Results for “quantitative-trading”

Backtests quantitative trading strategies across 9 engines and 25 data sources, analyzes trade journals, and runs multi-agent research teams.

Develops and backtests quantitative trading strategies for the Chinese securities market using the QMT terminal's built-in Python framework, covering data retrieval, order placement, and position management.

Analyze URLs or text to discover ranked Polymarket, Hyperliquid, and Deribit markets with Quotient edge scores, paid via on-chain x402 settlement.

Access Quotient market intelligence via API key or x402 micropayments, with explicit payment challenge handling.

Designs and backtests systematic trading strategies using technical indicators, fundamental analysis, and statistical models, with clear entry/exit rules, risk controls, and documentation.

Identifies and analyzes statistical arbitrage opportunities through pair trading, using correlation analysis, cointegration testing, and z-score calculations to generate entry/exit signals for market-neutral strategies.

Analyze and simulate options trading strategies using Black-Scholes pricing, Greeks calculation, and risk management guidance.

Calculate risk-based position sizes for long stock trades using fixed fractional, ATR-based, or Kelly Criterion methods with portfolio constraints.

Executes on-chain token trades and queries data on Solana, Ethereum, BSC, and Base via the XXYY Open API.

Transforms Chan Theory technical analysis into an executable, reproducible research workflow with strict level, structure, and invalidation gates for A-shares, Hong Kong stocks, ETFs, indices, and futures. For research and study only; never issues stock tips or promises returns.

Provides expert guidance for systematic backtesting of trading strategies, covering methodology, stress testing, bias prevention, and result interpretation.