Recently algorithmic trading has revolutionized financial markets. This study investigates the application of the Kelly criterion and technical indicators pairs (relative strength index RSI, moving average convergence divergence (MACD) on-balance volume (OBV), Bollinger bands (BB)) to optimize trading strategies within the Vietnamese VN30 index. Historical data from 2021–2024 was split into 2 parts, one is to find parameters for Kelly Criteria, another is used to analyze and backtest the proposed models. Results indicate that combining RSI and MACD is effective during downtrends, while RSI with OBV and BB performs better in uptrends. The Kelly Criterion consistently enhances risk management during periods, especially in downtrends. This research fills a gap in the literature and offers a foundation for future studies on algorithmic trading in emerging markets.