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Bottom-Up Stock Selection Method

Bottom-Up Stock Selection Method. Korea Stock Market. Long Term Optimal Management. Agenda. Methodology Analysis and results Final remarks. Methodology. Steps : 1. Build the database 2. Develop a algorithm and program 3. Analyze results for each simple sorting factor

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Bottom-Up Stock Selection Method

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  1. Bottom-Up Stock Selection Method Korea Stock Market Long Term Optimal Management Long Term Optimal Management

  2. Agenda • Methodology • Analysis and results • Final remarks Long Term Optimal Management

  3. Methodology Steps: 1. Build the database 2. Develop a algorithm and program 3. Analyze results for each simple sorting factor 4. Build optimal portfolio using top and bottom fractiles of each sorting factor 5. Track results for the score based portfolio Long Term Optimal Management

  4. Analysis and results • For each sorting factor considered: • Returns and volatility: for the hold period of analysis • Stability: Average return for different periods of time • % times outperforming the index benchmark in bullish and bearish periods Long Term Optimal Management

  5. Analysis and results Selected sorting factor considered in our analysis: • Dividend yield • Earnings yield • Book to price ratio • Cash earnings to price yield • Prospective price earnings 12 month forward • Prospective price earnings fiscal year • Revenue Growth Long Term Optimal Management

  6. Korea Stock Market Performance Long Term Optimal Management

  7. Average return Long Term Optimal Management

  8. % Period Outperform Market Long Term Optimal Management

  9. EY Factor Performance% Return Long Term Optimal Management

  10. CF Factor Performance% Return Long Term Optimal Management

  11. Out of sample EY factorIndex Long Term Optimal Management

  12. Score based allocation • Mean-Variance optimization • Subjective scoring system • Other methods • multivariate analysis • Cross-sectional regressions Long Term Optimal Management

  13. Final Remarks Decisions that have great impact over results: • Using arithmetic or geometric mean return • Using equally or MCap weighted portfolio • High correlation among fractiles • Data consistency through time for each factor • Minimum fractile size Long Term Optimal Management

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