Market stability vs. market resilience: Regulatory policies experiments in an agent-based model with low- and high-frequency trading

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe investigate the effects of different regulatory policies directed towards high-frequency trading (HFT) through an agent-based model of a limit order book able to generate flash crashes as the result of the interactions between low-and high-frequency (HF) traders. We analyze the impact of the imposition of minimum resting times, of circuit breakers (both ex-post and ex-ante types), of cancellation fees and of transaction taxes on asset price volatility and on the occurrence and duration of flash crashes. In the model, lowfrequency agents adopt trading rules based on chronological time and can switch between fundamentalist and chartist strategies. In contrast, high-frequency traders activation is event-driven and depends on price fluctuations. In addition, high-frequency traders employ low-latency directional strategies that exploit market information and they can cancel their orders depending on expected profits. Monte-Carlo simulations reveal that reducing HF order cancellation, via minimum resting times or cancellation fees, or discouraging HFT via financial transaction taxes, reduces market volatility and the frequency of flash crashes. However, these policies also imply a longer duration of flash crashes. Furthermore, the introduction of an ex-ante circuit breaker markedly reduces price volatility and removes flash crashes. In contrast, ex-post circuit breakers do not affect market volatility and they increase the duration of flash crashes. Our results show that HFT-targeted policies face a trade-off between market stability and resilience. Policies that reduce volatility and the incidence of flash crashes also imply a reduced ability of the market to quickly recover from a crash. The dual role of HFT, as both a cause of the flash crash and a fundamental actor in the post-crash recovery underlies the above trade-off.

Mathematical Problems in Algorithmic Trading and Financial Regulation

“…They show that MRT tightens the bid-ask spread by a marginal amount, however they assume that market participants trade in the same manner before and after the MRT rule is implemented. In our work the depth and volume of the LOs of the MM depend on the MRT and we find that the bid-ask spread increases because MRTs cause an increase in the depth of the LOs Leal and Napoletano (2017). use an ABM in which the interactions between low-and high-frequency traders can generate flash crashes.…”

Policy Modeling and Applications: State-of-the-Art and Perspectives

“…Further in economics, ABM is used to criticize current, quantitative, yet perfect (without endogenous crises) economic models [54][55][56]. Finally, it is worth mentioning the use of ABM to test policies applied to the financial markets, from the early contributions of LeBaron [57,58] and Westerhoof [59] to the detailing of the effects of transaction taxes and trading halts on assets volatility [60].…”

The Design and Regulation of High Frequency Traders

“…Budish et al (2015) in contrast looks at the optimal market architecture and argues that moving from continuous double auctions to discrete batch auction reduces the value of very small speed advantages and so encourages competition on price instead of speed, benefiting market participants. Leal and Napoletano (2017) use an agent based model to consider flash crashes and the effect of several regulations. Their model is based around slow traders and HFT's who use pre-specified strategies (although slow traders may switch between chartist and fundamentalist strategies) to submit orders within trading windows of fixed length.…”