Abstrakt
The 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 a 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. However, the results are not robust to the size of the artificial market as non-linearities emerge when the size of the market is increased.