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Develop a stock selection strategy with dynamic factor weights to outperform S&P 500. Analysis includes fixed and dynamic factor weights, identification of significant portfolios, and comparison of strategies. Factors include Cashflow to Price, Debt to Equity, Market Capitalization, and Price to Book. Dynamic strategy involves adding dummy variables for S&P500 momentum. Results show outperformance of multi-factor model strategy over S&P500. Consideration for future: transaction costs evaluation.
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Dynamic Factor Weights Red Devil Partners Joon Seong Choi, Youngjun Yoo, Richard Park, YK Kim
Overview • Our purpose is to develop a stock selection strategy in order to outperform S&P 500. • Our analysis includes both fixed and dynamic factor weights.
Steps • Specify list of factors • Univariate screens • Identify 5 fractiles for each factor • Choose significant portfolios • Optimize weights for portfolios with S&P500 volatility • Compare fixed weight strategy and dynamic weight strategy
Identified factors • Factors (1m lagged) - Cashflow to Price - Debt to Equity - Market Capitalization - Price to Book
Factor Screen Cashflow to Price(5) : value weighted Debt to Equity(5) : value weighted Market Cap(1) : equal weighted Price to Book(5) : equal weighted
Optimization: fixed weights • Form a portfolio with same volatility of S&P500
Dynamic weight strategy Add dummy variables 3 months S&P500 momentum In negative momentum, buy more portfolio with negative correlation with S&P500 (Price to book (5))
Optimization: dynamic weights • Form a dynamic portfolio with same volatility of S&P500
Conclusion Multi-factor model strategy outperforms universe return (e.g. S&P500) Dynamic weight strategy outperform fixed weight strategy Future consideration: Transaction cost should be considered to evaluate strategies