Join Tackle Trading's Gino Poore, Noah Davidson, and Matt Justice as they discuss the impact seasonality has on the markets and how historical market data can make prediction more reliable. In this Coaches Show audio replay, the Tackle Trading coaches cover more than just market conditions and economic news for the week. While market conditions were indeed covered, the focus was seasonality's effect on markets and how historical seasonal data can help make predictive models. Seasonality in trading is much like you may picture the word when it comes to the retail space: certain sectors consistently perform better or worse during specific times of the year. For example, retail tends to pick up toward the end of the year thanks to the rush of holidays that occur. In mid-Spring, it tends to be energy and basic goods that do well; there are no major holidays for a long stretch, and with temperatures switching up, energy consumption increases after the mildness of early Spring. In taking this historical data of sector performance over the years in each month, patterns emerge that carry over from year to year, which makes predicting what may happen in the markets more reliable (but never 100% certain or risk-free).