The current research assesses the risks commonly attributed to the presence of HFT in the context of different market structures deployed by the U.S. exchanges. In particular, we find that, by design, the so-called “normal” exchanges have the lowest market quality, including the highest...

We find that Robinhood ownership changes are unrelated with future returns, suggesting that zero-commission investors behave as noise traders. We exploit Robinhood platform outages to identify the causal effects of commission-free traders on financial markets. Exogenous negative shocks to...

We present a dynamic equilibrium model to understand differences and interactions between informational and trading speed advantages. The model is a stochastic asynchronous game, with endogenous trading decisions and non-cooperation among agents, in a limit order market. We show that welfare and...

We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt...

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...

The paper analyses the effects of technology-based innovative techniques on Bulgarian capital market -algorithmic trading, in general, and high frequency trading (HFT), in particular - from macroeconomic costs-benefits perspective. Overwhelmingly, empirical studies emphasize that HFT improves...

We propose a parsimonious agent-based model of a financial market at the intra-day time scale that is able to jointly reproduce many of the empirically validated stylised facts. These include properties related to returns (leptokurtosis, absence of linear autocorrelation, volatility clustering),...

Robo-advisors are novel tools in financial markets that provide investors with low-cost financial advice, usually based on individual characteristics like risk attitudes. In a portfolio choice experiment running over 10 weeks, we study how much investors benefit from robo advice. We also study...

We study empirically how competition among high-frequency traders (HFTs) affects their trading behavior and market quality. Our analysis exploits a unique dataset, which allows us to compare environments with and without high-frequency competition, and contains an exogenous event - a tick size...

We analyze how market fragmentation affects market quality of SME and other less actively traded stocks. Compared to large stocks, they are less likely to be traded on multiple venues and show, if at all, low levels of fragmentation. Concerning the impact of fragmentation on market quality, we...