리밸런싱 프리미엄 측정에 관한 연구: 국내 주식시장 실증분석

초록

This study examines the existence and determinants of rebalancing premium in the South Korean stock market using 111 stocks continuously traded on KOSPI and KOSDAQ from January 2000 to May 2025. The rebalancing premium refers to the excess return generated by a strategy that periodically rebalances portfolio weights to target levels compared to a buy-and-hold strategy. Following the methodology of Maeso and Martellini (2020), we employ a rolling window approach with 1,000 resampling iterations per period. Our empirical findings reveal significant rebalancing premiums in the South Korean market. An equal-weight portfolio of 50 stocks rebalanced monthly generates an average annual excess return of 288 basis points over the buy-and-hold strategy, with a 94% probability of outperformance, exceeding the 84% reported for the U.S. market. The magnitude of the rebalancing premium demonstrates a positive relationship with portfolio size, ranging from 157 basis points for two-stock portfolios to 287 basis points for 111-stock portfolios over five-year periods. Monthly rebalancing generates the highest premium at 288 basis points annually, compared to 168 basis points for annual rebalancing. After accounting for transaction costs of 50 basis points, monthly rebalancing maintains a substantial premium of 242 basis points. Factor decomposition using the Fama-French-Carhart four-factor model reveals strong negative momentum exposures, confirming the contrarian nature of rebalancing strategies. While regression intercepts remain positive (310-366 basis points annually), GRS tests fail to reject the null hypothesis of jointly zero alphas, suggesting that observed premiums can be largely explained by systematic factor exposures rather than representing independent alpha. The findings support implementing systematic rebalancing strategies in Korean portfolios, as premiums remain substantial even after accounting for realistic transaction costs. However, practitioners should recognize these returns stem from the mechanical contrarian nature of rebalancing that implicitly times well-known risk factors.

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