Despite being around for over 50 years, one could say that Artificial Intelligence (AI) gave the world its first glimpse of power and potential when Deep Blue, a supercomputer developed by IBM crushed Garry Kasparov, the then at the time Chess grandmaster in a 1997 chess bout.
AI has then gone on to defeat world top poker, Go, and you name it players. Proving in the process that it far outpaces and out calculates the emotionally stitched human mind. With its continued development, it is now generally agreed that AI stands at the brink of revolutionizing entire industries ranging from law, manufacturing, health care, entertainment, etc, and trading.
In fact, the AI revolution has already started, though many don’t notice it, or don’t even imagine the ways in which it delicately intertwines with our everyday lives.
AI and Machine Learning (ML) in our favorite things.
Large companies that we all love, such as Amazon, Facebook, Spotify, Netflix, and more have deployed AI-related solutions in their business models that directly interact with end-users. For example, the Netflix recommendation engine, used for providing a personalized streaming experience and their creation of user-specific thumbnail images rely on AI and Machine Learning. Instagram and many other social networks utilize machine learning to block illegal content such as child pornography and recruitment for acts of terror. If you’ve ever been on Spotify, then maybe you noticed the ‘Discover Weekly’ customized list of 30 new songs that the music platform recommends to you on each Monday? Those recommendations are put together using Machine Learning by going through a whole lot of data, more than is humanly possible to do by each Monday, to receive a fitting list of songs for our ears.
We all love Amazon, and Amazon love itself some AI because of the 30%+ of revenue it generates for the company. Imagine how much effort it would take for a group of humans, however big, to sit and analyze customer purchases, preferences, views, and fine-tune the recommendation engine to provide site visitors with a list of products that the customers want or need to purchase?
Ever driven in a Tesla before? Those cars make a whole lot of use out of AI, data, hardware, and software. Every car is surrounded by cameras that provide 360-degree visibility and up to 250 meters of range, and all kinds of sensors that pick up hand placement on the wheel, surrounding objects, and so forth. Tesla cars come with AI chips, that make lightspeed calculations and evaluations based on traffic conditions, objects, and information to provide a full self-driving capability. Seems like AI and ML remove a huge burden from our shoulders.
Getting into the world of finances and trading.
Prior to the sophistication of AI, major banks, hedge funds, and financial institutions relied majorly on human factors for analyzing financial statements and reports, media, investor presentations, etc. Now, they rely heavily on ML and AI analytics to process colossal amounts of information pertaining to both the digital and non-digital realms to gain a much more detailed big and small picture of things than would be possible solely with human efforts in processing data. This data can then be further refined to acquire valuable financial and trading information.
Traditional hectic number crunching and mental gymnastic methods to process data and make trading decisions are gradually losing their relevance in the lives of different levels of traders. Professional traders have been forced to essentially upgrade themselves and their operations as technology continues to evolve. At the start of the 21st century, traders had to adapt and adopt bots into their strategies to trade against the rising dominance of trading bots and programs. Over the course of the last few years, adapting traders have been pitted against AI.
One of the most powerful advantages that AI has vs trading bots, is that as opposed to bots, AI can adapt its trading strategies automatically, therefore, operate independently and not require consistent human involvement and surveillance. AI has gotten to a point where it can develop and configure its own trading strategies while analyzing titanic amounts of data related to market dynamics and trends to improve itself with a constant stream of information and execute on decisions. Oh and by the way, despite being able to mimic the behavior of analysts (or an army of them), AI isn’t a victim of human emotions such as fear and greed which impede the profitability of traders.
Further advantages of AI trading over modern “by hand” trading
- AI can quickly gather and analyze vast quantities, I’m talking hundreds of millions of different points of structured and unstructured data regarding current and past events from various sources and carry out trades based on its algorithm and analysis without an emotional human factor.
- Data and patterns that AI can process and analyze (very quickly) are quite often not so obvious to human traders. In many cases that data is either incomprehensible or inaccessible.
- By analyzing media data, such as social network posts, blogs, news headlines, Twitter, and etc, AI can conduct accurate sentiment analysis and make predictions on market movements. Again, no human factor involved that would be a detriment to trading.
- AI’s automated and continuous self-improving nature make it vastly more efficient and competitively advantageous than manual trading with a good system.
- AI can build and operate on foolproof models during volatile market periods. Whereas an average emotionally driven trader with a limited data pool would see their portfolio receive a haircut.
- AI can automatically manage and adjust risk, diversify asset portfolios based on real-time processed data.
- AI can operate 24 hours a day. We humans, cannot.
We at Wavetrader, with supreme confidence, believe that the future of smart trading has AI and ML in its foundation, so does our product.
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