This dissertation consists of two essays that study two different financial markets using empirical methods from the industrial organization literature. The first chapter studies customer search behavior and asymmetric adjustment of rates in the US deposit market. The second chapter explores the market for retail investors' orders to buy/sell securities in the US stock market.Branch-level data from the US deposit market shows that in periods the federal funds rate goes up, banks raise the deposit rates far less than one-for-one, and as a result, the deposit rate spread increases as well. However, in periods the Fed funds rate falls, the spread becomes negligible. In the first chapter, I design and estimate a model with heterogeneous search cost depositors to justify the deposit rate dispersion in this highly competitive market and to rationalize the asymmetric rate adjustment in different periods. I find that customers place significant weight on past rates when formulating their prior beliefs. My results suggest that the Fed funds rate fluctuations will have a larger and more asymmetric impact on deposit rates when customers rely more heavily on past rates in forming their priors. Also, my estimates reveal a large fraction of high-search-cost depositors that provide banks with significant monopoly power and allow for the incomplete pass-through of increases in the Fed funds rate into deposit rates. The current structure of the retail equity order market in the US is like a dealership market. More specifically, brokers and market makers negotiate about the quantity of order volume and average price improvement offered to retail investors. In the second chapter of this dissertation, I study the economic effects of restructuring this market to a limit order one. In such a framework, similar to an auction market, brokers submit retail orders to the market, and market makers need to compete with each other on an order-by-order basis. To do so, I develop and estimate a structural model of the retail order market with three key components: a micro-founded model of the market maker's behavior in executing equity orders, a bargaining model to capture the negotiation between a market maker and a broker, and the broker’s optimization problem to allocate the order volume across market makers. I find that retail investors, overall, gain slightly better price improvements under the simulated structure. The difference between the simulation and current outcomes is statistically significant for some market makers. However, this is not the case for all market makers in my data sample.