Investors' Exchange LLC (IEX) is a newly approved public exchange that is designed to discourage aggressive high-frequency trading. We explain how IEX differs from traditional continuous double auction markets and present summary data on IEX transactions by trader class and or- der type. Our...

Several financial exchanges have recently introduced messaging delays (e.g., a 350 microsecond delay at IEX and NYSE American) intended to protect ordinary investors from high-frequency traders who exploit stale orders. We propose an equilibrium model of this exchange design as a modification of...

This work focuses on two of the more frequent practices in financial (especially capital) markets - the use of hidden orders and High-Frequency Trading (HFT). Although the use of each of them may reach 40% of the market turnover - even 60% for HFT, the actual knowledge on how they affect...

Starting from February 2007 world market is facing what we call enantiodromia. The indices are correcting. It is not known whether this is the final correction but there is no doubt that the bubble has burst and air out of it is gushing out slowly (fast on an extended time frame). The biggest...

This paper investigates the profitability of a trading strategy based on training a model to identify stocks with high or low predicted returns. A tail set is defined to be a group of stocks whose volatility-adjusted price change is in the highest or lowest quantile, for example the highest or...

In this paper, we investigated the profitability of technical analysis as applied to the stock markets of the BRICS member nations. In addition, we searched for evidence that technical analysis and fundamental analysis can complement each other in these markets. To implement this research, we...

Statistical learning models have profoundly changed the rules of trading on the stock exchange. Quantitative analysts try to utilise them predict potential profits and risks in a better manner. However, the available studies are mostly focused on testing the increasingly complex machine learning...

Modern Portfolio Theory assumes that decisions are made by individual agents. In reality most investors are involved in group decision-making. In this research we propose to realize group decision-making process by application of Ensemble Learning algorithm, in particular Random Forest....