Abstract
Recent crisis revived interest in financial transaction taxes (FTTs) as a means to offset negative risk externalities. However, up-to-date academic research does not provide sufficient insights into the effects of transaction taxes on financial markets, as the literature has here-to-fore been focused too narrowly on Gaussian variance as a measure of volatility.
In this paper we argue that it is imperative to understand the relationship between price jumps, Gaussian variance, and FTTs. While Gaussian variance is not necessarily problem in itself, the non-normality of return distribution caused by price jumps affects not only the performance of many risk-hedging algorithms but directly influences the frequency of catastrophic market events.
To study the aforementioned relationship we use an agent-based model of financial markets. Its results show that FTTs may increase the variance while decreasing the impact of price jumps.
This result implies that regulators may face a trade-off between overall variance and price jumps when designing optimal tax.