Strategic thinking pervades human interactions. In a complex world where the consequences are determined by the joint actions of related groups, it is natural and sometimes critical to anticipate the reactions of others and take those into account. The most well-developed theory of strategic interaction is the game theoretical notion of Nash equilibrium. In this model, equilibrium is defined as the collection of strategies such that every player maximizes the expected payoff, given the strategy of others. In addition, the epistemic game theory finds mutual knowledge of rationality to be a necessary condition for Nash equilibrium. However, experimental economics have documented much evidence which challenges Nash equilibrium as the best prediction of strategic interactions. In addition, behavioral game theorists have developed several structural non-equilibrium models that systematically deviate from Nash equilibrium. For instance, the level-k thinking model and the cognitive hierarchy model both assume players adjust their strategies through iterated best responses. Both models introduce levels of sophistication, characterized by the rounds of iterated reasoning, as a predictor of strategic interactions. Experiments suggest that in general, these models outperform Nash equilibrium in terms of predicting the outcome of strategic interactions. My dissertation focuses on understanding the effect of strategic sophistication in market environments. Namely, I study how trading behaviors are determined by participants' levels of reasoning with an emphasis on financial markets. The first chapter of my dissertation investigates the effect of strategic reasoning on financial markets with a level-k thinking framework. A level-k speculator performs k rounds of iterative reasoning to infer information from asset prices. In contrast to the rational expectations equilibrium, the level-k framework produces a unified theory of momentum and contrarian trading strategies. I discuss ho