Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High- Frequency Trading

We 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 ash crashes. In the model, low- frequency 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 ash 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 ash 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-o 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

Trading à haute fréquence et régulation économique, un arbitrage inéluctable entre stabilité et résilience des marchés financiers

Au cours des dernières décennies, le trading à haute fréquence (THF) a fortement augmenté sur les marchés américains et européens. Le THF représente un défi majeur pour les autorités de régulation du fait, d’une part, de la grande variété de stratégies de trading qu’il englobe (AFM, 2010 ; SEC, 2010) et d’autre part des incertitudes qui planent toujours autour des avantages nets de cette innovation financière pour les marchés financiers (Lattemann et al., 2012 ; ESMA, 2014 ; Aguilar, 2015). Par ailleurs, bien que le THF ait été identifié comme l’une des causes probables des krachs éclairs (Jacob Leal et al., 2016), aucun consensus n’a encore réellement émergé sur les causes fondamentales de ces phénomènes extrêmes. Certains pays ont déjà décidé de réguler le THF[*]. Cependant, les approches adoptées jusqu’à présent varient en fonction des régions. [Premier paragraphe

Momentum effect in individual stocks and heterogeneous beliefs among fundamentalists

International audienceThis paper investigates whether the observed momentum effect in individual stocks, caused by positive serial correlations in monthly returns over short horizons, can be explained by fundamentalists' heterogeneous beliefs when chartists are present in the market. To this end, we propose a heterogeneous agent model wherein agents follow different strategies and information about asset fundamentals diffuses slowly. On the one hand, fundamentalists predict future prices based on the observed discrepancy between the current stock price and its fundamental value. However, due to slow diffusion of firm-specific information, fundamentalists have heterogeneous beliefs about asset fundamentals. On the other hand, chartists predict future prices based on the observation of past price movements. Computer-based simulations reveal that the interplay of fundamentalists and chartists can robustly generate positive serial correlations in monthly returns over short horizons, stock price overreaction to news events and price misalignments. In particular, we find that (i.) slow diffusion of information does not suffice to explain the momentum effect in individual stocks; (ii.) the interplay of fundamentalists and chartists robustly generates short-term momentum in returns, which is mainly driven by the pervasive presence of chartists; (iii.) we find that, when trend followers dominate the market, stock price overreacts and subsequently corrects due to slow diffusion of firm-specific information

Fundamentalists, Chartists and Asset pricing anomalies

online décembre 2014 compté en 2014International audienceThis paper investigates whether excess volatility of asset prices and serial correlations of stock monthly returns may be explained by the interactions between fundamentalists and chartists. Fundamentalists forecast future prices cum dividends through an adaptive learning rule. In contrast, chartists forecast future prices based on the observation of past price movements. Numerical simulations reveal that the interplay of fundamentalists and chartists robustly generates excess volatility of asset prices, volatility clustering, trends in prices (i.e. positive serial correlations of returns) over short horizons and oscillations in prices (i.e. negative serial correlations of returns) over long horizons, often observed in financial data. Moreover, we find that the memory of the learning rule plays a key role in explaining the above-mentioned stylized facts. In particular, we establish that excess volatility of asset prices; volatility clustering and autocorrelation of returns at different horizons emerge when fundamentalists have short memory. However, volatility clustering as well as short-run and long-run dependencies, observed in financial time series, are more pronounced when fundamentalists have longer memory

High-Frequency Trading: Does Latency Floor Matter?

International audienc

High-Frequency Trading: Does Latency Floor Matter?

International audienc

Algorithm trading, what if it is just an illusion? Evidence from experimental financial markets

International audienc

Algorithmic trading, what if it is just an illusion? Evidence from experimental financial markets

International audienc

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

Prev. avril 2017 Compté juin 2017International audienceWe investigate the effects of a set of 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 traders. In particular, we study the impact of the imposition of minimum resting times, of circuit breakers, of cancellation fees and of transaction taxes on asset price volatility and on the occurrence and the duration of flash crashes. Monte-Carlo simulations reveal that HFT-targeted policies imply a trade-off between market stability and resilience. Indeed, we find that policies able to tackle volatility and flash crashes also hinder the market from quickly recovering after a crash. This result is mainly due to the dual role of HFT, as both a cause of flash crashes and a key player in the post-crash recovery