Adaptive Layered Buying Strategy Using Mode and Standard Deviation of Daily Price Range: Evidence from BBRI Indonesia Stock Market - Cevi Herdian; Rama Pramasandy (Jurnal Indonesia Sosial Sains, 2026)
The Indonesian stock market exhibits substantial price volatility, making fixed-interval averaging strategies less effective under changing market conditions. This study proposes an adaptive averaging strategy based on the historical distribution of daily price ranges. Daily open, high, low, and close (OHLC) price data for Bank Rakyat Indonesia (BBRI), covering the period from November 2003 to July 2026 and comprising 5,602 observations, were analyzed. The adaptive buying interval was estimated using the mode of non-zero daily price ranges combined with two standard deviations. The resulting interval was then used to construct a layered buying strategy with exponential position sizing. Simulation results indicated that the proposed strategy substantially reduced the average acquisition cost while maintaining manageable capital requirements. Under a seven-level buying strategy, total capital deployment reached IDR 23.68 million, assuming purchases began in January 2025. Furthermore, the simulated portfolio generated a positive unrealized return of 59.28% under the historical price scenario. These findings suggest that statistical measures of price volatility provide a practical basis for determining adaptive averaging intervals in long-term equity investment. The proposed framework offers a simple yet robust alternative to conventional fixed-interval averaging strategies.