Trade execution has attracted lots of attention from academia and financial industry due to its significant impact on investment return. Recently, limit order strategies for trade execution were backtested on historical order/trade data and dynamic price adjustment was proposed to respond state variables in execution. This paper emphasizes the effect of dynamic volume adjustment on limit order strategies and proposes dynamic focus (DF) strategies, which incorporate a series of market orders of different volume into the limit order strategy and dynamically adjusts their volume by monitoring state variables such as inventory and order book imbalance in real-time. The sigmoid function is suggested as the quantitative model to represent the relationship between the state variables and the volume to be adjusted. The empirical results on historical order/trade data of the Australian Stock Exchange show that the DF strategy can outperform the limit order strategy, which does not adopt dynamic volume adjustment.