Thanks to the advent of artificial intelligence, we’ve been able to improve the way we trade, invest and manage our risks.
When I read Federico Cecconi’s “AI in the Financial Markets: New Algorithms and Solutions” and with the latest research I’ve done on this sector, I gained a lot more understanding of the technological revolution in investing and its far-reaching impact. So I say to you…. Happy reading!
Reinforcing algorithmic trading
I’d like to point out that AI-powered algorithmic trading has done something remarkable for the financial markets. According to a report by Infomineo, AI tools allow traders to take into account economic conditions, market trends, trading strategies that are complicated, in fact, I would say they take into account several factors.
The high-frequency advantage
There’s something called high-frequency trading (HFT), and it has found a kind of strong ally in AI. The infomineo study reveals that, thanks to AI, people involved in HFT can get what’s called an autonomous value chain…
in fact you don’t need to know what it is, who cares, just they’ll reduce execution times to a few microseconds. That’s the difference between profit and loss in fast-moving markets.
Trading software AI: your digital market analyst
Close your eyes, close your eyes! And think of a market analyst who works non-stop, 24 hours a day, seven days a week. Now, I know that 99.99999999% of you haven’t really closed your eyes, but I wanted to give you an idea of how modern trading software works with AI.
It’s crazy when you consider that they can monitor thousands of stocks at the same time and analyze market trends in real time. Not to mention the fact that they give instant stock recommendations and alert traders directly to how prices are moving.
As I learned from Cecconi’s book, AI trading platforms go so far as to test strategies and run simulations, and as traders have a kind of virtual trial, so they can make their approaches better.
The brains of financial AI: machine learning
Machine learning is the head of the whole thing. Machine learning algorithms are able to analyze large datasets and discover patterns that the human eye can’t see, improving the way we make decisions without the need for an emotional being, as Forbes points out.
Adaptive trading strategies
When it comes to machine learning, there are a few things that are captivating about it, and that’s its ability to adapt.
In fact, current trading algorithms are designed to obey strict rules. What makes the difference, then, is that systems powered by machine learning have every right to adjust their strategies, which are, let’s not forget, real-time, according to the way market conditions are evolving.
AI-driven trading strategies: Outperforming the market
It’s great when AI improves existing strategies, and even better when it creates brand new ones. From sentiment analysis to predictive modeling, there’s plenty to choose from.
The wheel of algorithms: AI’s traffic controller
When I was reading Mr. Cecconi’s book, there’s one sick evolution I came across, and that’s the “algo wheel”. It’s a kind of traffic controller for trades and so they send orders to the algorithms and brokers that are most efficient and it depends mostly on real-time market conditions.
So, since they’re going to reduce the presence of humans to make trades, it promises performance and efficiency with “algo wheels”.
Sentiment analysis : Market mood
As I mentioned in my previous article on natural language processing, AIs are getting better and better at assessing market sentiment. When they analyze newsletters, social network messages and even corporate earnings calls, they’ll be able to detect the tiniest changes that humans wouldn’t be able to see at all.
Real-world applications: AI in action
Don’t think that all this is just blablabla no jutsu like Naruto, absolutely not! He already has real results from everything I’ve said above. I’d like to show you a few examples.
Nasdaq’s AI-powered order type
NASDAQ has introduced a type of order that works with AI, so they’ve given orders to an AI and thanks to this, there’s a 20.3% improvement in execution rates and an 11.4% reduction in plagiarism.
BlackRock’s Aladdin
Investment giant BlackRock came up with the idea of turning its risk management function into a way of making a lot more money with Aladdin, an AI-based software tool for risk assessment and portfolio management.
Goldman Sachs’ automated trading desk
Here’s a nugget that shows just how much AI is impacting the financial market, and it’s Goldman Sachs. In its US equities trading desk in New York there were only 600 human traders 2000 and in 2017 there were only two, simple! AI systems had taken over, humans were useless.
The future of AI in financial markets
The more time passes, the more the time when artificial intelligence will have almost unlimited potential accelerates. From what I’ve read of Cecconi’s work and industry trends, these are some of the developments we can still look forward to.
Hyper-customized investment strategies
We could create investment strategies that are suitable for risk profiles thanks to AI, and these strategies could also be suitable for objectives and even for what each investor prefers in terms of ethics. And all in real time.
Ethical considerations in AI-driven finance
As AI spreads further and further into financial markets, ethical considerations become a property. So there are issues we need to tackle, such as fairness, transparency and accountability, so that AI can benefit all players in the market.
The black box problem
Another challenge of AI in finance is its “black box” nature. In fact, as systems become increasingly complex, it’s important to guarantee transparency, as I said above, but also explicability, particularly for regulatory compliance.
Systemic risk
For systems that control a part of the larger market, the fact that these systems malfunction or act in an unexpected way can entail a risk of cascading failure, which is why it’s important to have safeguards and security devices in place.
Conclusion
The key to harnessing the full potential of AI in finance will be to strike the right balance between technological progress and ethical considerations.
That’s why I’m saying that whether you’re a seasoned trader, a curious investor or just someone who’s interested in what the intersection of technology and finance might look like, staying informed about the role AI
plays in the markets isn’t something you can choose or not, it’s an obligation.
