We present the first direct evidence of algorithmic imprints during batch auctions. Order anticipation is an integral part of high-frequency traders' strategies. Hence, some participants may have economic incentive to encrypt noise in the data. We use machine learning to identify five types of...

The project proposes a type of Artificial Neural Network (ANN) known as Long Short Term Memory (LSTM) to predict the prices for a portfolio of best stocks from five different sectors since election. The current price, technical and fundamental indicators will be learned to predict the next...

This paper offers a novel perspective on the implications of increasingly autonomous and “black box” algorithms, within the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and particularly its subfield of machine learning (ML) methods...