First, we create an algorithm that classifies bonds into different levels of liquidity, using appropriate liquidity measures and two different methods (SNNs and logistic regression). This procedure provides a ground for a comparison of how well either approach captures relevant liquidity characteristics, which, in turn, enables the researchers to determine whether the increased complexity of the SNN provides any improvements in liquidity classification compared to a basic logistic regression.