We investigate the role algorithmic trading (AT) on days when the absolute value of the market return is more than two percent. We find that the abnormal return of a stock is related to the stock's AT intensity, that high AT intensity stocks experience less price drops (surges) on days when the...

This paper proposes the Shannon entropy as an appropriate one-dimensional measure of behavioural trading patterns in financial markets. The concept is applied to the illustrative example of algorithmic vs. non-algorithmic trading and empirical data from Deutsche Börse's electronic cash equity...

We examine the effect of high frequency trading on market quality from theperspective of a limit order trader. By competing with slower limit order traders, highfrequency traders (HFT) impose a welfare externality by crowding out slower non-HFTlimit orders. The order book imbalance immediately...

In this research, we test whether common trading oscillators can outperform the buy-and-hold strategy (B&H) using six popular ETFs for the period of the last 20 years. We use the original setups of those oscillators and also other setups or oscillators combinations in order to achieve the best...

Liquidity suppliers lean against the wind. We analyze whether high-frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is HFTs trading "with the wind," that is, in the same direction. We find that HFTs initially lean...

Purpose: This article analyzes the influence of familiarity bias on respondents' decision-making process, using results from online experiments. Design/methodology/approach: A total of 255 research participants from post-Soviet countries completed 510 online tests that were presented in the form...

This paper documents a stark periodicity in intraday volume and in the number of trades. We find activity in both variables spikes by about 20% at regular intervals of 5 or 10 minutes throughout the trading day. We argue that this activity is the result of algorithmic trading influenced by human...

This study examines the impact of corporate earnings announcements on trading activity and speed of price adjustment, analyzing algorithmic and non–algorithmic trades during the immediate period pre– and post– corporate earnings announcements. We confirm that algorithms react faster and...

I show that the growth of high-frequency trading, due to its heavy reliance on computer algorithms, can be associated with a reduction of human errors and financial anomalies in the market. Trades in which a non-high-frequency trader is the liquidity demander exhibit abnormally high buy (sell)...