StratCraft
Strategy Type

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 algorithms2 libraries
Algorithm Network

How factor algorithms connect across libraries

📊Factor/Alpha
🔬
Microsoft Qlib3 algos
🤖
AI Hedge Fund2 algos
Alpha158intermediate
Alpha360intermediate
TopkDropoutStrategyintermediate
Warren Buffett Agentintermediate
Charlie Munger Agentintermediate
Trading Decision Pipeline

How factor algorithms work together in a trading system

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
Algorithm Comparison

Compare factor algorithms across key dimensions

Algorithm Comparison MatrixClick a column to expand details
Metric
Alpha158Qlib (Microsoft)
Alpha360Qlib (Microsoft)
TopkDropoutStrategyQlib (Microsoft)
Warren Buffett AgentAI Hedge Fund
Charlie Munger AgentAI Hedge Fund
🎯Complexity⭐⭐⭐intermediate⭐⭐⭐intermediate⭐⭐⭐intermediate⭐⭐⭐intermediate⭐⭐⭐intermediate
📈Prediction TypeMixedMixedMixedMixedMixed
⚡Training Speed⚡⚡⚡⚡⚡⚡⚡⚡⚡⚡
🎯Accuracy📊📊📊📊📊📊📊📊📊📊
💡Best ForGeneral purposeGeneral purposeGeneral purposeGeneral purposeGeneral purpose
Complexity:

Qlib (Microsoft)

Alpha158
Qlib (Microsoft)
Factor / Alphaintermediate

Collection of 158 technical alpha factors including price, volume, and volatility features.

Speed⚡⚡
Accuracy📊📊📊
Source:qlib/contrib/data/handler.py
Alpha360
Qlib (Microsoft)
Factor / Alphaintermediate

Extended collection of 360 technical alpha factors for comprehensive feature engineering.

Speed⚡⚡
Accuracy📊📊📊
Source:qlib/contrib/data/handler.py
TopkDropoutStrategy
Qlib (Microsoft)
Factor / Alphaintermediate

Top-K stock selection with random dropout for portfolio diversification.

Speed⚡⚡
Accuracy📊📊📊
Key Parameters
topk50Number of stocks to hold
n_drop5Number of stocks to randomly drop
Source:qlib/contrib/strategy/signal_strategy.py

AI Hedge Fund

Warren Buffett Agent
AI Hedge Fund
Factor / Alphaintermediate

Value investing agent analyzing intrinsic value, margin of safety, and fundamental metrics.

Speed⚡⚡
Accuracy📊📊📊
Charlie Munger Agent
AI Hedge Fund
Factor / Alphaintermediate

Quality analysis agent focusing on competitive moats, management quality, and business economics.

Speed⚡⚡
Accuracy📊📊📊
Related Strategy Types
Machine Learning →Indicator-Based →All Algorithms →

Factor & Alpha Trading Strategies — Algorithm Reference

Alpha158 (Qlib (Microsoft))
Collection of 158 technical alpha factors including price, volume, and volatility features. Source: 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. Source: 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. Key parameters: topk (Number of stocks to hold), n_drop (Number of stocks to randomly drop). Source: 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. Source: 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. Source: https://github.com/virattt/ai-hedge-fund.