Multi-factor selection & rebalance
Encode client-given factor blends, score ranking, and position constraints into backtestable, auto-rebalancing execution code.
Cases
Common stock and futures strategy types. Cases only show how client-given objective rules or model outputs become code; the rules/models themselves come from clients and do not constitute investment advice or strategy recommendations.
Sector / style rotation
Implement scheduled rebalances and constraint checks from client-given rotation signals, position caps, and turnover cadence.
ETF grid & DCA
Turn client-given grid spacing, add/reduce conditions, and DCA cadence into backtestable executable code.
Multi-symbol CTA trend
Automate client-given trend tests, sizing formulas, and drawdown/exposure caps across symbols, with historical backtests.
Machine-learning signal execution
Wire client-given model signals or inference outputs into feature alignment, order placement, and risk-constraint engineering.
Calendar / cross-instrument arb
Monitor and trade client-given spread thresholds, leg ratios, and margin constraints, with reproducible backtests.
Index-enhancement portfolio
Build, rebalance, and backtest portfolios from client-given benchmark constraints, excess-return targets, and risk budgets.
Intraday breakout & risk controls
Implement auto-trading and backtests from client-given range breakouts, volume filters, and stop/target/time-exit conditions.