrics.point_in_time=true
research.queue=active
Company positioning
FROM RAW MARKET DATA TO STRATEGY-READY INTELLIGENCE
MAMAKQUANT is designed to own the full data and strategy pipeline instead of depending only on third-party vendors. The goal is to transform blockchain, exchange, and market data into clean, point-in-time-correct, research-ready, and execution-ready signals.
Research Velocity
Point-in-time data contracts make it faster to test, reject, and refine factors with institutional discipline.
Execution Readiness
Validated signals are designed to move toward monitored deployment, risk checks, and execution feedback.
Core systems
THE MAMAKQUANT STACK
A vertically integrated stack for market intelligence, quantitative research, validation, and execution.
MQ
MQNODE
Node-native data and metric infrastructure
MQNODE ingests blockchain, exchange, and market data into structured databases for metric generation, on-chain monitoring, entity labeling, and point-in-time data pipelines.
- Blockchain node data ingestion
- Exchange price and market feeds
- Time-series metric storage
- Entity and wallet clustering
- Reserve and flow monitoring
- API-ready data contracts
MQ
MQENGINE / MQBTDASH
Research, backtesting, and visualization layer
MQENGINE converts raw and derived metrics into testable trading signals. MQBTDASH provides visualization, strategy diagnostics, performance analytics, and research workflows.
- Factor research
- Backtesting engine
- Sharpe, Calmar, drawdown, win-rate analytics
- Equity curve visualization
- Walk-forward and robustness testing
- Strategy validation pipeline
MQ
MQBOT
Automated strategy execution framework
MQBOT is the execution layer for deploying validated strategies into live trading environments with monitoring, risk controls, and OMS integration.
- Strategy execution modules
- CTA, mean-reversion, event-driven, HFT, and sniping modules
- Exchange execution connectors
- Real-time logging
- OMS feedback loop
- Risk and position monitoring
MQ ChainActivity
MQ CHAINACTIVITY
Entity-aware on-chain market intelligence
MQ CHAINACTIVITY is designed to convert raw blockchain transactions into entity-aware, sector-aware, and strategy-ready intelligence.
01
Raw Chain Events
02
Entity & Address Graph
03
Protocol / Sector / Asset Mapping
04
Metric Engine
05
Dashboard / API / Strategy Signal
CEX reserve and flow tracking
Wallet clustering and labeling
Deposit, consolidation, cold wallet, and withdrawal flow mapping
Protocol and sector activity
Point-in-time signal generation
Infrastructure edge
BUILT FOR DATA CONTROL, SPEED, AND RESEARCH DEPTH
MAMAKQUANT is designed around ownership of data sources, modular infrastructure, and a clean path from raw data to deployment-ready intelligence.
Self-owned node infrastructure
Direct blockchain access for stronger provenance, lower vendor dependency, and richer raw event coverage.
Private metric engine
Internal derivation logic turns raw data into consistent research and monitoring surfaces.
Modular containers
Worker services can evolve independently across ingestion, reconciliation, research, and execution.
PostgreSQL / TimescaleDB data layer
Structured relational and time-series storage for auditability, replay, and stable API contracts.
Real-time worker pipelines
Streaming and scheduled jobs keep data fresh while preserving validation boundaries.
API-first architecture
Every major layer is designed to expose clean internal or external contracts.
Research-to-execution feedback loop
Live behavior, fills, errors, and market context can flow back into research diagnostics.
Future multi-chain expansion
The architecture is built to extend beyond a single chain, venue, or signal family.
Roadmap
ROADMAP
The current build focuses on the core quant infrastructure stack, with future modules expanding research automation, API distribution, and institutional surfaces.
Current / Core
MQNODE
MQENGINE / MQBTDASH
MQBOT
MQ CHAINACTIVITY
Future
MAMAKQUANTBRAIN
MAMAKQUANT API
Institutional dashboard
Multi-chain intelligence expansion
Strategy marketplace / strategy registry
Automated factor discovery
MAMAKQUANTBRAIN
Automated factor discovery and research intelligence
MAMAKQUANTBRAIN is planned as an automated research layer for discovering, ranking, validating, and monitoring quantitative factors across crypto and multi-asset markets.
Research philosophy
RESEARCH-FIRST. INFRASTRUCTURE-OWNED. EXECUTION-AWARE.
MAMAKQUANT is not only a trading bot. It is a full-stack quantitative infrastructure project where data quality, point-in-time correctness, strategy validation, risk control, and execution feedback are part of the same system.
01
Point-in-time correctness
02
Data quality before signal generation
03
Robustness before deployment
04
Infrastructure ownership as edge
Contact
CONTACT MAMAKQUANT
For partnerships, exchange relationships, data infrastructure discussions, or institutional conversations, send us a message.