The Market Corner: the month in review
Written by Filippo Lecchini
The rise of the machines
With the wide adoption of smart phones and the boom of applications for all sort of purposes technology is taking over various aspects of everyone’s life. While technological progress didn’t start with the iPhone, the range of the opportunities and access for the general population has largely expanded in the last few years. Machine Learning, Artificial Intelligence and Data Analytics have become part of the public discourse almost everywhere.
The financial markets are no exception. Algorithms have been around for a long time and led eventually to the creation of automated trading systems, rule based programs that execute orders based on certain thresholds and signals. Eventually this type of volume became prevalent in the equities and futures markets and has been for a while, so the question becomes how these advancements are going to impact the financial industry.
The first obvious consequence is the continuous evolution of the existing systems: the amount of data available, the increased effort to collect them and the much improved storage capacity allow managing an amount of information that was unthinkable just a few years ago. A wealth of new models based on different variables and relationships can now be tested and validated.
The machine learning approach is brand new and its full potential is still to be unveiled. The newer algorithms don’t use simple triggers but rather “learn” from the data. The programmatic effort in this scenario is about how to interact with the information which in turn leads to trading decisions, rather than setting a simple rule to initiate a trade. The algo will make the decisions, will not just execute them.
Fintech firms already use knowledge of the customers as provided at account opening to build an ideal profile for risk and investment, using the information to manage the account over time. A few quant hedge funds let the machines make trading decisions. Other applications are in risk management and fraud detection where a few behavioral variables can be systematically incorporated in each customer’s profile (e.g. frequency and amount of money transfers) rather than being randomly inspected or noticed by coincidence.
In a way none of this should be a surprise: there is plenty of research that shows how data driven approaches as opposed to discretion eliminate mistakes and cognitive biases, but the extent to which these ideas can be exploited is now much wider and seemingly limitless thanks to the new technologies.
It all reverts around the value of data, all of a sudden the most valuable commodity in every type of business. People can learn to their advantage as well: if for example they can detect that their ability to focus is better in the morning hours they can increase their probability of trading successfully by avoiding trading in the afternoon. This is by and large unchartered territory and there are certainly privacy concerns but for those willing to embrace the change new opportunities await.
August is upon us and policy makers around the world will be on recess for some time. The FOMC meeting at the end of July is expected to be uneventful but the probability of a hike at the end of September as implied by the FED funds futures, currently stands at 92% after the GDP numbers released on 7/27 were rather bullish on growth.
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