Laomate
MOD-01
Strategy engine
Rule-based engines for laddered accumulation, volatility-band rebalancing and stop-loss variants on leveraged and sector ETFs. Every rule is versioned and testable.
Private betaSeongnam, KR
Quant research and trading automation for systematic ETF strategies.
Laomate turns years of market data into tested, rule-based strategies — then runs them every trading day through your own brokerage account, with risk gates and a full audit trail. Claude is our research engine.
Started2026.03
Commits1,290+
Research rounds40+
Price history10 yrs
01 / Product
One platform, from hypothesis to live order.
Research a rule, test it against history, watch the market regime, and execute on schedule — without spreadsheets or manual order entry.
MOD-02
Backtesting & simulation
Replay strategies over daily and intraday history with realistic fills, tick-size rounding and shared cash pools across a 13-asset universe.
MOD-03
Market early-warning
Multi-track risk signals combine volatility, drawdown and macro indicators into a single regime level that gates how much capital each strategy may use.
MOD-04
Screening & indicators
A daily-ingested catalog of 20+ tradable ETFs with RSI tracking, fear & greed gauges, economic indicators and per-symbol charts.
MOD-05
Broker automation
Orders go out through the user's own Korean brokerage API on a fixed daily schedule, with idempotent run gates, pre-trade validation and encrypted credentials.
MOD-06
Audit trail & alerts
Every order, fill and decision is logged with sensitive data redacted. Daily summaries and warnings are pushed to the operator in real time.
01 Research
Form a hypothesis
Collect price and intraday data.
02 Test
Backtest across regimes
Keep only rules that survive stress periods.
03 Monitor
Gate by risk level
Early-warning sets allowed exposure.
04 Execute
Scheduled orders
Through the broker API, logged and verified.
02 / Claude
Claude is our research engine.
Claude reads the data, tests the rules and writes the engine code. Next, we are bringing it into the product itself.
Today
Quant research engineer
- 01Manages and analyzes large price datasets — 10 years of daily bars plus intraday minute data for a 13-asset universe.
- 02Time-series analysis: drawdown regimes, volatility clustering, closing-auction vs. VWAP execution studies.
- 03Turns trading-rule hypotheses into backtests and runs structured research rounds (40+ so far), recording what was accepted and rejected.
- 04Writes, reviews and tests the TypeScript strategy engines and Python execution worker.
Next · Claude API
Inside the platform
- 01A research assistant that runs backtests on request and explains the results in plain language.
- 02Daily market briefs explaining why the early-warning level changed and what it means for each strategy.
- 03Anomaly review of fills and logs before the next session — a human approves any change to live rules.
- 04Structured extraction from market data and reports into the research database.
03 / Changelog
Shipping since March 2026.
Project started. Core state machine, strategy templates, order queue, pre-trade validation, brokerage adapter and first dashboard.
Laomate brand. Daily scheduler with idempotent run gates, live-environment safety guards and a portfolio overview dashboard.
Market screening: ETF catalog, RSI tracking, economic indicators, fear & greed gauge. Trading-terminal design system.
Second brokerage integration and multi-broker routing. Korean-listed ETF support with tick-size quantization.
Regime research on exhaustion markets; stop-loss rules for balanced strategies. Execution-price (VWAP) data surfaced in the product.
Intraday data backfill: closing-30-minute VWAP history for path-dependent fill modeling.
13-asset shared-cash-pool backtest dashboard with yearly settlement, plus adjusted daily OHLC panels from listing date.
10-year closing-auction vs. limit-VWAP execution study; research round 42 with long-horizon validation of drawdown and volatility dials.
04 / About
Built for systematic investors.
Laomate started in Korea in March 2026 as a way to run systematic ETF strategies without manual order entry, and grew into a research platform for testing trading rules against real market data before any capital is put at risk.
The product is in private beta with invite-only, operator-approved accounts.
- Company
- Laomate
- Founded
- 2026.03
- Location
- Seongnam-si, Gyeonggi-do, South Korea
- Stage
- Bootstrapped · Private beta
- Stack
- Next.js · Python · PostgreSQL · Claude
- Contact
- taehyeon@laomate.dev
Join the private beta.
We are onboarding a small group of systematic investors. Tell us which markets and strategies you run.