Artificial Intelligence for financial services
As the popularity and profitability of high frequency trading declines, the next evolution of algorithmic trading may be dependent on smarter machines, allowing a broader class of trades to reap the benefits of automation and sophistication.
Future of Smarter Faster Machines
The proliferation of smarter machines will further shift the focus of machine-based trading to rapidly respond to real-life event:
As the race for speed transitions to the development of strategies responding to real-life events, market makers’ trading strategies may become more diversified as they access a vast amount of different data sources and infer different market conditions from that data
When trading algorithms become more intelligent by incorporating machine learning, the breadth and accuracy of their analyses will expand, and could result in convergence toward a single view of the market
Growing public discontent with algorithmic trading may lead to regulations on the use of automatic data feeds or smart machines in executing trades, reverting some parts of market-making activities to manual processes
Smarter, faster machines will allow broader types of trades beyond high frequency trading to reap the benefits of automation and sophistication
Ask questions, discover and test hypotheses, and make decisions automatically based on advanced analytics on extensive data sets.
The involvement of humans in the overall trading process may decrease as machines automate a wide range of core activities from hypothesising to decision making
Self-correct and continuously improve trading strategies with minimal human interaction through machine learning and prescriptive analytics.
The accuracy, consistency and speed of trades will improve through automation and self-learning