Considering the importance of stock price synchronicity as an indicator of the information content of the accounting system and a measure for efficiency of the market, This research aims to provide a price synchronicity model for stocks using financial and non-financial criteria by Meta-heuristic algorithm.

The data collection method employed was survey-based and library studies. The study population of this research consists of 167 companies listed on the Tehran Stock Exchange from the 2011 to the end of 2021, which were selected randomly and data were analyzed by meta-heuristic algorithms of Invasive Weed Optimization and Particle Swarm Optimization using MATLAB 2016 and Mini Tab software.

Findings indicate that the IWO algorithm is more accurate than PSO algorithm in estimating the coefficients of financial and non-financial factors affecting price synchronicity. Some financial and non-financial factors have a positive impact on price synchronicity while others have a negative impact. The ratio of non-executive managers and the size of the board of directors have a positive effect on price synchronicity. Information asymmetry has a negative impact on price synchronicity. The liquidity rank of stocks has a negative impact on price synchronicity. Operating profit margin has a positive effect on price synchronicity. The fixed asset turnover ratio has a positive effect on price synchronicity. Political communications have a negative impact on price synchronicity. Environmental factors have a negative impact on price synchronicity. Oil prices have a negative impact on price synchronicity, while being associated with commercial groups has a positive effect on price synchronicity.