In this study we investigate how bankruptcy affects the market behaviour of prices of stocks on Warsaw's Stock Exchange. As the behaviour of prices can be seen in a myriad of ways, we investigate a particular aspect of this behaviour, namely the predictability of these price formation processes. We approximate their predictability as the structural complexity of logarithmic returns. This method of analysing predictability of price formation processes using information theory follows closely the mathematical definition of predictability, and is equal to the degree to which redundancy is present in the time series describing stock returns. We use Shannon's entropy rate (approximating Kolmogorov-Sinai entropy) to measure this redundancy, and estimate it using the Lempel-Ziv algorithm, computing it with a running window approach over the entire price history of 50 companies listed on the Warsaw market which have gone bankrupt in the last few years. This enables us not only to compare the differences between predictability of price formation processes before and after their filing for bankruptcy, but also to compare the changes in predictability over time, as well as divided into different categories of companies and bankruptcies. There exists a large body of research analysing the efficiency of the whole market and the predictability of price changes enlarge, but only a few detailed studies analysing the influence of external stimulion the efficiency of price formation processes. This study fills this gap in the knowledge of financial markets, and their response to extreme external events.