intelligentcross
AI and Machine Learning Gain Momentum with Algo Trading & ATS Amid Volatility
An increasing number of capital markets firms are adopting machine learning and other artificial intelligence techniques to build algorithmic trading systems that learn from data without relying on rules-based systems. With the hiring of data scientists, advances in cloud computing, and access to open source frameworks for training machine learning models, AI is transforming the trading desk. Already the largest banks have rolled out self-learning algorithms for equities trading. "Machine learning is a natural next step of algorithmic trading because machine learning identifies patterns and behaviors in historical data and learns from it," said Robert Hegarty, managing partner, Hegarty Group, a consultancy focusing on financial services, technology, data, and AI/machine learning. While traditional algorithms are created by programmers and quant strategists, these algorithms based on if/then rules do not learn on their own; they need to be updated.
IntelligentCross ATS Surpasses 1 Billion Shares Delivering on Its Mission to Reduce Implicit Costs of Trading
Stamford, CT, May 20, 2019 (GLOBE NEWSWIRE) -- Imperative Execution, Inc. โ the financial technology company that created IntelligentCross, an AI-powered alternative trading system built to reduce implicit trading costs โ today announced performance results for its first eight months of operations. The venue has matched more than 1.5 billion shares since its launch with an observed price impact following these trades of 0.13bp, which is nearly ten times less than the 1.37bp average following comparable execution on U.S. securities exchanges. At the current rate of U.S. equities daily turnover, savings of that magnitude could save investors $10B per year. IntelligentCross is the industry's first smart venue to use artificial intelligence to optimize order matching to help investment managers and brokers reduce trading costs and improve execution quality on behalf of their clients. Its design was borne out of its founders' years trading on the buy-side, where traders are obsessed with implementation shortfall (IS) costs โ in other words, the difference, or "slippage," between the arrival price and the execution price for completing a trade.