According to most financial experts, it is not possible to study the predictability of stock prices without considering the risks affecting stock returns. On the other hand, identify-ing risks requires determining the share of risk in the total risk and the probability of risk occurrence in different regimes. Accordingly, different DMA models with full dy-namics compared to TVP-BMA, BMA and TVP models have been used in the present study to provide this predictability. Findings showed that the DMA model is more effi-cient than other research models based on MAFE and MSFE indices. The present re-search was conducted in the period of 1-2003 to 12-2013 (including 144 periods) and was implemented in MATLAB 2014 software space. As the research results show, the bank interest rate coefficient in 45 periods, the first lag rate of the bank interest rate in 37 periods, the inflation rate coefficient in 17 periods, first lag coefficient of inflation rate in 26 periods, oil price coefficient in 78 periods, first lag rate of oil price in 85 peri-ods, exchange rate coefficient in 64 periods and first lag rate of the exchange rate in 35 periods have a significant effect on stock returns. The final conclusion shows that the stock variables of oil price and the exchange rate had the highest impact on stock returns during the studied period.