Artificial intelligence (AI) is becoming more and more ingrained in our lives, and that includes its applications with respect to portfolio management. The question is no longer whether portfolio managers will adopt the use of AI, it’s when they will choose to do so and how much of its potential they will embrace. Here are five reasons why the inclusion of AI is worth consideration when it comes to portfolio management.
1. Artificial intelligence can access and process volumes of data that even a team of active wealth managers working 24/7 simply could not.
The explosion of data growth has been exponential, with over 80% of the data on the internet having been created in just the last two years. We could add more humans geometrically in an attempt to process this data, but some context illustrates how difficult that would be without the aid of computers: in 1992, global internet traffic was 100 GB per day; by 2016 that amount of traffic grew to 26,600 GB per second. Unlike humans, AI systems can analyze huge tracts of data 24/7 without getting overwhelmed.
2. AI does not get emotional about data or market fluctuations.
The machine learning algorithms of an artificial neural network take everything into account, including human biases and their effects. They gauge mood and sentiment about financial instruments without ever getting moody or sentimental. Although any systematic/algorithmic trading system cuts out human biases from trading decisions, AI deploys an adaptive, intelligent system. It analyzes vast tracts of crowd-sourced data sets — news items, social media posts, market reports, etc. — and propels this information forward, forecasting with greater accuracy and less bias than a human counterpart.
3. AI is self-learning and evolving.
Artificial neural networks constantly process the historical performance and volatility of stocks and indices, as well as the above-mentioned behavior of investors. This level of data mining and processing allows for non-linear patterns to be revealed through predictive analytics — something that is only possible with AI’s computational power.
4. AI is tailored to the client’s needs, and is constantly monitoring.
When structured with overall investment objectives, a portfolio employing artificial intelligence also means personal and robust risk mitigation on a scale not previously possible. Positions are continuously monitored, with losers removed immediately while winners build momentum.
5. AI is more accessible than ever to investors.
Applying the power of machine learning to financial markets was, until very recently, solely the domain of those whose pockets were as deep as their algorithms were secret. This has changed considerably in recent years, with some firms building their own native AI systems, and the availability for any firm to enter into a licensing agreement that allows them to distribute information from a proprietary AI framework. For the investor this means there are more options to embrace AI than ever before.
AI, Risk/Return & Investment Goals
The power of AI and machine learning and their accessibility to those who manage portfolios has never been greater. And we’re just scratching the surface of what AI can do for risk/return requirements and specific investment goals. We know that the amount of data available is both awesome and increasing on a trajectory that’s only going to get more vertical. We now possess the added benefit of harnessing large-scale computational power to manage that data and achieve those goals.
TrueRisk Labs builds AI. Our machine learning platforms are constructed specifically for applications across the financial services industry, allowing both investors and fintech professionals access to the power of a true, native artificial intelligence.