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Inverse Volatility with Stock2vec Clustering

Strategy

  1. Stock2vec Clustering
    • make dailty log-return series Embedding Vectors by Word2vec-Skipgram
    • pass the embedding vectors to K-Means Clustering Algorithm
      • num_clusters : 5
  2. Stock2Vec Clustering + Double Inverse Volatility
    • inverse volatility between assets in one cluster
    • inverse volatility between clusters
  3. Stock2Vec Clustering + inverse volatility + min volatility
    • inverse volatility between assets in one cluster
    • minimize portfolio volatility using clusters
  4. Risk parity
  5. Minimum Volatility
  6. Maximum Sharpe Ratio
  7. Equal Weight
  8. Inverse Volatility

Implemenation

python main.py

Data

  • ETF (2008.01 ~ 2022.02)
    • VTI : Vanguard Total Stock Market Index Fund ETF
    • VEA : Vanguard Developed Markets Index Fund ETF
    • VWO : Vanguard Emerging Markets Stock Index Fund ETF
    • IAU : iShares COMEX Gold Trust ETF
    • DBC : Invesco DB Commodity Index Tracking Fund
    • XLB : Materials Select Sector SPDR Fund
    • XLE : Energy Select Sector SPDR Fund
    • XLF : Financial Select Sector SPDR Fund
    • XLI : Industrial Select Sector SPDR Fund
    • XLK : Technology Select Sector SPDR Fund
    • XLP : Consumer Staples Select Sector SPDR Fund
    • XLU : Utilities Select Sector SPDR Fund
    • XLV : Health Care Select Sector SPDR Fund
    • XLY : 미 경기소비재 ETF

Result

결과

Requirements

finance-datareader==0.9.31
gensim==4.1.2
matplotlib
numpy==1.19.3
pandas==1.3.4
scikit-learn==1.0.2
scipy==1.8.0
tqdm==4.62.3