This paper investigates the impact of a financial transaction tax (FTT) in a classic financial market setting. The benchmark analysis is based on an extension of the model presented in Kyle (1985). Opposed to the existing literature, I am able to find equilibrium values with a linear tax. Results of the benchmark model confirm standard findings of FTT’s, such as an increased bidask spread and an overall less deep market. Importantly, I find that the introduction of a tax leads to a non-linear pricing function. In turn, the model predicts a decrease in market depth and trading aggressiveness for small trades, whereas for larger trades the introduction of a FTT only leads to increased spreads and prices.

This paper investigates the effect of transaction taxes in a multi-market setting. We develop an asymmetric information model in which informed and liquidity traders may trade in equity and derivative markets. We find that taxing stock markets has large effects on volume, while it can lead to positive effects on liquidity due to an alleviation of the adverse selection problem in the taxed market. When possible effects on market-making competition are included the effect on liquidity is ambiguous. Additionally, we find that options are generally less affected by taxation. We empirically test some of our model’s hypotheses with high-frequency data for Italy, France, and Spain on equity, derivative and OTC markets. We find evidence that supports our theoretical findings and sheds light on how different tax designs affect trading volume and liquidity across financial markets.

This project aims at empirically testing the presence of informed trading in financial markets that exhibit a financial transaction tax. Using different proxies for informed trading we test the hypothesis that taxed markets exhibit lower proportions of informed trading on the examples of FTT’s in Europe.

This project aims at investigating the evolution of liquidity in LOB’s. Following Sandås (2001) we estimate a version of the model presented in Glosten (1994) using flow data from Nasdaq’s LOB.