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Releases: borghei/orbiter

v0.3.0 — AI-Powered Portfolio Intelligence

12 Mar 14:46
@borghei borghei
v0.3.0
9cab8d0

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v0.3.0 — AI-Powered Portfolio Intelligence Latest
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What's New in v0.3.0

Black-Litterman with AI-Generated Views

Combine market equilibrium with subjective views — manually or via AI. Supports Claude, OpenAI, and Perplexity through a unified middleware with provider adapters.

from orbiter import BlackLitterman, View, get_ai

views = [View(asset="SOL", return_view=0.30, confidence=0.7)]
result = BlackLitterman(returns).optimize(views)

# Or generate views with AI
ai = get_ai("claude")  # reads ANTHROPIC_API_KEY from env

Sentiment-Enhanced Regime Detection

Goes beyond price-only HMM by fusing Fear & Greed Index, perpetual funding rates, and exchange net flows for earlier regime shift detection.

DeFi Yield-Adjusted Optimization

Staking yields from DeFiLlama (7000+ protocols) are factored into the efficient frontier. ETH earning 3.5% APY is not the same as idle ETH.

3 New Strategies

  • black-litterman — subjective + quantitative views
  • sentiment-regime — multi-signal regime detection
  • yield-adjusted — DeFi yield-aware allocation

By the Numbers

  • 10 optimization strategies (was 7)
  • 159 tests passing (was 94)
  • 6 new modules: ai.py, black_litterman.py, prompts.py, sentiment.py, defi.py, + enhanced regime.py

Install

pip install orbiter-crypto
pip install orbiter-crypto[ai]        # + Claude/OpenAI SDKs
pip install orbiter-crypto[dashboard]  # + Streamlit/Plotly
Assets 6
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v0.2.1

12 Mar 14:18
@borghei borghei
v0.2.1
00a52eb

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v0.2.1

Fix image rendering on PyPI — use absolute URLs for banner and screenshots.

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v0.2.0

12 Mar 14:13
@borghei borghei
v0.2.0
756104b

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v0.2.0

Orbiter v0.2.0

Lightweight crypto portfolio optimizer with 7 optimization strategies, 8 risk metrics, and an interactive dashboard.

Features

  • 7 strategies: Max Sharpe, Min Volatility, Min CVaR, Risk Parity, HRP, Regime-Aware, Factor-Max-Sharpe
  • 8 risk metrics: Sharpe, Sortino, CVaR, Max Drawdown, Calmar, Omega, annualized return/volatility
  • Walk-forward backtesting with out-of-sample validation
  • Stress testing: Monte Carlo (normal & Student-t) + correlation stress
  • Regime detection: HMM-based bull/bear/sideways detection
  • Factor model: Market, momentum, size, liquidity factors
  • Transaction cost modeling: Maker/taker fees, Almgren-Chriss slippage
  • Rebalancing simulation: Calendar, threshold, hybrid triggers
  • Interactive Streamlit dashboard
  • CLI: orbiter optimize, orbiter backtest, orbiter stress, orbiter discover, orbiter dashboard

Install

pip install orbiter-crypto
pip install orbiter-crypto[dashboard]
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