The purpose of this study is to model the effect of returns and trading volume on the bid-ask spread using monthly and annual data during the Covid-19 Pandemic, as well as compare the panel data regression model to see the effect of returns and trading volume on the bid-ask spread based on monthly data periods and annually during the Covid-19 Pandemic. The results showed that the best model for monthly and annual data during the Covid-19 Pandemic was a random effect data model with individual effects or cross sections. In the random effect data model with individual effects or cross-section for monthly data, it is found that volume has a significant effect on the bid-ask spread at a significant level of 5%. Meanwhile, for annual data, it is found that returns have a significant effect on the bid-ask spread at a significant level of 5%. The best model based on monthly and annual data periods is the random effects data model with individual effects or cross sections using annual data.