claude

ruflo-neural-trader

Neural trading strategies — self-learning LSTM/Transformer/N-BEATS models with Rust/NAPI backtesting

0 on GitHubby ruvnetv0.2.0MITupdated 25 days ago
/

Plugin ruflo-neural-trader from marketplace ruflo in Prasanth595/ruflo. Commands read from the repo's manifest — 19 days ago.

What it installs

Skills (6)

  • trader-backtest

    Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation

  • trader-portfolio

    Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan

  • trader-regime

    Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy

  • trader-risk

    Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status

  • trader-signal

    Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction

  • trader-train

    Train neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals

Slash commands (1)

  • /ruflo-neural-trader:trader

    Neural trading via npx neural-trader — strategies, backtesting, signals, risk, portfolio optimization

Subagents (4)

  • backtest-engineer

    Backtesting specialist using npx neural-trader Rust/NAPI engine — walk-forward validation, Monte Carlo simulation, parameter optimization

  • market-analyst

    Market regime detection and technical analysis using npx neural-trader — RSI, MACD, Bollinger Bands, volume profile, regime classification

  • risk-analyst

    Portfolio risk assessment and position sizing using npx neural-trader — VaR/CVaR, Kelly criterion, circuit breakers, correlation monitoring

  • trading-strategist

    Designs and optimizes neural trading strategies using npx neural-trader — LSTM/Transformer models, Rust/NAPI backtesting, Z-score anomaly detection

View source on GitHub

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