戦略タイプ
Factor & Alpha Trading Strategies
Quantitative Signal-Based Portfolio Construction
Factor and alpha strategies use quantitative signals derived from financial data to predict asset returns. These strategies exploit systematic risk premia and market inefficiencies through statistical factor models and signal-based portfolio construction.
5 アルゴリズム2 ライブラリ
アルゴリズムネットワーク
ファクター / アルファアルゴリズムのライブラリ間連携
Factor/Alpha
Microsoft Qlib3 algos
AI Hedge Fund2 algos
Alpha158intermediate
Alpha360intermediate
TopkDropoutStrategyintermediate
Warren Buffett Agentintermediate
Charlie Munger Agentintermediate
トレーディング判断パイプライン
ファクター / アルファアルゴリズムが取引システム内でどのように協調するか
1
Factor Computation
Alpha signal generation
Technical indicators (158/360)
Fundamental factors
Alternative data signals
2
Asset Scoring
Cross-sectional ranking
Factor normalization
Composite score calculation
3
Portfolio Construction
Position allocation
Top-K stock selection
Weight optimization
4
Rebalancing
Periodic adjustment
Scheduled rebalance
Drift threshold triggers
5
Risk Control
Exposure management
Factor neutrality
Sector/industry constraints
アルゴリズム比較
主要な観点でファクター / アルファアルゴリズムを比較
アルゴリズム比較マトリクス列をクリックして詳細を表示
| 項目 | Alpha158Qlib (Microsoft) | Alpha360Qlib (Microsoft) | TopkDropoutStrategyQlib (Microsoft) | Warren Buffett AgentAI Hedge Fund | Charlie Munger AgentAI Hedge Fund |
|---|---|---|---|---|---|
| 複雑度 | ⭐⭐⭐intermediate | ⭐⭐⭐intermediate | ⭐⭐⭐intermediate | ⭐⭐⭐intermediate | ⭐⭐⭐intermediate |
| 予測タイプ | 混合 | 混合 | 混合 | 混合 | 混合 |
| 学習速度 | ⚡⚡ | ⚡⚡ | ⚡⚡ | ⚡⚡ | ⚡⚡ |
| 精度 | 📊📊 | 📊📊 | 📊📊 | 📊📊 | 📊📊 |
| 最適用途 | 汎用 | 汎用 | 汎用 | 汎用 | 汎用 |
Qlib (Microsoft)
Collection of 158 technical alpha factors including price, volume, and volatility features.
速度⚡⚡
精度📊📊📊
ソース：
qlib/contrib/data/handler.pyExtended collection of 360 technical alpha factors for comprehensive feature engineering.
速度⚡⚡
精度📊📊📊
ソース：
qlib/contrib/data/handler.pyFactor & Alpha Trading Strategies, アルゴリズムリファレンス
- Alpha158 (Qlib (Microsoft))
- Collection of 158 technical alpha factors including price, volume, and volatility features. ソース: https://github.com/microsoft/qlib/blob/main/qlib/contrib/data/handler.py.
- Alpha360 (Qlib (Microsoft))
- Extended collection of 360 technical alpha factors for comprehensive feature engineering. ソース: https://github.com/microsoft/qlib/blob/main/qlib/contrib/data/handler.py.
- TopkDropoutStrategy (Qlib (Microsoft))
- Top-K stock selection with random dropout for portfolio diversification. 主要パラメータ: topk (Number of stocks to hold), n_drop (Number of stocks to randomly drop).ソース: https://github.com/microsoft/qlib/blob/main/qlib/contrib/strategy/signal_strategy.py.
- Warren Buffett Agent (AI Hedge Fund)
- Value investing agent analyzing intrinsic value, margin of safety, and fundamental metrics. ソース: https://github.com/virattt/ai-hedge-fund.
- Charlie Munger Agent (AI Hedge Fund)
- Quality analysis agent focusing on competitive moats, management quality, and business economics. ソース: https://github.com/virattt/ai-hedge-fund.